Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “potential energy surface”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Aldehyde cool-flame chemistry explains a missing source of organic acids

Combustion emission is a significant source of organic acids, impacting atmospheric chemistry and climate. Their formation mechanisms, however, remain poorly understood, leading to underestimation in kinetic models. We investigate the cool-flame oxidation of key combustion intermediates—C 1 –C 4 aldehydes and benzaldehyde. Using in-situ synchrotron vacuum ultraviolet photoionization mass spectrometry, we observe the direct conversion of aldehydes to organic acids, a process enhanced by HO 2 radicals. Quantum chemistry calculations reveal that the reaction of RC(O)O 2 with HO 2 on the singlet potential energy surface contributes to organic acids. Incorporating this pathway into a kinetic model significantly improves organic acid prediction. Despite the high-temperature nature of engine combustion, significant spatial and temporal inhomogeneities (e.g., near-wall regions and crevice volumes) lead to localized cool-flame conditions, facilitating organic acid formation and emission. Elucidating the acid formation under cool-flame conditions provides a critical mechanism for accurately modelling anthropogenic organic acid emissions and developing mitigation strategies.

SVUV-PIMS↗
DOE OSTI2022

Vibrationally resolved optical excitations of the nitrogen-vacancy center in diamond

A comprehensive description of the optical cycle of spin defects in solids requires the understanding of the electronic and atomistic structure of states with different spin multiplicity, including singlet states which are particularly challenging from a theoretical standpoint. We present a general framework, based on spin-flip time-dependent density function theory, to determine the excited state potential energy surfaces of the many-body singlet states of spin defects; we then predict the vibrationally resolved absorption spectrum between singlet shelving states of a prototypical defect, the nitrogen-vacancy center in diamond. Our results, which are in very good agreement with experiments, provide an interpretation of the measured spectra and reveal the key role of specific phonons in determining absorption processes, and the notable influence of non-adiabatic interactions. The insights gained from our calculations may be useful in defining strategies to improve infrared-absorption-based magnetometry and optical pumping schemes. The theoretical framework developed here is general and applicable to a variety of other spin defects and materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

Abstract This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases ofd-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupieddstates near the Fermi level, we determine that the large, sharpddensity of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.

Chemistry↗
DOE OSTI2025

Systematic softening in universal machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning models. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening effect in three uMLIPs: M3GNet, CHGNet, and MACE-MP-0, which is characterized by energy and force underprediction in atomic-modeling benchmarks including surfaces, defects, solid-solution energetics, ion migration barriers, phonon vibration modes, and general high-energy states. The PES softening behavior originates primarily from the systematically underpredicted PES curvature, which derives from the biased sampling of near-equilibrium atomic arrangements in uMLIP pre-training datasets. Our findings suggest that a considerable fraction of uMLIP errors are highly systematic, and can therefore be efficiently corrected. We argue for the importance of a comprehensive materials dataset with improved PES sampling for next-generation foundational MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Cross-functional transferability in foundation machine learning interatomic potentials

The rapid development of foundation potentials (FPs) in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface. The accuracy of FPs can be further improved by bridging the model from lower-fidelity datasets to high-fidelity ones. In this work, we analyze the challenge of this transfer learning (TL) problem within the CHGNet framework. We show that significant energy scale shifts and poor correlations between GGA and r 2 SCAN hinder cross-functional transferability. By benchmarking different TL approaches on the MP-r 2 SCAN dataset, we demonstrate the importance of elemental energy referencing in the TL of FPs. By comparing the scaling law with and without the pre-training on a low-fidelity dataset, we show that significant data efficiency can still be achieved through TL, even with a target dataset of sub-million structures. We highlight the importance of proper TL and multi-fidelity learning in creating next-generation FPs on high-fidelity data.

Huang, Xu [University of California, Berkeley, CA ↗
DOE OSTI2020

Reactants, products, and transition states of elementary chemical reactions based on quantum chemistry

Reaction times, activation energies, branching ratios, yields, and many other quantitative attributes are important for precise organic syntheses and generating detailed reaction mechanisms. Often, it would be useful to be able to classify proposed reactions as fast or slow. However, quantitative chemical reaction data, especially for atom-mapped reactions, are difficult to find in existing databases. Therefore, we used automated potential energy surface exploration to generate 12,000 organic reactions involving H, C, N, and O atoms calculated at the ω B97X-D3/def2-TZVP quantum chemistry level. We report the results of geometry optimizations and frequency calculations for reactants, products, and transition states of all reactions. Additionally, we extracted atom-mapped reaction SMILES, activation energies, and enthalpies of reaction. We believe that this data will accelerate progress in automated methods for organic synthesis and reaction mechanism generation—for example, by enabling the development of novel machine learning models for quantitative reaction prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dissociation dynamics of the diamondoid adamantane upon photoionization by XUV femtosecond pulses

This work presents a photodissociation study of the diamondoid adamantane using extreme ultraviolet femtosecond pulses. The fragmentation dynamics of the dication is unraveled by the use of advanced ion and electron spectroscopy giving access to the dissociation channels as well as their energetics. To get insight into the fragmentation dynamics, we use a theoretical approach combining potential energy surface determination, statistical fragmentation methods and molecular dynamics simulations. We demonstrate that the dissociation dynamics of adamantane dications takes place in a two-step process: barrierless cage opening followed by Coulomb repulsion-driven fragmentation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Ultraviolet spectroscopy of pressurized and supercritical carbon dioxide

Abstract Carbon dioxide (CO 2 ) is prevalent in planetary atmospheres and sees use in a variety of industrial applications. Despite its ubiquitous nature, its photochemistry remains poorly understood. In this work we explore the density dependence of pressurized and supercritical CO 2 electronic absorption spectra by vacuum ultraviolet spectroscopy over the wavelength range 1455-2000 Å. We show that the lowest absorption band transition energy is unaffected by a density increase up to and beyond the thermodynamic critical point (137 bar, 308 K). However, the diffuse vibrational structure inherent to the spectrum gradually decreases in magnitude. This effect cannot be explained solely by collisional broadening and/or dimerization. We suggest that at high densities close proximity of neighboring CO 2 molecules with a variety of orientations perturbs the multiple monomer electronic state potential energy surfaces, facilitating coupling between binding and dissociative states. We estimate a critical radius of ~4.1 Å necessary to cause such perturbations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling

Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modelling. Although classical force fields often fail to describe the coupling between electronic states and ionic rearrangements, the more accurate ab initio molecular dynamics suffers from computational complexity that prevents long-time and large-scale simulations, which are essential to study technologically relevant phenomena. Here we present the Crystal Hamiltonian Graph Neural Network (CHGNet), a graph neural network-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies, forces, stresses and magnetic moments from the Materials Project Trajectory Dataset, which consists of over 10 years of density functional theory calculations of more than 1.5 million inorganic structures. The explicit inclusion of magnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons, enhancing its capability to describe both atomic and electronic degrees of freedom. We demonstrate several applications of CHGNet in solid-state materials, including charge-informed molecular dynamics in Li x MnO 2 , the finite temperature phase diagram for Li x FePO 4 and Li diffusion in garnet conductors. We highlight the significance of charge information for capturing appropriate chemistry and provide insights into ionic systems with additional electronic degrees of freedom that cannot be observed by previous MLIPs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Uncertainty-driven dynamics for active learning of interatomic potentials

Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the data set. Here we develop a strategy to more rapidly discover configurations that meaningfully augment the training data set. The approach, uncertainty-driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. The performance of UDD-AL is demonstrated for two AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore the chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Theoretical study of the reaction mechanism and kinetics of the phenyl + propargyl association

Potential energy surface for the phenyl + propargyl radical recombination reaction has been studied at the CCSD(T)-F12/cc-pVTZ-f12//B3LYP/6-311G** level of theory for the closed-shell singlet species and at the triplet–singlet gap CASPT2/cc-pVTZ-CCSD(T)-F12/cc-pVTZ-f12//CASSCF/cc-pVTZ level of theory for the diradical species. High-pressure limit rate constants for the barrierless channels were evaluated with variable reaction coordinate transition state theory (VRC-TST). Rice–Ramsperger–Kassel–Marcus Master Equation (RRKM-ME) calculations have been performed to assess temperature- and pressure-dependent phenomenological rate constants and product branching ratios. Here, the entrance channels of the radical association reaction produce 3-phenyl-1-propyne and phenylallene which can further dissociate/isomerize into a variety of unimolecular and bimolecular products. Theoretical evidence is presented that, at combustion relevant conditions, the phenyl + propargyl recombination provides a feasible mechanism for the addition of a second five-member ring to the first six-member aromatic ring producing the prototype two-ring species indene and indenyl. Rate expressions for all important reaction channels in a broad range of temperatures and pressures have been generated for kinetic modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Unraveling the structural stability and the electronic structure of ThO 2 clusters

Unraveling the correlations between the geometry, the relative energy and the electronic structure of metal oxide nanostructures is crucial for a better control of their size, shape and properties. Here, we investigated these correlations for stoichiometric thorium dioxide clusters ranging from ThO 2 to Th 8 O 16 using a chemically-driven geometry search algorithm in combination with state-of-the-art first principles calculations. This strategy allows us to homogeneously screen the potential energy surface of actinide oxide clusters for the first time. It is found that the presence of peroxo and superoxo groups tends to increase the total energy of the system by at least 3.5 eV and 7 eV, respectively. For the larger clusters, the presence of terminal oxygen atoms increases the energy by about 0.5 eV. Regarding the electronic structure, it is found that the HOMO–LUMO gap is larger in systems containing only bridging oxygen atoms (~2–3.5 eV) than for systems containing oxo groups (~1–3 eV), peroxo groups (~0–2 eV), and superoxo groups (~0–1 eV). Furthermore, while the LUMO is always dominated by thorium orbitals, the composition of the HOMO changes in the presence or the absence of oxo, peroxo and/or superoxo groups: in the presence of peroxo groups, it is dominated by thorium orbitals, in all other cases, it is dominated by oxygen orbitals, and is rather localized in the presence of terminal oxo or superoxo groups. These correlations are of great interest for synthesizing clusters with tailored properties, especially for applications in the field of nuclear energy and heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The water trimer reaction OH + (H 2 O) 3 → (H 2 O) 2 OH + H 2 O

All important stationary points on the potential energy surface (PES) for the reaction OH + (H 2 O) 3 → (H 2 O) 2 OH + H 2 O have been fully optimized using the “gold standard” CCSD(T) method with the large Dunning correlation-consistent cc-pVQZ basis sets. Three types of pathways were found. For the pathway without hydrogen abstraction, the barrier height of the transition state (TS1) is predicted to lie 5.9 kcal mol -1 below the reactants. The two major complexes (H 2 O) 3 ∙∙∙OH (CP1 and CP2a) are found to lie 6.3 and 11.0 kcal mol -1 , respectively, below the reactants [OH + (H 2 O) 3 ]. For one of the H-abstraction pathways the lowest classical barrier height is predicted to be much higher, 6.1 kcal mol -1 (TS2a) above the reactants. For the other H-abstraction pathway the barrier height is even higher, 15.0 (TS3) kcal mol -1 . Vibrational frequencies and the zero-point vibrational energies connected to the PES are also reported. Fianlly, the energy barriers for the H-abstraction pathways are compared with those for the OH + (H 2 O) 2 and OH + H 2 O reactions, and the effects of the third water on the energetics are usually minor (0.2 kcal mol -1 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Raman spectrum and polarizability of liquid water from deep neural networks

We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a relatively small number of molecular configurations is sufficient to predict the polarizability of arbitrary liquid configurations in close agreement with ab initio density functional theory calculations. In combination with a neural network representation of the interatomic potential energy surface, the scheme allows us to calculate the Raman spectra along 2-nanosecond classical trajectories at different temperatures for H 2 O and D 2 O. The vast gains in efficiency provided by the machine learning approach enable longer trajectories and larger system sizes relative to ab initio methods, reducing the statistical error and improving the resolution of the low-frequency Raman spectra. Decomposing the spectra into intramolecular and intermolecular contributions elucidates the mechanisms behind the temperature dependence of the low-frequency and stretch modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

On the mechanism of soot nucleation. II. E-bridge formation at the PAH bay

A recently proposed mechanism of soot nucleation based upon the formation of a rotationally-activated dimer in the collision of an aromatic molecule and a radical leading to a stable, doubly-bonded E-bridge between them, rooted in the existence of a five-membered ring on the molecule edge, has been further investigated with a focus on the 5-6 E-bridge forming in the reaction of a PAH cyclopenta group with a bay site of another PAH. As a prototype reaction of this kind, we examined the reaction between 4-phenanthrenyl and acenaphthylene and, to project these results to larger aromatic structures, we also explored the size effect of the E-bridge forming reactions by computing the 1-naphthyl + acenaphthylene system and comparing these results with the prior results for pyrenyl + acepyrene. The two systems have been studied through high-level G3(MP2,CC)//B3LYP/6-311G(d,p) ab initio calculations of their potential energy surfaces combined with the RRKM/Master Equation calculations of reaction rate constants. With PAH monomers of similar sizes involved, the formation of E-bridge structures at the bay radical sites appeared to be faster and lead to increased nucleation rates as compared to the zigzag-forming ones. Furthermore, a model combining both the bay and zigzag rotationally-induced formation of E-bridges successfully reaches the level of nucleation fluxes comparable to those of the irreversible pyrene dimerization, thus affirming the rotationally-activated dimerization as a feasible mechanism for soot particle nucleation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Non-adiabatic quantum interference in the ultracold Li + LiNa → Li 2 + Na reaction

Electronically non-adiabatic effects play an important role in many chemical reactions. However, how these effects manifest in cold and ultracold chemistry remains largely unexplored. Here for the first time we present from first principles the non-adiabatic quantum dynamics of the reactive scattering between ultracold alkali-metal LiNa molecules and Li atoms. We show that non-adiabatic dynamics induces quantum interference effects that dramatically alter the ultracold rotationally resolved reaction rate coefficients. The interference effect arises from the conical intersection between the ground and an excited electronic state that is energetically accessible even for ultracold collisions. These unique interference effects might be exploited for quantum control applications such as a quantum molecular switch. The non-adiabatic dynamics are based on full-dimensional ab initio potential energy surfaces for the two electronic states that includes the non-adiabatic couplings and an accurate treatment of the long-range interactions. A statistical analysis of rotational populations of the Li2 product reveals a Poisson distribution implying the underlying classical dynamics are chaotic. The Poisson distribution is robust and amenable to experimental verification and appears to be a universal property of ultracold reactions involving alkali metal dimers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Gas-phase pyrolysis of trans 3-pentenenitrile: competition between direct and isomerization-mediated dissociation

The flash pyrolysis of trans 3-pentenenitrile (3-PN, CH 3 –$CH=CH$–CH 2 –CN) was studied by combining the results of VUV photoionization mass spectra with broadband microwave spectra recorded as a function of the temperature of the pyrolysis tube. The two separated functional groups (vinyl and nitrile) open up isomerization as an initial step in competition with unimolecular dissociation. Primary products were detected by keeping the 3-PN concentration low and limiting reaction times to the traversal time of the gas in the pyrolysis tube (~100 μs). The reaction is quenched and products are cooled by expansion into vacuum before interrogation over the 8–18 GHz region using chirped-pulse broadband methods. 118 nm VUV photoionization of the same reaction mixture provides a means of detecting all products with ionization potentials below 10.5 eV with minimal fragmentation. These results are combined with a detailed computational investigation of the C 5 H 7 N and related potential energy surfaces, leading to a consistent picture of the unimolecular decomposition of 3-PN. Loss of two H-atoms to form a 79 amu product is proven from its microwave transitions to contain trans-Z-2,4-pentadienenitrile, while no pyridine is observed. Methyl loss, HCN loss, and breaking the central C(2)–C(3) bond all occur following isomerization of the position of the double bond, thereby opening up low-energy pathways to these decomposition channels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Inelastic scattering in isotopologues of O 2 –Ar: the effects of mass, symmetry, and density of states

The two species considered here, O 2 (oxygen molecule) and Ar (argon-atom), are both abundant components of Earth's atmosphere and hence familiar collision partners in this medium. O 2 is quite reactive and extensively involved in atmospheric chemistry, including Chapman's cycle of the formation and destruction of ozone; while Ar, like N 2 , typically plays the nevertheless crucial role of inert collider. Inert species can provide stabilization to metastable encounter-complexes through the energy transfer associated with inelastic collisions. The interplay of collision frequency and energy transfer efficiency, with state lifetimes and species concentrations, contributes to the rich and varied chemistry and dynamics found in diverse environments ranging from planetary atmospheres to the interstellar and circumstellar media. The nature and density of bound and resonance states, coupled electronic states, symmetry, and nuclear spin-statistics can all play a role. Here, we systematically investigate some of those factors by looking at the O 2 –Ar system, comparing rigorous quantum-scattering calculations for the 16 O 16 O– 40 Ar, 18 O 16 O– 40 Ar, and 18 O 18 O– 40 Ar isotope combinations. A new accurate potential energy surface was constructed for this purpose holding the O 2 bond distance at its vibrationally averaged distance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗