Publications of Akhil Sugathan Nair

Journal Article (1)

2023
Journal Article
Biswajit, Mondal, Arijit Jana, Jayoti Roy, Astrid Campos Mata, Akhil Sugathan Nair, Ananthu Mahendranath, Soumyabrata Roy, Biswarup Pathak, Pulickel M. Ajayan and Thalappil Pradeep: Structure and Electrocatalytic Performance of Cocrystallized Ternary Molybdenum Oxosulfide Clusters for Efficient Water Splitting.

Talk (3)

2024
Talk
Nair, Akhil Sugathan: Leveraging Multi-Fidelity Data In AI-Driven Sequential Learning of Materials Properties: Identifying Stable Water Splitting Catalysts.
(DPG Spring Meeting of the Condensed Matter Section (SKM), Berlin, Germany, Mar 2024).
Talk
Sugathan Nair, Akhil: Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis.
(International Workshop on Data-Driven Computational and Theoretical Materials Design, Shanghai, China, Oct 2024).
2023
Talk
Sugathan Nair, Akhil: Multi-Fidelity Modelling for Materials Discovery with Sequential Learning.
(NOMAD Workshop on Data-centric Cruising for New and Novel Materials, Mechanisms, and Insights, Kiel, Germany, Sep 2023).

Working Paper (2)

2024
Working Paper
Behler, Jörg, Gabor Csanyi, Lucas Foppa, Kisung Kang, Marcel F. Langer, Johannes T. Margraf, Akhil Sugathan Nair, Thomas A.R. Purcell, Patrick Rinke, Matthias Scheffler, Alexandre Tkatchenko, Milica Todorovic, Oliver T. Unke and Yi Yao: Workflows for Artificial Intelligence.
Working Paper
Sugathan Nair, Akhil, Lucas Foppa and Matthias Scheffler: Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis.
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