Alex M. Ganose

Imperial College London — United Kingdom

Materials Science · Physical Sciences

38h-index6.3kcitations155works11.62yr avg
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Research Topics

Machine Learning in Materials Science(44), Perovskite Materials and Applications(27), Chalcogenide Semiconductor Thin Films(17), X-ray Diffraction in Crystallography(17), Advanced Thermoelectric Materials and Devices(15)

Publications155 total

Elucidating Hydroxide Transport in Anion Exchange Polymer Membranes Via Machine Learning Interatomic Potentials
2026Open Access
Solution-based synthesis of nanocrystalline KBiS <sub>2</sub> films at low temperatures and study of photoinduced charge generation
Journal of Materials Chemistry C·2025Open Access
Layered Alkali-Copper Selenides: Deciphering Thermoelectric Properties and Reaction Pathways for Nanostructuring β-CsCu <sub>5</sub> Se <sub>3</sub>
ACS Energy Letters·2025
Wasserspaltung „ohne Wasser“: Spaltung von Kristallwasser hydratisierter Salze
Angewandte Chemie·2025Open Access
Water‐Splitting “Without Water”: Splitting of the Crystallised Water of Hydrated Salts
Angewandte Chemie International Edition·2025Open Access
Controlling Zn2+ hydration shell dynamics for long-life zinc anodes in zinc-ion energy storage
Chemical Engineering Journal·2025· 2 citedOpen Access
Thermodynamics of Ring-Opening Polymerisation Informatics Collection (TROPIC): a database to enable polymer chemical recycling
Faraday Discussions·2025Open Access
Author response for "A Python workflow definition for computational materials design"
2025
3D Porous Zinc Scaffold Anodes for Enhanced Stability and Performance in Zinc-Ion Energy Storage Systems
ACS Nano·2025· 10 citedOpen Access
Accelerated data-driven materials science with the Materials Project
Nature Materials·2025· 85 citedOpen Access
A Python workflow definition for computational materials design
arXiv (Cornell University)·2025Open Access
Advances in theory and computational methods for next-generation thermoelectric materials
Applied Physics Reviews·2025· 5 cited
Atomate2: Modular workflows for materials science
2025· 8 citedOpen Access
A python workflow definition for computational materials design
Digital Discovery·2025Open Access
Atomate2: modular workflows for materials science
Digital Discovery·2025· 19 citedOpen Access
Correction: Atomate2: modular workflows for materials science
Digital Discovery·2025Open Access
Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry
Chemical Society Reviews·2025· 20 citedOpen Access
Discovering synthesis targets: general discussion
Faraday Discussions·2024
Discovering structure–property correlations: general discussion
Faraday Discussions·2024· 1 citedOpen Access
Solvatomorphic diversity dictates the stability and solubility of metal–organic polyhedra
Chemical Science·2024· 2 citedOpen Access
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Frequent Co-authors

David O. Scanlon(29), Anubhav Jain(10), Aron Walsh(10), Christopher N. Savory(7), Kristin A. Persson(6), Junsoo Park(5), Robert G. Palgrave(5), Annalise E. Maughan(4), James R. Neilson(4), Hugo Bronstein(4), Matthew K. Horton(4), Seán R. Kavanagh(4), Alireza Faghaninia(2), Adam Jackson(2), Keith T. Butler(2), Richard H. Friend(2), Jason M. Munro(2), W. W. Winnie Leung(2), John Buckeridge(2), Mingjian Wen(2)