Visualization and Quantification of Geometric Diversity in Metal–Organic Frameworks
Source abstract
Abstract
With ever-growing numbers of metal-organic framework (MOF) materials being reported, new computational approaches are required for a quantitative understanding of structure-property correlations in MOFs. Here, we show how structural coarse-graining and embedding ("unsupervised learning") schemes can together give new insights into the geometric diversity of MOF structures. Based on a curated data set of 1262 reported experimental structures, we automatically generate coarse-grained and rescaled representations which we couple to a kernel-based similarity metric and to widely used embedding schemes. This approach allows us to visualize the breadth of geometric diversity within individual topologies and to quantify the distributions of local and global similarities across the structural space of MOFs. The methodology is implemented in an openly available Python package and is expected to be useful in future high-throughput studies.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Learning in Materials Science · Metal-Organic Frameworks: Synthesis and Applications · X-ray Diffraction in Crystallography
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry, Inorganic Chemistry Laboratory, University of Oxford, Oxford OX1 3QR, U.K.
Samara Center for Theoretical Material Science (SCTMS) Samara State Technical University, Molodogvardeyskaya Street 244, Samara 443100, Russian Federation
Samara University, Ac. Pavlov Street 1, Samara 443011, Russian Federation
Samara Branch of P.N. Lebedev Physical Institute of the Russian Academy of Science, Novo-Sadovaya Street 221, Samara 443011, Russian Federation
Dipartimento di Chimica, Università Degli Studi di Milano, Milano 20133, Italy
Funding
Universit?? degli Studi di Milano · Research Councils UK · Russian Science Foundation · Russian Foundation for Basic Research · European Commission
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