Investigating band gap directness using machine learning (2021)
- Authors:
- USP affiliated authors: OLIVEIRA JUNIOR, OSVALDO NOVAIS DE - IFSC ; POPOLIN NETO, MÁRIO - ICMC
- Unidades: IFSC; ICMC
- Subjects: NANOPARTÍCULAS; APRENDIZADO COMPUTACIONAL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: American Physical Society - APS
- Publisher place: College Park
- Date published: 2021
- Source:
- Título: Bulletin of the American Physical Society
- ISSN: 0003-0503
- Volume/Número/Paginação/Ano: v. 66, n. 1, abstr. C21.00009, Mar. 2021
- Conference titles: APS March Meeting
-
ABNT
MELO, Elton Ogoshi de et al. Investigating band gap directness using machine learning. Bulletin of the American Physical Society. College Park: American Physical Society - APS. Disponível em: https://meetings.aps.org/Meeting/MAR21/Session/C21.9. Acesso em: 27 dez. 2025. , 2021 -
APA
Melo, E. O. de, Popolin Neto, M., Acosta, C. M., Nascimento, G. M., Rodrigues, J., Oliveira Junior, O. N. de, et al. (2021). Investigating band gap directness using machine learning. Bulletin of the American Physical Society. College Park: American Physical Society - APS. Recuperado de https://meetings.aps.org/Meeting/MAR21/Session/C21.9 -
NLM
Melo EO de, Popolin Neto M, Acosta CM, Nascimento GM, Rodrigues J, Oliveira Junior ON de, Longstaffe JG, Dalpian GM. Investigating band gap directness using machine learning [Internet]. Bulletin of the American Physical Society. 2021 ; 66( 1):[citado 2025 dez. 27 ] Available from: https://meetings.aps.org/Meeting/MAR21/Session/C21.9 -
Vancouver
Melo EO de, Popolin Neto M, Acosta CM, Nascimento GM, Rodrigues J, Oliveira Junior ON de, Longstaffe JG, Dalpian GM. Investigating band gap directness using machine learning [Internet]. Bulletin of the American Physical Society. 2021 ; 66( 1):[citado 2025 dez. 27 ] Available from: https://meetings.aps.org/Meeting/MAR21/Session/C21.9 - Random Forest interpretability - explaining classification models and multivariate data through logic rules visualizations
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