Speakers: 

Prof. Chris Blackman, UCL

Prof. Guanjie He, UCL

Time: 10:00–11:30  April 15, 2026

Venue: GZIC D1-b110

Abstract

AI for Science is profoundly transforming research methods in chemistry, materials, and energy, becoming a key driver of scientific discovery. In 2024, UCL alumni and scholars won two Nobel Prizes for breakthroughs related to AI for Science, highlighting UCL’s deep expertise and global influence in this interdisciplinary field.

We have invited UCL's Professor Chris Blackman and Professor Guanjie He to give a lecture and share the cutting-edge advances and future directions. The lecture will provide an in-depth analysis of AI’s core advantages in chemistry and materials science, including accelerating high‑throughput materials screening, accurately predicting material properties, and elucidating interfacial reaction mechanisms. Through concrete research scenarios, it will demonstrate the transformative value of AI for traditional chemical research..

Biography

Prof. Chris Blackman is a Professor of Inorganic Chemistry in the Department of Chemistry at University College London (UCL). His research interests focus on scalable thin film deposition techniques, particularly atmospheric pressure chemical vapour deposition (APCVD) and aerosol-assisted CVD (AACVD). These methods enable the fabrication of high-quality metal oxide films with controlled morphology and crystallinity, suitable for integration into sensors, photocatalysts, and smart coatings. His group has pioneered the single-step synthesis of Au- and Pt-functionalized WO₃ nanoneedles, which exhibit high sensitivity and selectivity toward gases such as hydrogen and nitrogen dioxide. More recently, Professor Blackman has expanded into atomic layer deposition (ALD) to fabricate ultra-thin films and multilayered heterostructures with atomic precision, which are being explored for use in microelectronics, optoelectronics, and advanced sensing devices. Emerging directions in his research include the use of in situ and operando materials characterisation methods to gain insight into optimising functional properties and targeting the detection of hard-to-sense analytes.

Prof. Guanjie He is the Vice Dean (International) of Faculty of Mathematical & Physical Sciences and PhD supervisor of Materials Chemistry and Engineering at UCL. He is also an ERC Starting Grant Awardee, a Fellow of the Royal Society of Chemistry (FRSC), a Fellow of the Institute of Materials, Minerals and Mining (FIMMM). His research focuses on the preparation of novel materials and advanced characterization and simulation, particularly their applications in electrochemical energy storage and conversion. His AI-empowered practices include integrating machine learning with molecular simulation and high-throughput experimentation to overcome the trial‑and‑error bottleneck of traditional research and to accelerate electrode material design and performance prediction; data-driven optimisation of aqueous battery stability and energy density, offering new approaches for next-generation clean energy storage. He has published over 150 academic papers as a corresponding/first author in prestigious journals including Joule, Nature Communications, JACS, Angew. Chem. with extensive citations. He also serves on the editorial boards of multiple international journals, promoting academic exchange at the intersection of chemistry and AI.