Potential Energy Matrices Research Articles

Quasi-Diabatization Based on Minimizing Derivative Couplings in a Limited Configuration Space: Elimination of Boundary Condition Dependence.

Due to the cuspidal ridges of adiabatic potential energy surfaces (PESs) and singularities of nonadiabatic couplings (NACs), obtaining an analytical expression for the adiabatic Hamiltonian is difficult. Thereby, nonadiabatic dynamics simulations are often carried out on-the-fly, which is time-consuming. This motivates us to construct quasi-diabatic representations, which have smooth PESs and diabatic couplings. In this study, we propose a new quasi-diabatization method based on minimizing derivative couplings (MDC) in a limited configuration space. The boundary conditions are first considered and finally released to obtain the adiabatic-to-diabatic rotation angles and transformation matrices. As demonstrated in representative one- and two-dimensional models and the widely studied linear H3 molecule, MDC performs significantly better than the direct integration quasi-diabatization approach. In particular, accurate diabatic potential energy matrices have been successfully obtained even when the NACs of all configurations in the considered space are nonnegligible.

Floquet-Engineered Photodissociation Simulated Using Coupled Potential Energy and Dipole Matrices.

We simulate the nonadiabatic molecular dynamics of ammonia photodissociation in the presence of an external laser field by using an approximate Floquet Hamiltonian. The dipole-field interaction gives rise to seams of light-induced conical intersection (LICI), which can significantly change the topography of the coupled potential energy surfaces. We perform quasiclassical trajectories based on recently reported diabatic potential energy matrices (DPEM) and dipole matrices. It is shown that the branching ratio of ground and excited state NH2 is drastically altered by laser-dipole interaction, which is a signature of nonadiabatic effects induced by light.

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+).

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.

Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies and Physical Considerations: Toward Quantum Dynamic Accuracy.

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()/NH3() 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() and NH3() 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.

The impact of non-adiabatic effects on reaction dynamics: a study based on the adiabatic and non-adiabatic potential energy surfaces of CaH2.

The two-state non-adiabatic potential energy matrices of the CaH2+ system are calculated via a diabatization approach by using a neural network model. Subsequently, the adiabatic and non-adiabatic potential energy surfaces (PESs) are constructed based on these non-adiabatic potential energy matrices. Furthermore, based on the adiabatic and non-adiabatic PESs, the Ca+(4s2S) + H2(X1Σ+g) → H(2S) + CaH+(X1Σ+) reaction is studied using the time-dependent wave packet method. Comparative analysis of the experimental and theoretical integral reaction cross-sections (ICSs) indicates that the maximum deviation between the results obtained from the adiabatic PES and the corresponding experimental value is 12.7 bohr2; in contrast, the maximum discrepancy between the theoretical result derived from the non-adiabatic PES and the experimental value is merely 0.42 bohr2. The potential well along the reaction path acts as a 'filter', selectively guiding intermediates with longer lifetimes in the potential well back to the reactant channel. This phenomenon indicates that the non-adiabatic effects significantly influence the reaction dynamics of the CaH2+ system.

Representation of Diabatic Potential Energy Matrices for Multiconfiguration Time-Dependent Hartree Treatments of High-Dimensional Nonadiabatic Photodissociation Dynamics.

Conventional quantum mechanical characterization of photodissociation dynamics is restricted by steep scaling laws with respect to the dimensionality of the system. In this work, we examine the applicability of the multi-configurational time-dependent Hartree (MCTDH) method in treating nonadiabatic photodissociation dynamics in two prototypical systems, taking advantage of its favorable scaling laws. To conform to the sum-of-product form, elements of the ab initio diabatic potential energy matrix (DPEM) are re-expressed using the recently proposed Monte Carlo canonical polyadic decomposition method, with enforcement of proper symmetry. The MCTDH absorption spectra and product branching ratios are shown to compare well with those calculated using conventional grid-based methods, demonstrating its promise for treating high-dimensional nonadiabatic photodissociation problems.

Permutationally Restrained Diabatization by Machine Intelligence.

Simulations of electronically nonadiabatic processes may employ either the adiabatic or diabatic representation. Direct dynamics calculations are usually carried out in the adiabatic basis because the energy, force, and state coupling can be evaluated directly by many electronic structure methods. However, although its straightforwardness is appealing, direct dynamics is expensive when combined with quantitatively accurate electronic structure theories. This generates interest in analytically fitted surfaces to cut the expense, but the cuspidal ridges of the potentials and the singularities and vector nature of the couplings at high-dimensional, nonsymmetry-determined intersections in the adiabatic representation make accurate fitting almost impossible. This motivates using diabatic representations, where the surfaces are smooth and the couplings are also smooth and-importantly-scalar. In a recent previous work, we have developed a method called diabatization by deep neural network (DDNN) that takes advantage of the smoothness and nonuniqueness of diabatic bases to obtain them by machine learning. The diabatic potential energy matrices (DPEMs) learned by the DDNN method yield not only diabatic potential energy surfaces (PESs) and couplings in an analytic form useful for dynamics calculations, but also adiabatic surfaces and couplings in the adiabatic representation can be calculated inexpensively from the transformation. In the present work, we show how to extend the DDNN method to produce good approximations to global permutationally invariant adiabatic PESs simultaneously with DPEMs. The extended method is called permutationally restrained DDNN.

High-fidelity first principles nonadiabaticity: diabatization, analytic representation of global diabatic potential energy matrices, and quantum dynamics.

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.

Finite element bending and free vibration analysis of layered plates using new first order shear deformation theory

Displacement based finite element using equivalent-single-layer theory is proposed. Variationally consistent new first-order shear deformation theory (NFSDT) is used to derive total potential energy, mass, stiffness and force matrices. Present NFSDT has only two variables against three variables in Mindlin’s first order theory. Resulting finite element equations are elastically uncoupled with only inertial coupling. Present finite element equations have strong similarity with finite elements based on classical plate theory. Proposed finite element is free from shear locking. Effectiveness of the proposed element is brought out by simulating static bending and free vibration analysis of three layered thin to moderately thick symmetric sandwich plates. Effectiveness of the proposed finite element is demonstrated using test cases from scientific literature.

An efficient way to incorporate the geometric phase in the time-dependent wave packet calculations in a diabatic representation.

We present a new approach to incorporate the geometric phase in the time-dependent wave packet calculations based on the analytic diabatic potential energy matrices for two-state systems connecting via a conical intersection. The approach only requires information on the location of the conical intersection and the adiabatic potential energy surface of the ground electronic state and merely takes the same computational cost as a diabatic calculation. Demonstrations of the benchmark H + H2/HD reactions show that the new approach can accurately include the geometric phase in dynamics calculation and can be easily extended to the cold regime where the GP effects become more pronounced. Due to its simplicity and numerical efficiency, the new approach has the potential to extend the dynamics study of the geometric effects to a wide range of reaction systems.

Diabatization by Machine Intelligence.

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.

Permutation invariant polynomial neural network approach to fitting potential energy surfaces. IV. Coupled diabatic potential energy matrices.

A machine learning method is proposed for representing the elements of diabatic potential energy matrices (PEMs) with high fidelity. This is an extension of the so-called permutation invariant polynomial-neural network (PIP-NN) method for representing adiabatic potential energy surfaces. While for one-dimensional irreducible representations the diagonal elements of a diabatic PEM are invariant under exchange of identical nuclei in a molecular system, the off-diagonal elements require special symmetry consideration, particularly in the presence of a conical intersection. A multiplicative factor is introduced to take into consideration the particular symmetry properties while maintaining the PIP-NN framework. We demonstrate here that the extended PIP-NN approach is accurate in representing diabatic PEMs, as evidenced by small fitting errors and by the reproduction of absorption spectra and product branching ratios in both H2O( ) and NH3( ) non-adiabatic photodissociation.

Improved potential energy surfaces of thioanisole and the effect of upper surface variations on the product distribution upon photodissociation

Electronically nonadiabatic photodissociation can be investigated in detail by experiments. This provides an opportunity to validate the current theory of electronically nonadiabatic processes, but is great challenge because the time scale of photodissociation processes can be long compared to the current capability for accurate direct dynamics simulations. To circumvent this difficulty, we have been using analytic diabatic potential energy matrices, such that the simulation time scale can be extended to the nanosecond region without neglecting the effects of external electron correlation. In previous work, we have developed full-dimensional three-state potential energy matrices for thioanisole photodissociation. In the current work, we extend this work in two main ways: (i) we improve the treatment of the initial torsional potential, and (ii) we shift the potential energy surfaces to investigate the quantitative effect on the dissociation lifetimes and product branching ratios of changing the energy and location of the S1–S2 conical intersection.

In Silico Molecular Modeling and Docking Studies on Novel Mutants (E229V, H225P and D230C) of the Nucleotide-Binding Domain of Homo sapiens Hsp70.

In this study, we explored the possibility of determining the synergistic interactions between nucleotide-binding domain (NBD) of Homo sapiens heat-shock 70kDa protein (Hsp70) and E1A 32kDa of adenovirus serotype 5 motif (PNLVP) in the efficiency of killing of tumor cells in cancer treatment. At present, the protein interaction between NBD and PNLVP motif is still unknown, but believed to enhance the rate of virus replication in tumor cells. Three mutant models (E229V, H225P and D230C) were built and simulated, and their interactions with PNLVP motif were studied. The PNLVP motif showed the binding energy and intermolecular energy values with the novel E229V mutant at -7.32 and -11.2kcal/mol. The E229V mutant had the highest number of hydrogen bonds (7). Based on the root mean square deviation, root mean square fluctuation, hydrogen bonds, salt bridge, secondary structure, surface-accessible solvent area, potential energy and distance matrices analyses, it was proved that the E229V had the strongest and most stable interaction with the PNLVP motif among all the four protein-ligand complex structures. The knowledge of this protein-ligand complex model would help in designing Hsp70 structure-based drug for cancer therapy.

Towards the realization of ab initio dynamics at the speed of molecular mechanics: simulations with interpolated diabatic Hamiltonian.

Understanding photochemical processes often requires accurate descriptions of the nonadiabatic events involved. The cost of accurate quantum chemical simulations of the nonadiabatic dynamics of complex systems is typically high. Here, we discuss the use of interpolated quasi-diabatic potential-energy matrices, which aims to reduce the computational cost with minimal sacrifices in accuracy. It is shown that interpolation reproduces the reference ab initio information satisfactorily for a sizeable chromophore in terms of its adiabatic energies and derivative coupling vectors. Actual nonadiabatic simulation results of the chromophore in the gas phase and in aqueous solution are presented, and it is demonstrated that the interpolated quasi-diabatic Hamiltonian can be applied to studying nonadiabatic events of a complex system in an ensemble manner at a much-reduced cost. Limitations, and how they can be overcome in future studies, are also discussed.

Quantum grow—A quantum dynamics sampling approach for growing potential energy surfaces and nonadiabatic couplings

A quantum sampling algorithm for the interpolation of diabatic potential energy matrices by the Grow method is introduced. The new procedure benefits from penetration of the wave packet into classically forbidden regions, and the accurate quantum mechanical description of nonadiabatic transitions. The increased complexity associated with running quantum dynamics is reduced by using approximate low order expansions of the nuclear wave function within a Multi-configuration time-dependent Hartree scheme during the Grow process. The sampling algorithm is formulated and applied for three representative test cases, demonstrating the recovery of analytic potentials by the interpolated ones, and the convergence of a dynamic observable.

Spectral properties of linear gyroscopic systems

We study how the natural frequencies of a linear gyroscopic system behave under variations in the kinetic and potential energy matrices as well as in the gyroscopic force matrix.

A Diabatic Representation Including Both Valence Nonadiabatic Interactions and Spin−Orbit Effects for Reaction Dynamics

A diabatic representation is convenient in the study of electronically nonadiabatic chemical reactions because the diabatic energies and couplings are smooth functions of the nuclear coordinates and the couplings are scalar quantities. A method called the fourfold way was devised in our group to generate diabatic representations for spin-free electronic states. One drawback of diabatic states computed from the spin-free Hamiltonian, called a valence diabatic representation, for systems in which spin-orbit coupling cannot be ignored is that the couplings between the states are not zero in asymptotic regions, leading to difficulties in the calculation of reaction probabilities and other properties by semiclassical dynamics methods. Here we report an extension of the fourfold way to construct diabatic representations suitable for spin-coupled systems. In this article we formulate the method for the case of even-electron systems that yield pairs of fragments with doublet spin multiplicity. For this type of system, we introduce the further simplification of calculating the triplet diabatic energies in terms of the singlet diabatic energies via Slater's rules and assuming constant ratios of Coulomb to exchange integrals. Furthermore, the valence diabatic couplings in the triplet manifold are taken equal to the singlet ones. An important feature of the method is the introduction of scaling functions, as they allow one to deal with multibond reactions without having to include high-energy diabatic states. The global transformation matrix to the new diabatic representation, called the spin-valence diabatic representation, is constructed as the product of channel-specific transformation matrices, each one taken as the product of an asymptotic transformation matrix and a scaling function that depends on ratios of the spin-orbit splitting and the valence splittings. Thus the underlying basis functions are recoupled into suitable diabatic basis functions in a manner that provides a multibond generalization of the switch between Hund's cases in diatomic spectroscopy. The spin-orbit matrix elements in this representation are taken equal to their atomic values times a scaling function that depends on the internuclear distances. The spin-valence diabatic potential energy matrix is suitable for semiclassical dynamics simulations. Diagonalization of this matrix produces the spin-coupled adiabatic energies. For the sake of illustration, diabatic potential energy matrices are constructed along bond-fission coordinates for the HBr and the BrCH(2)Cl molecules. Comparison of the spin-coupled adiabatic energies obtained from the spin-valence diabatics with those obtained by ab initio calculations with geometry-dependent spin-orbit matrix elements shows that the new method is sufficiently accurate for practical purposes. The method formulated here should be most useful for systems with a large number of atoms, especially heavy atoms, and/or a large number of spin-coupled electronic states.

Interpolation of multidimensional diabatic potential energy matrices

A method for constructing diabatic potential energy matrices by interpolation of ab initio quantum chemistry data is described and tested. This approach is applicable to any number of interacting electronic states, and relies on a formalism and a computational procedure that are more general than those presented previously for the case of two electronic states. The method is tested against an analytic model for three interacting electronic states of NH(3) (+).

Interpolation of diabatic potential-energy surfaces: Quantum dynamics on ab initio surfaces

A method for constructing diabatic potential-energy matrices from ab initio quantum chemistry data is described and tested for use in exact quantum reactive scattering. The method is a refinement of that presented in a previous paper, in that it accounts for the presence of the nonremovable derivative coupling. The accuracy of quantum dynamics on this type of diabatic potential is tested by comparison with an analytic model and for an ab initio description of the two lowest-energy states of H3.