161 citations · 228 across the 5 of their papers we have counts for
5 papers
A chemical language model for reticular materials design
Dhruv Menon, Vivek Singh, Xu Chen +7
Reticular chemistry has enabled the synthesis of tens of thousands of metal-organic frameworks (MOFs), yet the discovery of new materials still relies largely on intuition-driven l…
Single and Multi-Hop Question-Answering Datasets for Reticular Chemistry with GPT-4-Turbo
Nakul Rampal, Kaiyu Wang, Matthew Burigana +11
The rapid advancement in artificial intelligence and natural language processing has led to the development of large-scale datasets aimed at benchmarking the performance of machine…
A Multi-Grained Symmetric Differential Equation Model for Learning Protein-Ligand Binding Dynamics
Shengchao Liu, Weitao Du, Hannan Xu +8
In drug discovery, molecular dynamics (MD) simulation for protein-ligand binding provides a powerful tool for predicting binding affinities, estimating transport properties, and ex…
Image and Data Mining in Reticular Chemistry Using GPT-4V
Zhiling Zheng, Zhiguo He, Omar Khattab +5
The integration of artificial intelligence into scientific research has reached a new pinnacle with GPT-4V, a large language model featuring enhanced vision capabilities, accessibl…
A GPT-4 Reticular Chemist for Guiding MOF Discovery
Zhiling Zheng, Zichao Rong, Nakul Rampal +3
We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction betwee…