All ME graduating PhD students
a. whose degrees are ratified by the Graduate School Board (GSB) during the past year between 1 July and 30 June;
b. whose theses’ overall quality is rated as “excellent” by the Board of Examiners (BoE) concerned; AND
c. whose PhD study is completed within the maximum period of study.
The bestowal of an award is subject to the quality and credentials of the candidates’ PhD theses. If no suitable candidates are identified in a given year, the selection panel reserves the right not to confer the award.
There are two award classes, namely Outstanding and Merit, recognizing students’ performance at different levels.
- Outstanding Award
- Merit Award – up to 2 (optional, depending on the number and quality of submissions)
The recipient of the Outstanding PolyU ME PhD Thesis Award will be nominated to the FRC for consideration in the PolyU PhD Thesis Award.
- Originality and innovation
- Academic, societal or industry impact
- International recognition
- Quality of thesis
- Oral presentation
Dr Wu Lizhen
PolyU PhD Thesis Award for Merit (STEM Category) 2026
Green hydrogen production via water electrolysis is a promising route toward carbon neutrality, but its large-scale application is hindered by severe bubble-induced mass transport resistance at industrial current densities. In this thesis, bubble management in water electrolyzers is systematically investigated through macro-scale flow-field engineering and micro-scale electrode design. A dual-layer flow field is proposed to enable capillary-driven bubble self-pumping, thereby decoupling bubble removal from water supply and reducing mass-transfer losses. A data-driven surrogate model trained by numerical simulations is further developed to rapidly optimize the flow-field geometry, with experimental validation confirming its reliability. At the electrode scale, stainless-steel mesh, felt, and sintered powder electrodes are compared using deep-learning-assisted bubble tracking. Long-term degradation is also analyzed by combining electrochemical impedance spectroscopy, distribution of relaxation times, and multiscale visualization. The results reveal that bubble dynamics, rather than electrochemically active surface area alone, governs high-rate electrolysis performance, providing guidance for next-generation durable electrolyzers.
PolyU PhD Thesis Award for Merit (STEM Category) 2026
PolyU ME PhD Thesis Award - Outstanding Award
Thesis Title: Bubble management at high-rate water electrolysis for green hydrogen production
Green hydrogen production via water electrolysis is a promising route toward carbon neutrality, but its large-scale application is hindered by severe bubble-induced mass transport resistance at industrial current densities. In this thesis, bubble management in water electrolyzers is systematically investigated through macro-scale flow-field engineering and micro-scale electrode design. A dual-layer flow field is proposed to enable capillary-driven bubble self-pumping, thereby decoupling bubble removal from water supply and reducing mass-transfer losses. A data-driven surrogate model trained by numerical simulations is further developed to rapidly optimize the flow-field geometry, with experimental validation confirming its reliability. At the electrode scale, stainless-steel mesh, felt, and sintered powder electrodes are compared using deep-learning-assisted bubble tracking. Long-term degradation is also analyzed by combining electrochemical impedance spectroscopy, distribution of relaxation times, and multiscale visualization. The results reveal that bubble dynamics, rather than electrochemically active surface area alone, governs high-rate electrolysis performance, providing guidance for next-generation durable electrolyzers.
- Chief Supervisor: Prof. AN Liang
Dr Wang Qingqing
PolyU ME PhD Thesis Award - Merit Award
This thesis pioneers a "totally-additive-manufacturing" paradigm, the first demonstration that load-bearing composite structures and their internal sensing networks can be co-fabricated in a single seamless printing process. At its core is an original class of printed nanocomposite sensors that uniquely bridges three traditionally segregated regimes: quasi-static strain, acoustic vibration, and ultrasonic guided waves up to 600 kHz, a bandwidth unattainable by any single conventional sensor. Landmark demonstrations include a fully printed smart wing whose integrated sensing network localizes impact events with an accuracy of 90%, offering autonomous integrity monitoring for weight-critical aerospace and deep-space structures; the first sensor implanted within structural batteries, achieving ultra-low strain detection (0.009%) and early warning against thermal runaway for electric vehicles; and a wearable acoustic sensor attaining 95.9% speech recognition accuracy. This work establishes both the scientific foundation and the manufacturing route toward intelligent multifunctional composite structures.
PolyU ME PhD Thesis Award - Merit Award
Thesis Title: Additively Manufactured Nanocomposite Sensors with Low-dimensional Nanofillers for Multiphysics Sensing: from structural battery status evaluation to health monitoring of composites
This thesis pioneers a "totally-additive-manufacturing" paradigm, the first demonstration that load-bearing composite structures and their internal sensing networks can be co-fabricated in a single seamless printing process. At its core is an original class of printed nanocomposite sensors that uniquely bridges three traditionally segregated regimes: quasi-static strain, acoustic vibration, and ultrasonic guided waves up to 600 kHz, a bandwidth unattainable by any single conventional sensor. Landmark demonstrations include a fully printed smart wing whose integrated sensing network localizes impact events with an accuracy of 90%, offering autonomous integrity monitoring for weight-critical aerospace and deep-space structures; the first sensor implanted within structural batteries, achieving ultra-low strain detection (0.009%) and early warning against thermal runaway for electric vehicles; and a wearable acoustic sensor attaining 95.9% speech recognition accuracy. This work establishes both the scientific foundation and the manufacturing route toward intelligent multifunctional composite structures.
- Chief Supervisor: Prof. SU Zhongqing
Dr Wang Wei
PolyU ME PhD Thesis Award - Merit Award
In this thesis, we develop two phase-field fracture models (PFFMs) to investigate: (1) the mechanical failure mechanisms in all-solid-state batteries (ASSBs) using Landau-Ginzburg framework, and (2) the fracture behavior of ion-exchange (IOX)-strengthened cover glass using a variational framework. Although the phase-field (PF) method mitigates the nonlinearity of crack propagation by introducing a diffusive interface and is compatible with finite element (FE) solver, the standalone FE fracture simulations remain computationally intensive. To overcome this limitation, we propose a numerical solver acceleration, particularly through AI-accelerated FE framework, to enhance computational efficiency. This approach offers a promising route for efficiently solving highly nonlinear PFFMs in large scales and in multi-physical fields, eventually achieving quantitative analysis to further guide experiments.
PolyU ME PhD Thesis Award - Merit Award
Thesis Title: Phase-Field Fracture Modeling And Numerical Solver Acceleration
In this thesis, we develop two phase-field fracture models (PFFMs) to investigate: (1) the mechanical failure mechanisms in all-solid-state batteries (ASSBs) using Landau-Ginzburg framework, and (2) the fracture behavior of ion-exchange (IOX)-strengthened cover glass using a variational framework. Although the phase-field (PF) method mitigates the nonlinearity of crack propagation by introducing a diffusive interface and is compatible with finite element (FE) solver, the standalone FE fracture simulations remain computationally intensive. To overcome this limitation, we propose a numerical solver acceleration, particularly through AI-accelerated FE framework, to enhance computational efficiency. This approach offers a promising route for efficiently solving highly nonlinear PFFMs in large scales and in multi-physical fields, eventually achieving quantitative analysis to further guide experiments.
- Chief Supervisor: Prof. RUAN Haihui
Dr LIANG Zhaojian
PolyU PhD Thesis Award for Merit (STEM Category) 2025
To store fluctuating renewable energy like solar power, efficient and durable energy-conversion devices are essential. Our research investigated how solid oxide electrolysis cells (SOECs) react to rapid changes in power, similar to when a cloud passes over a solar panel. We found that electricity, gas, and heat within the SOEC respond at different timescales: gas adjusts within a second, while heat changes occur over minutes. By connecting the principles of fluid mechanics and electrochemistry, we derived general characteristic times that predict these dynamic behaviours. These characteristic times were validated experimentally and across various electrochemical devices in the literature, establishing a universal framework for designing safer and more efficient energy systems. With these insights, we developed a control method for a solar-powered SOEC system that uses fast gas adjustments to manage slow heat changes. This maintains safe temperatures and high efficiency, making a crucial step for reliable, large-scale renewable energy storage.
PolyU PhD Thesis Award for Merit (STEM Category) 2025
Thesis Title:Theoretical investigations of the transient characteristics of solid oxide electrolysis cells (SOECs) under unstable operational conditions
To store fluctuating renewable energy like solar power, efficient and durable energy-conversion devices are essential. Our research investigated how solid oxide electrolysis cells (SOECs) react to rapid changes in power, similar to when a cloud passes over a solar panel. We found that electricity, gas, and heat within the SOEC respond at different timescales: gas adjusts within a second, while heat changes occur over minutes. By connecting the principles of fluid mechanics and electrochemistry, we derived general characteristic times that predict these dynamic behaviours. These characteristic times were validated experimentally and across various electrochemical devices in the literature, establishing a universal framework for designing safer and more efficient energy systems. With these insights, we developed a control method for a solar-powered SOEC system that uses fast gas adjustments to manage slow heat changes. This maintains safe temperatures and high efficiency, making a crucial step for reliable, large-scale renewable energy storage.
- Chief Supervisor: Prof. LI Mengying
Dr FAN Haiyan
PolyU PhD Thesis Award for Merit 2024
Natural materials usually have inherent acoustic characteristics that are difficult to meet the special needs in precise sound control. In this thesis, the proposed metamaterials show unprecedented abilities to engineer the characteristics of sound including but not limited to amplitude, phase, frequency and mode shape, thereby improving sound detection resolution and enhancing the signal-to-noise ratio. This thesis starts with one-dimensional (1D) metamaterials with additional loss treatments to produce a gathering effect of the weak acoustic signals, which amplifies the signals by 9 times. Then, we extend to a two-dimensional (2D) space, achieving high directivity anti-interference sound wave beam based on the valley Hall effect, solving the problem that target acoustic signal propagation is susceptible to interference. Last but not least, a three-dimensional (3D) metamaterial with fluid-solid interaction coming into play which improves the identification ability of underwater small target acoustic signals. These works offer potential applications in acoustic detection and identification of underwater small targets.
PolyU PhD Thesis Award for Merit 2024
Thesis Title: Non-Hermitian Topological Phases in Elastic and Acoustic Lattices
Natural materials usually have inherent acoustic characteristics that are difficult to meet the special needs in precise sound control. In this thesis, the proposed metamaterials show unprecedented abilities to engineer the characteristics of sound including but not limited to amplitude, phase, frequency and mode shape, thereby improving sound detection resolution and enhancing the signal-to-noise ratio. This thesis starts with one-dimensional (1D) metamaterials with additional loss treatments to produce a gathering effect of the weak acoustic signals, which amplifies the signals by 9 times. Then, we extend to a two-dimensional (2D) space, achieving high directivity anti-interference sound wave beam based on the valley Hall effect, solving the problem that target acoustic signal propagation is susceptible to interference. Last but not least, a three-dimensional (3D) metamaterial with fluid-solid interaction coming into play which improves the identification ability of underwater small target acoustic signals. These works offer potential applications in acoustic detection and identification of underwater small targets.
- Chief Supervisor: Prof. SU Zhongqing
