An international research team led by Professor Philip C.Y. Chow at The University of Hong Kong (HKU) has unveiled a new catalyst that overcomes a major challenge in producing green hydrogen at scale. This innovation makes the process of producing oxygen efficiently and reliably in the harsh acidic environment used by today’s most promising industrial electrolysers.

A research team from the Faculty of Engineering at The University of Hong Kong (HKU) has harnessed citywide genetic data and developed a novel genome-resolved tracking method to uncover precisely how antibiotic-resistant bacteria and their resistance genes move across Hong Kong’s environment, offering vital insights into strategies for safeguarding public health.

35 million euros, 210 scientists, 12 years of research: after the maximum duration of three funding periods, the Transregional Collaborative Research Centre TRR 142 ‘Tailor-made non-linear photonics: From fundamental concepts to functional structures’ is officially winding down in December 2025. Scientists at Paderborn University and TU Dortmund University have achieved great things and literally shone a light into darkness with their research contributions.

Professor Nicholas X. Fang, Jockey Club STEM Professor in the Department of Mechanical Engineering, Faculty of Engineering, and Professor Xiang Zhang, HKU President and Vice-Chancellor, and Chair of Physics in the Department of Physics, Faculty of Science, have been jointly awarded the 2025 Brillouin Medal by the International Phononics Society (IPS). The honour recognises their pioneering discovery of ultrasonic metamaterials with negative elastic modulus.

A cross-institutional research team led by researchers from the Department of Electrical and Electronic Engineering (EEE), under the Faculty of Engineering at The University of Hong Kong (HKU), have achieved a major breakthrough in the field of artificial intelligence (AI) hardware by developing a new type of analog-to-digital converter (ADC) that uses innovative memristor technology.

An Osaka Metropolitan University-led research team assessed how varying IVM durations affect developmental competence and embryo quality in oocytes with fast- or slow-predicted NMS classified via machine learning.