162 citations · 306 across the 9 of their papers we have counts for
10 papers
Natural Language Embeddings of Synthesis and Testing conditions Enhance Glass Dissolution Prediction
Sajid Mannan, K. Sidharth Nambudiripad, Indrajeet Mandal +2
Long-term chemical durability of glass, crucial for immobilizing nuclear waste, is governed by glass properties such as composition, surface geometry, as well as external factors l…
Velocity Weakening in Anisotropic Friction on a Tilted Titania Nanorod Forest
Debottam Datta, Enrico Gnecco, J. P. Singh +1
In this study, we demonstrate velocity-dependent directional friction on a surface structured with tilted (~57°) titania nanorods using standard and colloidal probe force microscop…
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…
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…
Glass Hardness: Predicting Composition and Load Effects via Symbolic Reasoning-Informed Machine Learning
Sajid Mannan, Mohd Zaki, Suresh Bishnoi +8
Glass hardness varies in a non-linear fashion with the chemical composition and applied load, a phenomenon known as the indentation size effect (ISE), which is challenging to predi…
Looking Through Glass: Knowledge Discovery from Materials Science Literature using Natural Language Processing
Vineeth Venugopal, Sourav Sahoo, Mohd Zaki +3
Most of the knowledge in materials science literature is in the form of unstructured data such as text and images. Here, we present a framework employing natural language processin…
Cooling Rate Effects on the Structure of 45S5 Bioglass: Computational and Experimental Evidence of Si--P Avoidance
Pratik Bhaskar, Yashasvi Maurya, Rajesh Kumar +10
Due to its ability to bond with living tissues upon dissolution, 45S5 bioglass and related compositions are promising materials for the replacement, regeneration, and repair of har…
Predicting Young's Modulus of Glasses with Sparse Datasets using Machine Learning
Suresh Bishnoi, Sourabh Singh, R. Ravinder +4
Machine learning (ML) methods are becoming popular tools for the prediction and design of novel materials. In particular, neural network (NN) is a promising ML method, which can be…
Quantized Friction across Ionic Liquid Thin Films
Alexander M. Smith, Kevin R. J. Lovelock, Nitya Nand Gosvami +2
Ionic liquids, salts in the liquid state under ambient conditions, are of great interest as precision lubricants. Ionic liquids form layered structures at surfaces, yet it is not c…
Enhanced quality factors and force sensitivity by attaching magnetic beads to cantilevers for atomic force microscopy in liquid
Sebastian Hoof, Nitya Nand Gosvami, Bart W. Hoogenboom
Dynamic-mode atomic force microscopy (AFM) in liquid remains complicated due to the strong viscous damping of the cantilever resonance. Here we show that a high-quality resonance (…