162 citations · 306 across the 9 of their papers we have counts for
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cond-mat.mtrl-sci2025
UniFFBench: Evaluating Universal Machine Learning Force Fields Against Experimental Measurements
Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales +5
Universal machine learning force fields (UMLFFs) promise to revolutionize materials science by enabling rapid atomistic simulations across the periodic table. However, their evalua…
cs.CY2025★ 3 cited
Autonomous Microscopy Experiments through Large Language Model Agents
Indrajeet Mandal, Jitendra Soni, Mohd Zaki +5
Large language models (LLMs) are revolutionizing self driving laboratories (SDLs) for materials research, promising unprecedented acceleration of scientific discovery. However, cur…