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PotLib 2023: New version of a potential energy surface library for chemical systems
POTLIB is a library of global and semiglobal potential energy surface subprograms. The library currently features 410 entries, including both single-state entries and multi-state entries. When one calls the routine of a single-state entry, it returns the ground-electronic-state adiabatic potential energy surface at the input geometry. In addition, some entries also return the gradient of the surface. Further, when one calls a multi-state entry, it returns a diabatic potential energy matrix (DPEM). If the entry also has the gradient of the DPEM, one can compute adiabatic surfaces, their gradients, and the nonadiabatic coupling vectors (NACs) from the DPEM and its gradient by diagonalization. Some but not all the routines conform to one of a set of standard interfaces. The goal is to facilitate chemical dynamics research by collecting and disseminating a comprehensive collection of state-of-the-art potential energy routines (developed by a wide, international group of researchers) with systematic and well-defined interfaces for use with chemical dynamics programs. Systems in the library include CHArO 2 , CHN 2 O + , CH 2 O, CH 2 O 2 , CH 3 N 2 , CH 3 O, CH 4 , CH 4 Br, CH 4 Cl, CH 4 F, CH 4 O, CH 4 OCl, CH 4 OF, CH 4 OH, CH 5 , CH$^{+}_{5}$, CH 5 N, CH 5 O 2 , CH 8 O 2 , C 2 H 2 N 2 O, C 2 H 2 O, C 2 H 4 N, C 2 H 4 O 4 , C 2 H 6 Cl, C 2 H 6 F, C 2 H 6 H, C 2 H 6 O, C 2 H 6 OH, C 2 H 7 , C 2 O 2 , C 3 H 4 O 2 , C 3 H 7 NO, C 6 H 6 O, C 6 H 6 S, C 7 H8S, HBrCl, HCl 2 , HF 2 , HI 2 , HLiF, HNaF, HO 2 , HO 3 , HOBr, HSiO, H 2 Br, H 2 ClO, H 2 F, H 2 F 2 , H 2 FO, H 2 Na, H 2 O, H 2 O 2 , H 2 OBr, H 3 , H 3 Cl, H 3 ClN, H 3 ClO, H 3 N, H 3 O, H 3 O 2 , H$^{+}_{3}$, H 3 S, H 4 ClSi, H 4 N, H 4 NO, H 4 O 2 , H 5 GeO, H 5 Si, H$^{+}_{7}$, Al m H n , Al n , Ar N O, K 2 Rb 2 , NO 2 , N 2 O, N 2 O 2 , N 3 , N 4 , O 3 , and O 4 .
Theoretical study of the CO 2 –O 2 van der Waals complex: potential energy surface and applications
A four-dimensional-potential energy surface (4D-PES) of the atmospherically relevant carbon dioxide–oxygen molecule (CO 2 –O 2 ) van der Waals complex is mapped using the ab initio explicitly correlated coupled cluster method with single, double, and perturbative triple excitations (UCCSD(T)-F12b), and extrapolation to the complete basis set (CBS) limit using the cc-pVTZ-F12/cc-pVQZ-F12 bases and the l –3 formula. An analytic representation of the 4D-PES was fitted using the method of interpolating moving least squares (IMLS). These calculations predict that the most stable configuration of CO 2 –O 2 complex corresponds to a planar slipped-parallel structure with a binding energy of V ~ –243 cm –1 . Another isomer is found on the PES, corresponding to a non-planar cross-shaped structure, with V ~ –218 cm –1 . The transition structure connecting the two minima is found at V ~ –211 cm –1 . We also performed comparisons with some CO 2 –X van der Waals complexes. Moreover, we provide a SAPT analysis of this molecular system. Then, we discuss the complexation induced shifts of CO 2 and O 2 . Afterwards, this new 4D-PES is employed to compute the second virial coefficient including temperature dependence. A comparison between quantities obtained in our calculations and those from experiments found close agreement attesting to the high quality of the PES and to the importance of considering a full description of the anisotropic potential for the derivation of thermophysical properties of CO 2 –O 2 mixtures.
Between Harmonic Crystal and Glass: Solids with Dimpled Potential-Energy Surfaces Having Multiple Local Energy Minima
Solids with dimpled potential-energy surfaces are ubiquitous in nature and, typically, exhibit structural (elastic or phonon) instabilities. Dimpled potentials are not harmonic; thus, the conventional quasiharmonic approximation at finite temperatures fails to describe anharmonic vibrations in such solids. At sufficiently high temperatures, their crystal structure is stabilized by entropy; in this phase, a diffraction pattern of a periodic crystal is combined with vibrational properties of a phonon glass. As temperature is lowered, the solid undergoes a symmetry-breaking transition and transforms into a lower-symmetry phase with lower lattice entropy. Here, we identify specific features in the potential-energy surface that lead to such polymorphic behavior; we establish reliable estimates for the relative energies and temperatures associated with the anharmonic vibrations and the solid–solid symmetry-breaking phase transitions. We show that computational phonon methods can be applied to address anharmonic vibrations in a polymorphic solid at fixed temperature. To illustrate the ubiquity of this class of materials, we present a range of examples (elemental metals, a shape-memory alloy, and a layered charge-density-wave system); we show that our theoretical predictions compare well with known experimental data.
Revealing Excited‐State Trajectories on Potential Energy Surfaces with Atomic Resolution in Real Time
Abstract Photoexcited molecular trajectories on potential energy surfaces (PESs) prior to thermalization are intimately connected to the photochemical reaction outcome. The excited‐state trajectories of a diplatinum complex featuring photo‐activated metal–metal σ ‐bond formation and associated Pt−Pt stretching motions were detected in real time using femtosecond wide‐angle X‐ray solution scattering. The observed motions correspond well with coherent vibrational wavepacket motions detected by femtosecond optical transient absorption. Two key coordinates for intersystem crossing have been identified, the Pt−Pt bond length and the orientation of the ligands coordinated with the platinum centers, along which the excited‐state trajectories can be projected onto the calculated PESs of the excited states. This investigation has gleaned novel insight into electronic transitions occurring on the time scales of vibrational motions measured in real time, revealing ultrafast nonadiabatic or non‐equilibrium processes along excited‐state trajectories involving multiple excited‐state PESs.
Revealing Excited‐State Trajectories on Potential Energy Surfaces with Atomic Resolution in Real Time
Abstract Photoexcited molecular trajectories on potential energy surfaces (PESs) prior to thermalization are intimately connected to the photochemical reaction outcome. The excited‐state trajectories of a diplatinum complex featuring photo‐activated metal–metal σ ‐bond formation and associated Pt−Pt stretching motions were detected in real time using femtosecond wide‐angle X‐ray solution scattering. The observed motions correspond well with coherent vibrational wavepacket motions detected by femtosecond optical transient absorption. Two key coordinates for intersystem crossing have been identified, the Pt−Pt bond length and the orientation of the ligands coordinated with the platinum centers, along which the excited‐state trajectories can be projected onto the calculated PESs of the excited states. This investigation has gleaned novel insight into electronic transitions occurring on the time scales of vibrational motions measured in real time, revealing ultrafast nonadiabatic or non‐equilibrium processes along excited‐state trajectories involving multiple excited‐state PESs.
Feasibility of a Novel Density Functional Method Outside the Kohn-Sham Framework for Modeling Global Potential Energy Surfaces of Molecular Chemical Reactions (Final Technical Report)
The project aimed towards the construction of computational methods capable of modeling the global potential energy surface (PES) of small molecules, molecular ions, and radicals — including the parts of the PES which correspond to chemical reactions, and the reaction paths connecting reactants, intermediates, and reaction products. This goal may seem humble at first glance, but for chemical systems with more than about six atoms in total, at the time the project was proposed, there were no established theoretical methods capable of simulating such systems reliably, not even for small molecules in the gas phase which are electronically benign. This restriction severely hampers our ability to model and control chemical processes under harsh conditions. With the goal of constructing a method capable of modeling such chemical systems, we proposed to pursue a novel approach towards a Multi-Configuration (MC) DFT outside the traditional frameworks of Kohn-Sham theory and other methods of coupling wave function theory with DFT. Rather than being a complete active space (CAS) method, the proposed DOCI-DFT would employ a special restricted form of the active space wave function, called Doubly-Occupied CI (DOCI)—this wave function form is sufficient to describe not only heterolytic, but also homolytic bond dissociation processes at the zeroth order (i.e., as active space wave function). There are no other standard mean field methods which can do so. In the original proposal, we also outlined strong formal and practical arguments speaking for this method. The project proposal was accepted by the Department of Energy and provided two years of seed funding for one graduate student, as well as two years of two weeks PI summer-salary for the PI. However, ultimately the project could not be effectively pursued due to severe interferences outside the context scientific problems and was cancelled. Apart from two weeks of PI salary (and associated fringe & overhead costs issues by the performing institution), no costs were charged against the award, with the entire rest of funding returned to the Department of Energy. This report reiterates the primary background information regarding the project, its original goals, and outlines the preliminary work performed during the two weeks of DOE funding charged.
Theoretical Kinetics Predictions for Reactions on the NH 2 O Potential Energy Surface
Recent modeling studies of ammonia oxidation, which are motivated by the prospective role of ammonia as a zero-carbon fuel, have indicated significant discrepancies among the existing literature mechanisms. In this study, high-level theoretical kinetics predictions have been obtained for reactions on the NH 2 O potential energy surface, including the NH 2 + O, HNO + H, and NH + OH reactions. These reactions have previously been highlighted as important reactions in NH 3 oxidation with high sensitivity and high uncertainty. The potential energy surface is explored with coupled cluster calculations, including large basis sets and high-level corrections to yield high-accuracy (~0.2 kcal/mol 2σ uncertainty) estimates of the stationary point energies. Variational transition state theory is used to predict the microcanonical rate constants, which are then incorporated in master equation treatments of the temperature- and pressure-dependent kinetics. For radical–radical channels, the microcanonical rates are obtained from variable reaction coordinate transition state theory implementing directly evaluated multireference electronic energies. The analysis yields predictions for the total rate constants as well as the branching ratios. We find that the NO + H 2 channel contributes 10% of the total NH 2 + O flux at combustion temperatures, although this channel is not included in modern NH 3 oxidation mechanisms. Modeling is used to illustrate the ramifications of these rate predictions on the kinetics of NH 3 oxidation and NO x formation. Finally, the present results for NH 2 + O are important for predicting the chain branching and formation of NO in the oxidation of NH 3 and thermal DeNO x .
RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces
With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.
Comparative analysis of internal energy excitation and dissociation of nitrogen predicted by independently developed ab initio potential energy surfaces
In this article we present a comparative atomic level study analyzing the vibrational excitation and dissociation of molecular nitrogen due to N 2 ( 1 Σ g + )+N( 4 S u ) and N 2 ( 1 Σ g + )+N 2 ( 1 Σ g + ) interactions governed by independently developed potential energy surfaces at the University of Minnesota and NASA Ames Research Center. Further, vibrational excitation was studied for N 2 +N 2 interactions from T=10000 to 25000 K and for N 2 +N from T=5000 to 30000 K. Nonequilibrium dissociation is studied from T=10000 to 30000 K under the quasi-steady-state condition for N 2 +N 2 and N 2 +N interactions. Finally, an inviscid Mach 20 dissociating nitrogen flow over a cylinder with a Knudsen number of 0.015 is carried out to study the impact of molecular interactions predicted by independently developed potential energy surfaces on a canonical hypersonic flow.
Methods in PES-Learn: Direct-Fit Machine Learning of Born–Oppenheimer Potential Energy Surfaces
The release of PES-L EARN version 1.0 as an open-source software package for the automatic construction of machine learning models of semi-global molecular potential energy surfaces (PESs) is presented. Improvements to PES-L EARN ’s interoperability are stressed with new Python API that simplifies workflows for PES construction via interaction with QCSchema input and output infrastructure. In addition, a new machine learning method is introduced to PES-L EARN : kernel ridge regression (KRR). The capabilities of KRR are emphasized with examination of select semi-global PESs. All machine learning methods available in PES-L EARN are benchmarked with benzene and ethanol datasets from the rMD17 database to illustrate PES-L EARN ’s performance ability. Fitting performance and timings are assessed for both systems. Finally, the ability to predict gradients with neural network models is presented and benchmarked with ethanol and benzene. PES-L EARN is an active project and welcomes community suggestions and contributions.
Comprehensive Kinetics on the C 7 H 7 Potential Energy Surface under Combustion Conditions
The automated kinetics workflow code, KinBot, was used to explore and characterize the regions of the C 7 H 7 potential energy surface that are relevant to combustion environments and especially soot inception. We first explored the lowest-energy region, which includes the benzyl, fulvenallene + H, and cyclopentadienyl + acetylene entry points. We then expanded the model to include two higher-energy entry points, vinylpropargyl + acetylene and vinylacetylene + propargyl. The automated search was able to uncover the pathways from the literature. In addition, three important new routes were discovered: a lower-energy pathway connecting benzyl with vinylcyclopentadienyl, a decomposition mechanism from benzyl that results in side-chain hydrogen atom loss to produce fulvenallene + H, and shorter and lower energy routes to the dimethylene-cyclopentenyl intermediates. We systematically reduced the extended model to a chemically relevant domain composed of 63 wells, 10 bimolecular products, 87 barriers, and 1 barrierless channel and constructed a master equation using the CCSD(T)-F12a/cc-pVTZ//ωB97X-D/6-311++G(d,p) level of theory to provide rate coefficients for chemical modeling. Our calculated rate coefficients show excellent agreement with measured ones. We also simulated concentration profiles and calculated branching fractions from the important entry points to provide an interpretation of this important chemical landscape.
Exploring the Tl 2H 2 potential energy surface: A comparative analysis with group 13 systems and experiment
Abstract Thallium chemistry is experiencing unprecedented importance. Therefore, it is valuable to characterize some of the simplest thallium compounds. Stationary points along the singlet and triplet TlH potential energy surface have been characterized. Stationary point geometries were optimized with the CCSD(T)/aug‐cc‐pwCVQZ‐PP method. Harmonic vibrational frequencies were computed at the same level of theory while anharmonic vibrational frequencies were computed at the CCSD(T)/aug‐cc‐pwCVTZ‐PP level of theory. Final energetics were obtained with the CCSDT(Q) method. Basis sets up to augmented quintuple‐zeta cardinality (aug‐cc‐pwCV5Z‐PP) were employed to obtain energetics in order to extrapolate to the complete basis set limits using the focal point approach. Zero‐point vibrational energy corrections were appended to the extrapolated energies in order to determine relative energies at 0 K. It was found that the planar dibridged isomer lies lowest in energy while the linear structure lies highest in energy. The results were compared to other group 13 MH (M = B, Al, Ga, In, and Tl) theoretical studies and some interesting variations are found. With respect to experiment, incompatibilities exist.
Mapping spin contamination-free potential energy surfaces using restricted open-shell methods with Grassmannians
The Lagrange-based Grassmann interpolation (G-Int) method has been extended for open-shell systems using restricted open-shell methods in building spin contamination-free potential energy surfaces.
Two-dimensional ring polymer molecular dynamics determination of the MnO + + H 2 /D 2 reaction rates on a Δ-machine learned potential energy surface
In this work, we investigate the impact of nuclear quantum effects in the kinetics of the MnO + + H 2 reaction, a prototypical system for gas-phase H 2 activation by transition metal oxide ions. The DFT based potential energy surfaces (PESs) for the lowest-lying quintet and septet spin states reported in our previous work are improved by 2953 newly calculated CCSD(T)/AVDZ points using a delta-machine learning (Δ-ML) method. To examine nuclear quantum effects, the rate coefficients are computed using ring-polymer molecular dynamics (RPMD). Due to the mechanistic complexity of the reaction, two reaction coordinates are necessary to map out the free-energy surface and an extended RPMD rate theory is developed. The calculated RPMD rate coefficients on the new PES are in better agreement with experimental data. The calculated kinetic isotope effects (KIEs) range from 1.6 to 1.8, also in good agreement with the experimental values. Additionally, the converged RPMD rate coefficients are 2.3 to 3.1 times higher than their classical counterparts across the studied temperature range, suggesting the presence of moderate nuclear quantum effects in this reaction.
Comparison of multifidelity machine learning models for potential energy surfaces
Multifidelity modeling is a technique for fusing the information from two or more datasets into one model. It is particularly advantageous when one dataset contains few accurate results and the other contains many less accurate results. Within the context of modeling potential energy surfaces, the low-fidelity dataset can be made up of a large number of inexpensive energy computations that provide adequate coverage of the N-dimensional space spanned by the molecular internal coordinates. The high-fidelity dataset can provide fewer but more accurate electronic energies for the molecule in question. Here, we compare the performance of several neural network-based approaches to multifidelity modeling. We show that the four methods (dual, Δ-learning, weight transfer, and Meng–Karniadakis neural networks) outperform a traditional implementation of a neural network, given the same amount of training data. We also show that the Δ-learning approach is the most practical and tends to provide the most accurate model.
Dissociative electron attachment to 5-bromo-uracil: non-adiabatic dynamics on complex-valued potential energy surfaces
Electron induced dissociation reactions are relevant to many fields, ranging from prebiotic chemistry to cancer treatments. However, the simulation of dissociation electron attachment (DEA) dynamics is very challenging because the auto-ionization widths of the transient negative ions must be accounted for. We propose an adaptation of the ab initio multiple spawning (AIMS) method for complex-valued potential energy surfaces, along the lines of recent developments based on surface hopping dynamics. Our approach combines models for the energy dependence of the auto-ionization widths, obtained from scattering calculations, with survival probabilities computed for the trajectory basis functions employed in the AIMS dynamics. The method is applied to simulate the DEA dynamics of 5-bromouracil in full dimensionality, i.e., taking all the vibrational modes into consideration. The propagation starts on the $π_{2}^{*}$ resonance state and describes the formation of Br - anions mediated by non-adiabatic couplings. The potential energies, gradients and non-adiabatic couplings were computed with the fractional-occupancy molecular orbital complete-active-space configuration-interaction method, and the calculated DEA cross section are consistent with the observed DEA intensities.
Trapping Ca + inside a molecular cavity: computational study of the potential energy surfaces for Ca + -[ n ]cycloparaphenylene, n = 5–12
Ion trap quantum computing utilizes electronic states of atomic ions such as Ca + to encode information on to a qubit. To explore the fundamental properties of Ca + inside molecular cavities, we describe here a computational study of Ca + bound inside neutral [n]-cycloparaphenylenes (n = 5–12), often referred to as “nanohoops”. This ab initio study characterizes optimized structures, harmonic vibrational frequencies, potential energy surfaces, and ion molecular orbital distortion as functions of increasing nanohoop size. Here the results of this work provide a first step in guiding experimental studies of the spectroscopy of these ion-molecular cavity complexes.