Bis-Tridentate Ir(III) Phosphors for High-Efficiency and Long-Lifetime Organic Light-Emitting Diodes
Hong Kong Principal Investigator: Prof Chi Yun (City University of Hong Kong)
Mainland Principal Investigator: Prof Liao Liang-Sheng (Soochow University)
Organic light-emitting diode (OLED) is a lighting device in which the emissive layer is a film made of organic compound that emits light in response to the applied electric current. In recent days, this technology has been improved substantially such that both OLED display and lighting luminaries can have efficiency comparable or even better than the liquid crystal displays (LCD) and inorganic light emitting diodes (LED). Hence, relevant products have gained their importance in our daily life and acquired remarkable market value of several tens of billion dollars annually. This lighting industry consists of many distinctive innovation sectors such as material supplies, equipment, products design and manufacturing. At present, 90% of OLED related materials and end products sold in the global market were provided by companies located in the United States, Japan and Korea, despite that China has made a clear signal and wanted to become one major player in this arena within next few years. In order to overcome the technological blockade reinforced by these foreign companies, we must develop our own knowhow in materials, enabling local or domestic companies with fair access to the supplies and production technologies, and to bypass the current patent restriction on material designs and device fabrications.
Assembly and Molecular Mechanism Studies on Membrane Remodeling Complex
Hong Kong Principal Investigator: Dr Fan Jun (City University of Hong Kong)
Mainland Principal Investigator: Prof Sun Fei (Institute of Biophysics, Chinese Academy of Science)
Membrane remodeling is critical for many aspects of cellular function, including the biogenesis of organelles and transport carriers, cell motility, and cytokinesis. Two of the best characterized protein families that participate in membrane remodeling are ADP-ribosylation factor (Arf) of small G protein and sorting nexin (SNX) family protein containing the Bin-Amphiphysin-Rvs (BAR) domain. Arfs and SNXs regulate membrane traffic and dynamics, such as modulating membrane lipid composition, defining tubular endosomal network, and organizing trafficking among endocytic and recycling pathways. Therefore, it is essential to understand how these proteins interact cell membrane. However, the molecular mechanism of membrane remodeling remains unclear, due to lack of three dimensional (3D) structure of the remodeling complex.
This project aims to obtain the 3D structures of these remodeling complexes using cryo-EM experiment and molecular dynamics (MD) simulations. More specifically, the 3D structure of remodeling complexes includes two important interfaces, the protein-protein (PP) interface to stabilize the protein lattice structure, and the protein-membrane (PM) interface for the protein to bind to the membrane. Molecular protein lattice structure, interaction mechanisms, and key residues on the two interfaces will be investigated using experimental and computational methods.
In order to reveal the PP interface, the mainland team will first obtain the electron density map of the complex structure of SNX1 (Arf6) protein on lipid tube using cryo-EM experiments. Atomic models will be fitted using UCSF Chimera. Afterwards, the PI will apply a computational method to further refine the protein lattice structure, and reveal key residues to maintain the lattice. Moreover, with respect to the PM interface, the PI will perform Monte Carlo calculations to search for the optimal binding orientation between protein and membrane; afterwards, all-atom MD simulations will be carried out to further refine the PM interface. Key residues responsible for the protein binding will be identified. In addition, the binding specificity of SNX1 to lipid molecules will be investigated from the energy point of view. To verify the simulation predictions, the mainland team will carry out in vivo and in vitro mutagenesis experiments, and quantify the protein binding rate as well as the tabulation rate.
The computational and experimental results will provide new insights into the molecular mechanism of membrane remodeling by SNXs and Arfs proteins, elucidate how proteins assemble on the membrane surface, and make it possible to further investigate their functional mechanism in intracellular transport pathway in the future.
Exploration of Cell Chirality Using Material Surface Patterning
Hong Kong Principal Investigator: Dr Chen Ting-Hsuan (City University of Hong Kong)
Mainland Principal Investigator: Prof Ding Jiandong (Fudan University)
Do cells have chirality, or left-right asymmetry? If yes, how to measure and use it? It is a fundamental question in basic science. In recent years, researchers observe that cells can orient and migrate with chiral bias, and such chiral bias can later cause formation of tissue architecture with LR asymmetry. Since tissue is in diverse forms, cell differentiation must play an important role. However, observation of cell chirality needs special material surface, which is not easily accessible. Here, to tackle this question, we will start a collaboration based on complementary expertise of micropatterning on hydrogel in Prof. Jiandong Ding’s group in Fudan University and the characterization of cell chirality in Dr. Ting-Hsuan Chen’s group in City University of Hong Kong. We plan to fabricate hydrogel micropatterns to culture bone marrow mesenchymal stem cells. By monitoring the cell chirality, we will first investigate whether the cell chirality can early respond to and even itself regulate lineage specification. Next, we will sort the stem cells into subgroups with varied differentiation potentials to elucidate the relationship between cell chirality and lineage commitment. Finally, we will explore the possibility of using cell chirality as a marker for predicting the lineage fate of cells.
Existence and Regularity of Solutions to the Boltzmann Equation
Hong Kong Principal Investigator: Prof Duan Renjun (The Chinese University of Hong Kong)
Mainland Principal Investigator: Prof Li Weixi (Wuhan University)
The collisional kinetic theory is one core subject in non-equilibrium statistical physics. Its main objective is to describe the motion of a rarefied gas flow by determining the velocity distribution function of gas particles in terms of the intermolecular interaction mechanism and further investigating the macroscopic properties of the flow, such as temperature, pressure, viscosity and heat-conductivity. Thus, the kinetic theory has proven very useful in connecting the Newtonian dynamics at the microscopic level and the classical fluid dynamics at the macroscopic level.
There exist many kinds of challenging research topics in kinetic theory. Among them is the study of the famous Boltzmann equation that may date back to Maxwell and Boltzmann himself in the 19th century.
This project concerns the mathematical study of the spatially inhomogeneous Boltzmann equation in case of the angular non-cutoff, with emphasis on the global existence and regularity of solutions of lower regularity.
The Boltzmann equation without cutoff is a kind of degenerate parabolic equation and the main difficulty arises from the non-local property of collision operator coupled with the degeneracy in spatial variables. It is an open problem for the existence of bounded weak solutions, and so far we have the Hölder regularity of bounded solutions and the higher order regularity remains unknown.
In this project we will prove the existence of bounded weak solutions under the smallness assumption on initial data, and further then use Hörmander theory to get the higher order regularity of weak solutions. The main tool will be the microlocal analysis, involving in particular the symbolic calculus and global hypoelliptic techniques for the linearized Boltzmann operator. We will study here not only the Cauchy problem in the whole space but also the boundary value problem in the domain with boundaries.
On the basis of the extensive studies of the non-cutoff Boltzmann equation recently done by many research groups, we would expect this project to provide further independent understandings of the global existence and regularity of bounded weak solutions in the perturbation framework.
The Synaptic, Cellular and Circuit Plasticity Mechanisms Underlying the Role of the Small-molecule Neuropeptide Orexin in Central Vestibular Compensation
Hong Kong Principal Investigator: Prof Yung Wing-ho (The Chinese University of Hong Kong)
Mainland Principal Investigator: Prof Zhu Jingning (Nanjing University)
Vestibular disorders, characterized by postural imbalance, gait disturbance, vertigo, and nystagmus, are common in the general population and strongly affect the quality of life. Interestingly, some of the vestibular dysfunctions are gradually ameliorated over time in both humans and animals. This process of natural recovery from vestibular deficits is known as vestibular compensation. Obviously, facilitating vestibular compensation is an important beneficial strategy for the clinical treatment of vestibular dysfunctions. Moreover, vestibular compensation is also an indispensable window for understanding the post-lesion plasticity in the adult central nervous system. Yet little is known about the exact neural mechanism underlying vestibular compensation. Here, we focus on orexin, a small-molecule neuropeptide restrictedly synthesized in the hypothalamus. Based on the previous series of works of the Hong Kong PI and the mainland co-PI on the central motor system and neuroplasticity, especially the findings on vestibular motor control and compensation published on Neuron and Journal of Neuroscience, we will investigate, from an integrative neurobiological perspective, on the function and mechanism of orexin and orexinergic afferent system in the cerebellum and brainstem vestibular nucleus in the pathophysiological processes in vestibular diseases, and particularly, in the synaptic, cellular and circuit plasticity, to elucidate the role of orexin and orexinergic system in central vestibular compensation from molecular to behavioral levels. A variety of cutting-edge techniques, including optogenetics, chemogenetics as well as in vivo multi-channel recording and in vivo fiber photometry, will be applied. The results will not only contribute to our understanding of the neural mechanism underlying vestibular compensation in basic theory, but also provide novel insight into clinic prevention and treatment of vestibular diseases.
Generative Adversarial Learning Based Magnetic Resonance Image Enhancement: Modeling and Algorithm
Hong Kong Principal Investigator: Prof Zeng Tieyong (The Chinese University of Hong Kong)
Mainland Principal Investigator: Prof Zhang Guixu (East China Normal University)
With the advancement of technology in modern hospital, medical imaging is playing an increasingly important role in the diagnostic and treatment of hospital. There are many types of imaging methods, such as Magnetic Resonance Imaging (MRI), Computed Tomography, Positron Emission Tomography and X-ray, among which MRI is one of the most widely applied systems due to its absence of ionizing radiation and superior contrast resolution.
Usually, chemical composition which serves as a contrast agent is taken by patients in MRI scanners to increase the contrast of internal body structure, which is vital for making an accurate diagnosis. However, there are always struggles between carefully prescribing compounds in controlled doses to avoid any body damage and enhancing the quality of Magnetic Resonance (MR) images. Different from cellphone images, the MRI system measures the spatial frequency information along with other parameters that will form the final image in the physical slice plane. Due to this reason, in the concern of patient safety, advanced image processing technologies should be applied in this reconstruction process to get better images.
In the quest for improving image quality merely from the acquired raw MR data, we combine variational approaches and deep learning methods to design a new accurate and efficient system for MR image enhancement. We will first fuse the multi-sequence MR images to obtain a single enhanced image, which is then used for multi-modality image fusion. Next, we will apply a detail-enhanced model guided by reasonable medical image priors to the fused result. At last, we will construct an MR image enhancement framework based on generative adversarial learning. Our proposed MR image enhancement system gives full play to the advantages of variational method and deep learning. The enhanced results, which have high contrast and sharp edges, can be obtained in a very short time and with acceptable hardware overhead. We strongly believe that the system has an extremely high practical clinical value and will efficiently help physicians to make accurate diagnoses.
Development of High Performance Perovskite Blue Light-emitting Diodes
Hong Kong Principal Investigator: Prof Zhao Ni (The Chinese University of Hong Kong)
Mainland Principal Investigator: Prof Wang Jianpu (Nanjing Tech University)
This project aims to develop highly efficient and stable organometal halide perovskite (OHP) -based blue light-emitting diodes (LEDs) through holistic efforts in material and device design, film engineering, and studies of device physics and degradation mechanisms.
OHP based LEDs have shown great application potential in energy-efficient lighting and display because of their low-temperature processability, high luminescence efficiency, and excellent color purity. Recently, green and near-infrared OHP LEDs have achieved external quantum efficiencies (EQEs) of above 20%; In contrast, perovskite-based blue LEDs have so far exhibited poor performance (i.e., EQEs of a few percent and very short lifetime) due mainly to the phase instability (i.e., phase segregation during device operation) of the light-emitting layer, which is typically based on a chloride–bromide mixed-halide perovskite. Such performance limitation will prevent the application of perovskite LEDs in full-color display as well as lighting.
To address the aforementioned challenge, this collaborative project is set to combine the expertise of Nanjing Tech University team (on design of perovskite materials and fabrication of high efficiency LEDs) and The Chinese University of Hong Kong team (on film engineering, defect passivation and device physics) to develop strategies to improve both the efficiency and stability of perovskite blue LEDs. Specifically, we will (1) realize controllable preparation of stable blue-emitting perovskite materials through A-site cation design, composition tuning and lattice dimension engineering, (2) obtain low defect density and stable perovskite films with optimal morphology through additive modification, solvent-induced film reconstruction and surface defect passivation, and (3) achieve blue perovskite LEDs with high efficiency and good stability through further development of charge transport layer materials and interface modification methods, as well as study of the device physics and degradation mechanisms in the developed OHP devices.
Through this project, we will develop new material and device strategies for achieving wide-bandgap perovskite light-emitting systems. The fundamental findings and technological know-hows generated from this project will contribute to the performance enhancement and commercialization of OHP based LED and laser technologies.
Efficient and stable polymer solar cells: From new materials, built-in potential and interfacial engineering perspectives
Hong Kong Principal Investigator: Prof Zhu Furong (Hong Kong Baptist University)
Mainland Principal Investigator: Prof Ding Liming (National Center for Nanoscience and Technology)
Polymer solar cells (PSCs) are a promising alternative photovoltaic technology to conventional inorganic solar cells due to their low-cost solution process fabrication capability. A broad range of distinct device technologies based on polymeric photoactive materials and nonfullerene acceptors are being developed very rapidly. Power conversion efficiency (PCE) of >15% for single junction PSCs and >17% for tandem PSCs have been demonstrated recently. OSCs can be made flexible, semitransparent and are light weight. The unique flexibility and semi-transparency feature also add a decorative and aesthetic dimension to PSCs so that they can be used on curved and irregular surfaces, which cannot be done using traditional rigid silicon solar cells. In the near future, the functional PSC products will be eventually proven viable that can be integrated onto windowpanes in homes, offices, and even automobiles, enhancing the functionality of already utilized transparent surfaces for converting light into electricity. The application of PSCs also is in line with the energy conservation, environmental protection and sustainable development. High performance nonfullerene PSCs have attracted significant attentions. However, their performance is hampered facing some technical and processing challenges, including new organic photoactive materials with enhanced absorption in infrared region and the operation stability.
Significant progresses have been made in the development of nonfullerene PSCs. Apart from the high efficiency, the stability is another key issue for commercialization of PSCs. The recent study indicates that nonfullerene acceptor materials have a profound impact on the stability of PSCs. However, researches on the mechanism of efficient operation of nonfullerene PSCs are still limited. Especially, the charge generation, transport and recombination processes in the nonfullerene PSCs are not fully understood. The key issues causing the degradation in PSCs and how nonfullerene acceptors affect the efficiency and stability of PSCs remain unclear. In parallel to the studies of the correlation between the building units of nonfullerene acceptors, including core groups, end groups and side chains, on the efficiency of PSCs, in this joint program, we aim to develop high performance nonfullerene PSCs through an improved understanding of the effects of morphology and vertical stratification of bulk heterojunction (BHJ) on built-in potential, charge transfer and charge recombination, which underpin the optimal cell performance and stability of PSCs. We will investigate the working mechanisms (including the built-in potential and interfacial engineering related issues) for nonfullerene PSCs and elucidate how to retain a stable and high built-in potential across the BHJ through interfacial modification and device engineering for efficient and stable operation of PSCs. It is anticipated that the outcomes of this research will offer technical and theoretical support for the commercialization of polymer solar cells.
Mathematical modeling and analysis of deep neural networks for solving structured differential and integral models
Hong Kong Principal Investigator: Prof Tai Xue-Cheng (Hong Kong Baptist University)
Mainland Principal Investigator: Prof Tang Tao (Southern University of Science and Technology)
Differential and integral models are essential in numerous applications in physics, material science, engineering, and image processing. These models often enclose some particular structures inherited from physical principles, such as quantity conservation, energy dissipation, parameter limiting behavior, etc. Traditional numerical solvers will result in complex linear or nonlinear systems, which can be very expensive to get accurate solutions. Meanwhile, these complex systems may contain special structures, or only depend on a small group of parameters. In practice, we need to solve them thousands of times. On the other hand, these systems can be viewed as mappings, whose domains have much lower dimensionality. Recent years, neural networks have been demonstrated super effectiveness in learning these mappings. In this project, we intend to use neural networks to solve structured differential and integral models. Differing from the traditional numerical solvers, we do not discretize the continuum models directly. Instead, we attempt to establish natural networks and meaningful loss functions for the neural networks in the first step, such as free energy for the energy dissipation models, variation form of differential equations. Then we integrate the robust and accurate structure preserving discretization into the optimization of the loss functions, which will offer us more accurate gradient directions. Consequently, the outputs of the neural networks are more trustful. The second target of this project is to explore the accuracy limit of neural networks. We try to provide deep mathematical insights into overall error accumulation and build connections between error estimate in the numerical differential equations and machine learning. Such rigorous mathematical analysis is rare but desired. Recently, we have seen more and more applications that need to solve differential and integral models in high dimensions. The idea using CNN representations also offers a good strategy for solving these equations in high dimension and this will be part of our research.
Aqueous two-phase system-(ATPS-)templated fabrication of conjugated double-network hydrogel scaffolds for osteochondral repair
Hong Kong Principal Investigator: Dr Shum Ho Cheung (The University of Hong Kong)
Mainland Principal Investigator: Dr Deng Yi (Sichuan University)
Osteochondral defect is a high-incidence disease involving lesions of hyaline cartilage and underlying subchondral bone defects, and is caused by diverse etiologies such as osteoarthritis, cancer, athletic injuries, and aging. However, a lack of reliable sources of tissues and potential transplantation failure due to immune rejection and low survival rate of tissues significantly jeopardize patients’ recovery. Despite immense advances in tissue engineering, synthetic scaffolds have not fulfilled their promise for osteochondral regeneration. The discontented performance is particularly attributed to the challenge in creating an integrative hydrogel with two or multiple distinct compositions and properties that resemble those of the co-existing cartilage and bone in osteochondral tissues. Attempts to address this problem by stitching two hydrogels together with different properties have met with limited success due to the difficulty in maintaining a robust interface between them. Aqueous two-phase system (ATPS), which is comprised of two immiscible aqueous phases containing high concentrations of water-soluble polymeric additives, represents an exciting platform to fabricate biocompatible hydrogels with novel structures. The degree of aqueous phase separation that drives the formation of two immiscible phases can be harnessed to control the morphologies of solution mixtures, which can then be both crosslinked to form a pair of interpenetrated double-network (DN) hydrogels. This unique hierarchical intermeshing structure provides a robust interface and significantly improves the mechanical properties of hydrogels. Based on our proof-of-concept work, we will apply a custom-developed 3D printing technique using modified microfluidic devices to construct two-layer DN hydrogel scaffolds for osteochondral repair. To evaluate their therapeutic effects, we need to understand the interplay between DN hydrogels and stem cells/tissues.
The proposed project aims to (1) understand the effects of polymeric additives and ATPS formulation on the physicochemical properties of ATPS-templated DN hydrogels, (2) evaluate stem cell growth and differentiation on ATPS-templated DN hydrogels with distinct properties, and (3) develop 3D printable, biocompatible DN hydrogels as two-layer scaffolds for osteochondral repair.
This interdisciplinary project is jointly proposed by the two PIs from the University of Hong Kong and Sichuan University, combining the complementary strengths of both research teams. In the short term, this project will provide a fundamental understanding of the physics of DN hydrogels by all-aqueous system templating, and explore the novel therapeutic strategy of two-layer scaffolds towards treating osteochondral defect. In the long term, it will contribute to the development of integrative implants with stratified biological effects for curing other tissue or organ disorders.
The role of RNF169 in DNA double-strand break repair pathway choice and genome stability maintenance
Hong Kong Principal Investigator: Dr Huen Michael Shing-Yan (The University of Hong Kong)
Mainland Principal Investigator: Prof Huang Jun (Zhejiang University)
DNA double-strand breaks (DSBs) are arguably the most deleterious form of DNA damage. To counter their otherwise toxic effects on genome integrity, mammalian cells have evolved multiple DNA repair pathways to swiftly and effectively mend DSBs. While it remains unclear how these mechanistically-distinct DNA repair pathways are coordinated and selected to engage individual DSBs, it has become established that proper choice of DSB repair pathways is critical for genome integrity protection, and that mis-use of DSB repair pathways compromises genome stability and contributes to genome instability-associated diseases, including cancer. In this application we propose to investigate the molecular bases that regulate DSB repair pathway choice, and will examine their roles in faithful DNA repair and genome stability maintenance. Findings from the proposed work will not only advance our understanding of genome integrity protection, but will reveal therapeutic opportunities in the management and treatment of genome instability-associated diseases.
Perturbation of mammalian and mosquito adaptive immunity by flaviviruses
Hong Kong Principal Investigator: Prof Jin Dong-Yan (The University of Hong Kong)
Mainland Principal Investigator: Dr Cheng Gong (Tsinghua University)
Mosquito-borne viruses including Dengue virus (DENV), Japanese encephalitis virus (JEV) and Zika virus (ZIKV) are important human pathogens. Among them DENV poses a constant threat to public health in Southern China including Hong Kong. Although why some of these viruses have become more transmissible and pathogenic remains elusive, host antiviral immunity is an important determinant of infection outcome.
In this joint project, the two sides will pool our complementary expertise and resources to shed new mechanistic light on how DENV and ZIKV perturb mammalian and mosquito adaptive immunity. Particularly, we will define how these viruses activate PD-1/PD-L1 immune checkpoint to evade the killing of infected cells by T cells. We will also determine whether and how viral DNA of DENV and ZIKV might be produced as an antiviral response in mosquito hemolymph and in mammalian cells.
Our findings will provide important clues as to how DENV and ZIKV suppress T cell response in mammals leading to severe diseases but activate RNAi-based systemic adaptive immunity in mosquitoes resulting in nonpathogenic persistent infection. Our work might also reveal new strategies for antiviral and vaccine development.
Proteomics-based identification of tumor metastasis-associated proteins and functional and mechanistic study of MEST in esophageal cancer
Hong Kong Principal Investigator: Prof Lung Maria Li (The University of Hong Kong)
Mainland Principal Investigator: Prof Li Bin (Jinan University)
This project aims to study what drives metastasis in esophageal carcinoma (EC). EC is a highly invasive and metastatic cancer. We have established human EC cell lines. Differential analysis showed that a gene named MEST (mesoderm-specific transcript) was the top candidate associated with invasion and metastasis. The function of this gene in cancer is unknown. Preliminary studies now show that MEST in EC is dysregulated and that its overexpression is associated with metastasis and patient survival. Furthermore, MEST overexpression is associated with EC cell invasion and tumor metastasis. It appears to be involved in ERK signaling. MEST is associated and helps to regulate other important proteins such as SRCIN1 and RASAL. Computational prediction indicated a miR-449a is a potential upstream regulator of MEST. How it correlates with metastasis and patient survival will be studied. We hypothesize that MEST directly interacts with several proteins to deregulate cell signaling. Deciphering the role of MEST in regulating the ERK pathway and determining how it affects metastasis and growth will be studied. The outcome of our studies is expected to help identify effective biomarkers in cancer diagnosis and prognosis and to aid in novel therapeutic strategies.
Study of the lineage relationship between hematopoietic stem cells and tissue-resident macrophages using a high-precision single-cell tracing technique
Hong Kong Principal Investigator: Prof Qu Jianan (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Xu Jin (South China University of Technology)
Tissue-resident macrophages (TRMs), a heterogeneous population of immune cells that reside in all kinds of tissues/organs, play a central role in immune surveillance, homeostatic adaptation and tissue repair. Accumulated evidence shows a causal association of TRMs with a variety of human disorders, such as cancer, obesity, diabetes and neurodegenerative diseases. Therefore, understanding the origin(s) and developmental characteristics of TRMs is essential for developing novel therapeutic strategies targeting these diseases. However, there has been a long standing debate over whether TRMs are derived from hematopoietic stem cells (HSCs) or non-HSC hematopoietic precursors. The controversy in this field is mainly attributed to the limitations of cell lineage tracing methods used in previous studies. Here, we propose a high-precision single-cell labeling strategy that aims to truthfully and unambiguously depict the lineage correlations between TRMs and HSCs using a zebrafish model system. The PI’s group has recently established a light-mediated cell lineage tracing method with high spatial-temporal resolution. In a pilot study, we developed an infrared (IR) laser mediated single-cell labeling technique by integrating an IR laser heat shock module with a two-photon microscopy system and a high-sensitivity fluorescent thermometer. Using this newly established system, we demonstrated that single-cell labeling can be achieved in various kinds of tissues including muscle, brain and hematopoietic tissues. We further demonstrated the feasibility of labeling a single hemogenic endothelial (HE) cell, the precursor giving rise to hematopoietic stem/progenitor cells (HSPCs). In this proposed research, we will further improve the labeling efficiency of the current system and achieve higher efficiency and efficacy of single HE labeling at aorta-gonad mesonephros (AGM) of zebrafish, the specific location where HSPCs emerge. With this single cell labeling strategy, we will trace the location and differentiation potential of single HSPC, and uncover their relationship with TRMs in different tissues. Success of the proposed research will address the long-debating question on TRMs origin(s), and provide cellular foundation for the study of TRM development and function.
Experimental and numerical investigation of the physical origin of large-scale circulation in turbulent thermal convection
Hong Kong Principal Investigator: Prof Tong Penger (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Dr Huang Shidi (Southern University of Science & Technology)
Large-scale flows are often observed in thermal convection systems in nature and industry. Examples include oceanic circulation, mantle convection, Earth's outer core convection, and convection in crystal growth and chemical mixing processes. These large-scale flows carry a large amount of heat and materials and thus have a great influence on our daily life and many engineering applications. Despite their importance, we do not know at present why a coherent large-scale circulation (LSC) is formed in many apparently different thermal convection systems. In the laboratory, controlled turbulent convection is generated and systematically studied in a closed Rayleigh-Bénard cell, which is heated from below and cooled from above with a vertical temperature gradient parallel to gravity. In this well-controlled convection system, a coherent LSC with a quasi-two-dimensional (quasi-2D) single-roll structure emerges when the thermal driven force (buoyancy) is sufficiently large. Despite the extensive studies of the LSC dynamics over the years, the physical origin of the LSC formation in turbulent thermal convection remains elusive.
In this research, we plan to carry out a combined experimental and numerical study of the LSC dynamics near its onset in turbulent Rayleigh-Bénard convection. To find a common mechanism that drives the LSC formation, we will conduct a comparative study using circular and rectangular quasi-2D convection cells filled with three different working fluids, respectively, from liquid metal and water to silicone oils. By investigating how the large-scale flow is formed over different cell shapes and aspect ratios (geometric features) and different fluid properties (the Prandtl numbers), we will be able to identify the key elements that determine the onset conditions of the LSC. Moreover, as the LSC can produce a shear on the boundary layer and supply energy to turbulent fluctuations, we will examine how the boundary layer dynamics and small-scale turbulent statistics change when the LSC emerges, which has not been explored previously. The obtained experimental and numerical results will allow us to fully characterize and understand the interplay between the LSC formation, boundary layer dynamics and small-scale turbulent statistics, and thus provide a unique answer to the physical origin of the LSC in turbulent thermal convection. New knowledge gained from this research will guide scientists and engineers in modeling the large-scale convective flows in nature and managing heat and materials transport in industrial applications.
Development of Aggregation-Induced Emission (AIE) Nanodots with Near-Infrared Afterglow Luminescence for Tumor Diagnosis and Image-Guided Tumor Resection
Hong Kong Principal Investigator: Dr Kwok Tsz Kin (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Ding Dan (Nankai University)
The estimation of tumor location/margin by surgeons rely mainly on inspection, palpation and their own experience. New diagnostic techniques with high resolution and sensitivity, real-time reporting and easy to use, is thus highly appreciated. Fluorescence imaging not only offers high sensitivity, non-invasiveness and excellent resolution but also provides spatial and temporal information in-situ. Unfortunately, the short lifetime of fluorescent materials is not practically useful as the fluorescence fades away quickly once the removal of light excitation. In contrast, afterglow imaging has emerged as a research hotspot in the field of optical imaging. Afterglow imaging through the collection of persistent luminescence from a material after the cessation of photoexcitation holds enormous promise for advanced bioimaging. Because continuous photoexcitation is not required, the afterglow imaging can minimize the interference of tissue autofluorescence to achieve higher sensitivity and signal to noise ratio to fluorescence. These advantages decidedly make it a more-desirable modality for the intraoperative guidance of tumor resection.
In this project, by using the concepts of aggregation-induced emission (AIE) and afterglow imaging, researchers in HKUST and Nankai University collaboratively propose to develop afterglow near-infrared (NIR) luminescent AIE probes for tumor diagnosis and image-guided tumor resection. A series of AIE afterglow AIE dots with NIR emission and narrow-distributed particle size will be prepared. In addition, their potential applications in tumor diagnosis and image-guided tumor resection will be explored by establishing tumor-bearing mouse models.
Search for Majorana zero modes on magnetic impurities and vortex cores in iron-based superconductors
Hong Kong Principal Investigator: Prof Dai Xi (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Zhang Tong (Fudan University)
A physical system that can realise Non-Abelian statistics is the material foundation of topological quantum computing and one of the ways to realise fault-tolerant quantum computing in solid state systems, which is being vigorously investigated all over the world. In the present proposal, we propose to realize it by placing magnetic impurities to the surface of iron superconductors containing topological surface states. We are going to study the possibility of inducing superconducting vortices by the coupling between magnetic impurities and the superconductors and the resulting Majorana zero mode in the center of them. The objectives of the project are to 1) Establish the general mechanism for the appearance of Majorana zero modes in FeTe1-xSex and other related materials; 2) reveal the physical origin of the quantum anomalous vortex induced in different kinds of iron-based superconductors doped with magnetic impurities; and 3) study how two or more MZMs in vortex cores can couple with each other to demonstrate the fundamental nonlocal nature of quantum mechanics.
Information-driven supply chain collaboration and service management in the new retail era
Hong Kong Principal Investigator: Prof Chen Ying-Ju (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Guan Xu (Huazhong University of Science and Technology)
The new retail era not only brings the rapid development of information technology and mobile communication, but also dramatically changes the consumer’s shopping behavior and the enterprises’ business operation mode. This project investigates the information-driven supply chain collaboration and service management problems in this novel retail era. First, we identify the consumer’s social learning behavior towards to different information transmission methods and uncover the impact of consumer review on the firm’s pricing and contract selection strategies. We then build a supply chain model with bilateral information asymmetry, and derive the joint retailer’s market information acquisition and supplier’s product quality disclosure strategies that can lead to supply chain coordination. Furthermore, we construct a supply chain model with endogenous channel selection decision and explore the strategic interactions between the change of channel structure and the information transmission format or between the retailer’s information acquisition and supplier’s channel selection decisions. Finally, based on the consumers ‘personalized needs, we build several supply chain value-added service models and propose respective supply chain optimization mechanisms with respect to the time limited logistic service, payment method and cross-channel shopping and return policy. This project can provide both theoretical evidence and practical guidance for the firms to better adopt their information transmission strategies to improve individual and overall performances in the new retail era.
Investigation of structure and property enhancement of atomically-dispersed bimetallic catalysts
Hong Kong Principal Investigator: Prof Wang Ning (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Liu Hongyang (Institute of Metal Research (IMR), Chinese Academy of Science)
Atomically dispersed bimetallic catalysts have emerged as one of the new research frontiers of catalysis research. This new type of catalysts provides great catalytic activity and selectivity due to the active sites being mostly single atoms of the primary noble metal species. Recently, we collaborated with the mainland partner and discovered new bimetallic catalysts (Pt-Sn and Pt-Fe), which have been demonstrated to possess high catalytic performance. The detailed bimetal structural configuration and its catalytic mechanisms are still unknown. We plan to carry out collaborative research to address many unclear issues in this novel catalysis system. The success of this joint project will deepen our understanding of the physiochemical nature of the atomic distribution and morphologies of bimetallic catalysts, and lead to new designs of bimetallic catalysts for potential engineering applications.
Observation and model study of the impact of vertical variations in boundary layer on the evolution of ozone pollution episodes in southern China
Hong Kong Principal Investigator: Prof Ning Zhi (The Hong Kong University of Science and Technology)
Mainland Principal Investigator: Prof Li Ying (Southern University of Science and Technology)
Ozone concentration has been rising continuously in major city clusters of China in recent years. It has become the primary pollutant in the Pearl River Delta Region of southern China. Ozone is a secondary pollutant, which has a non-linear relationship with its precursors. Numerical model is an effective means to simulate ozone formation and transport and can be used to design effective control strategies. Previous studies have revealed that the boundary layer ozone has a significant impact on the near-surface ozone concentrations. However, due to the lack of the ozone vertical observations, the accuracy of the model boundary layer simulation is one of the key uncertainties in ozone simulations and predictions. Recognizing such problems, and taking note of recent equipment development, there are more and more effort in the quantification of vertical structure and variations of ozone using different methodologies. These include vertical measurement tower with wind and air quality measurements like the one established by Shenzhen to capture to low level tropospheric boundary layer variations up to 350 m; the development of drone-based air quality sensing platform or tethered balloon system capable of short-term measurement of ozone from ground to about 1 km, and ozone lidar providing ozone variations from surface to about 3 km above ground. In this joint project, we intend to take advantage of these new vertical measurements to better understand the vertical variations of ozone, and how they can impact the development of ozone pollution episodes in southern China, to improve the ability of our current air quality models in capturing these vertical variations of ozone in the boundary layer, and use these improved models to better predict the occurrence and peak concentrations of ozone episodes, and better understand the transport and transformation of ozone during severe ozone episodes in Southern China.
Stochastic Optimal Control Theory under Model Uncertainty and Their Applications in Financial Risk Management
Hong Kong Principal Investigator: Prof Sun Defeng (The Hong Kong Polytechnic University)
Mainland Principal Investigator: Prof Wu Zhen (Shandong University)
Remarkably, the identification and management of financial risks have always been viewed as one of the most central topics in quantitative finance and economics. This topic has consistently attracted intensive attention across the academic, industrial and regulatory communities. Accordingly, considerably rich outcomes in theoretical analysis and numerical algorithms have been proposed and then well developed in the last half-century. However, in the last decade, it has been witnessed that the financial risks have become much more complicated with rather complex and interactive structures formalized, especially along with the dramatic explosion of large-sized market data emerged. Consequently, it becomes really imperative to propose and develop some new theory and algorithms to revisit risk identifying, predicting and control coping with the aforementioned complex structure and large data.
This project aims to provide an effective platform to stimulate collaborations between the two research teams led by Prof. Wu Zhen from Shandong University and Prof. Sun Defeng from The Hong Kong Polytechnic University. It will integrate the research strengths of two teams: the former is very established in dynamic stochastic control, while the latter is very established in financial optimization and numerical algorithms.
In this project, the two teams will jointly explore several interesting cutting-edge topics emerging from the recent progress in risk management, including risk identification, measurement of financial big data, and the related risk stochastic control. Specifically, we will focus on the following two objectives.
1. On the risk management side, we will establish a new theoretical framework of stochastic optimal control subject to hidden financial risks and sparse correlation structures.
2. On the risk measurement side, we will investigate how to incorporate the recent advances of deep learning and large-scale sparse optimization techniques in analyzing and identifying the hidden market risk factors.
Synthesis of High Entropy Magnetic Nanoparticles (MNP) and MNP-Embedded Microswimmers for Targeted Heating in Biological Ducts
Hong Kong Principal Investigator: Dr Ruan Haihui (The Hong Kong Polytechnic University)
Mainland Principal Investigator: Prof Liu Xiongjun (State Key Laboratory for Advanced Metals and Materials / University of Science and Technology Beijing)
Magnetic hyperthermia based on magnetic nanoparticles (MNPs) has become a fast-developing tumor-targeted therapy in recent years due to its remarkable therapeutic effect and minimal influence on healthy tissues. To improve the capacity of heat generation and the accuracy of tumor targeting for magnetic hyperthermia, this project aims at the development of novel sperm-like micro-swimmers embedded with High-Entropy MNPs (HEMNPs), which can swim and heat under the actuation of external acoustic and magnetic fields respectively. The development of HEMNPs aims at much higher specific loss power than that of the conventional iron oxide nanoparticles. The entropy-based alloy design philosophy will be the underline principle for searching the compositional space and the carbothermal shock method will be employed to synthesis HEMNPs with multi-principal metallic and metalloid elements. The relationship among composition, structure, and magnetic properties will be established through a systematic investigation of the effects of alloying elements and heat treatment process, which will lead to the further optimization of the composition and heat treatment parameters to maximize the magnetothermal performance. For developing micro-swimmers, theoretical models will first be established to describe the swimming mechanism and heating performance and to optimize the geometry and material selection of a sperm-like micro-swimmer. Eventually, micro-swimmers will be batch-produced through a 3D micro-printing process from the mixture of HEMNPs and photopolymer resins, and their swimming and heating performances will be systematically assessed. The implement of the proposed research will provide a guideline for developing high-performance MNPs and exploring the new steerable targeted magnetic hyperthermia.
Calcium-Binding Protein S100A4 as a Novel Adjuvant for Boosting Vaccination with Varicella-Zoster Virus Glycoprotein E
Hong Kong Principal Investigator: Dr Zou Xiang (The Hong Kong Polytechnic University)
Mainland Principal Investigator: Prof Wei Bin (Shanghai University)
Diseases caused by a virus called varicella-zoster virus (VZV) present a major health threat and socio-economic burden world-wide. Infection with VZV during childhood results in chickenpox (varicella) manifested with a blister-like rash, itching, tiredness, and fever. The initial symptoms are followed by the hiding of viruses in the neurons, a status similar to hibernation. The hidden viruses may be activated during adulthood upon incompletely understood mechanisms (e.g. fatigue and compromised immunity) which leads to the onset of herpes zoster (shingles) in tissues close to the nerves. Patients with shingles may experience severe, persistent pain, which substantially compromises the quality of life. The incidence of herpes zoster increases dramatically in older people. Vaccination is considered the most cost-effective strategy in developing control measures against infectious diseases. Successful vaccination depends on a substance included in the vaccine formulation known as adjuvant which can help mobilize and activate the immune system so that specific immune responses to pathogens with better potency and longer duration can be achieved. Our preliminary research discovered that a particular human internal protein, S100A4, has powerful immune regulatory functions and can be potentially used as an adjuvant for boosting immunization. The advantage of using this molecule lies in its better safety profile as S100A4 is a human endogenous protein. This stands in contrast to the widely tested adjuvant candidates derived from pathogen products which might cause side effects in vaccine recipients. This pre-clinical research will be carried out using experimental mouse models. We will immunize mice with a VAV protein in the presence or absence of S100A4 and assess the quality of the immune responses. In particular, we will analyse the effect of S100A4 on the generation of effective VZV-specific T cells, as T cell immunity is critical in suppressing VZV reactivation. To fundamentally demonstrate the efficacy of S100A4-containing vaccine formulation in defense against viral attack, we will immunize the mice followed by live virus challenge. Mouse survival rates will be compared between immunizations in the presence or absence of S100A4. The successful completion of this project will significantly expand the knowledge base for understanding the strategies in preventing shingles onset by suppressing VAV reactivation. Furthermore, the project is likely to provide implications for therapeutic development by including S100A4 in vaccines against other viral diseases.