MOFSimplify: Machine Learning Models with Extracted Stability Data of Three Thousand Metal-Organic Frameworks. - Aditya Nandy; Gianmarco Terrones; Naveen Arunachalam; Chenru Duan; David W. Kastner; Heather J. Kulik (CoRR, 2021)

Rapid Exploration of a 32.5M Compound Chemical Space with Active Learning to Discover Density Functional Approximation Insensitive and Synthetically Accessible Transitional Metal Chromophores. - Chenru Duan; Aditya Nandy; Gianmarco Terrones; David W. Kastner; Heather J. Kulik (CoRR, 2022)

Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties. - Gianmarco Terrones; Chenru Duan; Aditya Nandy; Heather J. Kulik (CoRR, 2022)

A Database of Ultrastable MOFs Reassembled from Stable Fragments with Machine Learning Models. - Aditya Nandy; Shuwen Yue; Changhwan Oh; Chenru Duan; Gianmarco G. Terrones; Yongchul G. Chung; Heather J. Kulik (CoRR, 2022)

SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms. - Gianmarco G. Terrones; Yu Chen; Archit Datar; Li-Chiang Lin; Heather J. Kulik; Yongchul G. Chung (Zenodo, 2023)

SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms. - Gianmarco G. Terrones; Yu Chen; Archit Datar; Li-Chiang Lin; Heather J. Kulik; Yongchul G. Chung (Zenodo, 2023)

SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms. - Gianmarco G. Terrones; Yu Chen; Archit Datar; Li-Chiang Lin; Heather J. Kulik; Yongchul G. Chung (J. Open Source Softw., 2023)