1
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Hou S, Wang Z, Xie C. Accurate and Efficient Schemes for Mapping Out Two Isolated Seams of Conical Intersections with Neural Networks Solely Based on Adiabatic Energies: A Case Study of H + + NO( X2Π) → H + NO +( X1Σ +). J Phys Chem A 2024. [PMID: 39121359 DOI: 10.1021/acs.jpca.4c04392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2024]
Abstract
A new scheme in the neural network (NN) diabatization approach that solely utilizes the adiabatic energies for constructing the global diabatic potential energy matrices (PEMs) of the molecular systems with two isolated seams of conical intersections (CIs) is proposed. Taking a prototype charge transfer reaction H+ + NO(X2Π) → H + NO+(X1Σ+), where two seams of CIs are located at the different linear geometries N-O-H and O-N-H, for example, the diabatization with the new scheme including a diabatic state constraint is shown to map out the topographies of both two linear CIs with 100% of the success rate in 10 different trainings, while the diabatization without such constraint hardly represents CIs, in which the avoided crossings appear instead. Simultaneously, we propose a scheme to separate the whole reactive space into three different regions and define the minimal Euclidean distances for each region to efficiently sample the energy points for the NN trainings. Through adjusting the minimal Euclidean distances, the number of the adiabatic energy data needed in the construction of diabatic PEM can be heavily decreased, lowered from ∼2000 to ∼280 energy points, which is much less than the number (>22 000) of ab initio energy points used in earlier spline diabatic PEM. Further quantum dynamic calculations show that the reaction probabilities, vibrational state distributions, and vibrational state resolved differential cross sections are well reproduced on the new NN diabatic PEM, validating these schemes for constructing the diabatic PEM.
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Affiliation(s)
- Siting Hou
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
| | - Zhimo Wang
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
| | - Changjian Xie
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
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2
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Weike N, Eisfeld W, Dunseath KM, Viel A. Hydrogen-iodine scattering. II. Rovibronic analysis and collisional dynamics. J Chem Phys 2024; 161:014302. [PMID: 38953441 DOI: 10.1063/5.0219156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Accepted: 06/06/2024] [Indexed: 07/04/2024] Open
Abstract
Our recently published [Weike et al., J. Chem. Phys. 159, 244119 (2023)] spin-orbit coupled diabatic potential energy model for HI is used in a thorough analysis of bound and quasi-bound states as well as elastic and inelastic processes in H + I collisions. The potential energy model, designed explicitly for studying scattering, accurately describes the various couplings in the system, which lead to complex dynamics. Ro-vibronic bound and quasi-bound states related to the adiabatic electronic ground state and an excited electronic state are analyzed. Calculations using the full 104 × 104 diabatic matrix model or a single adiabatic state are compared in order to investigate approximations in the latter. Elastic and inelastic scattering cross sections as well as thermal rates between the ground and first excited fine structure levels of iodine are computed for collision energies up to 12 500 cm-1. Resonances related to the quasi-bound states are analyzed in terms of their energy, width, lifetime, and decay probabilities. The effect of different resonances on the thermal rates is discussed. Resonances between 30 000 and 40 000 cm-1 are also studied for selected values of the total angular momentum, in particular their decay probabilities into different final states of iodine and hence their potential effect on branching ratios in photodissociation of HI.
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Affiliation(s)
- Nicole Weike
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Kevin M Dunseath
- Univ Rennes, CNRS, IPR (Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
| | - Alexandra Viel
- Univ Rennes, CNRS, IPR (Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
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3
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Neville SP, Schuurman MS. Calculation of quasi-diabatic states within the DFT/MRCI(2) framework: The QD-DFT/MRCI(2) method. J Chem Phys 2024; 160:234109. [PMID: 38899687 DOI: 10.1063/5.0214637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Accepted: 05/23/2024] [Indexed: 06/21/2024] Open
Abstract
We describe a procedure for the calculation of quasi-diabatic states within the recently introduced DFT/MRCI(2) framework [S. P. Neville and M. S. Schuurman, J. Chem. Phys. 157, 164103 (2022)]. Based on an effective Hamiltonian formalism, the proposed procedure, which we term QD-DFT/MRCI(2), has the advantageous characteristics of being simultaneously highly efficient and effectively black box in nature while directly yielding both quasi-diabatic potentials and wave functions of high quality. The accuracy and efficiency of the QD-DFT/MRCI(2) formalism are demonstrated via the simulation of the vibronic absorption spectra of furan and chlorophyll a.
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Affiliation(s)
- Simon P Neville
- National Research Council Canada, 100 Sussex Drive, Ottawa, Ontario K1A 0R6, Canada
| | - Michael S Schuurman
- National Research Council Canada, 100 Sussex Drive, Ottawa, Ontario K1A 0R6, Canada
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie Curie, Ottawa, Ontario K1N 6N5, Canada
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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]
Abstract
The diabatization of reactive systems for more than just a couple of states is a very demanding problem and generally requires advanced diabatization techniques. Especially for dissociative processes, the drastic changes in the adiabatic wave functions often would require large diabatic state bases, which quickly become impractical. Recently, we addressed this problem by the compensation states approach developed in the context of our hybrid diabatization scheme. This scheme utilizes wave function as well as energy data in combination with a diabatic potential model. In regions where the initial diabatic state basis becomes insufficient for an appropriate representation of the adiabatic states, new model states are generated. The new model states compensate for the state space not spanned by the initial diabatic basis. Such a compensation state is obtained by projecting the initial diabatic state space out of the adiabatic wave function. This yields a very efficient basis representation of the electronic Hamiltonian. The present work presents two new aspects. First, it is shown how other operators like the spin-orbit operator in the framework of the Effective Relativistic Coupling by Asymptotic Representation (ERCAR) can be evaluated in this compact model state space without losing the correct wave function information and accuracy. Second, the extension of the approach to multidimensional potential energy surface models is presented for methyl iodide including the C-I dissociation coordinate and the angular H3C-I bending coordinates.
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Affiliation(s)
- Nicole Weike
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Fabian Fritsch
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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5
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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
Abstract
The Effective Relativistic Coupling by Asymptotic Representation (ERCAR) approach is a method to generate fully coupled diabatic potential energy surfaces (PESs) including relativistic effects, especially spin-orbit coupling. The spin-orbit coupling of a full molecule is determined only by the atomic states of selected relativistically treated atoms. The full molecular coupling effect is obtained by a diabatization with respect to asymptotic states, resulting in the correct geometry dependence of the spin-orbit effect. The ERCAR approach has been developed over the last decade and initially only for molecules with a single relativistic atom. This work presents its extension to molecules with more than a single relativistic atom using the iodine molecule as a proof-of-principle example. The theory for the general multiple atomic ERCAR approach is given. In this case, the diabatic basis is defined at the asymptote where all relativistic atoms are separated from the remaining molecular fragment. The effective spin-orbit operator is then a sum of spin-orbit operators acting on isolated relativistic atoms. PESs for the iodine molecule are developed within the new approach and it is shown that the resulting fine structure states are in good agreement with spin-orbit ab initio calculations.
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Affiliation(s)
- Nicole Weike
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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Sršeň Š, von Lilienfeld OA, Slavíček P. Fast and accurate excited states predictions: machine learning and diabatization. Phys Chem Chem Phys 2024; 26:4306-4319. [PMID: 38234256 PMCID: PMC10829538 DOI: 10.1039/d3cp05685f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 01/02/2024] [Indexed: 01/19/2024]
Abstract
The efficiency of machine learning algorithms for electronically excited states is far behind ground-state applications. One of the underlying problems is the insufficient smoothness of the fitted potential energy surfaces and other properties in the vicinity of state crossings and conical intersections, which is a prerequisite for an efficient regression. Smooth surfaces can be obtained by switching to the diabatic basis. However, diabatization itself is still an outstanding problem. We overcome these limitations by solving both problems at once. We use a machine learning approach combining clustering and regression techniques to correct for the deficiencies of property-based diabatization which, in return, provides us with smooth surfaces that can be easily fitted. Our approach extends the applicability of property-based diabatization to multidimensional systems. We utilize the proposed diabatization scheme to achieve higher prediction accuracy for adiabatic states and we show its performance by reconstructing global potential energy surfaces of excited states of nitrosyl fluoride and formaldehyde. While the proposed methodology is independent of the specific property-based diabatization and regression algorithm, we show its performance for kernel ridge regression and a very simple diabatization based on transition multipoles. Compared to most other algorithms based on machine learning, our approach needs only a small amount of training data.
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Affiliation(s)
- Štěpán Sršeň
- Department of Physical Chemistry, University of Chemistry and Technology, Technická 5, 162 28 Prague, Czech Republic.
- Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 17, 1090 Wien, Austria
| | - O Anatole von Lilienfeld
- Vector Institute for Artificial Intelligence, Toronto, ON, M5S 1M1, Canada
- Departments of Chemistry, Materials Science and Engineering, and Physics, University of Toronto, St. George Campus, Toronto, ON, Canada
- Machine Learning Group, Technische Universität Berlin and Institute for the Foundations of Learning and Data, 10587 Berlin, Germany
| | - Petr Slavíček
- Department of Physical Chemistry, University of Chemistry and Technology, Technická 5, 162 28 Prague, Czech Republic.
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7
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Weike N, Viel A, Eisfeld W. Hydrogen-iodine scattering. I. Development of an accurate spin-orbit coupled diabatic potential energy model. J Chem Phys 2023; 159:244119. [PMID: 38156638 DOI: 10.1063/5.0186787] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/05/2023] [Indexed: 01/03/2024] Open
Abstract
The scattering of H by I is a prototypical model system for light-heavy scattering in which relativistic coupling effects must be taken into account. Scattering calculations depend strongly on the accuracy of the potential energy surface (PES) model. The methodology to obtain such an accurate PES model suitable for scattering calculations is presented, which includes spin-orbit (SO) coupling within the Effective Relativistic Coupling by Asymptotic Representation (ERCAR) approach. In this approach, the SO coupling is determined only for the atomic states of the heavy atom, and the geometry dependence of the SO effect is accounted for by a diabatization with respect to asymptotic states. The accuracy of the full model, composed of a Coulomb part and the SO model, is achieved in the following ways. For the SO model, the extended ERCAR approach is applied, which accounts for both intra-state and inter-state SO coupling, and an extended number of diabatic states are included. The corresponding coupling constants for the SO operator are obtained from experiments, which are more accurate than computed values. In the Coulomb Hamiltonian model, special attention is paid to the long range behavior and accurate c6 dispersion coefficients. The flexibility and accuracy of this Coulomb model are achieved by combining partial models for three different regions. These are merged via artificial neural networks, which also refine the model further. In this way, an extremely accurate PES model for hydrogen iodide is obtained, suitable for accurate scattering calculations.
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Affiliation(s)
- Nicole Weike
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Alexandra Viel
- Univ Rennes, CNRS, IPR (Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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8
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Li C, Hou S, Xie C. Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies and Physical Considerations: Toward Quantum Dynamic Accuracy. J Chem Theory Comput 2023. [PMID: 37216273 DOI: 10.1021/acs.jctc.2c01074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
A permutation invariant polynomial-neural network (PIP-NN) approach for constructing the global diabatic potential energy matrices (PEMs) of the coupled states of molecules is proposed. Specifically, the diabatization scheme is based merely on the adiabatic energy data of the system, which is ideally a most convenient way due to not requiring additional ab initio calculations for the data of the derivative coupling or any other physical properties of the molecule. Considering the permutation and coupling characteristics of the system, particularly in the presence of conical intersections, some vital treatments for the off-diagonal terms in diabatic PEM are essentially needed. Taking the photodissociation of H2O(X~/B~)/NH3(X~/A~) and nonadiabatic reaction Na(3p) + H2 → NaH(Σ+) + H for example, this PIP-NN method is shown to build up the global diabatic PEMs effectively and accurately. The root-mean-square errors of the adiabatic potential energies in the fitting for three different systems are all small (<10 meV). Further quantum dynamic calculations show that the absorption spectra and product branching ratios in both H2O(X~/B~) and NH3(X~/A~) nonadiabatic photodissociation are well reproduced on the new diabatic PEMs, and the nonadiabatic reaction probability of Na(3p) + H2 → NaH(Σ+) + H obtained on the new diabatic PEMs of the 12A1 and 12B2 states is in reasonably good agreement with previous theoretical result as well, validating this new PIP-NN method.
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Affiliation(s)
- Chaofan Li
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
| | - Siting Hou
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
| | - Changjian Xie
- Institute of Modern Physics, Shaanxi Key Laboratory for Theoretical Physics Frontiers, Northwest University, Xi'an 710127, China
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9
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Guan Y, Yarkony DR, Zhang DH. Permutation invariant polynomial neural network based diabatic ansatz for the (E + A) × (e + a) Jahn-Teller and Pseudo-Jahn-Teller systems. J Chem Phys 2022; 157:014110. [PMID: 35803819 DOI: 10.1063/5.0096912] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
In this work, the permutation invariant polynomial neural network (PIP-NN) approach is employed to construct a quasi-diabatic Hamiltonian for system with non-Abelian symmetries. It provides a flexible and compact NN-based diabatic ansatz from the related approach of Williams, Eisfeld, and co-workers. The example of H3 + is studied, which is an (E + A) × (e + a) Jahn-Teller and Pseudo-Jahn-Teller system. The PIP-NN diabatic ansatz is based on the symmetric polynomial expansion of Viel and Eisfeld, the coefficients of which are expressed with neural network functions that take permutation-invariant polynomials as input. This PIP-NN-based diabatic ansatz not only preserves the correct symmetry but also provides functional flexibility to accurately reproduce ab initio electronic structure data, thus resulting in excellent fits. The adiabatic energies, energy gradients, and derivative couplings are well reproduced. A good description of the local topology of the conical intersection seam is also achieved. Therefore, this diabatic ansatz completes the PIP-NN based representation of DPEM with correct symmetries and will enable us to diabatize even more complicated systems with complex symmetries.
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Affiliation(s)
- Yafu Guan
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, People's Republic of China
| | - David R Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Dong H Zhang
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, People's Republic of China
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10
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Weike N, Chanut E, Hoppe H, Eisfeld W. Development of a fully coupled diabatic spin-orbit model for the photodissociation of phenyl iodide. J Chem Phys 2022; 156:224109. [PMID: 35705416 DOI: 10.1063/5.0088205] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The theoretical treatment of the quantum dynamics of the phenyl iodide photodissociation requires an accurate analytical potential energy surface (PES) model. This model must also account for spin-orbit (SO) coupling. This study is the first step to construct accurate SO coupled PESs, namely, for the C-I dissociation coordinate. The model is based on the Effective Relativistic Coupling by Asymptotic Representation (ERCAR) method developed over the past ten years. The SO-free Hamiltonian is represented in an asymptotic diabatic basis and then combined with an atomic effective relativistic coupling operator determined analytically. In contrast to the previously studied cases (HI, CH3I), the diabatic basis states are due to excitations in the phenyl fragment rather than the iodine atom. An accurate analytical model of the ab initio reference data is determined in two steps. The first step is a simple reference model describing the data qualitatively. This reference model is corrected through a trained artificial neural-network to achieve high accuracy. The SO-free and the fine structure states resulting from this ERCAR model are discussed extensively in the context of the photodissociation.
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Affiliation(s)
- Nicole Weike
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Emma Chanut
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Hannes Hoppe
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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Rey M. Novel methodology for systematically constructing global effective models from ab initio-based surfaces: A new insight into high-resolution molecular spectra analysis. J Chem Phys 2022; 156:224103. [PMID: 35705402 DOI: 10.1063/5.0089097] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
In this paper, a novel methodology is presented for the construction of ab initio effective rotation-vibration spectroscopic models from potential energy and dipole moment surfaces. Non-empirical effective Hamiltonians are obtained via the block-diagonalization of selected variationally computed eigenvector matrices. For the first time, the derivation of an effective dipole moment is carried out in a systematic way. This general approach can be implemented quite easily in most of the variational computer codes and turns out to be a clear alternative to the rather involved Van Vleck perturbation method. Symmetry is exploited at all stages to translate first-principles calculations into a set of spectroscopic parameters to be further refined on experiment. We demonstrate on H2CO, PH3, CH4, C2H4, and SF6 that the proposed effective model can provide crucial information to spectroscopists within a very short time compared to empirical spectroscopic models. This approach brings a new insight into high-resolution spectrum analysis of polyatomic molecules and will be also of great help in the modeling of hot atmospheres where completeness is important.
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Affiliation(s)
- Michael Rey
- Groupe de Spectrométrie Moléculaire et Atmosphérique, UMR CNRS 7331, BP 1039, F-51687 Reims Cedex 2, France
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12
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Shu Y, Varga Z, Kanchanakungwankul S, Zhang L, Truhlar DG. Diabatic States of Molecules. J Phys Chem A 2022; 126:992-1018. [PMID: 35138102 DOI: 10.1021/acs.jpca.1c10583] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Quantitative simulations of electronically nonadiabatic molecular processes require both accurate dynamics algorithms and accurate electronic structure information. Direct semiclassical nonadiabatic dynamics is expensive due to the high cost of electronic structure calculations, and hence it is limited to small systems, limited ensemble averaging, ultrafast processes, and/or electronic structure methods that are only semiquantitatively accurate. The cost of dynamics calculations can be made manageable if analytic fits are made to the electronic structure data, and such fits are most conveniently carried out in a diabatic representation because the surfaces are smooth and the couplings between states are smooth scalar functions. Diabatic representations, unlike the adiabatic ones produced by most electronic structure methods, are not unique, and finding suitable diabatic representations often involves time-consuming nonsystematic diabatization steps. The biggest drawback of using diabatic bases is that it can require large amounts of effort to perform a globally consistent diabatization, and one of our goals has been to develop methods to do this efficiently and automatically. In this Feature Article, we introduce the mathematical framework of diabatic representations, and we discuss diabatization methods, including adiabatic-to-diabatic transformations and recent progress toward the goal of automatization.
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Affiliation(s)
- Yinan Shu
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States
| | - Zoltan Varga
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States
| | - Siriluk Kanchanakungwankul
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States
| | - Linyao Zhang
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States.,School of Energy Science and Engineering, Harbin Institute of Technology, Harbin 150001, P. R. China
| | - Donald G Truhlar
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455-0431, United States
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13
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Li Y, Liu J, Li J, Zhai Y, Yang J, Qu Z, Li H. A new permutation-symmetry-adapted machine learning diabatization procedure and its application in MgH 2 system. J Chem Phys 2021; 155:214102. [PMID: 34879675 DOI: 10.1063/5.0072004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
This work introduces a new permutation-symmetry-adapted machine learning diabatization procedure, termed the diabatization by equivariant neural network (DENN). In this approach, the permutation symmetric and anti-symmetric elements in diabatic potential energy metrics (DPEMs) were simultaneously simulated by the equivariant neural network. The diabatization by deep neural network scheme was adopted for machine learning diabatization, and non-zero diabatic coupling was included to increase accuracy in the near degenerate region. Based on DENN, the global DPEMs for 11A' and 21A' states of MgH2 have been constructed. To the best of our knowledge, these are the first global DPEMs for the MgH2 system. The root-mean-square-errors (RMSEs) for diagonal elements (H11 and H22) and the off-diagonal element (H12) around the conical intersection region were 5.824, 5.307, and 5.796 meV, respectively. The RMSEs of global adiabatic energies for two adiabatic states were 4.613 and 12.755 meV, respectively. The spectroscopic calculations of the 11A' state in the linear HMgH region are in good agreement with the experiment and previous theoretical results. The differences between calculated frequencies and corresponding experiment values are 1.38 and 1.08 cm-1 for anti-symmetric stretching fundamental vibrational frequency and first overtone. The global DPEMs obtained in this work should be useful for further quantum mechanics dynamic simulations on the MgH2 system.
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Affiliation(s)
- You Li
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Jingmin Liu
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Jiarui Li
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Yu Zhai
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Jitai Yang
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Zexing Qu
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
| | - Hui Li
- Institute of Theoretical Chemistry, College of Chemistry, Jilin University, 2519 Jiefang Road, Changchun 130023, People's Republic of China
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14
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Guan Y, Xie C, Yarkony DR, Guo H. High-fidelity first principles nonadiabaticity: diabatization, analytic representation of global diabatic potential energy matrices, and quantum dynamics. Phys Chem Chem Phys 2021; 23:24962-24983. [PMID: 34473156 DOI: 10.1039/d1cp03008f] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Nonadiabatic dynamics, which goes beyond the Born-Oppenheimer approximation, has increasingly been shown to play an important role in chemical processes, particularly those involving electronically excited states. Understanding multistate dynamics requires rigorous quantum characterization of both electronic and nuclear motion. However, such first principles treatments of multi-dimensional systems have so far been rather limited due to the lack of accurate coupled potential energy surfaces and difficulties associated with quantum dynamics. In this Perspective, we review recent advances in developing high-fidelity analytical diabatic potential energy matrices for quantum dynamical investigations of polyatomic uni- and bi-molecular nonadiabatic processes, by machine learning of high-level ab initio data. Special attention is paid to methods of diabatization, high fidelity construction of multi-state coupled potential energy surfaces and property surfaces, as well as quantum mechanical characterization of nonadiabatic nuclear dynamics. To illustrate the tremendous progress made by these new developments, several examples are discussed, in which direct comparison with quantum state resolved measurements led to either confirmation of the observation or sometimes reinterpretation of the experimental data. The insights gained in these prototypical systems greatly advance our understanding of nonadiabatic dynamics in chemical systems.
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Affiliation(s)
- Yafu Guan
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA.
| | - Changjian Xie
- Institute of Modern Physics, Northwest University, Xi'an, Shaanxi 710069, China.
| | - David R Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA.
| | - Hua Guo
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico, 87131, USA.
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Westermayr J, Marquetand P. Machine Learning for Electronically Excited States of Molecules. Chem Rev 2021; 121:9873-9926. [PMID: 33211478 PMCID: PMC8391943 DOI: 10.1021/acs.chemrev.0c00749] [Citation(s) in RCA: 162] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Indexed: 12/11/2022]
Abstract
Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculations, which are computationally expensive. In this review, we focus on not only how machine learning is employed to speed up such excited-state simulations but also how this branch of artificial intelligence can be used to advance this exciting research field in all its aspects. Discussed applications of machine learning for excited states include excited-state dynamics simulations, static calculations of absorption spectra, as well as many others. In order to put these studies into context, we discuss the promises and pitfalls of the involved machine learning techniques. Since the latter are mostly based on quantum chemistry calculations, we also provide a short introduction into excited-state electronic structure methods and approaches for nonadiabatic dynamics simulations and describe tricks and problems when using them in machine learning for excited states of molecules.
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Affiliation(s)
- Julia Westermayr
- Institute
of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
| | - Philipp Marquetand
- Institute
of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
- Vienna
Research Platform on Accelerating Photoreaction Discovery, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
- Data
Science @ Uni Vienna, University of Vienna, Währinger Strasse 29, 1090 Vienna, Austria
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16
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Abstract
Electronically excited states of molecules are at the heart of photochemistry, photophysics, as well as photobiology and also play a role in material science. Their theoretical description requires highly accurate quantum chemical calculations, which are computationally expensive. In this review, we focus on not only how machine learning is employed to speed up such excited-state simulations but also how this branch of artificial intelligence can be used to advance this exciting research field in all its aspects. Discussed applications of machine learning for excited states include excited-state dynamics simulations, static calculations of absorption spectra, as well as many others. In order to put these studies into context, we discuss the promises and pitfalls of the involved machine learning techniques. Since the latter are mostly based on quantum chemistry calculations, we also provide a short introduction into excited-state electronic structure methods and approaches for nonadiabatic dynamics simulations and describe tricks and problems when using them in machine learning for excited states of molecules.
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Affiliation(s)
- Julia Westermayr
- Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
| | - Philipp Marquetand
- Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
- Vienna Research Platform on Accelerating Photoreaction Discovery, University of Vienna, Währinger Strasse 17, 1090 Vienna, Austria
- Data Science @ Uni Vienna, University of Vienna, Währinger Strasse 29, 1090 Vienna, Austria
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17
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Abstract
Theoretical simulations of electronic excitations and associated processes in molecules are indispensable for fundamental research and technological innovations. However, such simulations are notoriously challenging to perform with quantum mechanical methods. Advances in machine learning open many new avenues for assisting molecular excited-state simulations. In this Review, we track such progress, assess the current state of the art and highlight the critical issues to solve in the future. We overview a broad range of machine learning applications in excited-state research, which include the prediction of molecular properties, improvements of quantum mechanical methods for the calculations of excited-state properties and the search for new materials. Machine learning approaches can help us understand hidden factors that influence photo-processes, leading to a better control of such processes and new rules for the design of materials for optoelectronic applications.
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18
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Wang Y, Guan Y, Guo H, Yarkony DR. Enabling complete multichannel nonadiabatic dynamics: A global representation of the two-channel coupled, 1,2 1A and 1 3A states of NH 3 using neural networks. J Chem Phys 2021; 154:094121. [PMID: 33685133 DOI: 10.1063/5.0037684] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Global coupled three-state two-channel potential energy and property/interaction (dipole and spin-orbit coupling) surfaces for the dissociation of NH3(Ã) into NH + H2 and NH2 + H are reported. The permutational invariant polynomial-neural network approach is used to simultaneously fit and diabatize the electronic Hamiltonian by fitting the energies, energy gradients, and derivative couplings of the two coupled lowest-lying singlet states as well as fitting the energy and energy gradients of the lowest-lying triplet state. The key issue in fitting property matrix elements in the diabatic basis is that the diabatic surfaces must be smooth, that is, the diabatization must remove spikes in the original adiabatic property surfaces attributable to the switch of electronic wavefunctions at the conical intersection seam. Here, we employ the fit potential energy matrix to transform properties in the adiabatic representation to a quasi-diabatic representation and remove the discontinuity near the conical intersection seam. The property matrix elements can then be fit with smooth neural network functions. The coupled potential energy surfaces along with the dipole and spin-orbit coupling surfaces will enable more accurate and complete treatment of optical transitions, as well as nonadiabatic internal conversion and intersystem crossing.
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Affiliation(s)
- Yuchen Wang
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Yafu Guan
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Hua Guo
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA
| | - David R Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
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19
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Yin Z, Braams BJ, Fu B, Zhang DH. Neural Network Representation of Three-State Quasidiabatic Hamiltonians Based on the Transformation Properties from a Valence Bond Model: Three Singlet States of H3+. J Chem Theory Comput 2021; 17:1678-1690. [DOI: 10.1021/acs.jctc.0c01336] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Zhengxi Yin
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Bastiaan J. Braams
- Centrum Wiskunde & Informatica (CWI), the Dutch National Center for Mathematics and Computer Science, 1098 XG Amsterdam, Netherlands
| | - Bina Fu
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
| | - Dong H. Zhang
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
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20
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Viel A, Williams DMG, Eisfeld W. Accurate quantum dynamics simulation of the photodetachment spectrum of the nitrate anion (NO 3 -) based on an artificial neural network diabatic potential model. J Chem Phys 2021; 154:084302. [PMID: 33639724 DOI: 10.1063/5.0039503] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The photodetachment spectrum of the nitrate anion (NO3 -) is simulated from first principles using wavepacket quantum dynamics propagation and a newly developed accurate full-dimensional fully coupled five state diabatic potential model. This model utilizes the recently proposed complete nuclear permutation inversion invariant artificial neural network diabatization technique [D. M. G. Williams and W. Eisfeld, J. Phys. Chem. A 124, 7608 (2020)]. The quantum dynamics simulations are designed such that temperature effects and the impact of near threshold detachment are taken into account. Thus, the two available experiments at high temperature and at cryogenic temperature using the slow electron velocity-map imaging technique can be reproduced in very good agreement. These results clearly show the relevance of hot bands and vibronic coupling between the X̃ 2A2 ' ground state and the B̃ 2E' excited state of the neutral radical. This together with the recent experiment at low temperature gives further support for the proper assignment of the ν3 fundamental, which has been debated for many years. An assignment of a not yet discussed hot band line is also proposed.
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Affiliation(s)
- Alexandra Viel
- University Rennes, CNRS, IPR (Institut de Physique de Rennes) - UMR 6251, F-35000 Rennes, FranceTheoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - David M G Williams
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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21
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Abstract
Understanding nonadiabatic dynamics is important for chemical and physical processes involving multiple electronic states. Direct nonadiabatic dynamics simulations are often employed to observe such processes on a femtosecond time scale. One often needs to do the simulation on a longer time scale, but direct simulation based on electronic structure calculations of the surfaces and couplings is expensive due to the large number of electronic structure calculations needed for ensemble averaging or simulation of longer-time processes. An alternative approach is to construct an analytical representation of potential energy surfaces (PESs) and couplings, which allows for faster dynamics calculations. Diabatic representations are preferred for such purposes because of the smoothness of the surfaces and couplings and the scalar nature of the couplings. However, many diabatization procedures are complicated by the need to consider orbitals or vector coupling elements, and these can make the process very labor-intensive. To circumvent these difficulties, we here propose diabatization by a deep neural network (DDNN) based on a new architecture for a deep neural network that requires neither orbital input nor vector input. The DDNN method allows convenient and semiautomatic diabatization, and it is demonstrated here for a model problem and for producing diabatic potential energy matrices for thiophenol.
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Affiliation(s)
- Yinan Shu
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455-0431, United States
| | - Donald G Truhlar
- Department of Chemistry, Chemical Theory Center, and Minnesota Supercomputing Institute, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455-0431, United States
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22
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Westermayr J, Marquetand P. Machine learning and excited-state molecular dynamics. MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2020. [DOI: 10.1088/2632-2153/ab9c3e] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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23
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Hong Y, Yin Z, Guan Y, Zhang Z, Fu B, Zhang DH. Exclusive Neural Network Representation of the Quasi-Diabatic Hamiltonians Including Conical Intersections. J Phys Chem Lett 2020; 11:7552-7558. [PMID: 32835486 DOI: 10.1021/acs.jpclett.0c02173] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
We propose a numerically simple and straightforward, yet accurate and efficient neural networks-based fitting strategy to construct coupled potential energy surfaces (PESs) in a quasi-diabatic representation. The fundamental invariants are incorporated to account for the complete nuclear permutation inversion symmetry. Instead of derivative couplings or interstate couplings, a so-called modified derivative coupling term is fitted by neural networks, resulting in accurate description of near degeneracy points, such as the conical intersections. The adiabatic energies, energy gradients, and derivative couplings are well reproduced, and the vanishing of derivative couplings as well as the isotropic topography of adiabatic and diabatic energies in asymptotic regions are automatically satisfied. All of these features of the coupled global PESs are requisite for accurate dynamics simulations. Our approach is expected to be very useful in developing highly accurate coupled PESs in a quasi-diabatic representation in an efficient machine learning-based way.
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Affiliation(s)
- Yingyue Hong
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Zhengxi Yin
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Yafu Guan
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Zhaojun Zhang
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
| | - Bina Fu
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
| | - Dong H Zhang
- State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, P.R. China 116023
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24
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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]
Affiliation(s)
- David M. G. Williams
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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25
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Neville SP, Seidu I, Schuurman MS. Propagative block diagonalization diabatization of DFT/MRCI electronic states. J Chem Phys 2020; 152:114110. [DOI: 10.1063/1.5143126] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Affiliation(s)
- Simon P. Neville
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie Curie, Ottawa, Ontario K1N 6N5, Canada
| | - Issaka Seidu
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie Curie, Ottawa, Ontario K1N 6N5, Canada
| | - Michael S. Schuurman
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, 10 Marie Curie, Ottawa, Ontario K1N 6N5, Canada
- National Research Council of Canada, 100 Sussex Drive, Ottawa, Ontario K1A 0R6, Canada
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26
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Xie C, Malbon CL, Xie D, Yarkony DR, Guo H. Nonadiabatic Dynamics in Photodissociation of Hydroxymethyl in the 32A(3px) Rydberg State: A Nine-Dimensional Quantum Study. J Phys Chem A 2019; 123:1937-1944. [DOI: 10.1021/acs.jpca.8b12184] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Changjian Xie
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
| | - Christopher L. Malbon
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Daiqian Xie
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China
| | - David R. Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Hua Guo
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, United States
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27
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Bai S, Barbatti M. Mechanism of Spin-Exchange Internal Conversion: Practical Proxies for Diabatic and Nonadiabatic Couplings. J Chem Theory Comput 2019; 15:1503-1513. [PMID: 30735372 DOI: 10.1021/acs.jctc.8b00923] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Spin-exchange internal conversion (SEIC) is a general class of reactions having singlet fission and triplet fusion as particular cases. Based on a charge transfer (CT) mediated mechanism and analytical derivation with a model Hamiltonian, we propose proxies for estimating the coupling strength in both diabatic and adiabatic pictures for general SEIC reactions. In the diabatic picture, we demonstrated the existence of a bilinear relationship between the coupling strength and molecular orbital overlap, which provides a practical way to predict diabatic couplings. In the adiabatic picture, we showed that nonadiabatic couplings can be approximated by simple functions of the wave function CT coefficients. These approaches were verified through the investigation of singlet oxygen photosensitization, where both 1Δg and 1Σg oxygen states can be competitively generated by a triplet fusion reaction. The interplay between the CT-mediated mechanism, the spatial factors of the bimolecular complex, and the electronic structure of the oxygen molecule during the reaction explains the curiously small coupling to the 1Σg state along specific incidence directions. The results from both the diabatic and adiabatic pictures provide a comprehensive understanding of the reaction mechanism, which applies to general SEIC problems.
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Affiliation(s)
- Shuming Bai
- Aix-Marseille Univ., CNRS, ICR , 13397 Marseille , France
| | - Mario Barbatti
- Aix-Marseille Univ., CNRS, ICR , 13397 Marseille , France
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28
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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
Affiliation(s)
- David M. G. Williams
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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29
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Lang RA, Japahuge A, Zeng T. General formalism of vibronic Hamiltonians for tetrahedral and octahedral systems: Problems that involve A-type states and a-type vibrations. Chem Phys 2018. [DOI: 10.1016/j.chemphys.2018.08.028] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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30
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Xie C, Zhu X, Yarkony DR, Guo H. Permutation invariant polynomial neural network approach to fitting potential energy surfaces. IV. Coupled diabatic potential energy matrices. J Chem Phys 2018; 149:144107. [DOI: 10.1063/1.5054310] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Changjian Xie
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA
| | - Xiaolei Zhu
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - David R. Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Hua Guo
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA
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31
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Penfold TJ, Gindensperger E, Daniel C, Marian CM. Spin-Vibronic Mechanism for Intersystem Crossing. Chem Rev 2018; 118:6975-7025. [DOI: 10.1021/acs.chemrev.7b00617] [Citation(s) in RCA: 401] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Thomas J. Penfold
- Chemistry - School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon-Tyne NE1 7RU, United Kingdom
| | - Etienne Gindensperger
- Laboratoire de Chimie Quantique, Institut de Chimie UMR-7177, CNRS - Université de Strasbourg, 1 Rue Blaise Pascal 67008 Strasbourg, France
| | - Chantal Daniel
- Laboratoire de Chimie Quantique, Institut de Chimie UMR-7177, CNRS - Université de Strasbourg, 1 Rue Blaise Pascal 67008 Strasbourg, France
| | - Christel M. Marian
- Institut für Theoretische Chemie, Heinrich-Heine-Universität Düsseldorf, Universitätsstrasse 1, 40225 Düsseldorf, Germany
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32
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Wittenbrink N, Eisfeld W. Extension of the effective relativistic coupling by asymptotic representation (ERCAR) approach to multi-dimensional potential energy surfaces: 3D model for CH3I. J Chem Phys 2018. [DOI: 10.1063/1.5011757] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Nils Wittenbrink
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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33
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Hu X, Zhou L, Xie D. State-to-state photodissociation dynamics of the water molecule. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1350] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Xixi Hu
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering; Nanjing University; Nanjing China
| | - Linsen Zhou
- Department of Chemistry and Chemical Biology; University of New Mexico; Albuquerque NM USA
| | - Daiqian Xie
- Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry, School of Chemistry and Chemical Engineering; Nanjing University; Nanjing China
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34
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Zeng T, Hickman RJ, Kadri A, Seidu I. General Formalism of Vibronic Hamiltonians for Tetrahedral and Octahedral Systems: Problems That Involve T, E States and t, e Vibrations. J Chem Theory Comput 2017; 13:5004-5018. [DOI: 10.1021/acs.jctc.7b00787] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Tao Zeng
- Department of Chemistry, Carleton University, Ottawa, Ontario K1S5B6, Canada
| | - Riley J. Hickman
- Department of Chemistry, Carleton University, Ottawa, Ontario K1S5B6, Canada
| | - Aya Kadri
- Department of Chemistry, Carleton University, Ottawa, Ontario K1S5B6, Canada
| | - Issaka Seidu
- Department of Chemistry, Carleton University, Ottawa, Ontario K1S5B6, Canada
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35
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Xie C, Malbon C, Yarkony DR, Guo H. Nonadiabatic photodissociation dynamics of the hydroxymethyl radical via the 22A(3s) Rydberg state: A four-dimensional quantum study. J Chem Phys 2017; 146:224306. [DOI: 10.1063/1.4985147] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Changjian Xie
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA
| | - Christopher Malbon
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - David R. Yarkony
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Hua Guo
- Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA
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36
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Wittenbrink N, Eisfeld W. An improved spin-orbit coupling model for use within the effective relativistic coupling by asymptotic representation (ERCAR) method. J Chem Phys 2017; 146:144110. [PMID: 28411618 DOI: 10.1063/1.4979949] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
An improved atomic spin-orbit model is presented, which is designed to be used within the framework of the effective relativistic coupling by asymptotic representation method. This method is used for the generation of highly accurate coupled potential energy surfaces (PESs) to represent the fine structure energies of appropriate systems. The approach is demonstrated using CH3I and its photodissociation as a typical example. The method is based on a specific diabatization of electronic spin-space ("spin-free") states with respect to the asymptote at which a single relativistic atom is separated from a molecular non-relativistic fragment. Thus, the relativistic coupling effects can be treated entirely within the atomic framework. So far, an effective spin-orbit coupling operator which only accounts for intra-state coupling within each atomic spin-space state was used. In the present work, this approach is extended to account for inter-state couplings among different atomic spin-space states as well. It is shown that this extended approach improves the accuracy of the PESs significantly for higher excited states and also enhances the accuracy of low energy states. In particular, it improves the representation of the spin-orbit induced conical intersection among the 3Q0 and 1Q1 states of CH3I, which is of high relevance for the nonadiabatic quantum dynamics of the photodissociation.
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Affiliation(s)
- Nils Wittenbrink
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
| | - Wolfgang Eisfeld
- Theoretische Chemie, Universität Bielefeld, Postfach 100131, D-33501 Bielefeld, Germany
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37
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Affiliation(s)
- Tao Zeng
- Department of Chemistry, Carleton University, Ottawa, Ontario K1S5B6, Canada
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38
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Grofe A, Qu Z, Truhlar DG, Li H, Gao J. Diabatic-At-Construction Method for Diabatic and Adiabatic Ground and Excited States Based on Multistate Density Functional Theory. J Chem Theory Comput 2017; 13:1176-1187. [PMID: 28135420 PMCID: PMC5793876 DOI: 10.1021/acs.jctc.6b01176] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
We describe a diabatic-at-construction (DAC) strategy for defining diabatic states to determine the adiabatic ground and excited electronic states and their potential energy surfaces using the multistate density functional theory (MSDFT). The DAC approach differs in two fundamental ways from the adiabatic-to-diabatic (ATD) procedures that transform a set of preselected adiabatic electronic states to a new representation. (1) The DAC states are defined in the first computation step to form an active space, whose configuration interaction produces the adiabatic ground and excited states in the second step of MSDFT. Thus, they do not result from a similarity transformation of the adiabatic states as in the ATD procedure; they are the basis for producing the adiabatic states. The appropriateness and completeness of the DAC active space can be validated by comparison with experimental observables of the ground and excited states. (2) The DAC diabatic states are defined using the valence bond characters of the asymptotic dissociation limits of the adiabatic states of interest, and they are strictly maintained at all molecular geometries. Consequently, DAC diabatic states have specific and well-defined physical and chemical meanings that can be used for understanding the nature of the adiabatic states and their energetic components. Here we present results for the four lowest singlet states of LiH and compare them to a well-tested ATD diabatization method, namely the 3-fold way; the comparison reveals both similarities and differences between the ATD diabatic states and the orthogonalized DAC diabatic states. Furthermore, MSDFT can provide a quantitative description of the ground and excited states for LiH with multiple strongly and weakly avoided curve crossings spanning over 10 Å of interatomic separation.
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Affiliation(s)
- Adam Grofe
- Institute of Theoretical Chemistry, Jilin University, Changchun, Jilin Province 130023, China
- Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Zexing Qu
- Institute of Theoretical Chemistry, Jilin University, Changchun, Jilin Province 130023, China
| | - Donald G. Truhlar
- Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Hui Li
- Institute of Theoretical Chemistry, Jilin University, Changchun, Jilin Province 130023, China
| | - Jiali Gao
- Institute of Theoretical Chemistry, Jilin University, Changchun, Jilin Province 130023, China
- Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, United States
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Eisfeld W, Viel A. Vibronic eigenstates and the geometric phase effect in the2E″ state of NO3. J Chem Phys 2017; 146:034303. [DOI: 10.1063/1.4973983] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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