Learning organo‐transition metal catalyzed reactions by graph neural networks.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 341, doi. 10.1002/jcc.27243
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- Publication type:
- Article
Works matching IS 01928651 AND DT 2024 AND VI 45 AND IP 6
Results: 6
1
2
Protein3D: Enabling analysis and extraction of metal‐containing sites from the Protein Data Bank with molSimplify.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 352, doi. 10.1002/jcc.27242
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- Publication type:
- Article
3
Small molecules (CO<sub>2</sub>, iPrNCO, and iPrNCNiPr) activation by the metallomimetics (μ‐Hydrido) diborane anion: A DFT investigation on mechanism and chemoselectivity controlling.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 331, doi. 10.1002/jcc.27240
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- Publication type:
- Article
4
Bridging Eulerian and Lagrangian Poisson–Boltzmann solvers by ESES.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 306, doi. 10.1002/jcc.27239
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- Publication type:
- Article
5
Predictions of photophysical properties of phosphorescent platinum(II) complexes based on ensemble machine learning approach.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 321, doi. 10.1002/jcc.27238
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- Publication type:
- Article
6
Issue Information.
- Published in:
- Journal of Computational Chemistry, 2024, v. 45, n. 6, p. 301, doi. 10.1002/jcc.27139
- Publication type:
- Article