Accelerated discovery of defect tolerant organo-halide perovskites
Source abstract
Abstract
A machine learning based, “accelerated” materials discovery strategy to predict the defects of HOIP-candidate materials is presented. We rationalize defect tolerant perovskite materials classification and structure-property relationships.
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Machine Learning in Materials Science · Perovskite Materials and Applications · Polyoxometalates: Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Physics, Marmara University, 34722, Ziverbey, Istanbul, Turkey
Funding
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
References (39)
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