1 citations · 1 across the 4 of their papers we have counts for
5 papers
Capturing Coordination Core Topology in Metal--Organic Frameworks Using Persistent Mayer Homology
Caleb Simiyu Khaemba, Chun-Long Chen, Guo-Wei Wei
Local coordination cores are critically important in metal-organic frameworks (MOFs) and polyoxometalates (POMs), as they govern the fundamental chemical and structural properties…
Commutative Algebra Modeling in Materials Science -- A Case Study on Metal-Organic Frameworks (MOFs)
Caleb Simiyu Khaemba, Hongsong Feng, Dong Chen +2
Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in mater…
Interaction Topological Transformer for Multiscale Learning in Porous Materials
Dong Chen, Jian Liu, Chun-Long Chen +1
Porous materials exhibit vast structural diversity and support critical applications in gas storage, separations, and catalysis. However, predictive modeling remains challenging du…
CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction
Hongsong Feng, Faisal Suwayyid, Mushal Zia +4
Recently, Suwayyid and Wei have introduced commutative algebra as an emerging paradigm for machine learning and data science. In this work, we integrate commutative algebra machine…
Category-Specific Topological Learning of Metal-Organic Frameworks
Dong Chen, Chun-Long Chen, Guo-Wei Wei
Metal-organic frameworks (MOFs) are porous, crystalline materials with high surface area, adjustable porosity, and structural tunability, making them ideal for diverse applications…