Matches in SemOpenAlex for { <https://semopenalex.org/work/W3157337682> ?p ?o ?g. }
- W3157337682 endingPage "110528" @default.
- W3157337682 startingPage "110528" @default.
- W3157337682 abstract "It is urgent to discover new functional materials quickly, but experimental research is a huge challenge to search for target materials from the vast chemical space. Here, we propose a two-step machine learning strategy to accelerate the discovery of the photovoltaic oxide double perovskites. According to the leave-one-out cross-validation results, the support vector classification (SVC) and support vector regression (SVR) methods are selected to establish the perovskite classification model and the bandgap regression model from three classification algorithms and three regression algorithms, respectively. The models perform well in cross-validation and independent test set validation, indicating their excellent predictive ability. The prediction accuracy of the SVC classifier on the test set reaches 0.968. For the SVR model, the bandgap correlation coefficient in the test set is 0.919. The SVC classifier filters out the candidates of perovskite structures from enormous virtual samples. Then the bandgaps of candidate perovskites are predicted by the SVR regression model. Successfully, 60 promising oxide double perovskites for photovoltaic applications are screened out from 6529 virtual samples. Especially 19 perovskites with bandgap values between 1.25 eV and 1.45 eV are close to the ideal bandgap value (1.34 eV). Further data analysis shows that Fe, Ni, Sc and Co occupying B′-site and Bi, Ta, Nb, Sb, V, and Mn occupying B″-site are most likely to form narrow-bandgap oxide double perovskites. This work provides an effective approach for the design and discovery of new oxide double perovskites via machine learning techniques." @default.
- W3157337682 created "2021-05-10" @default.
- W3157337682 creator A5016817645 @default.
- W3157337682 creator A5021682632 @default.
- W3157337682 creator A5027671551 @default.
- W3157337682 creator A5054457407 @default.
- W3157337682 creator A5056465234 @default.
- W3157337682 date "2021-08-01" @default.
- W3157337682 modified "2023-10-11" @default.
- W3157337682 title "Rapid discovery of narrow bandgap oxide double perovskites using machine learning" @default.
- W3157337682 cites W1532236978 @default.
- W3157337682 cites W1802734970 @default.
- W3157337682 cites W1849148947 @default.
- W3157337682 cites W1987272966 @default.
- W3157337682 cites W1991253195 @default.
- W3157337682 cites W2029637177 @default.
- W3157337682 cites W2057327293 @default.
- W3157337682 cites W2078019609 @default.
- W3157337682 cites W2154053567 @default.
- W3157337682 cites W2161230069 @default.
- W3157337682 cites W2315160168 @default.
- W3157337682 cites W2343462019 @default.
- W3157337682 cites W2612997415 @default.
- W3157337682 cites W2758960636 @default.
- W3157337682 cites W2790304262 @default.
- W3157337682 cites W2793175425 @default.
- W3157337682 cites W2794454887 @default.
- W3157337682 cites W2798057722 @default.
- W3157337682 cites W2803395311 @default.
- W3157337682 cites W2806173046 @default.
- W3157337682 cites W2806681928 @default.
- W3157337682 cites W2808873021 @default.
- W3157337682 cites W2887639109 @default.
- W3157337682 cites W2901649800 @default.
- W3157337682 cites W2911964244 @default.
- W3157337682 cites W2915789204 @default.
- W3157337682 cites W2917442361 @default.
- W3157337682 cites W2921873493 @default.
- W3157337682 cites W2937239854 @default.
- W3157337682 cites W2939172886 @default.
- W3157337682 cites W2948861682 @default.
- W3157337682 cites W2954110457 @default.
- W3157337682 cites W2954205360 @default.
- W3157337682 cites W2971782071 @default.
- W3157337682 cites W3007957713 @default.
- W3157337682 cites W3024266484 @default.
- W3157337682 cites W3026201578 @default.
- W3157337682 cites W3026487645 @default.
- W3157337682 cites W3036776898 @default.
- W3157337682 cites W3045599769 @default.
- W3157337682 cites W3091459767 @default.
- W3157337682 cites W3094091324 @default.
- W3157337682 cites W4249953957 @default.
- W3157337682 doi "https://doi.org/10.1016/j.commatsci.2021.110528" @default.
- W3157337682 hasPublicationYear "2021" @default.
- W3157337682 type Work @default.
- W3157337682 sameAs 3157337682 @default.
- W3157337682 citedByCount "25" @default.
- W3157337682 countsByYear W31573376822021 @default.
- W3157337682 countsByYear W31573376822022 @default.
- W3157337682 countsByYear W31573376822023 @default.
- W3157337682 crossrefType "journal-article" @default.
- W3157337682 hasAuthorship W3157337682A5016817645 @default.
- W3157337682 hasAuthorship W3157337682A5021682632 @default.
- W3157337682 hasAuthorship W3157337682A5027671551 @default.
- W3157337682 hasAuthorship W3157337682A5054457407 @default.
- W3157337682 hasAuthorship W3157337682A5056465234 @default.
- W3157337682 hasConcept C119599485 @default.
- W3157337682 hasConcept C119857082 @default.
- W3157337682 hasConcept C12267149 @default.
- W3157337682 hasConcept C127413603 @default.
- W3157337682 hasConcept C154945302 @default.
- W3157337682 hasConcept C155011858 @default.
- W3157337682 hasConcept C169903167 @default.
- W3157337682 hasConcept C181966813 @default.
- W3157337682 hasConcept C185592680 @default.
- W3157337682 hasConcept C191897082 @default.
- W3157337682 hasConcept C192562407 @default.
- W3157337682 hasConcept C2779851234 @default.
- W3157337682 hasConcept C41008148 @default.
- W3157337682 hasConcept C41291067 @default.
- W3157337682 hasConcept C49040817 @default.
- W3157337682 hasConcept C8010536 @default.
- W3157337682 hasConcept C95623464 @default.
- W3157337682 hasConceptScore W3157337682C119599485 @default.
- W3157337682 hasConceptScore W3157337682C119857082 @default.
- W3157337682 hasConceptScore W3157337682C12267149 @default.
- W3157337682 hasConceptScore W3157337682C127413603 @default.
- W3157337682 hasConceptScore W3157337682C154945302 @default.
- W3157337682 hasConceptScore W3157337682C155011858 @default.
- W3157337682 hasConceptScore W3157337682C169903167 @default.
- W3157337682 hasConceptScore W3157337682C181966813 @default.
- W3157337682 hasConceptScore W3157337682C185592680 @default.
- W3157337682 hasConceptScore W3157337682C191897082 @default.
- W3157337682 hasConceptScore W3157337682C192562407 @default.
- W3157337682 hasConceptScore W3157337682C2779851234 @default.
- W3157337682 hasConceptScore W3157337682C41008148 @default.
- W3157337682 hasConceptScore W3157337682C41291067 @default.