Cargando…
Autonomous and dynamic precursor selection for solid-state materials synthesis
Solid-state synthesis plays an important role in the development of new materials and technologies. While in situ characterization and ab-initio computations have advanced our understanding of materials synthesis, experiments targeting new compounds often still require many different precursors and...
Autores principales: | Szymanski, Nathan J., Nevatia, Pragnay, Bartel, Christopher J., Zeng, Yan, Ceder, Gerbrand |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618174/ https://www.ncbi.nlm.nih.gov/pubmed/37907493 http://dx.doi.org/10.1038/s41467-023-42329-9 |
Ejemplares similares
-
Precursor recommendation for inorganic synthesis by machine learning materials similarity from scientific literature
por: He, Tanjin, et al.
Publicado: (2023) -
Machine-Learning
Rationalization and Prediction of
Solid-State Synthesis Conditions
por: Huo, Haoyan, et al.
Publicado: (2022) -
Assessing Thermodynamic Selectivity of Solid-State
Reactions for the Predictive Synthesis of Inorganic Materials
por: McDermott, Matthew J., et al.
Publicado: (2023) -
Text-mined dataset of inorganic materials synthesis recipes
por: Kononova, Olga, et al.
Publicado: (2019) -
Evaluating structure selection in the hydrothermal growth of FeS(2) pyrite and marcasite
por: Kitchaev, Daniil A., et al.
Publicado: (2016)