most citedNatural Language Embeddings of Synthesis and Testing conditions Enhance Glass Dissolution Prediction

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2026

AI scientists produce results without reasoning scientifically

Martiño Ríos-García, Nawaf Alampara, Chandan Gupta +5

Large language model (LLM)-based systems are increasingly deployed to conduct scientific research autonomously, yet whether their reasoning adheres to the epistemic norms that make…

cond-mat.mtrl-sci20261 cited

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…

cs.CY2025

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…

cond-mat.mtrl-sci2025

Reactive Glass Metal Interaction under Ambient Conditions Enables Surface Modification of Gold Nanoislands

Sinorul Haque, Shweta R. Keshri, G. Ganesh +13

Stabilizing gold nanoparticles with tunable surface composition via reactive metal support interactions under ambient conditions remains a significant challenge. We discovered that…

cs.LG2025

Probing the limitations of multimodal language models for chemistry and materials research

Nawaf Alampara, Mara Schilling-Wilhelmi, Martiño Ríos-García +5

Recent advancements in artificial intelligence have sparked interest in scientific assistants that could support researchers across the full spectrum of scientific workflows, from…