323 citations · 484 across the 17 of their papers we have counts for
19 papers
A Database of Ultrastable MOFs Reassembled from Stable Fragments with Machine Learning Models
Aditya Nandy, Shuwen Yue, Changhwan Oh +4
High-throughput screening of large hypothetical databases of metal-organic frameworks (MOFs) can uncover new materials, but their stability in real-world applications is often unkn…
Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties
Gianmarco Terrones, Chenru Duan, Aditya Nandy +1
Photoactive iridium complexes are of broad interest due to their applications ranging from lighting to photocatalysis. However, the excited state property prediction of these compl…
Active Learning Exploration of Transition Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores
Chenru Duan, Aditya Nandy, Gianmarco Terrones +2
Transition metal chromophores with earth-abundant transition metals are an important design target for their applications in lighting and non-toxic bioimaging, but their design is…
Ligand additivity relationships enable efficient exploration of transition metal chemical space
Naveen Arunachalam, Stefan Gugler, Michael G. Taylor +7
To accelerate exploration of chemical space, it is necessary to identify the compounds that will provide the most additional information or value. A large-scale analysis of mononuc…
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery
Chenru Duan, Fang Liu, Aditya Nandy +1
Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. N…
Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character Across Known Transition Metal Complex Ligands
Chenru Duan, Adriana J. Ladera, Julian C. -L. Liu +3
Accurate virtual high-throughput screening (VHTS) of transition metal complexes (TMCs) remains challenging due to the possibility of high multi-reference (MR) character that compli…