Project Reference No. : C1009-22GF
Project Title : An Enabling Technology for 6G Wireless Communications
Project Coordinator : Professor CHAN Chi-hou
University : City University of Hong Kong
Layman Summary
While the fifth-generation (5G) mobile communication systems are still being deployed, the race on 6G R&D is rapidly gaining momentum. Innovations and applications inconceivable today will be rolled out to change our lifestyles and our society's operations. In this project, we aim to build a terahertz (THz) communication link testbed that allows agile response to evolving requirements, challenges, and standardization of 6G. To meet the ultra-wide bandwidth requirement, we propose developing THz radiator integrated circuits (ICs) to modulate baseband signals. We adopt in-memory computing with customized designs of resistive random-access memory devices and content-addressable memory hardware to shorten the communication latency and support ultra-fast data-intensive baseband processing. The speed of the communication link will be enhanced using the multiple-input-and-multiple- output (MIMO) technology. Metasurfaces will be designed to manipulate the radiated fields for enhancing the communication range and throughput. Successful development and integration of the proposed technologies will place us at the forefront of research on 6G disruptive technologies.
Project Reference No. : C1014-22GF
Project Title : An Upcycling Solution to the Paradox of Clean Energy Development
Project Coordinator : Professor LIEW Kim-meow
University : City University of Hong Kong
Layman Summary
The project will upcycle waste glass and recycled carbon fibers from end-of-life solar panels and wind turbine blades by using these materials as key components of fiber-reinforced alkali-activated cement composites (FRAC). This process will consist of five major tasks: (1) devise a process control strategy to recycle glass and carbon fibers from end-of-life solar panels and wind turbine blades; (2) develop a body of knowledge on the design, mechanisms, and characterization of waste derived FRAC; (3) evaluate strength development of FRAC and optimize their mechanical performance; (4) examine the long-term durability and leachability of FRAC; and (5) assess their environmental and economic impacts. This proposed project will advance the scientific frontiers of waste upcycling by developing an innovative method for transforming waste into valuable and eco-friendly construction materials. This will also help Hong Kong to achieve its sustainable development goals, thereby supporting the Climate Action Plan 2030+.
Project Reference No. : C1017-22GF
Project Title : Fundamental Study Towards Real Spider Dragline Silk Performance Through Artificial Innovative Approach
Project Coordinator : Professor HU Jinlian
University : City University of Hong Kong
Layman Summary
Spider dragline silk has excellent comprehensive mechanical properties including high strength and high toughness, and has great potential in aerospace, military, medical and other fields. Due to the aggressive nature of spiders, it is impossible to collect spider silk on a large scale like silkworms. Therefore, artificial spider silk is mainly mass produced by expressing recombinant spider silk protein a.k.a. spidroin in heterologous hosts. However, the hydrogen bond network of current artificial spider silk is easily destroyed in wet environment, and the wet strength is reduced, which greatly limits the application of artificial spider silk. Moreover, during the fiber-forming process, the molecular assembly mechanism from the spidroin solution to the solid spider silk have not yet been fully understood. This project aims to introduce covalent bonds into spider silk to stabilize the molecular structure and improve the wet stability of artificial spider silk. At the same time, this project will be supplemented by Low Dose in-situ TEM and molecular dynamics simulation to study the self-assembly behavior of spidroin molecules during the fiber-forming process. The smooth implementation of this project will contribute to the large-scale production of high-performance artificial spider silk and provide iterative design solutions for other protein materials.
Project Reference No. : C1024-22GF
Project Title : Molecular Mechanism of RNA Transport and Specificity of their Spatial Distribution in Neuron
Project Coordinator : Dr. LAI Kwok-on
University : City University of Hong Kong
Layman Summary
The neuron contains long and branching extensions called axons and dendrites. To change the protein composition within these extensions, neuron needs a specialized machinery to transport specific mRNAs over long distances to these distal sites. The RNAs are packed into granules by multiple RNA-binding proteins and carried along the cytoskeleton by motor proteins known as kinesin. Different mRNAs can be transported independently and heterogeneously distributed, but whether and how specific mRNAs may be localized at neuronal connections (the synapses) are poorly understood. Furthermore, the extent of diversity in their transport within the intact brain remain unexplored. In this proposal, we will employ an interdisciplinary approach that includes advanced cellular and in vivo imaging, genome editing, chemical biology and mass spectrometry to comprehensively investigate the mRNA transport specificity in neurons, as well as to decipher the underlying mechanisms. Dysfunction of RNA transport is associated with specific diseases, from autism to neurodegeneration. Our study may help to understand the specific transport defects in various brain disorders.
Project Reference No. : C1029-22GF
Project Title : Enabling Metadata-private and Accountable Networks at Scale
Project Coordinator : Professor WANG Cong
University : City University of Hong Kong
Layman Summary
Over the past decade, we have witnessed the proliferation of end-to-end encryption (E2EE) among many popular online services, such as WhatsApp and Signal for encrypted messaging, ProtonMail for encrypted emails, etc. While encryption hides the traffic payload, today's E2EE platforms do not protect the communication metadata, including the identities of the communicating parties, the timing, and volume of the traffic. Such metadata often exhibits unique characteristics about encrypted traffic, and has long been known as privacy-revealing, as powerful attackers today can not only monitor but also actively interfere with network traffic. In this project, we plan to develop new security and privacy-enhancing technologies to push forward the frontier of modern E2EE platforms, and set up the foundational framework for future metadata-private and accountable E2EE communication systems. This collaborative research serves for the rising demand for data security and privacy, potentially benefiting online enterprise and consumer services in HK and beyond.
Project Reference No. : C2003-22WF
Project Title : NAD capping of RNA: mechanism and functions
Project Coordinator : Professor XIA Yiji
University : Hong Kong Baptist University
Layman Summary
Living organisms employ complex mechanisms for precise control of gene expression. Modification of RNA molecules is one of these mechanisms, and a major type of RNA modification is RNA capping. Eukaryotic mRNAs typically contain the methylguanosine (m7G) cap on the 5' end which is critical for gene expression, whereas prokaryotic RNAs were previously thought to be uncapped. Recently, some RNAs in both prokaryotic and eukaryotic cells have been found to contain NAD as a 5' cap, indicating a previously unknown mechanism in controlling gene expression through non-canonical RNA capping. The mechanism that controls NAD capping and the molecular and biological functions of NAD-capped RNAs (NAD-RNAs) remain elusive.
We have developed multiple methods for identification and characterization of NAD-capped RNAs (NAD-RNAs) in various organisms. Our findings indicate that NAD-RNAs likely have regulatory functions. In this study, we will use E. coli and Arabidopsis as the model organisms to understand the molecular mechanisms that control NAD capping. Molecular and genetic approaches will be employed to reveal the molecular mode of action of some NAD-RNAs, particularly in transcriptional control. This project will be carried out through multi-disciplinary collaboration with investigators who have complementary knowledge and skills in molecular biology, RNA biology, analytical chemistry, structural biology, biochemistry, and cell biology.
Project Reference No. : Ref. C2013-22GF
Project Title : Genomic Insights into Environmental Adaptation and Diversity of Deep-sea Siboglinidae
Project Coordinator : Professor QIU Jianwen
University : Hong Kong Baptist University
Layman Summary
Siboglinidae is a family of annelids that are widely distributed in the deep ocean, but little is known about their phylogenetic position and how symbiosis has contributed to their successful colonization of various deep-sea habitats. In this project, we aim to provide an improved phylogenomic framework of Annelida, determine the phylogenetic placement and drivers of evolution of Siboglinidae by revealing the genomic footprints in the four major lineages of Siboglinidae such as how they coordinate metabolism with symbionts to meet their nutritional needs, and how different lineages of siboglinids evolved to exploit different chemosynthetic environments. We also aim to construct a comprehensive genomic database of Annelida with a user-friendly interface to promote the use of genomic resources.
Project Reference No. : C4006-22GF
Project Title : Lingnan Culture and the World: Construction and Change in the Cultural Landscape of Cantonese Literati from the Late Qing to the Republican Era in China (1821-1949)
Project Coordinator : Professor LAI Chi-tim
University : The Chinese University of Hong Kong
Layman Summary
The proposed project examines the construction and evolution of the Lingnan culture as seen in the lives and experiences of 150 key personalities among the Cantonese literati and merchant-gentry of the late Qing and Republican era (1821-1949) - an age of great change in the history of modern China.
A major characteristic of this project is its macro-mapping of the Lingnan cultural landscape, which breaks through the confines of individual disciplines, and the simplistic dichotomies between local and global, East and West. It challenges the prevailing discourse of a linear development of the Lingnan from the traditional to the modern, giving full play to the complexity, multiplicity, and inter-dynamics in the Lingnan culture in the focus period. The notion of Lingnan literati here moves beyond the traditional scholar-gentry within the geographical boundaries of Guangdong to encompass the diverse personalities involved in art, literature, language, music, religion, education, material culture, science, and more in Guangdong, adjacent Cantonese-speaking areas, including Hong Kong and Macau, as well as overseas Cantonese-migrant communities. This project will underline Lingnan's unique role in the local and global history of culture and knowledge, situating it in the intersections of the Chinese heritage and the incoming cultures from the West and other culturally active parts of the world.
The remarkable breadth of this project is facilitated by its time-tested team of interdisciplinary investigators, collaborative mechanism, and research design. Cross-disciplinary dialogues will take place in collaborative publications, seminars, conferences, open-access digital database, public lecture series, and exhibitions, which both integrate and triangulate findings. The digital database will also serve as a long-term resource portal for future researchers and the public at large. With these diverse outputs, the project will meet its goals in a historiographical sense, connect scholars across disciplines, and present its findings to the public of the digital age.
Finally, this project aligns with the call for attention on Guangdong-Hong Kong-Macao connections in the new Greater Bay Area development initiatives. It will put Lingnan culture on the global stage, exhibit a collaborative model for Lingnan studies, and contribute to raising awareness and valorizing the value of the Lingnan people and their culture.
Project Reference No. : C4012-22GF
Project Title : Mechanism of Cognitive Flexibility: from Core Brain Areas to Network Analysis
Project Coordinator : Professor YUNG Wing-ho
University : The Chinese University of Hong Kong
Layman Summary
Cognitive flexibility refers to the ability to adjust our thoughts and behaviors according to the changing environment and internal goals. It is often manifested as the adoption of a different strategy to solve a problem at hand or the ability to handle more than one task at a time, that is, multi-tasking. Cognitive flexibility is critical not only for survival but also for maximising rewards and is regarded as a cornerstone of intelligence, a hallmark of higher animals like human and other mammals. A reduced or lack of cognitive control is found in a large variety of brain disorders, including autism, obsessive compulsive disorder, schizophrenia, depression, stroke and neurodegenerative diseases like Alzheimer's and Parkinson's disease. Although a volume of work including our own supports that cognitive flexibility involves the interaction among multiple brain areas in cortical and subcortical regions constituting a high-level control network, little is known in terms of the essential components of this circuit and the neural mechanisms at both local circuit and network levels. Here we propose to exploit the rodent model to address these key questions. We have shown in our preliminary studies that mice can exhibit remarkable flexibility in a variety of strategy-switching and multi-tasking behavioral tests.
Based on the different tests and cutting edge experimental, analytical and modelling approaches, we propose (1) to identify of core brain areas common to different cognitive flexibility tasks, (2) to elucidate the neural activity of local circuits that contribute to cognitive flexibility as well as its improvement via training, (3) to analyse the connectivity among the core brain areas and their dynamics during the exhibition of flexible behaviors, to unveil the modes and principles of operation of the control circuit, and (4) to explore the network mechanisms of cognitive flexibility using computational neural network models. A particular strength of this collaborative research project is that we employ an integrated approach that harness the expertise and synergy of experimental and theoretical neuroscientists. The results will provide a comprehensive set of valuable experimental data as well as a theoretical framework essential for advancing our understanding of the brain mechanisms of cognitive flexibility.
Project Reference No. : C4024-22GF
Project Title : Multi-modal Deep Learning of Multi-omics Profiles, Radiology, and Histopathology Images to Advance Colorectal Cancer Classification for Precision Oncology
Project Coordinator : Professor WANG Xin
University : The Chinese University of Hong Kong
Layman Summary
Colorectal cancer (CRC) is a highly heterogeneous disease with respect to clinical outcomes and biological features, resulting in striking differences in disease progression and treatment response. To interrogate the complex heterogeneity of CRC, we previously contributed to the establishment of the consensus molecular subtyping (CMS) system. Since publication, CMS has been widely used as a robust classification system, setting a foundation for various preclinical and clinical studies.
Despite the versatile clinical utilities, the application of CMS has been significantly limited by several key hurdles. The vast majority of research studies about CRC cannot benefit from the CMS classifier based on gene expression profiling, which is costly and time consuming. Moreover, it remains unclear whether the CMS taxonomy can be applied to Chinese CRC patients, who account for nearly a quarter of the total new incidence worldwide.
In this project, we will leverage multi-modal deep learning of multi-omics profiles, radiology, and histopathology to discover CRC subtypes that are more biologically coherent and clinically relevant. Upon completion, the proposed study will contribute a more robust taxonomy to facilitate biomedical research and clinical applications, provide a versatile classification framework that is clinically translatable, and generate direct evidence of the prognostic and predictive values of CRC subtyping in multiple clinical applications. The accomplishment of the objectives will promote the clinical translation of CRC classification to facilitate precision oncology.
Project Reference No. : C4074-22GF
Project Title : Adaptive 3D Printing: Design, Manufacturing, Modeling and Optimization
Project Coordinator : Professor LIAO Wei-hsin
University : The Chinese University of Hong Kong
Layman Summary
3D printing (additive manufacturing, AM) technologies have been regarded as a promising technology, especially for fabricating structures with very complicated or customized designed features that cannot be obtained by conventional methods. This technology could realize the design and fabrication of models with adaptive designed mechanical properties by adaptive optimized toolpath in both micro- / meso-scales. The functionally graded materials are typical adaptive designed structures with a variation of features inside a model from place to place. In addition, structures with shape memory alloy and shape memory polymer fabricated by the 3D printing process can also realize adaptive properties, which can be deformed with the help of other physical stimuli, i.e., 4D printing - the additional degree of freedom allows the structures to transform over time in a designed and predictive way. In addition, toolpath pattern, which is the geometrical pattern for guiding the movement of laser beam, plays a significant role in controlling the quality of fabricated parts in the AM process. Nevertheless, there are many challenging issues to be addressed. In this collaborative project, we propose the novel adaptive 3D printing technology, aim at enabling the adaptive structure design, manufacturing with adaptive toolpath patterns, data-drive modeling and artificial intelligence (AI)-based toolpath optimization for 3D printing, which further extends the functionality of 3D printed objects by providing extra dimensions - the functionally graded adaptive structure design, novel toolpath generation framework, computationally feasible modeling and optimization methods, and applications with smart functions.
Project Reference No. : C5031-22GF
Project Title : Smart Self-adaptive Shearing Interferometry for Wavefront Optical Characterization
Project Coordinator : Professor CHEUNG Chi-fai Benny
University : The Hong Kong Polytechnic University
Layman Summary
Optical characterization refers to the use of photons of light to determine the properties of materials affecting the acceptability of an optical system or element, which has wide application in many different industrial fields such as the measurement of power maps, cylindrical distribution, and astigmatism axis in optometry and ophthalmology, and beam quality factor, far-field divergence angle and beam waist radius for the laser processing industry. For the characterization of optical materials such as metamaterials, more attention is paid to the refractive index distribution. For advanced optics applications, optical characterization focuses on the measurement of MTF, focal length, distortion, etc. Although there are some devices and instruments that can measure individual optical parameters in specific fields, there is a lack of development of instruments which are able to perform multiple optical properties measurement holistically in a single system. This longer-term interinstitutional collaborative research project led by Prof. Benny C.F. Cheung, Chair Professor of Ultra-precision Machining and Metrology and Director of State Key Laboratory of Ultra-precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. It aims to develop a novel smart self-adaptive shear interferometric (SSASI) method and system for making use of light wavefronts to determine the properties of materials affecting the acceptability of an optical system or element. The SSASI system developed in this project will provide versatile measurement capabilities for the development of interinstitutional frontier research collaboration among researchers from School of Optometry and Research Centre of SHARP Vision of The Hong Kong Polytechnic University on optical characterization of defocus spectacles for human myopia control in optometry and ophthalmology, Chinese University of Hong Kong on laser beam quality and beam shaping for two-photon processing, and City University of Hong Kong on metasurface optical characterization. It will help technology-based companies to validate the surface quality of the critical optical elements used in their products. The project will contribute to scientific advances in precision metrology, material science, optical engineering and measurement science and technology.
Project Reference No. : C5051-22GF
Project Title : Subambient Daytime Radiative Cooling Coating for Energy-Efficient Building Envelope
Project Coordinator : Professor DAI Jianguo
University : The Hong Kong Polytechnic University
Layman Summary
Buildings are responsible for about 90% of the total electricity consumption and approximately 60% of the total carbon dioxide emissions in Hong Kong. Building envelope plays a vital role in the thermal performance of buildings since it is in contact with the external environment that produces great temperature fluctuations and affects the thermal comfort of indoor space. Protective surface coatings are widely used on building envelopes to shield the structures from environmental weathering and to improve their durability and extend their service life. Recently, daytime passive radiative cooling technology has attracted significant attention as a means of energy conservation for building envelopes and represents revolutionary progress to upgrade traditional building coatings. This project aims to develop an innovative category of multi-functional white and colored passive radiative cooling coatings (RCCs) for building roof/wall applications and a smart transparent radiative cooling coating material for window use. The RCCs will be made from inorganic geopolymer, a clinker-free, and low carbon cementitious binder, and imbued with sub-ambient daytime radiative cooling capacity. On the other hand, the smart transparent RCC will be made with double-layer nanophotonic coatings whose properties are temperature-adaptive. The long-term bonding performance of the developed RCCs on different substrate materials and their weathering resistance will be carefully examined. Energy savings from applying these RCCs on building envelopes in relation to different building characteristics and climatic conditions will be determined by combined experimental study and numerical simulation. This research topic is multi-disciplinary and also interdisciplinary, requiring collaborative expertise from civil engineering, nano-optics and optical metamaterials, building energy, and materials science & engineering disciplines, and producing new insights and solutions for tackling the urgent building energy-saving problem highly relevant to Hong Kong and other densely populated subtropical cities. This project will contribute significantly to the net-zero-emission goal set by Hong Kong and the nation.
Project Reference No. : C5053-22GF
Project Title : Sonogenetics for specific deep neural circuit modulation and mitigation of Parkinsonian mice
Project Coordinator : Professor SUN Lei
University : The Hong Kong Polytechnic University
Layman Summary
The use of non-invasive tools to control the activities of defined populations of neurons with high precision is of enormous value for dissecting neural circuits in the brain and treating brain disorders. The existing strategies have their own advantages, but they either are invasive or lack enough spatiotemporal precision. Consequently, the stimulation could be unsuccessful or accompanied with undesired side-effects. Ultrasonic brain stimulation is an encouraging alternative with the advantages of non-invasiveness, fine spatiotemporal control, and deeper tissue penetration. It is considered as a promising method for studying human brain functions and curing brain disorders. However, the minimum focal spot of an ultrasound beam is still much larger than a small set of neurons, making it difficult to pinpoint a small target and precisely manipulate specific neural circuits and induce desired behaviors. To overcome such limits, researchers have proposed "sonogenetics" to sensitize the desired cells for ultrasonic activation, so that only the selected cells will be activated for sufficient precision. However, this idea is still in its nascent stages, to progress past the proof-of-concept stage and consider the significant advantage of ultrasound and the promise for eventual clinical transition, it is therefore compelling to enhance the technology. The success of this research will make a groundbreaking innovation to brain stimulation studies, adding a critical approach for brain stimulation with non-invasiveness, deep brain penetration, and precision. This strategy will open a new dimension for ultrasound brain stimulation to have a significant impact on public health related mental illness and neurological disorders. It may also become an enormously useful research tool in basic neuroscience.
Project Reference No. : C5063-22GF
Project Title : Transmission of antimicrobial resistance from hotspot sources to occupational populations and urban communities
Project Coordinator : Professor LI Xiang-dong
University : The Hong Kong Polytechnic University
Layman Summary
Antimicrobial resistance (AMR) from the overuse and misuse of antibiotics poses a huge challenge to the health of large populations globally. AMR hotspots in urban areas include clinical settings where high doses of antibiotics are prescribed to prevent and treat infections, and waste/wastewater treatment systems that receive high-level inputs of antimicrobial drugs (and residues) and resistance genes. Over 10 million people are employed in these key AMR source sectors worldwide. Personnel working in these major emission source settings are inevitably on the front line of long-term exposure to high levels of AMR. Priority should be given to assessing the risk of AMR among frontline workers at these hotspot locations. The major exposure pathway (e.g., inhalation, contact, and ingestion) for the occupational acquisition of AMR remains elusive in these urban hotspots. It is therefore vital to conduct systematic investigations to identify and quantify the key exposure pathways from sources to humans, and to determine the likelihood of the secondary transmission of AMR from the workplace back to related households and urban communities. In this proposed research project, we will compare the prevalence and profiles of AMR between employees working in typical wastewater treatment plants and public hospitals of Hong Kong against non-working personnel (e.g., connected household members and urban residents) to weigh the importance of different transmission routes leading to occupational acquisition of AMR, and probe the environmental remodeling mechanisms by which exogenous AMR colonize the occupational groups. We will then develop and evaluate a number of innovative and effective technologies ranging from spray control to antimicrobial surface coatings at the critical transmission step(s). The effectiveness of potential interventions in reducing occupational exposure and secondary transmission will be assessed within a dynamic model of AMR transmission pathways. The proposed study can facilitate the formulation of policies and technical guidelines to reduce occupational exposure to AMR in these key emission source locations, prevent the spread of highly resistant pathogenic bacteria to urban communities, and hence contribute to the implementation of a strategic plan to control antimicrobial resistance both locally and globally.
Project Reference No. : C6012-22GF
Project Title : Mechanistic study of the defense systems in marine cyanobacteria against bacteriophage infection
Project Coordinator : Dr. ZENG Qinglu
University : The Hong Kong University of Science and Technology
Layman Summary
Bacteria and viruses are the most abundant biological entities on Earth. Cyanophages, the viruses that specifically infect cyanobacteria, acquire a variety of metabolic genes from the hosts to facilitate viral infection. On the other hand, cyanobacteria have developed diverse antiphage defense systems to prevent infection. For example, cyanobacteria could incorporate exogenous nucleotide sequences from viruses into their genomes to evade infection, which is known as the clustered regularly interspaced short palindromic repeats (CRISPR) system. However, recent studies showed that the marine cyanobacteria Prochlorococcus and Synechococcus lack most of the known antiphage defense systems, indicating that marine cyanobacteria might employ unknown defense systems to fight against cyanophages. The current project will study the interactions between marine cyanobacteria and cyanophages to characterize the key genes and underlying mechanisms of antiphage defense systems. To achieve this goal, we will investigate the antiphage systems in both genome and protein levels. We will also use machine-learning algorithms to mine the antiphage defense systems from cyanobacterial metagenomes. This work will reveal novel antiphage defense systems in marine cyanobacteria and make a significant contribution to understanding the coevolution of cyanobacteria and cyanophages in the global oceans.
Project Reference No. : C6016-22GF
Project Title : High-performance ionic thermoelectric hydrogels for multifunctional smart skin and body heat harvesting
Project Coordinator : Professor HUANG Baoling
University : The Hong Kong University of Science and Technology
Layman Summary
Ionic thermoelectric hydrogels show great potential in low-grade heat harvesting and thermal sensing owing to their ultrahigh thermopower, excellent flexibility/stretchability, low cost and eco-friendliness. Despite significant advance in this area in recent years, the fundamental understanding of ionic thermoelectric phenomena in hydrogels has yet to be developed, which seriously hinder the further development of high-performance ionic hydrogels. Particularly, n-type hydrogels with decent thermopower are quite scarce and the redox thermopowers in aqueous thermocells are quite limited. It is thus desirable to develop effective strategies for modulating the ionic thermoelectric properties of ionic hydrogel for practical applications. Herein we propose to study the ion transport mechanism and its correlation with the ionic thermoelectric properties in quasi-solid-state ionic hydrogels through experimental synthesis/characterization and atomic-level theoretic calculations. Various factors that influence the thermopower in polymer electrolytes, such as composition, fillers, ion-matrix coupling, ion-ion interactions, and temperature, will be investigated. Based on these understandings, different strategies for tuning the thermoelectric properties of ionic hydrogels will be developed to achieve both n-type and p-type hydrogels with high thermopower and decent ionic conductivity for thermodiffusion and thermogalvanic devices. Ionic hydrogel-based multifunctional smart skins and hybrid body heat harvester will then be developed to explore the potential applications of high-performance ionic hydrogels in thermal sensing and low-grade heat harvesting.
Project Reference No. : C6020-22GF
Project Title : Shaping Gas Fuel Storage: Understanding the Thermal Properties of Porous Metal-Organic Frameworks
Project Coordinator : Professor LI Zhigang
University : The Hong Kong University of Science and Technology
Layman Summary
Energy consumption is experiencing a continuous rise. In terms of energy production, the growing worldwide demand on fossil fuels has brought significant environmental issues, especially the climate change caused by carbon emissions. Compared to liquid petroleum and solid coal, gas fuels such as hydrogen (H2) or methane (CH4) are more environmentally friendly owing to their low carbon emissions and higher gravimetric energy densities. The main challenge for gas fuels lies in the storage and transportation that usually require harsh conditions and consume massive amounts of energy, due to their extremely low boiling points, low densities, high critical pressures, and high diffusivities. Porous metal-organic frameworks (MOFs), owing to their ultrahigh porosity, high thermal and chemical stability, are regarded as a potential alternative for gas fuel storage or transportation under moderate conditions. However, in an actual gas storage system, the heat of adsorption (exothermic) and desorption (endothermic) will cause a large temperature change which has a negative impact on the usable gas capacity. In this project, we propose a synergistic scheme, including atomistic simulations and experimental validations, to advance the understandings and manipulate the physical and thermal properties of porous MOFs, and then provide design guidance for the future gas fuel storage systems.
Project Reference No. : C6022-22WF
Project Title : Novel Antibiotics from Genome Mining and Diversity-oriented Synthesis
Project Coordinator : Professor TONG Rongbiao
University : The Hong Kong University of Science and Technology
Layman Summary
Treatment and prevention of bacterial infections with prescribed antibiotics is a routine but important clinical procedure in hospitals. However, infections with bacteria resistant to multiple antibiotics are no longer isolated, sporadic incidents but predictable and evolving cases around the world. Approximately 800,000 people with bacterial infections die annually from antibiotic resistance, and it is predicted that by 2050 antibiotic resistance will be associated with more than 10 million deaths a year. The rise of antibiotic resistance has aroused a growing concern over our ability to effectively control and treat bacterial infections. Discovery of novel antibiotics is urgently needed to expand the arsenal of effective antibiotics with new molecular skeletons. This CRF project proposes to merge genome mining (computational approach) with chemical synthesis at the early stage to boost the discovery of novel antibiotics to combat resistant bacteria. Different from conventional bioactivity-based fermentation/isolation using the Waksman platform, genome mining leverages the publicly available data of bacterial genomes to link the biosynthetic gene clusters (BGCs) with enzymatic production of bioactive natural products. This approach largely overcomes the main limitation of the conventional approach (re-isolation of many known compounds) because > 97% of BGCs encoding new natural products have not yet been explored. As preliminary results, our genome mining led to the discovery of two families of potent antibacterial natural products, polycyclic xanthones (PCXs) and cyclodepsipeptides (CDPs), which also exhibit significant cytotoxicity. In this collaborative project, we aim to use this genome mining approach to identify more members of PCXs and CDPs with high antibacterial activity and reduced cytotoxicity. At the same time, we will launch chemical synthesis of the identified PCXs and CDPs natural products. The chemical synthesis will play a central role in the discovery of novel antibiotics through 1) securing a sufficient supply of lead compounds (natural or synthetic PCXs/CDPs), 2) delivering a library of analogues for activity-toxicity optimization, and 3) confirming the molecular structures of PCXs and CDPs when their structures can not be established by nuclear magnetic resonance analysis. Merging genome mining and chemical synthesis can substantially increase the chance of discovering novel antibacterial compounds for subsequent development into clinical antibiotics. At a later stage of this CRF project, we will attempt to identify the cellular target of our lead antibacterial compounds and elucidate their mode of action. Additionally, mouse models will be used to evaluate the in vivo efficacy and toxicity, providing solid data for preclinical trial.
Project Reference No. : C6026-22GF
Project Title : Improvement of the understanding of the 3-dimensional wind behaviors in urban areas of Hong Kong using Doppler LiDAR system
Project Coordinator : Professor FUNG Jimmy Chi-hung
University : The Hong Kong University of Science and Technology
Layman Summary
The vertical wind speed profile is crucial to Air Ventilation Assessment (AVA) and urban planning/design. However, reproducing vertical wind speed profiles is challenging, mainly due to the practical difficulties in observing upper-air wind conditions especially over urban terrain. In this project, we will use Doppler Light Detection and Ranging (LiDAR) technique (a state-of-the-art ground-based remote sensing technique) to achieve a better understanding of vertical wind profiles in high-density urban boundary layer. The main tasks include establishing a city-scale and long-term LiDAR network in Hong Kong, producing a spatial map of vertical wind profiles using Weather Research and Forecasting (WRF) model, as well as calibrating the current AVA methodology. An improved scientific and practice understanding of vertical wind profiles and the urban wind environment in a high-density city is of reference value to the relevant research community. It will allow better planning/design decisions to be made to improve the city's living environment.
Project Reference No. : C6033-22GF
Project Title : Emerging quantum phases in itinerant magnetic materials with novel electronic and magnetic properties
Project Coordinator : Dr. JÄCK Berthold
University : The Hong Kong University of Science and Technology
Layman Summary
Our lives are built around our ability to access and process vast amounts of information-everywhere and every time. This demand for mobile and remote computational power has fueled the need for ever smaller and more powerful computing chips and, at the same time, driven up the energy consumption of the information technology sector. It is becoming increasingly clear that these trends demand new technological breakthroughs that can address the technological and environmental challenges brought upon us by this fourth industrial revolution. Today, new quantum materials whose macroscopic properties can be designed and realized based on microscopic quantum phenomena show promise to induce the transition into a post-silicon era, in which powerful quantum computer and spintronic devices can operate beyond Moore's law with much reduced energy consumption. In this regard, itinerant magnets present a particularly promising class of electrically conducting materials that were found to host a plethora of interesting phenomena, such as the quantum anomalous Hall state and magnetic skyrmion lattices. These materials combine mobile electrons with localized magnetic moments and long-range magnetic order. It is the atomic-scale interaction between their electronic and magnetic degrees of freedom that creates a particularly large parameter space for such exotic quantum states to exist. The goal of the proposed project is to synthesize rare earth tri-tellurides and transition metal based kagome metals and to explore the emergence of magnetic skyrmions, topological electronic states, and quantum criticality in these materials. These two material classes are ideally suited to reach our goals, because their electronic, magnetic, and topological properties can be accurately controlled by their elemental composition, chemical doping, and strain within an isostructural series. We will combine computational materials design and model calculations with the synthesis of bulk crystals and thin films to fabricate materials with tailored properties. We will apply a broad array of physical probes to experimentally characterize the electronic and magnetic materials properties at microscopic and macroscopic length scales, to map out the magnetic phase diagram, and to identify the emergence of novel quantum states. To that end, our project team unites four experimentalist and one theorist. Their combined expertise in complementary measurement techniques and their international network of collaborators presents a unique opportunity to detect and study the emergent quantum phases of itinerant magnetic materials and to fabricate new materials and devices that could find use in future spintronics and topological quantum computing applications.
Project Reference No. : C7004-22GF
Project Title : Automating Distributed Machine Learning: Algorithms and System Optimization
Project Coordinator : Professor WU Chuan
University : The University of Hong Kong
Layman Summary
With the unprecedented advances in machine learning (ML) and the availability of massive datasets recently, we are now in the golden age of artificial intelligence (AI). Companies and institutions are increasingly deploying expensive AI infrastructure (e.g., AI clouds, GPU clusters), often with heterogeneous hardware accelerators (e.g., GPU, FPGA), to train complex ML models to provision various AI-driven services. To learn a good (often large) ML model (e.g., a deep neural network or DNN) over large volumes of data, extensive ML expertise is often needed, e.g., for constructing the neural network architectures and tuning model hyperparameters in order to achieve the state-of-the-art performance. Unfortunately, many users do not have such expertise. AutoML (aka automated machine learning) arises as a solution that enables non-expert access to ML by automating the process of ML model learning, which promises to substantially facilitate the penetration of AI in various economic, social and health domains. As single-node ML simply cannot scale to massive datasets and large models, distributed ML algorithms and systems, which perform model search and training using multiple accelerator devices and servers, are the new norm in today's AI clouds. In the context of distributed machine learning, AutoML becomes much more challenging, as it now involves a high dimension of tuneable strategies such as model placement and execution ordering over multiple devices, operation and tensor fusion/partition, communication scheduling, etc. Without adequate algorithms and system supports to enable automation, navigating an enormous tuning space for distributed training is a daunting task even for skilled domain experts, and naive solutions could easily lead to significantly low utilization/energy efficiency of the extremely expensive and power-hungry hardware, unacceptably long model training time, and poor model quality. Such low efficiency has been commonly observed among state-of-the-art distributed ML workloads in production AI clouds, especially when the number of GPUs/servers increases. This project aims to investigate highly efficient, optimized algorithms and system strategies to automate distributed ML, with the goal of achieving the most expedited model convergence and the best model performance with the most efficient hardware utilization. We start with neural architecture search and hyperparameter optimization to identify the best DNN models by exploiting distributed search and training. We then investigate distributed model training strategies for computation and communication acceleration, which facilitate automatic neural architecture and hyperparameter selection. We tackle the key issues in the large domain of automating distributed ML, and deploy our solutions in real-world AI scenarios.
Project Reference No. : C7008-22GF
Project Title : The immune microenvironment of recurrent HCC
Project Coordinator : Dr. WONG Carmen Chak-lui
University : The University of Hong Kong
Layman Summary
Hepatocellular carcinoma (HCC), the major form of primary liver cancer, is one of the deadliest cancers globally. There are several causes for the high mortality rate of HCC. First, HCC is highly resistant to traditional cancer therapies such as chemo- and radio-therapies. Second, most HCC patients are diagnosed at late stages which often involve metastasis. Third, even if the patients are suitable for surgeries, which are the most curative options for HCC, tumor recurrence occurs in 70-80% of patients within 5 years of surgical resection. Recurrent HCC becomes even more aggressive. Currently, there is no promising therapy for recurrent HCC. Immunotherapies are treatments that involve the activation of the immune system against cancer. As immunotherapies have emerged as one of the mainstay cancer treatments, a burning clinical question is whether immunotherapies could prevent and treat HCC recurrence. The immune microenvironment of a tumor describes the number, status, and the interactive networks of immune cells within the tumor. The immune microenvironment greatly influences HCC recurrence and importantly response to immunotherapies. To design rational and effective immunotherapies for recurrent HCC, we focus on understanding the relationship of the immune microenvironment and HCC recurrence. With our newly established pre-clinical experimental models for recurrent HCC, we aim to ask two important questions: (1) How does the immune microenvironment affect HCC recurrence; (2) How could we activate the immune cells in the tumor microenvironment by new therapeutic regimens to prevent and treat recurrent HCC? Our work will potentially yield new treatments for HCC recurrence which currently has dismal outcome.
Project Reference No. : C7016-22GF
Project Title : Development of Chemical Probes for YEATS2 and Their Uses in Mechanistic and Pharmacological Studies
Project Coordinator : Professor LI Xiang David
University : The University of Hong Kong
Layman Summary
Epigenetic proteins, which regulate the "writing", "erasing" and "reading" of histone and DNA modifications, are emerging drug targets. YEATS domains, as novel "readers" of histone lysine acetylation (Kac) and crotonylation (Kcr) marks, have been found to link to the initiation and progression of acute leukemia and a panel of solid tumors, such as non-small cell lung cancer. We and others have recently developed ENL, AF9, and GAS41 YEATS domain inhibitors, some of which showed promising anti-cancer effects. However, no inhibitors for the YEATS2 YEATS domain have been reported. We reasoned that the development of such inhibitors could not only provide useful tools to probe the functional roles of YEATS2 in gene regulation, but also offer potential leads for the development of drugs targeting YEATS2. In our pilot trial, we have obtained a cellularly active peptide-based inhibitor of YEATS2 YEATS domain, LS-1-124. In this proposed study, LS-1-124 will serve as a prototype for the construction of DNA-encoded libraries (DEL), which will be used for the selection of more potent and specific inhibitors of YEATS2 YEATS. Inhibitors with satisfactory performances will be further derived into proteolysis-targeting chimeras (PROTACs) to achieve the degradation of YEATS2. The obtained YEATS2-targeting compounds, both inhibitors and PROTACs, will be used to probe the roles, especially the YEATS-dependent ones, of YEATS2 in gene regulation. At the same time, the anti-cancer effects of YEATS2-targeting compounds will be extensively investigated in cell-based and animal models. We envision that the completion of this study may help explicate the biological significances of YEATS2 under physiological and pathological conditions, and also facilitate the development of novel therapeutic strategies for the human diseases associated with YEATS2 malfunctions.
Project Reference No. : C7037-22GF
Project Title : Many-body paradigm in quantum moiré material research
Project Coordinator : Dr. ZI Yang-meng
University : The University of Hong Kong
Layman Summary
Other than the weak-correlated materials on which our daily-life technologies based, such as silicon-based computers, solar cells, or lithium-ion batteries, novel materials based on strong electronic correlations are crucial for the development of the next-generation computing chips going beyond Moore's law, lossless energy transmission through superconductors, and other modern technologies for the major challenges in our society. The emerging 2D quantum moiré materials, e.g., twisted bilayer graphene, and twisted transition metal dichalcogenides, are among the best candidates for future electronics. In these moiré materials, topological flat-bands reduces the kinetic energy so that interactions become dominant and can induce exotic phases of matter such as correlated insulators and superconductivity. In this project, we will combine theory, computation and experimental efforts together, to understand the interplay of topology and correlation physics in the quantum moiré materials from a truely quantum many-body perspective. And in this way, we will be able to develop the many-body paradigm in quantum moiré material and to bring in new fundamental physics discoveries and benefit the society with new generation of quantum materials.
Project Reference No. : C7048-22GF
Project Title : Apocalypse now? Establishing long-term patterns in Austral-Asian tropical forest insect communities in response to global change
Project Coordinator : Dr. ASHTON Louise
University : The University of Hong Kong
Layman Summary
In recent years reports of declines in insect diversity have been widely reported, with most evidence from Europe and North America. Some reports are emerging that tropical insects are also in decline, even in pristine habitats. Divers of insect declines include climate change, insecticide use and habitat loss for agriculture. However, due to a lack of long-term monitoring data of insects in tropical regions, we have a very poor understanding of how insects are changing through time, leading to scientific debate on how universal an "Insect Armageddon" really is. Given that tropical forests tropics hold the highest terrestrial biodiversity and the keystone roles of insects in maintaining functional tropical forests, it is essential that we resolve some of the large uncertainty around how insect biodiversity is changing in these globally important ecosystems. A major factor behind the uncertainty about tropical insect dynamics is that generally long-term data sets do not exist. Unlike in Europe and North America, where high quality historical biodiversity data available, systematic insect sampling in tropical forests has occurred more recently. However, in some locations, tropical field research stations have been operational for many decades, and in these locations insect biodiversity studies (both published and unpublished) represent a valuable insight into how insect biodiversity is changing through time. Locating and harnessing these data sets while continuing to monitor insect diversity is therefore a high priority, to understand how biodiversity is changing, even in protected tropical forests. The rainforests of Australia and South-East Asia are biodiversity hotspots which have undergone large-scale habitat loss since European colonization but still host high levels of endemic biodiversity. We will collate and sample insect data from three field locations across Asia and Australia and use long-term climate and remote sensing data to characterize changes in landscape composition and climate in shaping insect dynamics in tropical forests.
Project Reference No. : C7064-22GF
Project Title : Integrative genome editing and protein engineering approaches to investigate the single- molecule dynamics and structures of microtubules in neuronal development and diseases
Project Coordinator : Dr. TI Shih Chieh
University : The University of Hong Kong
Layman Summary
Microtubules are dynamic cytoskeletal filaments that play critical roles in the development and maintenance of functional neurons by providing structural support to the highly polarized neuronal cells and guiding cargo transport to distinct subcellular compartments (e.g., axon, dendrites, and spines). While disrupting microtubule assembly and organization have been associated with neuronal defects, the underlying molecular mechanism by which microtubule structures and dynamics determine the morphology and functions of neurons remains unclear. This knowledge gap is mainly due to the lack of an integrative approach for a mechanistic understanding of how in vivo phenotypes of model organisms correlate to the biochemical and biophysical properties of in vitro reconstituted microtubules with a defined protein composition. α/β-tubulin heterodimers are the fundamental building blocks that confer the structural basis (i.e., lattice organization) and polymerization dynamics to microtubules. In higher eukaryotes, these tubulin subunits are encoded by expanded α- and β-tubulin gene families (i.e., isotypes) and undergo various post-translational modifications (PTMs). The combination of tubulin isotypes and PTMs has led to the "tubulin code" hypothesis: the diverse tubulin compositions of the filaments control the formation of functional microtubule networks in specific biological contexts, such as neurons. In clinical studies, dozens of mutations in tubulin isotypes or tubulin modifying enzymes have been related to neurological disorders. However, as mutagenesis analyses targeting microtubules cause complex phenotypes and could lead to embryonic lethality in mammals, it has been challenging to reveal mechanistic insights into the roles of tubulin isotypes, PTMs, and disease-related mutations in neuronal development. This proposed research addresses the above knowledge gap through integrative genome-editing and protein-engineering approaches that allow us to dissect the molecular mechanism underlying microtubule-dependent neuronal growth and regeneration. As mutations in MEC-12 (α-tubulin) and MEC-7 (β-tubulin) specifically affect the functions and morphology of the six mechanosensory neurons in C. elegans, we will employ these neurons and tubulin isotypes as a model to investigate the impacts of tubulin PTMs or disease-related tubulin mutations on neuronal development with single-cell resolution. In parallel, we will use our state-of-the-art strategy to generate recombinant MEC-12/MEC-7 for characterizing the structure, dynamics, and motor binding of wild-type and mutant MEC-12/MEC-7 microtubules by single-molecule microscopy. To correlate the genome-edited C. elegans with relevant mammalian neurons, we will further examine the phenotypes of neurons derived from neural stem cells harboring disease-related tubulin mutations. Together, our study will open a new avenue toward a molecular understanding of microtubule-dependent neuronal morphology and functions.
Project Reference No. : C7067-22GF
Project Title : Development of a Monolithic GaN Electronic-Optoelectronic Platform
Project Coordinator : Professor CHOI H.W.
University : The University of Hong Kong
Layman Summary
Gallium Nitride (GaN) is a third-generation semiconductor that has transformed electric lighting through energy-efficient light-emitting diodes, revolutionized optical storage with short wavelength laser diodes and reshaped power electronics with high electron mobility transistors (HEMTs) that can operate at high frequencies and power. These hugely successful devices are processed from wafers with non-identical epitaxial structures that are packaged individually. Building circuits with a combination of these devices, say GaN HEMTs as drivers for GaN laser diodes, would require the assembly these discrete packages on a printed circuit board. Monolithic integration of these devices of different functions would enable systems to be built on a chip-scale level with compactness, robustness and efficiency, just like integrated circuits (ICs) on the Silicon platform. An analogous platform based on GaN that offers both photonic and electronics components would open up vast opportunities in applications such as photonic integrated circuits (PICs), optical communications and optical computing just to name a few. We propose the development of an integrated GaN electronic-optoelectronic platform whereby both photonic and electronic devices can be processed from a single wafer to build functional integrated circuits and systems.
Project Reference No. : C7076-22GF
Project Title : iFactory: Cyber-Physical Factory that Mass Customizes Products
Project Coordinator : Professor HUANG Guoquan George
University : The Hong Kong Polytechnic University
Layman Summary
Based on insights gained from recent research and development efforts, this project is the first to propose and develop an Industry 4.0 intelligent factory following a formal computer architecture and operating system. By so doing, computer hardware and software techniques can be adapted for high-performance factory production management. The breakthrough is achieved through a trilogy of innovations: (1) digitizing a factory with smart IoT devices into a "factory computer" (iFactory); (2) innovating iFactory visibility and traceability (VT) to enable "look around" techniques just as used in the "Out of Order Execution (OoOE)" algorithm by CPUs (Central Processing Units); and (3) developing novel models for iFactory shopfloor operations management. In the proposed iFactory architecture, value-adding units (such as machine tools for changing forms or properties, and forklifts for changing locations of parts/products) are digitized to become intelligent processors. The computational powers, in both hardware and software forms, of digital twins of manufacturing resources (e.g., machines, human operators, materials, tools, storage spaces, etc.) are used to construct the iFactory CPU around the processor. Their IoT devices/sensors collect real-time process and operation data, and update the iFactory CPU memory at a timed heartbeat rate. With every such heartbeat, the CPU carries out its operational decisions for the processor to execute. The iFactory architecture provides new opportunities to explore and study factory uncertainties through cyber-physical visibility and spatial-temporal traceability, and to develop brand-new data-driven decision models for factory operations planning, scheduling and execution. iFactory demonstrates a new approach to implement Industry 4.0 smart manufacturing systems for high performance, responsiveness and resilience.
Project Reference No. : C7080-22GF
Project Title : Generative DfX in high-rise modular building: An expert-augmented cascade graph learning and optimisation approach
Project Coordinator : Professor LU W.W.
University : The University of Hong Kong
Layman Summary
High-rise modular building (HRMB) is highly advocated to address the housing crisis in high-density cities around the world. In line with this advocate is the principle of design for excellence (DfX) that is vigorously explored to unlock the full potential of modular building. DfX encompasses "excellence" criteria such as functionality, ease of manufacture and assembly, logistics, buildability, sustainability, and cost, which require multidisciplinary domain knowledge that is beyond the capability of any single designer. Computer-aided generative design seems to provide a promising strategy to handle the multifaceted knowledge requirement. This project aims to develop a computer-aided, designer-oriented generative DfX methodology for HRMB. We employ graph learning in a top-down manner to generate a rough building (floor plan), then flat design, and finally detailed module design. It then leverages advanced heuristic algorithms to optimise the generated design options from the bottom up, i.e., from module to flat and ultimately to building (floor plan). The process will be augmented by design knowledge and includes human experts in the loop. We will pilot the research in Hong Kong's HRMBs, a rich context for considering DfX in relation to factors including user groups, available construction technologies, manufacturing capacity, logistics, and site conditions. The research will deepen our understanding of HRMB design by considering a wide range of excellence criteria, and may open up a new design paradigm through which humans and machines collaborate to deliver design value.
Project Reference No. : C7082-22GF
Project Title : The Poshan drainage tunnel system as an intensively instrumented hillslope critical zone observatory to explore groundwater dynamics and its engineering and ecological implications
Project Coordinator : Professor JIAO Jimmy
University : The University of Hong Kong
Layman Summary
Hillslopes are important landscape units, especially in Hong Kong, where the terrain is hilly and construction on steep slopes leads to a high risk of landslides. The Government is exploring an option of developing rock caverns as a long-term land supply. However, a major concern is that such caverns will dewater the overlying slope, leading to deterioration of hillslope vegetation. Most landslides are caused by adverse groundwater conditions making it vitally important to understand the hydrogeological characteristics of hillsides. The hydraulic behaviour of hillslope groundwater has been relatively well studied, but the hydrochemical characteristics has received relatively less attention. Groundwater chemistry provides an integrated perspective on groundwater behaviour and chemical weathering, which are directly related to slope stability. Hong Kong's humid, subtropical weather enhances chemical weathering and the release of rock chemicals into the groundwater, leading to changes in composition along its flow path. Understanding chemical weathering and groundwater chemical evolution from its recharge to its discharge has been limited due to the expense of well installation for sampling. The Poshan drainage tunnel system consists of two tunnels and numerous spider drains extending upward from the tunnel roof to the shallow soil layer. The system is equipped with automatic flow and pressure sensors delivering data wirelessly in real time. It is the first of its kind in Hong Kong and even in the world to utilize tunnels and spider drains to form a robust drainage system designed to enhance the long-term hillslope stability by regulating the groundwater table. Such an intensively instrumented system can also serve as an unique hillslope observatory to monitor groundwater compositions and flow dynamics and their engineering and ecological implications. This project aims to explore the spatial-temporal characteristics of hydrogeochemistry and weathering processes inside a volcanic hillslope through long-term, high-frequency observations in the system which probes the various geological units to understand how the geology regulates hillslope hydrology and hydrogeochemical dynamics. The findings will provide not only fundamental scientific insights into hillslope hydrology and hydrochemistry but also recommendations related to public policy and safety and environmental issues related to hillslope stability and cavern development in an urban environment.
Project Reference No. : C7100-22GF
Project Title : Transferable Programming Methods for Mobile Manipulator Task Planning
Project Coordinator : Professor XI Ning
University : The University of Hong Kong
Layman Summary
It is an open, challenging, and critical problem for humans to program mobile robotic manipulators efficiently and intuitively to deal with various tasks that humans can easily do. These tasks normally involve frequent interactions with the environment, such as wiping table surfaces and collecting objects from tables. Traditional robot task programming is done either by hard coding or by human manual guidance using teach pendants or joysticks, both of which require careful tuning of parameters. In addition to the extensive training required for humans to be able to program robots, the program itself is usually task and environment specific and therefore cannot be easily transferred to other tasks or environments. It has been widely recognized that a transferable programming method is critical and essential to massively deploy mobile robotic manipulators on various tasks that exist in human daily life. In this research, a novel transferable programming method for mobile robotic manipulators, based on learning skills from human demonstrations of operations, will be developed. The robot program will be transferable to perform a series of tasks without much reprogramming. The specific technical objectives of this joint research include developing an immersive human demonstration method and system for programming mobile robotic manipulators; developing a transferable robot programming method for robot task planning based on both data-driven and model-driven approaches; theoretical analysis and study of the proposed transferable programming method; and experimental testing and evaluations of the programming method for mobile robotic manipulators in both laboratory settings as well as mock-up and real-world residential care facilities. The outcomes of this research will provide critical technology for the service industry in Hong Kong and create opportunities for training the next generation of scientists and engineers in robotics and health care services.
Project Reference No. : C7103-22GF
Project Title : Dissecting the pathogenesis of SARS-CoV-2 Omicron and emerging variants
Project Coordinator : Dr. CHU Hin
University : The University of Hong Kong
Layman Summary
Key questions on the virological features of Omicron, particularly on the mechanisms of virus infection, transmission, and replication, remain largely unexplained. In particular, current evidence suggests that Omicron is attenuated in virus replication in the lungs but the mechanism underlying its gained transmissibility and infectability remain unknown. This is the most pressing and urgent question for current SARS-CoV-2 research that should be fully addressed before the next pandemic emerge since this vulnerability can be exploited by other pathogens that are potentially more pathogenic than SARS-CoV-2. We hypothesize that Omicron has evolved to utilize additional host factors or utilize known host factors at an altered capacity that collectively contribute to its substantially gained transmissibility and/or infectability. Building on our established findings and platforms, we aim to address these urgent and important research gaps in this CRF study. The results from this project will provide important and novel insights into the pathogenesis, transmission, and countermeasures of the current COVID-19 pandemic, as well as better prepare us for the next highly contagious infectious disease pandemic.
CRF 2022/23 Collaborative Research Equipment Grant (CREG) ProposalsProject Reference No. : C1018-22EF
Project Title : Advanced Integrated In-Situ Laser Molecular Beam Epitaxy and Angle-Resolved Photoemission Spectroscopy Platform for Quantum Materials Research
Project Coordinator : Dr. LI Danfeng
University : City University of Hong Kong
Layman Summary
Quantum materials are those materials, in which quantum mechanical effects become dominant and/or produce intriguing "unseen" features. The design, synthesis and probing of quantum materials have now witnessed a remarkable level with atomic resolution. This quest for novel quantum phases and exotic quantum phenomena, as foundational premises to future technological applications, usually requires advanced techniques under extreme conditions and with ultra-high precision manipulation. To access the intrinsic "information" of the materials connecting these instruments to achieve an in-situ setup becomes the key. This project will construct Hong Kong's first "L-MBE+ARPES" system combining laser molecular beam epitaxy and angle resolved photoemission spectroscopy. This system will serve as a state-of-the-art platform integrating an "atom-by-atom" synthetic approach of quantum materials and a direct measurement of the electronic structure of the fresh surface of the grown materials. The growth-transfer-measurement strategy is pivotal to revealing the band structure, the surface states, the quantum confinement, and uncovering new exotic physics. The project aims to develop the system into a unique, powerful, sustainable, and user-friendly in-situ platform for quantum materials research.
Project Reference No. : C4001-22EF
Project Title : Hyperscanning to Explore the Human Mind in Ensemble
Project Coordinator : Professor WONG Patrick Chun Man
University : The Chinese University of Hong Kong
Layman Summary
We seek to establish the fNIRS Hyperscanning Shared Facility (fHSF), the first hyperscanning facility in Hong Kong for the study of human cognition in small groups. fHSF will enable local researchers and their collaborators to address next-generation questions about the human mind that go beyond one or two brains. fHSF will host a wireless, 10-person functional near-infrared spectroscopy (fNIRS) system for studies that require measurements of brain activities of up to 10 people simultaneously. The portable feature of this system and the advantage of fNIRS in accommodating small movement artifacts will facilitate a range of studies that require greater ecological validity in their behavioral paradigms and flexibility in their study populations. Our team of Co-PIs will conduct research in four areas to deepen our understanding of the human mind beyond our behavioral and single-person/two-person neuroimaging research. Area 1 (Group Communication and Relationships) will explore questions concerning the neural emergence of a leader, the mechanisms and plasticity of group conflicts, and the neural underpinnings of multilingual communication in small groups. Area 2 (Learning and Musical Performance in Group Settings) will attempt to offer biological explanations as to why learning outcomes may be affected by class size and the virtual learning modality. Similarly, we will investigate how neural synchrony of musicians performing in an ensemble may explain aesthetic outcomes. Area 3 (Family Systems) will consist of studies of the neuroscience of families, focusing on how relational variables (e.g., marital satisfaction) and behavioral intervention may modulate brain functions of members in young and intergenerational families. Area 4 (Communication Disorders) will investigate the neural basis of communication disorders that are by definition social (e.g., autism) or are exacerbated by an increase in group size (cognitive-based communication disorders). In addition to requiring a 10-person fNIRS system, new data acquisition and analytical approaches will need to be developed to meaningfully connect online behavioral variables and multi-person neural synchrony patterns. fHSF will develop and adapt new approaches for our studies and will also publish a new software program to assist with analyzing data from multi-person fNIRS experiments. Our team of Co-PIs consists of members from four local universities who have collaborative experience ranging from publications, RGC collaborative research grants (two CRF and one TRS projects), to establishment of a core MRI facility. The research institute that the PC directs will provide the necessary space to host fHSF.
Project Reference No. : C4062-22EF
Project Title : Establishment of Spatial Multi-Omics Core Facility
Project Coordinator : Professor CHAN Andrew Man-lok
University : The Chinese University of Hong Kong
Layman Summary
The major goal of this Collaborative Research Fund (Equipment Grant) is to establish a Spatial Multi-Omics core facilitate in Hong Kong. The human body is composed of approximately 37 trillion cells and around 200 different cell types. All these cells are organized in a highly compartmentalized manner, and their physical positions are regulated throughout life under either healthy or disease condition. To study human disease such as cancer, scientists normally study one cell type at a time in the laboratory. Alternatively, tissues are harvested and dissociated into their single cell constituents that can result in the loss of spatial information. The machine that we are planning to purchase can generate detailed molecular information of intact tissues at single cell resolution while preserving the spatial information of all cell types. The information generated will help in understanding the mechanism of some common human diseases such as cancer and Alzheimer's disease. The ability of this machine in discovering new drug targets will help future development of effective treatments for diverse diseases. Finally, this equipment will be available to all researchers in Hong Kong.
Project Reference No. : C5032-22EF
Project Title : Hong Kong Coastal HF-Radar Network
Project Coordinator : Dr. STOCCHINO Alessandro
University : The Hong Kong Polytechnic University
Layman Summary
High Frequency Radar (HFR) technology refers to land based remote sensing equipment capable of measuring surface currents and waves over distance up to few hundreds of km. Coastal radar technology is now widely recognized as a cost-effective and highly reliable tool to monitor coastal regions for both superficial current and wave climate in real time. It can be safely said that HFRs monitoring networks overcome several limitations of more standard oceanographic techniques based on ship-mounted instruments or moorings. The success of this technology is further demonstrated by the steadily increasing number of radar stations worldwide. The interest and need of a real-time areal ocean and coastal monitoring has now gone beyond the boundaries of the scientific community, reaching the interest of the government authorities assigned to the protection of the coastal environments and to the management of the risks related to natural events and human activities (maritime traffic, unwanted pollution releases). This is also due to the reliability and operability of the radar networks. At a regional level, HFRs networks provide real-time data in support of operational activities such as search and rescue operations, rapid responses in case of maritime accidents and spill of pollutants, and resource management. The wealth of information provided by a HFRs network has proven to be the best source of quantitative data for many oceanographic and coastal engineering research topics. The possibility to collect long time series of currents and wave over wide areas is of paramount importance for improving the quality of the coastal numerical models, understanding transport properties and connectivity of the different ocean basin (or coastal areas and the open ocean). In the present project we aim to design, deploy, and test a local high resolution HFRs network to cover two of the most interesting spots of the Hong Kong Waters, namely the Central Waters and the exit of the Pearl River Estuary. The radars will provide high resolution current and wave data over a range of few tenth of km. The new network will contribute to enormously increase the regional monitoring capabilities and the data will be shared to a wide range of stakeholders, from the scientific community to all governmental departments involved in coastal engineering, coastal protection against floods and extreme events and environmental management. The proposed network could be the cornerstone for several future research projects.
Project Reference No. : C6006-22EF
Project Title : A collision-cell equipped multi-collector inductively coupled plasma mass spectrometer (CC-MC-ICP-MS) for elucidating isotope fractionations in biological and chemical processes in the ocean
Project Coordinator : Professor ZHANG Qiong
University : The Hong Kong University of Science and Technology
Layman Summary
Trace metals, such as Fe, Cu, Zn, and Mn, are fundamental components of life. As essential elements of metalloproteins, they regulate the biogeochemical processes of key elements (e.g., oxygen, nitrogen, sulphur, and carbon) in the ocean and thus influence the functioning of ocean ecosystems and the global carbon cycle. Many trace metals have multiple stable isotopes that can be "fractionated" due to subtle differences in reaction rates and/or chemical bond strengths in different biogeochemical processes. The resultant variations in isotope ratios can be measured using high-resolution mass spectrometry. Metal stable isotopes are useful for tracing natural processes of global interest: the international collaborative project GEOTRACES measures many trace elements and their isotopes across the global ocean. The diverse array of metal isotopes measured in seawater, sediments, and glacial deposits are used to trace anthropogenic contaminants, provide new insights into modern-ocean processes, and reconstruct critical processes responsible for climate change over geological history. Despite the recognised importance of trace metal isotopes in the ocean and the increasing number of metal isotopes measured, there was no conceptual framework that can be widely applied across different isotope systems. More work is required to fundamentally understand the complicated oceanic processes that underlie the large-scale features observed in global datasets. Advances in instrumentation have made high-precision isotopic analysis more accurate, and the pace of investigation has quickened over the last decade motivated by the desire to develop these new tools as biogeochemical tracers that can be used to understand environmental and climate change. However, here in Hong Kong, we still lack the key infrastructure, including the trace-metal-clean laboratory and proper instrument, for measuring the stable isotopes of ultra-low-abundance trace metals in the marine environment. Therefore, we will build a metal-free-clean-suite, which is essential for sample preparation, and acquire a state-of-art dual-path collision cell-equipped multiple-collector inductively coupled plasma mass spectrometer (CC-MC-ICP-MS), to enable the ability for stable isotope analysis. Located in the Department of Ocean Science, HKUST, this facility will serve the whole scientific community in Hong Kong. This project will support numerous ongoing and prospective research projects investigating the biogeochemical processes governing the nutrient cycles, carbon pump, climate, food webs, and ecosystem structures in the modern, past, and future global ocean. The facilities will enable us to conduct cutting-edge research in ocean science and technology and develop foundations for the next generation of researchers.
Project Reference No. : C7070-22EF
Project Title : Establishment of light-sheet based microscopy systems for multidisciplinary biomedical research
Project Coordinator : Professor YU Cheng-han
University : The University of Hong Kong
Layman Summary
Spatial and temporal visualizations of the living matter are essential to drive the innovation of biomedical research. Light-sheet based fluorescence microscopy is an emerging imaging technique that decouples the illumination and detection paths and is designed to overcome the issues of light scattering and phototoxicity. Sheet-like excitation light is used to illuminate the specimen, and the detection lens is placed perpendicular to the light sheet and allows efficient collection of emitted fluorescence from the excitation plane of light sheet. Here, we aim to establish light-sheet based microscopy systems for multidisciplinary biomedical research. Specifically, we will acquire one Gaussian light-sheet microscope and one lattice light-sheet microscope to address various biomedical challenges ranged from organismal to the subcellular level. The establishment of light-sheet based microscopy systems will bring new collaborations among researchers in Hong Kong and make significant contributions in cell and cancer biology, as well as stem cell differentiation and neuroscience.
Project Reference No. : C7098-22EF
Project Title : Development of an ambient-operating correlative light and electron microscope (airCLEM)
Project Coordinator : Dr. YIN Xiaobo
University : The University of Hong Kong
Layman Summary
This project aims to develop an ambient-operating correlative light and electron microscope (airCLEM) at the University of Hong Kong. The instrument removes all major specimen constraints encountered in conventional electron microscopes. The airCLEM is enabled by a vacuum-sealing and electron-permeable silicon nitride (SiN) membrane, which seals the entire electron optics column and isolates it from the ambient, 1-atm working environment. It has been shown that a freestanding, 100-nm-thick SiN membrane can sustain a pressure difference much greater than 1 atm and allow more than 80% transmission of 30 keV monoenergetic electrons. When the energetic electron beam is focused just below the membrane with a distance shorter than its air scattering length (~70 um), its focusing and imaging capabilities remain undeteriorated, enabling unprecedented correlative optical imaging and spectroscopy at nanometer resolution on any type of sample, regardless of its condition-solid or liquid, conductive or insulating, organic or inorganic. Highly hydrated specimens and dynamic processes occurring at the liquid-vapour interface and even liquid-liquid interface, previously impossible for a conventional electron microscope, can be studied in real-time and even with reactive flows. Example of applications includes charge transfers of photosynthesis compounds, quantum efficiency analysis of organic semiconductor nanostructures, and watersplitting electrochemical cells. The airCLEM further allows localised cathodoluminescence (CL) excitations in air, removing sophisticated parabolic imaging optics, vacuum feed-through, and low light collection efficiency that limits the conventional CL imaging and spectroscopy technologies. The parfocal configuration of airCLEM optics and electron optics allows the detection and imaging of material-specific, angle-resolved, polarisation-discriminated light emissions over a full 2pi solid angle. It ensures correlative imaging with nanometer precision. For the first time, materials and specimens of interest can be simultaneously imaged and spectroscopically analysed under both a light microscope and an electron microscope without tedious process. The wide availability of such a unique technology and instrument is critical to moving emerging interdisciplinary research on today's highly complex materials forward. The platform will bring together materials scientists, physicists, chemists, engineers, and biologists, offering unprecedented research opportunities by providing electron beam technology to application areas where it has previously been prohibited.
CRF 2022/23 Young Collaborative Research Grant (YCRG) ProposalsProject Reference No. : C1002-22Y
Project Title : Large-scale lithium niobate photonic integrated circuits for neuromorphic computing
Project Coordinator : Dr. WANG Cheng
University : City University of Hong Kong
Layman Summary
The rise of artificial intelligence (AI) in recent years is accompanied by rapid growth in computational demands by 10-fold every year, while the computation power of traditional electronic processors "only" increases by 40% following Moore's law, leading to the use of more and more processors and in turn power consumptions that will soon become insurmountable. Integrated photonics is an excellent solution to address this issue since light signals interact with each other in a highly parallel and low-latency manner. The proposed collaborative research aims to develop a compact, low-power and highly adaptive photonic neuromorphic computing system using the recently emerged lithium niobate photonics platform, which offers the possibility of achieving large-scale, fast-programmable and low-loss photon manipulation on chip simultaneously. The lithium niobate photonic chip will be further flip-chip bonded with photodetectors and co-packaged with low-power electronic control circuits to achieve fully functional photonic neuromorphic computing systems for fast-reconfigurable AI acceleration and intelligent optical fiber signal processing applications.
Project Reference No. : C2002-22Y
Project Title : Climate- and environment-conscious urban growth in the Guangdong-Hong Kong- Macau Greater Bay Area (GBA): solutions and co-benefits
Project Coordinator : Dr. GAO Meng
University : Hong Kong Baptist University
Layman Summary
Global warming caused by human activities have invoked more intense and frequent extreme weather events around the world, and urbanization plays a nonnegligible role. Urban growth has been taking place at unprecedented pace and it is anticipated to continue in the future. Urbanization induces not only convenience of living and better access to healthcare, but it also creates a series of social and environmental issues. How we act to alleviate the adverse effects of urbanization remains a challenging issue, which requires knowledge in multiple disciplines, including urban planning, atmospheric science, environmental engineering, etc. Different spatial arrangement and distribution of urban lands are likely to significantly affect the magnitude of urban warming, diffusion of air pollutants, and human exposure to these risk factors. It has been demonstrated previously that compact and sprawling urban growth is prone to trigger intensified urban warming and to exert greater human heat stress. The Guangdong-Hong Kong-Macau Great Bay Area (GBA) was proposed in recent years as a key strategic planning in China's development blueprint, and the planning and development of the GBA is still in the early stages. A careful and thoughtful planning of urban lands would benefit urban climate, environment and human health, without sacrificing the goal of urban growth and economy development. Besides, how to better assess the impacts of the planning of lands on climate, environment and human health remains a concerned issue, as China plans to achieve carbon peak and carbon neutrality. To address these essential issues, this project aims to offer solutions to climate- and environment conscious urban growth, and to assess the co-benefits of climate, air quality and human health. This will be achieved with a team composed of members who have expertise in urban planning, climate science, atmospheric chemistry, and environmental health. In this project, we will develop a tool to optimize arrangements of lands to reduce urban warming, air pollution, and human exposure. A coupled climate-chemistry model will be improved with better secondary formation of pollution from urban sources. This modeling tool will further be used to assess how the optimized land arrangements would benefit urban warming and air pollution. The co-benefits of human health will also be assessed with cohort data. The results would offer valuable implications for the development of the GBA and contribute to the achievement of carbon peak and carbon neutrality.
Project Reference No. : C2005-22Y
Project Title : A novel TCM-based network pharmacology framework to human diseases and drug-disease relationship
Project Coordinator : Dr. TIAN Liang
University : Hong Kong Baptist University
Layman Summary
Traditional Chinese Medicine (TCM) is now practised worldwide for disease treatment using herbal ingredients. Although extensive research has been conducted for decades to quantify the effectiveness and efficacy of individual TCM compounds for drug discovery in a bottom-up manner, the pharmacological principles in TCM theory, developed over thousands of years, remain elusive from the perspective of modern medicine. This has impeded the modernization and standardization of TCM. To address this issue, we have assembled an interdisciplinary team of local and international scientists from various fields, such as physics, traditional Chinese medicine, data science, computer science, chemistry, and biology, among others. The team aims to elucidate the pharmacological principles of TCM theory in a top-down manner using state-of-the-art big-data and AI technologies, and to foster a novel TCM-based network pharmacology that quantitatively predicts disease-herb associations. This project aligns with the establishment and development of Hong Kong's first Chinese Medicine Hospital by Hong Kong Baptist University. It aims to provide a new perspective and objective basis for the diagnosis and treatment process of TCM and the integration of TCM evidence-based medicine with modern biology. As TCM strives to become an integral part of global healthcare, this project will help better understand its working principles and integrate TCM with other treatment methods, thereby contributing to the wellness of people worldwide.
Project Reference No. : C4001-22Y
Project Title : Light Protects Vision: Optogenetic Activation of Trk Signaling for Neuroprotection of Retinal Ganglion Cells in Ocular Diseases
Project Coordinator : Dr. DUAN Liting
University : The Chinese University of Hong Kong
Layman Summary
Retinal ganglion cells (RGCs) are retinal neurons that bridge visual input to the brain. RGC death can lead to vision impairment and blindness in many debilitating ocular diseases, such as retinal ischemia, diabetic retinopathy, and glaucoma. To date, no treatment can reverse RGC death or restore vision loss. Neuroprotective strategies that preserve RGCs hold great promise to prevent and treat these diseases. Mounting evidence indicates that neurotrophin/tropomyosin receptor kinase (Trk) signaling is neuroprotective to RGCs in disease states. However, the neuroprotective efficacies of current methods to activate Trk are compromised by the lack of specificity and controllability.Here based on optogenetic strategies, we will use light signals to activate Trk signaling in RGCs with unique advantages, including remote control, non-invasiveness, on/off switch, tunability in activation levels, and high specificity. We will evaluate the light-inducible neuroprotection in animal models of ocular diseases. In the long run, our work will present new opportunities for optogenetics-facilitated therapy for RGC death-implicated diseases.
Project Reference No. : C4002-22Y
Project Title : Developing Next-generation Mid-infrared Laser Sensors for Greenhouse Gas Monitoring
Project Coordinator : Professor REN Wei
University : The Chinese University of Hong Kong
Layman Summary
Global climate change is driven by the accumulation of greenhouse gases (GHGs) present in the atmosphere. Accurate monitoring of GHGs (carbon dioxide, methane, nitrous oxide, and fluorinated gases) is critical for local authorities to improve oversight and achieve carbon neutrality. Existing GHG sensors lack the full capability of high precision, high sensitivity, large dynamic range, multi-species detection, and field deployment. Optical frequency comb, a Nobel Prize-winning technology, provides a broadband coherent light source that emits hundreds or thousands of laser lines simultaneously. The unique combination of large bandwidth, high resolution and fast response makes frequency combs promising for the next-generation gas sensor development. The recent breakthrough of mid-infrared comb generation by electrically pumped quantum cascade lasers (QCLs) makes it possible to obtain a miniaturized and integrated chip-based gas sensor. In this project, we propose to develop novel sensor instrumentation for GHG detection using QCL-based frequency comb spectroscopy. Based on the emerging technique of dual-comb multi-heterodyne detection, we will first investigate the methods of controlling the repetition rate and offset frequency of QCL-combs. With the stabilized QCL-comb source, we will develop an ultrasensitive dual-QCL-comb sensor by extracting gas samples into a multipass cell or optical cavity; study theoretically and experimentally the fiber-enhanced dual-comb gas detection; finally deploy the sensor prototype for GHG monitoring in street canyon districts. Our proposed research will have a long-term impact by improving our understanding of GHG emissions and climate effects, accurately predicting their future changes, and enabling vigorous policies and measures to be formulated.
Project Reference No. : C4004-22Y
Project Title : Artificial Intelligence (AI)-assisted Risk-based Prostate Cancer Detection: A Synergy of Novel Biomarkers, Advanced Imaging, and Robotic-assisted Diagnosis
Project Coordinator : Professor CHIU Peter Ka-fung
University : The Chinese University of Hong Kong
Layman Summary
Prostate cancer (PCa) is the second most diagnosed male cancer worldwide, and its incidence in Asia is predicted to double within the next 20 years. Although the blood test prostate specific antigen (PSA) can be used for early diagnosis of prostate cancer, its accuracy is very low and frequently leads to a lot of unnecessary invasive biopsy. Due to the lack of an effective screening program, population screening is not performed and about 25-50% of prostate cancer in Asia is diagnosed in an advanced incurable stage. Our multidisciplinary team includes experts in prostate cancer management, novel biomarker development, bioinformatics, artificial intelligence (AI)-assisted medical diagnosis, and medical robotics. Promising results have been observed in our pilot studies in every part of this collaborative study, including the novel urine spermine test and a new microRNA panel for PCa diagnosis in Chinese men, AI-assisted automated prostate tumor detection in high-resolution ultrasound and MRI images, machine learning algorithms in PCa diagnosis, and a new robotic platform for MRI-guided prostate biopsy. Our current biopsy database and stored biologic samples and ultrasound/MRI images from hundreds of patients investigated for PCa in the past decade was used for developing the algorithms and these will be tested prospectively in this study. This proposal aims to create a novel, multi-modal, automated screening and diagnostic pathway for PCa involving urine tests, blood tests, imaging, and machine learning. This involves 5 steps: (1) Novel urine spermine and blood microRNA biomarkers, (2) Advanced robotic-assisted ultrasound imaging with AI-aided diagnosis, (3) Automated AI-aided Magnetic resonance imaging (MRI) diagnosis, (4) Machine learning techniques to estimate cancer risk based on biomarkers and AI-assisted imaging, and (5) robotic-assisted prostate biopsy. As there are millions of men that needs prostate cancer screening, we aim to design an automated screening algorithm which does not need a doctor's interpretation from steps 1 to 4. Doctors will determine if the patient needs a robotic-assisted MRI-guided prostate biopsy (step 5) according to the calculated risk score from step 4. In this project, prospective clinical validation of the above multi-modal diagnostic algorithms will be performed in 200 newly recruited men at risk of PCa. Our vision is to diagnose all clinically important PCa at a curable stage by instigating a new paradigm of AI risk-based cancer screening, while minimizing harm to patients and manpower costs.
Project Reference No. : C4005-22Y
Project Title : Fundamental-Studies-Guided Growing of High-Quality, Mechanically Stable, Reduced-Dimensional Perovskites for Scalable Flexible Optoelectronic Devices
Project Coordinator : Professor LU Xinhui
University : The Chinese University of Hong Kong
Layman Summary
Flexible optoelectronic devices, such as solar cells, light-emitting diodes and photodetectors, have great potential in real-world applications, including portable electronics, smart buildings and green houses, owning to their light weight, conformability and compatibility to large-scale roll-to-roll fabrication. Among all existing optoelectronic materials, halide perovskite stands out as a promising candidate for the active layer, as it offers adjustable bandgap, excellent device performance, and solution and low-temperature processibility. However, previous research studies on flexible perovskite devices (FPDs) were mainly based on experiences adopted from rigid devices. Key mechanisms of perovskite crystal growth on flexible substrates, as well as the correlation between composition, structure, mechanical properties and device performance remain elusive. This project plans to tackle these fundamental questions by a synergistic interdisciplinary collaborative effort of state-of-the-art structural characterization, computational simulation, interfacial engineering, and device engineering. We aim at developing mechanically stable, highly efficient, scalable FPDs through the proposed multi-length scale, static and kinetic studies combining theories and experiments. We will make use of the unique advantage of reduced-dimensional halide perovskite – the huge tolerance in mixing organic and inorganic components. The inorganic components contribute the optoelectrical functions, while the organic components maintain structural and mechanical stability by tuning the dimensionality and cross-linking grains and interfaces. The project will include three primary tasks: (1) the design of high-quality, mechanically stable, reduced-dimensional perovskite materials; (2) the study of perovskite film formation on flexible charge transport layers; and (3) the development of scalable fabrication and versatile device application.
Project Reference No. : C5002-22Y
Project Title : Coastal Urban Flooding under Climate Change: Evolution Mechanisms and Intelligent Analysis
Project Coordinator : Dr. DUAN Huan-feng
University : The Hong Kong Polytechnic University
Layman Summary
Under the influences of climate change, rapid urbanization and population growth worldwide, the living environment and survival resource situations become more and more challenging for mankind on the earth. Extreme climate and weather conditions, associated with hazards and disasters such as flooding, has been one of these consequences, which is especially prominent and critical for coastal regions due to compound impacts of sea level rise. For example, the recent super-typhoons "Hato" in 2017 and "Mangkhut" in 2018 have induced severe flood disasters in Hong Kong and other cities within the Greater Bay Area (GBA) of China. From a long-term point of view, about 15–28% of current coastal resident areas in the GBA of China are expected to be frequently flooded in 2100 due to the extreme weather events associated with climate change. This situation highlights the imperative need for coastal flood risk assessment in this coastal region. This collaborative research project explores the underlying mechanism and dynamics of coastal urban flooding under climate change, thereby developing an intelligent framework for coastal flooding analysis and risk assessment. To this end, this project involves inter-disciplinary and multi-institutional collaborative research on addressing coastal urban flooding issues through cutting-edge theory and advanced model development. The project team consists of five outstanding and energetic young researchers from three local universities (PolyU as coordinator, HKU and HKUST as key collaborators) and one senior researcher from an overseas collaborating university. Through their close collaborations, the following three key scientific problems and research contents are investigated: (1) spatiotemporal evolution characteristics of coastal compound events under climate change; (2) dynamic modeling and mechanism of coastal wave-runoff interactions and coastal flooding processes; and (3) intelligent framework of coastal flooding risk analysis. For this purpose, a comprehensive research methodology has been planned in this project and will be applied for systematic investigation in Hong Kong. This collaborative research project is expected to provide various benefits and positive impacts in the short, medium and long terms. In particular, the achievements and deliverables of this project could provide scientific foundations and technological supports for the prevention and mitigation of coastal urban flooding in Hong Kong and other coastal cities, so as to facilitate the strategic development of a sustainable and smart city in Hong Kong.
Project Reference No. : C6001-22Y
Project Title : Scalable manufacturing of antiviral self-cleaning surfaces against respiratory infectious diseases
Project Coordinator : Dr. LI Guijun
University : The Hong Kong University of Science and Technology
Layman Summary
Infectious respiratory diseases are severely affecting modern societies. There is a high risk of transmission of respiratory infectious diseases in public places. This collaborative project aims to develop a scalable-manufacturable antiviral surface that can be easily deployed in public facilities to mitigate the spread of respiratory infectious diseases. We will create these long-lasting self-cleaning surfaces to remove most droplets, ciliated surfaces to remove the sticky mucus, and metal nanoparticles to inactivate any remaining viruses. We will develop a roll-to-roll integrative system to scalable manufacture these films and test their antiviral performance at public places such as public traffic vehicles and hospitals.
Project Reference No. : C6003-22Y
Project Title : Toward 2060 Carbon Neutrality: Life-cycle Planning and Design of Photovoltaic Integrated Green Roof (PVIGR) Systems for Hong Kong and the Greater Bay Area
Project Coordinator : Dr. WANG Zhe
University : The Hong Kong University of Science and Technology
Layman Summary
The photovoltaic integrated green roof (PVIGR), where PV panel is placed over green roof, is a promising technology that is especially suitable for densely populated cities such as Hong Kong, because of its multiple carbon emission reduction, synergy between PV and green roof, and other environmental benefits. In this project, we aim to develop a first-of-its-kind location-specific optimized PVIGR design toolkit for Hong Kong and the Greater Bay Area, and then quantify the life cycle costs and benefits of PVIGR. To achieve this goal, we propose the following major research tasks: (1) to develop a novel model to assess spectral solar resources based on remote sensing, radiative modelling, and deep learning; (2) to develop heat and mass transfer model to investigate the thermal interactions among PV, green roof, building, and local micro-climate, which will be validated by experimental data; (3) to develop a web-based PV/PVIGR generation potential map that can help select the suitable roof space for PVIGR, and decide the optimal PV installation capacity; (4) to quantify the life-cycle environmental and social benefits of PVIGR through city-scale building energy simulation and public health analysis. The proposed project can help Hong Kong and GBA achieve its carbon neutrality goal in a more efficient way.
Project Reference No. : C6004-22Y
Project Title : Design Paradigm of Multiphase Soft Composite Materials with Emergent Mechanical Properties
Project Coordinator : Professor XU Qin
University : The Hong Kong University of Science and Technology
Layman Summary
Soft composites are widely used in various engineering applications, including soft robots, switchable adhesives, and smart sensing devices, due to their rich mechanical behaviors. Further, multiphase soft composites have been ideal model systems to study phase transition dynamics in biological cells. Therefore, a comprehensive understanding of the mechanics of soft composites is essential from both the engineering and scientific perspectives. However, due to complex interactions across a hierarchy of length scales, design principles of soft composites with novel mechanical features are currently lacking. To address the challenges, we will focus on model composite systems with at least one soft elastomer component to maintain a high extensibility, while a second phase will be incorporated into the elastomer based on desired functional responses. To explore multiphase interactions on different scales, particle-elastomer, droplet-elastomer, and fiber-elastomer composites, will be investigated. The expected results from the research will help to understand the mechanics of soft composites beyond classical theories. We also believe that the proposed design paradigms will improve the mechanical performance of many soft devices that fill the current gaps in natural materials.
Project Reference No. : C7002-22Y
Project Title : Zintl-related compounds for enhanced energy efficiency
Project Coordinator : Dr. CHEN Yue
University : The University of Hong Kong
Layman Summary
Polyanions that are covalently bonded in Zintl compounds accept electrons from cation compositions, resulting in electronic structures attractive for a range of energy-related applications. In this project, high-throughput screening will be carried out for the class of Zintl-related compounds using machine learning approaches to identify potential high-performance materials. Rigorous quantum-mechanical-based calculations will be performed to achieve a more complete understanding of the relation between electron-phonon coupling and the anharmonic lattice dynamics. The results obtained from different levels of theories will be verified by experimental studies. High-performance energy conversion devices will be fabricated for practical applications. Successful implementation of this project will not only provide an in-depth understanding of novel transport mechanisms but also facilitate real-world applications of Zintl-related compounds in energy conversion technologies.
Project Reference No. : C7003-22Y
Project Title : Development of wireless-powered optoelectronic device for precise control of bone homeostasis through the modulation of skeletal interoceptive circuit
Project Coordinator : Dr. QIAO Wei
University : The University of Hong Kong
Layman Summary
Despite great advances in our understanding of bone biology in recent years, there has been a limited therapeutic approach to precisely control bone metabolism and regeneration. Our recent findings show that, upon stimulation, the sensory nerves located in bone tissues can convey the signals to the central neural system to drive new bone formation. This project aims to develop a wireless-powered implantable device that can activate the sensory nerves in bone tissue with optogenetic technology. Therefore, this system provides a revolutionized strategy, which is potentially cheaper, simpler, and safer than conventional methods, for the therapeutic management of challenging orthopedic conditions, such as osteoporosis and non-union fracture.
Project Reference No. : C7004-22Y
Project Title : Development of therapeutic CRISPR-Cas enzymes for gene therapy
Project Coordinator : Dr. WONG Siu-lun, Alan
University : The University of Hong Kong
Layman Summary
With the initial clinical success of using CRISPR for gene therapy, there is a rising need for engineering compact CRISPR-Cas systems that can be delivered and perform more efficiently for gene editing in vivo. To boost Cas enzyme's activity while minimizing off-targeting effect, it requires the fine-tuning of the intricate balance of its contact with both the target DNA and sgRNA. To effectively explore the functional impact of mutagenesis of these contacting residues to guide Cas optimization, we propose a machine learning (ML)-assisted method to vastly condense the number of variants needed to be tested experimentally via systematic mutagenesis of multiple sites. We have succeeded in generating and cross-validating in silico and experimental datasets of multi-domain combinatorial mutagenesis libraries for Cas engineering. Our preliminary results showed that the ML approach reduces the experimental screening burden by as high as 90% while enriching top-performing variants by ~7.5-fold compared to the null model. This pioneering approach in coupling ML with experimental combinatorial mutagenesis en masse enables us to readily explore protein fitness landscape for optimizing protein function in a resource-efficient manner. The CRISPR technology is advancing rapidly. Here we will explore small-sized Cas systems to improve their activity, genome-wide specificity, and/or targeting range using our ML-coupled combinatorial mutagenesis platform. In vivo therapeutic efficacy of the top-performing candidates will be thoroughly characterized. Moving towards translating CRISPR technology for gene therapy, additional aspects to precisely control Cas expression and activity using advanced technologies such as near-infrared light-responsive ribonucleoprotein system for delivering Cas9 systems will be explored. We believe our new platforms can revolutionize the process of engineering and delivering various genome editing proteins for safer and efficacious therapeutics.