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Main Authors: Khaemba, Caleb Simiyu, Feng, Hongsong, Chen, Dong, Chen, Chun-Long, Wei, Guo-Wei
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.03124
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author Khaemba, Caleb Simiyu
Feng, Hongsong
Chen, Dong
Chen, Chun-Long
Wei, Guo-Wei
author_facet Khaemba, Caleb Simiyu
Feng, Hongsong
Chen, Dong
Chen, Chun-Long
Wei, Guo-Wei
contents Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry's constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.
format Preprint
id arxiv_https___arxiv_org_abs_2511_03124
institution arXiv
publishDate 2025
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spellingShingle Commutative Algebra Modeling in Materials Science -- A Case Study on Metal-Organic Frameworks (MOFs)
Khaemba, Caleb Simiyu
Feng, Hongsong
Chen, Dong
Chen, Chun-Long
Wei, Guo-Wei
Materials Science
Commutative Algebra
Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry's constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.
title Commutative Algebra Modeling in Materials Science -- A Case Study on Metal-Organic Frameworks (MOFs)
topic Materials Science
Commutative Algebra
url https://arxiv.org/abs/2511.03124