Cargando…
New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts
[Image: see text] Despite decades of effort, no earth-abundant homogeneous catalysts have been discovered that can selectively oxidize methane to methanol. We exploit active learning to simultaneously optimize methane activation and methanol release calculated with machine learning-accelerated densi...
Autores principales: | Nandy, Aditya, Duan, Chenru, Goffinet, Conrad, Kulik, Heather J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9135396/ https://www.ncbi.nlm.nih.gov/pubmed/35647589 http://dx.doi.org/10.1021/jacsau.2c00176 |
Ejemplares similares
-
Active Learning Exploration
of Transition-Metal Complexes
to Discover Method-Insensitive and Synthetically Accessible Chromophores
por: Duan, Chenru, et al.
Publicado: (2022) -
Low-cost machine learning prediction of excited state properties of iridium-centered phosphors
por: Terrones, Gianmarco G., et al.
Publicado: (2023) -
Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost
por: Duan, Chenru, et al.
Publicado: (2022) -
A quantitative uncertainty metric controls error in neural network-driven chemical discovery
por: Janet, Jon Paul, et al.
Publicado: (2019) -
Accurate Multiobjective Design in a Space of Millions
of Transition Metal Complexes with Neural-Network-Driven Efficient
Global Optimization
por: Janet, Jon Paul, et al.
Publicado: (2020)