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For: Manzhos S, Wang X, Dawes R, Carrington T. A Nested Molecule-Independent Neural Network Approach for High-Quality Potential Fits†. J Phys Chem A 2006;110:5295-304. [PMID: 16623455 DOI: 10.1021/jp055253z] [Citation(s) in RCA: 131] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Number Cited by Other Article(s)
1
Ma S, Cao Y, Shi YF, Shang C, He L, Liu ZP. Data-driven discovery of active phosphine ligand space for cross-coupling reactions. Chem Sci 2024;15:13359-13368. [PMID: 39183919 PMCID: PMC11339946 DOI: 10.1039/d4sc02327g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 07/18/2024] [Indexed: 08/27/2024]  Open
2
Manzhos S, Chen QG, Lee WY, Heejoo Y, Ihara M, Chueh CC. Computational Investigation of the Potential and Limitations of Machine Learning with Neural Network Circuits Based on Synaptic Transistors. J Phys Chem Lett 2024;15:6974-6985. [PMID: 38941557 PMCID: PMC11247485 DOI: 10.1021/acs.jpclett.4c01413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
3
Spencer RJ, Zhanserkeev AA, Yang EL, Steele RP. The Near-Sightedness of Many-Body Interactions in Anharmonic Vibrational Couplings. J Am Chem Soc 2024;146:15376-15392. [PMID: 38771156 DOI: 10.1021/jacs.4c03198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
4
Weike N, Fritsch F, Eisfeld W. Compensation States Approach in the Hybrid Diabatization Scheme: Extension to Multidimensional Data and Properties. J Phys Chem A 2024;128:4353-4368. [PMID: 38748493 DOI: 10.1021/acs.jpca.4c01134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
5
Pan X, Snyder R, Wang JN, Lander C, Wickizer C, Van R, Chesney A, Xue Y, Mao Y, Mei Y, Pu J, Shao Y. Training machine learning potentials for reactive systems: A Colab tutorial on basic models. J Comput Chem 2024;45:638-647. [PMID: 38082539 PMCID: PMC10923003 DOI: 10.1002/jcc.27269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 11/10/2023] [Accepted: 11/11/2023] [Indexed: 01/18/2024]
6
Weike N, Eisfeld W. The effective relativistic coupling by asymptotic representation approach for molecules with multiple relativistic atoms. J Chem Phys 2024;160:064104. [PMID: 38341788 DOI: 10.1063/5.0191529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 01/18/2024] [Indexed: 02/13/2024]  Open
7
Iyengar SS, Ricard TC, Zhu X. Reformulation of All ONIOM-Type Molecular Fragmentation Approaches and Many-Body Theories Using Graph-Theory-Based Projection Operators: Applications to Dynamics, Molecular Potential Surfaces, Machine Learning, and Quantum Computing. J Phys Chem A 2024;128:466-478. [PMID: 38180503 DOI: 10.1021/acs.jpca.3c05630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
8
Manzhos S, Ihara M. A controlled study of the effect of deviations from symmetry of the potential energy surface (PES) on the accuracy of the vibrational spectrum computed with collocation. J Chem Phys 2023;159:211103. [PMID: 38038200 DOI: 10.1063/5.0182373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 12/02/2023]  Open
9
Ricard TC, Zhu X, Iyengar SS. Capturing Weak Interactions in Surface Adsorbate Systems at Coupled Cluster Accuracy: A Graph-Theoretic Molecular Fragmentation Approach Improved through Machine Learning. J Chem Theory Comput 2023. [PMID: 38019639 DOI: 10.1021/acs.jctc.3c00955] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
10
Manzhos S, Ihara M. Neural Network with Optimal Neuron Activation Functions Based on Additive Gaussian Process Regression. J Phys Chem A 2023;127:7823-7835. [PMID: 37698519 DOI: 10.1021/acs.jpca.3c02949] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
11
Arab F, Nazari F, Illas F. Artificial Neural Network-Derived Unified Six-Dimensional Potential Energy Surface for Tetra Atomic Isomers of the Biogenic [H, C, N, O] System. J Chem Theory Comput 2023;19:1186-1196. [PMID: 36735891 PMCID: PMC9979606 DOI: 10.1021/acs.jctc.2c00915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
12
Manzhos S, Ihara M. The loss of the property of locality of the kernel in high-dimensional Gaussian process regression on the example of the fitting of molecular potential energy surfaces. J Chem Phys 2023;158:044111. [PMID: 36725493 DOI: 10.1063/5.0136156] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]  Open
13
Manzhos S, Tsuda S, Ihara M. Machine learning in computational chemistry: interplay between (non)linearity, basis sets, and dimensionality. Phys Chem Chem Phys 2023;25:1546-1555. [PMID: 36562317 DOI: 10.1039/d2cp04155c] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
14
Muther T, Dahaghi AK, Syed FI, Van Pham V. Physical laws meet machine intelligence: current developments and future directions. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10329-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
15
Zhu X, Iyengar SS. Graph Theoretic Molecular Fragmentation for Multidimensional Potential Energy Surfaces Yield an Adaptive and General Transfer Machine Learning Protocol. J Chem Theory Comput 2022;18:5125-5144. [PMID: 35994592 DOI: 10.1021/acs.jctc.1c01241] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
16
Dai J, Krems RV. Quantum Gaussian process model of potential energy surface for a polyatomic molecule. J Chem Phys 2022;156:184802. [PMID: 35568545 DOI: 10.1063/5.0088821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]  Open
17
Zhang L, Zhang S, Owens A, Yurchenko SN, Dral PO. VIB5 database with accurate ab initio quantum chemical molecular potential energy surfaces. Sci Data 2022;9:84. [PMID: 35277513 PMCID: PMC8917215 DOI: 10.1038/s41597-022-01185-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/19/2022] [Indexed: 11/09/2022]  Open
18
Theoretical Description of Water from Single-Molecule to Condensed Phase: a Review of Recent Progress on Potential Energy Surfaces and Molecular Dynamics. CHINESE J CHEM PHYS 2022. [DOI: 10.1063/1674-0068/cjcp2201005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
19
Manzhos S, Ihara M. Computational vibrational spectroscopy of molecule-surface interactions: what is still difficult and what can be done about it. Phys Chem Chem Phys 2022;24:15158-15172. [DOI: 10.1039/d2cp01389d] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
20
Yang Z, Chen H, Chen M. Representing Globally Accurate Reactive Potential Energy Surfaces with Complex Topography by Combining Gaussian Process Regression and Neural Network. Phys Chem Chem Phys 2022;24:12827-12836. [DOI: 10.1039/d2cp00719c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
21
Omodemi O, Sprouse S, Herbert D, Kaledin M, Kaledin AL. On the Cartesian Representation of the Molecular Polarizability Tensor Surface by Polynomial Fitting to Ab Initio Data. J Chem Theory Comput 2021;18:37-45. [PMID: 34958587 DOI: 10.1021/acs.jctc.1c01015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
22
Asnaashari K, Krems RV. Gradient domain machine learning with composite kernels: improving the accuracy of PES and force fields for large molecules. MACHINE LEARNING: SCIENCE AND TECHNOLOGY 2021. [DOI: 10.1088/2632-2153/ac3845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]  Open
23
DiRisio RJ, Lu F, McCoy AB. GPU-Accelerated Neural Network Potential Energy Surfaces for Diffusion Monte Carlo. J Phys Chem A 2021;125:5849-5859. [PMID: 34165989 DOI: 10.1021/acs.jpca.1c03709] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
24
Behler J. Four Generations of High-Dimensional Neural Network Potentials. Chem Rev 2021;121:10037-10072. [DOI: 10.1021/acs.chemrev.0c00868] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
25
Allen AEA, Dusson G, Ortner C, Csányi G. Atomic permutationally invariant polynomials for fitting molecular force fields. MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2021. [DOI: 10.1088/2632-2153/abd51e] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
26
Quintas-Sánchez E, Dawes R. Spectroscopy and Scattering Studies Using Interpolated Ab Initio Potentials. Annu Rev Phys Chem 2021;72:399-421. [PMID: 33503385 DOI: 10.1146/annurev-physchem-090519-051837] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
27
Manzhos S, Carrington T. Neural Network Potential Energy Surfaces for Small Molecules and Reactions. Chem Rev 2020;121:10187-10217. [PMID: 33021368 DOI: 10.1021/acs.chemrev.0c00665] [Citation(s) in RCA: 119] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
28
Sugisawa H, Ida T, Krems RV. Gaussian process model of 51-dimensional potential energy surface for protonated imidazole dimer. J Chem Phys 2020;153:114101. [DOI: 10.1063/5.0023492] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]  Open
29
Williams DMG, Eisfeld W. Complete Nuclear Permutation Inversion Invariant Artificial Neural Network (CNPI-ANN) Diabatization for the Accurate Treatment of Vibronic Coupling Problems. J Phys Chem A 2020;124:7608-7621. [DOI: 10.1021/acs.jpca.0c05991] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
30
Dral PO, Owens A, Dral A, Csányi G. Hierarchical machine learning of potential energy surfaces. J Chem Phys 2020;152:204110. [DOI: 10.1063/5.0006498] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]  Open
31
Manzhos S. Machine learning for the solution of the Schrödinger equation. MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2020. [DOI: 10.1088/2632-2153/ab7d30] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
32
Dral PO. Quantum Chemistry in the Age of Machine Learning. J Phys Chem Lett 2020;11:2336-2347. [PMID: 32125858 DOI: 10.1021/acs.jpclett.9b03664] [Citation(s) in RCA: 194] [Impact Index Per Article: 48.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
33
Dai J, Krems RV. Interpolation and Extrapolation of Global Potential Energy Surfaces for Polyatomic Systems by Gaussian Processes with Composite Kernels. J Chem Theory Comput 2020;16:1386-1395. [DOI: 10.1021/acs.jctc.9b00700] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
34
Schröder M. Transforming high-dimensional potential energy surfaces into a canonical polyadic decomposition using Monte Carlo methods. J Chem Phys 2020;152:024108. [DOI: 10.1063/1.5140085] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]  Open
35
Dral PO. Quantum chemistry assisted by machine learning. ADVANCES IN QUANTUM CHEMISTRY 2020. [DOI: 10.1016/bs.aiq.2020.05.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
36
Flynn SW, Mandelshtam VA. Sampling general distributions with quasi-regular grids: Application to the vibrational spectra calculations. J Chem Phys 2019;151:241105. [DOI: 10.1063/1.5134677] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]  Open
37
Brown SE. From ab initio data to high-dimensional potential energy surfaces: A critical overview and assessment of the development of permutationally invariant polynomial potential energy surfaces for single molecules. J Chem Phys 2019;151:194111. [PMID: 31757150 DOI: 10.1063/1.5123999] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
38
Schran C, Behler J, Marx D. Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground. J Chem Theory Comput 2019;16:88-99. [DOI: 10.1021/acs.jctc.9b00805] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
39
Karandashev K, Vaníček J. A combined on-the-fly/interpolation procedure for evaluating energy values needed in molecular simulations. J Chem Phys 2019;151:174116. [PMID: 31703487 DOI: 10.1063/1.5124469] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
40
Williams DMG, Viel A, Eisfeld W. Diabatic neural network potentials for accurate vibronic quantum dynamics—The test case of planar NO3. J Chem Phys 2019;151:164118. [DOI: 10.1063/1.5125851] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
41
Panadés-Barrueta RL, Martínez-Núñez E, Peláez D. Specific Reaction Parameter Multigrid POTFIT (SRP-MGPF): Automatic Generation of Sum-of-Products Form Potential Energy Surfaces for Quantum Dynamical Calculations. Front Chem 2019;7:576. [PMID: 31475138 PMCID: PMC6702682 DOI: 10.3389/fchem.2019.00576] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/30/2019] [Indexed: 11/13/2022]  Open
42
Ma S, Shang C, Liu ZP. Heterogeneous catalysis from structure to activity via SSW-NN method. J Chem Phys 2019. [DOI: 10.1063/1.5113673] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
43
Brorsen KR. Reproducing global potential energy surfaces with continuous-filter convolutional neural networks. J Chem Phys 2019;150:204104. [DOI: 10.1063/1.5093908] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]  Open
44
Christensen AS, Faber FA, von Lilienfeld OA. Operators in quantum machine learning: Response properties in chemical space. J Chem Phys 2019;150:064105. [DOI: 10.1063/1.5053562] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
45
McConnell SR, Kästner J. Instanton rate constant calculations using interpolated potential energy surfaces in nonredundant, rotationally and translationally invariant coordinates. J Comput Chem 2019;40:866-874. [PMID: 30677168 DOI: 10.1002/jcc.25770] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 11/25/2018] [Accepted: 11/27/2018] [Indexed: 11/07/2022]
46
Krems RV. Bayesian machine learning for quantum molecular dynamics. Phys Chem Chem Phys 2019;21:13392-13410. [DOI: 10.1039/c9cp01883b] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
47
Golub P, Manzhos S. Kinetic energy densities based on the fourth order gradient expansion: performance in different classes of materials and improvement via machine learning. Phys Chem Chem Phys 2018;21:378-395. [PMID: 30525136 DOI: 10.1039/c8cp06433d] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
48
Williams DMG, Eisfeld W. Neural network diabatization: A new ansatz for accurate high-dimensional coupled potential energy surfaces. J Chem Phys 2018;149:204106. [DOI: 10.1063/1.5053664] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]  Open
49
Inverse Multiquadratic Functions as the Basis for the Rectangular Collocation Method to Solve the Vibrational Schrödinger Equation. MATHEMATICS 2018. [DOI: 10.3390/math6110253] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
50
Petty C, Spada RFK, Machado FBC, Poirier B. Accurate rovibrational energies of ozone isotopologues up toJ= 10 utilizing artificial neural networks. J Chem Phys 2018;149:024307. [DOI: 10.1063/1.5036602] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]  Open
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