Machine Learning in Materials Science. [Editorial] (2024)
- Authors:
- Autor USP: SILVA, THEREZA AMÉLIA SOARES DA - FFCLRP
- Unidade: FFCLRP
- DOI: 10.1021/acs.jcim.4c00727
- Subjects: ALGORITMOS; APRENDIZADO COMPUTACIONAL; BIOMATERIAIS
- Language: Inglês
- Imprenta:
- Publisher place: Washington
- Date published: 2024
- Source:
- Título: Journal of Chemical Information and Modeling
- ISSN: 1549-9596
- Volume/Número/Paginação/Ano: v. 64, n. 10, p. 3959-3960, 2024
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: hybrid
- Licença: other-oa
-
ABNT
MERZ, Kenneth M et al. Machine Learning in Materials Science. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.jcim.4c00727. Acesso em: 26 dez. 2025. , 2024 -
APA
Merz, K. M., Choong, Y. S., Cournia, Z., Isayev, O., Soares, T. A., Wei, G. -W., & Zhu, F. (2024). Machine Learning in Materials Science. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1021/acs.jcim.4c00727 -
NLM
Merz KM, Choong YS, Cournia Z, Isayev O, Soares TA, Wei G-W, Zhu F. Machine Learning in Materials Science. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 10): 3959-3960.[citado 2025 dez. 26 ] Available from: https://doi.org/10.1021/acs.jcim.4c00727 -
Vancouver
Merz KM, Choong YS, Cournia Z, Isayev O, Soares TA, Wei G-W, Zhu F. Machine Learning in Materials Science. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 10): 3959-3960.[citado 2025 dez. 26 ] Available from: https://doi.org/10.1021/acs.jcim.4c00727 - Exploring the molecular dynamics of a lipid-A vesicle at the atom level: morphology and permeation mechanism
- Editing DNA and RNA through Computations [Editorial]
- Enhancing coarse-grained models through machine learning. [Editorial]
- The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial]
- Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial]
- Interfacial structurization between triolein and water from pH and buffer ions
- Bias amplification in gender, gender identity, and geographical affiliation
- Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial]
- Accelerating lipid flip-flop at low concentrations: a general mechanism for membrane binding peptides
- Computational chemistry in Asia [Editorial]
Informações sobre o DOI: 10.1021/acs.jcim.4c00727 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
003246111.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
