Innovation Wing Two

Ultrastrong and multifunctional aerogels with hyperconnective network of composite polymeric nanofiber

Aerogels are lightweight materials with extensive microscale pores, which could be used in thermal insulation, energy devices, aerospace structures, as well as emerging technologies of flexible electronics. However, traditional aerogels based on ceramics tend to be brittle, which limits their performance in load-bearing structures. Due to restrictions posed by their building blocks, recently developed classes of polymeric aerogels can only achieve high mechanical strength by sacrificing their structural porosity or lightweight characteristics.

TechTalk – Quantitative Predictive Theories through Integration of Quantum, Statistical, and Irreversible Thermodynamics

August 28, 2023 (Monday) 2-3pm
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable. Its derivatives to natural variables give fundamental physico-chemical properties of the system. It is historically divided into four categories: equilibrium thermodynamics by Gibbs, statistical thermodynamics by Gibbs and Landau, irreversible thermodynamics by Onsager and Prigogine, and quantum mechanics. The development of density function theory (DFT) enabled the quantitative prediction of properties of the ground state of a system from quantum mechanics. Their integration into predictive theories will be discussed in this presentation along with future perspectives. It will be shown that the zentropy theory combines the bottom-up DFT predictions with the revised top-down statistical thermodynamics, while the theory of cross phenomena keeps the entropy production due to irreversible processes in the combine law of thermodynamics to revise the Onsager flux equations. The zentropy theory is capable of quantitatively predicting free energy landscape, singularity and emergent divergences of properties at critical point free of parameters, while the theory of cross phenomena can predict the coefficients of internal processes between non-conjugate variables.

DeepPhase: Periodic Autoencoders for Learning Motion Phases Manifolds

Professor Komura’s research focuses on creating diverse human movements for computer animation, games, and virtual environments. His research team designed a new type of neural network called the Periodic Autoencoder that can identify repeating patterns in large sets of motion data without any additional information. This allows us to create unique movements in various styles, such as dance motions synchronized to music or dribbling movements in soccer. Additionally, the system can help find similar motions in large database, produce natural movements between a small number of key frame poses and estimate human movements even when the body is partially obscured in videos.

From Hospital-centric to Human-centric: “PERfECT” Wearables for Digital Health

“HKU PERfECT” is the first wearable platform that can simultaneously acquire the following three merits.

1. Highly sensitive: By combing electrochemical technology with microelectronic technology, the highest sensitivity is reached.

2. Smallest and lightest: By using the smallest possible electronic units and marrying emerging stretchable bioelectronic technologies, coin-sized and light (0.5 grams) PERfECT wearables have been used for diagnosis and treatment of various diseases, and rehabilitation.

3. Energy efficient: By using interdisciplinary research strategies spanning analytical chemistry, low-power microelectronics, and low-power wireless communication, PERfECT achieves the highest accuracy with the lowest power consumption, ideal for long-term using.

A Simulation Platform for Shared Mobility Services

This is a large-scale simulation platform for managing and controlling Hong Kong taxis. The simulator platform can be used to simulate the movements and trajectories of taxis for idle cruising, picking up passengers, and delivering passengers on a large-scale transportation network. The simulation platform is calibrated by a real dataset of Hong Kong taxis to ensure that the simulation well approximates the reality. This simulator is jointly developed by the teams of Dr. Jintao Ke at HKU and Prof. Hai Yang at HKUST. The simulation platform will be open for public use in the near future.

3D Printed Anti-counterfeiting Labels At the Microscale

Counterfeiting threatens the global economy and security. According the report issued by the United States Patent and Trademark Office (USPTO) in 2020 “the value of global counterfeiting and pirated products is estimated US $ 4.5 trillion a year.” Despite enormous efforts, conventional anti-counterfeiting approaches such as QR codes can be easily fabricated due to limited data encryption capacity on a 2D in-plane space.

How can we increase the encryption density in a limited space?