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20232026
most citedImage and Data Mining in Reticular Chemistry Using GPT-4V

67 citations · 76 across the 7 of their papers we have counts for

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5 papers · 1 filter

cond-mat.mtrl-sci2026

Reticulating Local Dynamics in Three-Dimensional Covalent Organic Frameworks

Francesco Tavani, Saber Mirzaei, M. Saeed Mirzaei +7

In covalent organic frameworks (COFs), the geometry of the building units predetermines the structure of the framework, yet comparable design principles relating the COF linkers to…

cond-mat.mtrl-sci2026

Local Structure and Dynamics of Three-Dimensional Covalent Organic Frameworks

Francesco Tavani, Saber Mirzaei, Jian Yin +7

Resolving and controlling the local dynamical properties of covalent organic frameworks (COFs) remains a central challenge, particularly when assembled from large, flexible buildin…

cond-mat.mtrl-sci2026

Data-driven Design of Metal-Organic Frameworks with Tunable Negative Thermal Expansion

Prathami Divakar Kamath, Francesco Tavani, Alin Marin Elena +6

Materials with negative thermal expansion (NTE) are essential for applications requiring precise control of thermal expansion. Owing to their exceptional chemical tunability, flexi…

cond-mat.mtrl-sci2026

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…

cond-mat.mtrl-sci2025★ 9 cited

System of Agentic AI for the Discovery of Metal-Organic Frameworks

Theo Jaffrelot Inizan, Sherry Yang, Aaron Kaplan +12

Generative models and machine learning promise accelerated material discovery in MOFs for CO2 capture and water harvesting but face significant challenges navigating vast chemical…