Intramolecular vibrational energy redistribution and the quantum ergodicity transition: a phase space perspective

The onset of facile intramolecular vibrational energy flow can be related to features in the connected network of anharmonic resonances in the classical phase space.

A facile strategy to realize a single/double photon excitation-dependent photosensitizer for imaging-guided phototherapy against HeLa cancer cells at separate irradiation channels

A facile strategy has been proposed to realize two-photon phototherapy against HeLa cancer cells with simultaneous one-photon fluorescence imaging modality at separate irradiation channels.

An accurate potential energy surface and ring polymer molecular dynamics study of the Cl + CH4→ HCl + CH3reaction

Thermal rate coefficients for the Cl + CH₄/CD₄reactions were studied on a new full-dimensional accurate potential energy surface with the spin–orbit corrections considered in the entrance channel.

A global ab initio potential energy surface and dynamics of the proton-transfer reaction: OH− + D2 → HOD + D−

The reaction mechanisms of OH⁻ + D₂ → HOD + D⁻ were first revealed by theory, based on an accurate full-dimensional PES.

From ab initio data to high-dimensional potential energy surfaces: A critical overview and assessment of the development of permutationally invariant polynomial potential energy surfaces for single molecules

The representation of high-dimensional potential energy surfaces by way of the many-body expansion and permutationally invariant polynomials has become a well-established tool for improving the resolution and extending the scope of molecular simulations. The high level of accuracy that can be attained by these potential energy functions (PEFs) is due in large part to their specificity: for each term in the many-body expansion, a species-specific training set must be generated at the desired level of theory and a number of fits attempted in order to obtain a robust and reliable PEF. In this work, we attempt to characterize the numerical aspects of the fitting problem, addressing questions which are of simultaneous practical and fundamental importance. These include concrete illustrations of the nonconvexity of the problem, the ill-conditionedness of the linear system to be solved and possible need for regularization, the sensitivity of the solutions to the characteristics of the training set, and limitations of the approach with respect to accuracy and the types of molecules that can be treated. In addition, we introduce a general approach to the generation of training set configurations based on the familiar harmonic approximation and evaluate the possible benefits to the use of quasirandom sequences for sampling configuration space in this context. Using sulfate as a case study, the findings are largely generalizable and expected to ultimately facilitate the efficient development of PIP-based many-body PEFs for general systems via automation.

Approximating Periodic Potential Energy Surfaces with Sparse Trigonometric Interpolation

The potential energy surface (PES) describes the energy of a chemical system as a function of its geometry and is a fundamental concept in computational chemistry. A PES provides much useful information about the system, including the structures and energies of various stationary points, such as local minima, maxima, and transition states. Construction of full-dimensional PESs for molecules with more than 10 atoms is computationally expensive and often not feasible. Previous work in our group used sparse interpolation with polynomial basis functions to construct a surrogate reduced-dimensional PESs along chemically significant reaction coordinates, such as bond lengths, bond angles, and torsion angles. However, polynomial interpolation does not preserve the periodicity of the PES gradient with respect to angular components of geometry, such as torsion angles, which can lead to nonphysical phenomena. In this work, we construct a surrogate PES using trigonometric basis functions, for a system where the selected reaction coordinates all correspond to the torsion angles, resulting in a periodically repeating PES. We find that a trigonometric interpolation basis not only guarantees periodicity of the gradient but also results in slightly lower approximation error than polynomial interpolation.

Embedded Atom Neural Network Potentials: Efficient and Accurate Machine Learning with a Physically Inspired Representation

We propose a simple, but efficient and accurate, machine learning (ML) model for developing a high-dimensional potential energy surface. This so-called embedded atom neural network (EANN) approach is inspired by the well-known empirical embedded atom method (EAM) model used in the condensed phase. It simply replaces the scalar embedded atom density in EAM with a Gaussian-type orbital based density vector and represents the complex relationship between the embedded density vector and atomic energy by neural networks. We demonstrate that the EANN approach is equally accurate as several established ML models in representing both big molecular and extended periodic systems, yet with much fewer parameters and configurations. It is highly efficient as it implicitly contains the three-body information without an explicit sum of the conventional costly angular descriptors. With high accuracy and efficiency, EANN potentials can vastly accelerate molecular dynamics and spectroscopic simulations in complex systems at ab initio level.

High-Level VSCF/VCI Calculations Decode the Vibrational Spectrum of the Aqueous Proton

The hydrated excess proton is a common species in aqueous chemistry, which complexes with water in a variety of structures. The infrared spectrum of the aqueous proton is particularly sensitive to this array of structures, which manifests as continuous IR absorption from 1000 to 3000 cm^-1 known as the "proton continuum". Because of the extreme breadth of the continuum and strong anharmonicity of the involved vibrational modes, this spectrum has eluded straightforward interpretation and simulation. Using protonated water hexamer clusters from reactive molecular dynamics trajectories, and focusing on their central H⁺(H₂O)₂ structures' spectral contribution, we reproduce the linear IR spectrum of the aqueous proton with a high-level local monomer quantum method and highly accurate many-body potential energy surface. The accuracy of this approach is first verified in the vibrational spectra of the two isomers of the protonated water hexamer in the gas phase. We then apply this approach to 800 H⁺(H₂O)₆ clusters, also written as [H⁺(H₂O)₂](H₂O)₄, drawn from multistate empirical valence bond simulations of the bulk liquid to calculate the infrared spectrum of the aqueous proton complex. Incorporation of anharmonic effects to the vibrational potential and quantum mechanical treatment of the proton produces a better agreement to the infrared spectrum compared to that of the double-harmonic approximation. We assess the correlation of the proton stretching mode with different atomistic coordinates, finding the best correlation with ⟨R_OH⟩, the expectation value of the proton-oxygen distance R_OH. We also decompose the IR spectrum based on normal mode vibrations and ⟨R_OH⟩ to provide insight on how different frequency regions in the continuum report on different configurations, vibrational modes, and mode couplings.

Ab Initio and Quasiclassical Trajectory Study of the O(3P) + 2-Propanol Hydrogen Abstraction Reaction

We present a theoretical study of the hydrogen abstraction reaction from 2-propanol by ground-state oxygen atoms. First, ab initio calculations are used to characterize the stationary points of the potential energy surface. Rotation around the C-C-O-H dihedral affords two conformers in 2-propanol, which gives rise to 13 hydrogen abstraction reaction pathways grouped into three channels, Cα, Cβ, and O, depending on the abstraction site. Reaction at Cα exhibits the lowest barrier and largest exothermicity, followed by reaction at Cβ, and at 2-propanol's oxygen atom. Additional ab initio calculations beyond the stationary points are employed to obtain a grid of energies with which a specific-reaction-parameters (SRP) PM6 semiemipirical Hamiltonian is derived for the title reaction. The SRP-PM6 model captures the energetics of the reaction with higher accuracy than some conventional first-principles methods but is efficient enough to allow for extensive reaction dynamics calculations. Quasiclassical trajectories are subsequently propagated with the SRP-PM6 Hamiltonian to obtain reaction dynamics properties that are compared to experiments. Product translational energy and angular distributions for reaction at Cα with the two conformers of 2-propanol are in good agreement with recent molecular-beam measurements, and they exhibit largely backward scattering with modest energy release to relative translation. Most of the energy is deposited into the organic product, substantiating a reaction mechanism dominated by rebound dynamics.

Molecular Dynamics Simulations on Relaxed Reduced-Dimensional Potential Energy Surfaces

Molecular dynamics (MD) simulations with full-dimensional potential energy surfaces (PESs) obtained from high-level ab initio calculations are frequently used to model reaction dynamics of small molecules (i.e., molecules with up to 10 atoms). Construction of full-dimensional PESs for larger molecules is, however, not feasible since the number of ab initio calculations required grows rapidly with the increase of dimension. Only a small number of coordinates are often essential for describing the reactivity of even very large systems, and reduced-dimensional PESs with these coordinates can be built for reaction dynamics studies. While analytical methods based on transition-state theory framework are well established for analyzing the reduced-dimensional PESs, MD simulation algorithms capable of generating trajectories on such surfaces are more rare. In this work, we present a new MD implementation that utilizes the relaxed reduced-dimensional PES for standard microcanonical (NVE) and canonical (NVT) MD simulations. The method is applied to the pyramidal inversion of a NH₃ molecule. The results from the MD simulations on a reduced, three-dimensional PES are validated against the ab initio MD simulations, as well as MD simulations on full-dimensional PES and experimental data.

A fragmented, permutationally invariant polynomial approach for potential energy surfaces of large molecules: Application to N-methyl acetamide

We describe and apply a method to extend permutationally invariant polynomial (PIP) potential energy surface (PES) fitting to molecules with more than 10 atoms. The method creates a compact basis of PIPs as the union of PIPs obtained from fragments of the molecule. An application is reported for trans-N-methyl acetamide, where B3LYP/cc-pVDZ electronic energies and gradients are used to develop a full-dimensional potential for this prototype peptide molecule. The performance of several fragmented bases is verified against a benchmark PES using all (66) Morse variables. The method appears feasible for much larger molecules.

Bridging the Gap between Direct Dynamics and Globally Accurate Reactive Potential Energy Surfaces Using Neural Networks

Direct dynamics simulations become increasingly popular in studying reaction dynamics for complex systems where analytical potential energy surfaces (PESs) are unavailable. Yet, the number and/or the propagation time of trajectories are often limited by high computational costs, and numerous energies and forces generated on-the-fly become wasted after simulations. We demonstrate here an example of reusing only a very small portion of existing direct dynamics data to reconstruct a 90-dimensional globally accurate reactive PES describing the interaction of CO₂ with a movable Ni(100) surface based on a machine learning approach. In addition to reproducing previous results with much better statistics, we predict scattering probabilities of CO₂ at the state-to-state level, which is extremely demanding for direct dynamics. We propose this unified way to investigate gaseous and gas-surface reactions of medium size, initiating with hundreds of preliminary direct dynamics trajectories, followed by low-cost and high-quality simulations on full-dimensional analytical PESs.

A critical comparison of neural network potentials for molecular reaction dynamics with exact permutation symmetry

Several symmetry strategies have been compared in fitting full dimensional accurate potentials for reactive systems based on a neural network approach.

An accurate full-dimensional permutationally invariant potential energy surface for the interaction between H2O and CO

The first full-dimensional accurate potential energy surface was developed for the CO + H₂O system based onca.102 000 points calculated at the CCSD(T)-F12a/AVTZ level using a permutation invariant polynomial-neural network (PIP-NN) method.

Anomalous kinetics of the reaction between OH and HO2on an accurate triplet state potential energy surface

The quasi-classical trajectory predicts the rate coefficient of the OH + HO₂→ H₂O + O₂reaction based on a full dimensional accurate PIP-NN PES, which is fit to 108 000 points calculated at the CCSD(T)-F12a/AVTZ level.

Quantum and classical IR spectra of (HCOOH)2, (DCOOH)2 and (DCOOD)2 using ab initio potential energy and dipole moment surfaces

Full-dimensional (24 modes) quantum calculation of the IR spectrum of (DCOOD)₂, and comparison with classical MD one.

Spiers Memorial Lecture : Introductory lecture: quantum dynamics of chemical reactions

This Spiers Memorial Lecture discusses quantum effects that can be calculated and observed in the chemical reactions of small molecules.

An accurate full-dimensional potential energy surface and quasiclassical trajectory dynamics of the H + H2O2 two-channel reaction

Quasiclassical trajectory calculations reveal interesting dynamics features based on an accurate FI-NN PES for the H + H₂O₂ two-channel reaction.