A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable The...
A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable Thermosets in the Low-Data Regime
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Publisher
Washington: American Chemical Society
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Language
English
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Washington: American Chemical Society
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Contents
Thermosets present sustainability challenges that could potentially be addressed through the design of deconstructable variants with tunable properties; however, the combinatorial space of possible thermoset molecular building blocks (e.g., monomers, cross-linkers, and additives) and manufacturing conditions is vast, and predictive knowledge for ho...
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A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable Thermosets in the Low-Data Regime
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TN_cdi_doaj_primary_oai_doaj_org_article_00c8cd52b9794f38bed153e33c53fd67
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_00c8cd52b9794f38bed153e33c53fd67
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ISSN
2374-7943
E-ISSN
2374-7951
DOI
10.1021/acscentsci.3c00502
