The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Molecular potential energy surfaces by interpolation
Abstract
A moving interpolation technique which provides an accurate representation of potential energy surfaces for polyatomic molecules is presented. The method uses the ab initio energy, energy gradient, and second derivatives calculated at dynamically important configurations. The interpolant of the energy and its derivatives converges to the exact value with increasing number of data. A procedure is given for finding the optimum configurations at which ab initio calculations are performed. The method is demonstrated by application to the six-dimensional surface of a diatomic plus diatomic reaction.
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Cites
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Gonzalez, C., & Schlegel, H. B. (1989) · The Journal of Chemical Physics · doi:10.1063/1.456010 · Cited by 6,159
Curve and surface fitting : an introduction
Lancaster, P., & Šalkauskas, K. (1986) · CERN Document Server (European Organization for Nuclear Research) · Cited by 797
On evaluating the reaction path Hamiltonian
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On the Analytical Mechanics of Chemical Reactions. Quantum Mechanics of Linear Collisions
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(1987) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(87)90088-7 · Cited by 503
Ab initio reaction paths and direct dynamics calculations
Baldridge, K. K., Gordon, M. S., Steckler, R., & Truhlar, D. G. (1989) · The Journal of Physical Chemistry · doi:10.1021/j100350a018 · Cited by 353
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On representing chemical environments
Bartók, A. P., Kondor, R., & Csányi, G. (2013) · Physical Review B · doi:10.1103/physrevb.87.184115 · Cited by 2,572
Current Status of Transition-State Theory
Truhlar, D. G., Garrett, B. C., & Klippenstein, S. J. (1996) · The Journal of Physical Chemistry · doi:10.1021/jp953748q · Cited by 2,279
Constructing high‐dimensional neural network potentials: A tutorial review
Behler, J. (2015) · International Journal of Quantum Chemistry · doi:10.1002/qua.24890 · Cited by 884
Four Generations of High-Dimensional Neural Network Potentials
Behler, J. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00868 · Cited by 873
Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations
Behler, J. (2011) · Physical Chemistry Chemical Physics · doi:10.1039/c1cp21668f · Cited by 781
Metadata
- Authors
- Ischtwan, J., & Collins, M. A.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 1994-06-01
- Volume
- 100
- Issue
- 11
- Pages
- 8080-8088
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2021891874
- Cited by
- 473
- References
- 18
- FWCI
- 4.64
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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