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Results for “Ab initio calculations”

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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nearly Identical but Not Isotypic: Influence of Lanthanide Contraction on Cs 2 NaLn(PS 4 ) 2 (Ln = La–Nd, Sm, and Gd–Ho)

The effect of the lanthanide contraction often results in topological and symmetry changes in compounds with the same compositions as a function of lanthanide cation size. Here we report on the first example of a lanthanide thiophosphate exhibiting a change in the lanthanide cation environment without any topological or symmetry change. A series of new lanthanide thiophosphates with mixed alkali cations was obtained via a flux crystal growth technique using a CsI flux. The obtained compounds Cs 2 NaLn(PS 4 ) 2 (Ln = La–Nd, Sm, Gd–Ho) were grown as large single crystals (~0.1–1 mm 3 ) and characterized using single crystal X-ray diffraction and magnetic susceptibility measurements. Moving across the series, the structural studies revealed a change in the lanthanide coordination environment dependent upon the identity of the lanthanide. Although all compounds in the Cs 2 NaLn(PS 4 ) 2 series crystallize in the same space group and have the same Wyckoff positions of the atoms, a slight size change between Sm 3+ and Gd 3+ causes a subtle change in coordination number from 9 (for Ln = La–Sm) to 8 (for Ln = Gd–Ho), resulting in two distinct but virtually identical structure types. Ab initio calculations were performed, and the observed experimental trend was corroborated computationally. Finally, magnetic measurements performed on the Cs 2 NaLn(PS 4 ) 2 (Ln = Ce, Pr, Nd, Gd, and Tb) compounds revealed paramagnetic behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions

Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water’s remarkable versatility as a solvent. However, accurately predicting the feasibility of hydrolysis through computational techniques is a difficult task, as subtle changes in reactant structure like heteroatom substitutions or neighboring functional groups can influence the reaction outcome. Furthermore, hydrolysis is sensitive to the pH of the aqueous medium, and the same reaction can have different reaction properties at different pH conditions. In this work, we have combined reaction templates and high-throughput ab initio calculations to construct a diverse data set of hydrolysis free energies. The developed framework automatically identifies reaction centers, generates hydrolysis products, and utilizes a trained graph neural network (GNN) model to predict ΔG values for all potential hydrolysis reactions in a given molecule. The long-term goal of the work is to develop a data-driven, computational tool for high-throughput screening of pH-specific hydrolytic stability and the rapid prediction of reaction products, which can then be applied in a wide array of applications including chemical recycling of polymers and ion-conducting membranes for clean energy generation and storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Atomic Energy Accuracy of Neural Network Potentials: Harnessing Pretraining and Transfer Learning

Machine learning-based interatomic potentials (MLIPs) have transformed the prediction of potential energy surfaces (PESs), achieving accuracy comparable to ab initio calculations. However, atomic energy predictions, often assumed to lack physical meaning, remain underexplored. In this study, we demonstrate that inaccuracies in atomic energy predictions reduce the robustness and transferability of Neural Network Potentials (NNPs) and atomic energy error can be masked in total energy predictions due to error cancellation. Here, we validate this finding using challenging configurations involving deformation and failure under tensile loading. By pretraining atomic energy predictions using empirical potentials and applying transfer learning with density functional theory (DFT) data, we achieve notable improvements in the accuracy of total energy, forces, and stress predictions. Furthermore, this approach enhances the robustness and transferability of NNPs, emphasizing the importance of atomic energy predictions in developing high-quality and reliable MLIPs.

Active Learning↗
DOE OSTI2023

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

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

Probing orientation-specific charge-dipole interactions between hexafluoroisopropanol and halides: A joint photoelectron spectroscopy and theoretical study

The interactions between hexafluoroisopropanol (HFIP) and halogen anions X? (F?, Cl?, Br?, and I?) have been investigated by negative ion photoelectron spectroscopy (NIPES) and ab initio calculations. The measured NIPE spectrum of each [HFIP·X]? (X = Cl, Br, and I) complex shows the identical pattern to the corresponding X? by shifting to the high electron binding energy side, indicative of formation of [HFIP···X?] structure, in which X? interacts with HFIP via charge-dipole interactions. However, the spectrum of [HFIP·F]? appears completely different from that of F?, and is more similar to the spectrum of the deprotonated HFIP anion (HFIP?H?). The geometry and electron density calculations indicate that a neutral HF molecule is formed upon HFIP interacting with F? via proton transfer, rendering a stable structure of [HFIP?H···HF]?. Two conformers of [HFIP?H·HF]? with HFIP being in synperiplanar and antiperiplanar configurations, respectively, are observed, providing direct experimental evidences to show the distinctly different and orientation-specific interactions between HFIP and halide anions.

Wang, Lei↗
DOE OSTI2022

Interplay of Electronic and Geometric Structure Tunes Organic Biradical Character in Bimetallic Tetrathiafulvalene Tetrathiolate Complexes

The synthesis and design of organic biradicals with tunable singlet–triplet gaps have become the subject of significant research interest, owing to their possible photochemical applications and use in the development of molecular switches and conductors. Recently, tetrathiafulvalene tetrathiolate (TTFtt) has been demonstrated to exhibit such organic biradical character in doubly ionized bimetallic complexes. In this article we use high-level ab initio calculations to interrogate the electronic structure of a series of TTFtt-bridged metal complexes, resolving the factors governing their biradical character and singlet–triplet gaps. Here, we show that the degree of biradical character correlates with a readily measured experimental predictor, the central TTFtt C–C bond length, and that it may be described by a one-parameter model, providing valuable insight for the future rational design of TTFtt based biradical compounds and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Experimental and Theoretical Study of Oxolan-3-one Thermal Decomposition

The thermal decomposition of oxolan-3-one, a common component of the bio-oil formed during biomass pyrolysis, has been studied using ab initio calculations and experiments employing pulsed gas-phase pyrolysis with matrix isolation FTIR product detection. Four pathways for unimolecular decomposition were predicted using computational methods. The dominant reaction channel led to carbon monoxide, formaldehyde, and ethylene, all of which were observed experimentally. Here, the other channels led to an assortment of products including ketene, water, propyne, and acetylene, which were all confirmed in the matrix-isolation FTIR spectra. There is also evidence for the production of substituted ketenes in pyrolysis, most likely hydroxyketene and methylketene.

09 BIOMASS FUELS↗
DOE OSTI2022

High Resolution Photoelectron Spectroscopy of the Acetyl Anion

High-resolution photoelectron spectra of cryogenically cooled acetyl anions (CH 3 CO - ) obtained using slow photoelectron velocity-map imaging are reported. The high resolution of the photoelectron spectrum yields a refined electron affinity of 0.4352 ± 0.0012 eV for the acetyl radical as well as the observation of a new vibronic structure that is assigned based on ab initio calculations. Three vibrational frequencies of the neutral radical are measured to be 1047 ± 3 cm -1 (ν 6 ), 834 ± 2 cm -1 (ν 7 ), and 471 ± 1 cm -1 (ν 8 ). Here this work represents the first experimental measurement of the ν 6 frequency of the neutral. The measured electron affinity is used to calculate a refined value of 1641.35 ± 0.42 kJ mol -1 for the gas-phase acidity of acetaldehyde. Analysis of the photoelectron angular distributions provides insight into the character of the highest occupied molecular orbital of the anion, revealing a molecular orbital with strong d-character. Additionally, details of a new centroiding algorithm based on finite differences, which has the potential to decrease data acquisition times by an order of magnitude at no cost to accuracy, are provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Theoretical and Experimental Study of the Spectroscopy and Thermochemistry of UC +/0/–

A combination of high-level ab initio calculations and anion photoelectron detachment (PD) measurements is reported for the UC, UC – , and UC + molecules. To better compare the theoretical values with the experimental photoelectron spectrum (PES), a value of 1.493 eV for the adiabatic electron affinity (AEA) of UC was calculated at the Feller–Peterson–Dixon (FPD) level. The lowest vertical detachment energy (VDE) is predicted to be 1.500 eV compared to the experimental value of 1.487 ± 0.035 eV. A shoulder to lower energy in the experimental PD spectrum with the 355 nm laser can be assigned to a combination of low-lying excited states of UC – and excited vibrational states. The VDEs calculated for the low-lying excited electronic states of UC at the SO-CASPT2 level are consistent with the observed additional electron binding energies at 1.990, 2.112, 2.316, and 3.760 eV. Potential energy curves for the Ω states and the associated spectroscopic properties are also reported. Compared to UN and UN + , the bond dissociation energy (BDE) of UC (411.3 kJ/mol) is predicted to be considerably lower. The natural bond orbitals (NBO) calculations show that the UC 0/+/– molecules have a bond order of 2.5 with their ground-state configuration arising from changes in the oxidation state of the U atom in terms of the 7s orbital occupation: UC (5f 2 7s 1 ), UC – (5f 2 7s 2 ), and UC + (5f 2 7s 0 ). Furthermore, the behavior of the UN and UC sequence of molecules and anions differs from the corresponding sequences for UO and UF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Identification of the Elusive Methyl-Loss Channel in the Crossed Molecular Beam Study of Gas-Phase Reaction of Dicarbon Molecules (C 2 ; X 1 Σ g + /a 3 Π u ) with 2-Methyl-1,3-butadiene (C 5 H 8 ; X 1 A')

The crossed molecular beams technique was utilized to explore the reaction of dicarbon C 2 (X 1 Σ g + /a 3 Π u ) with 2-methyl-1,3-butadiene (isoprene, CH 2 C(CH 3 )CHCH 2 ; X 1 A') at a collision energy of 28 ± 1 kJ mol⁻¹ using a supersonic dicarbon beam generated via photolysis (248 nm) of helium-seeded tetrachloroethylene (C 2 Cl 4 ). Here, experimental data combined with previous ab initio calculations provide evidence of the detection of the hitherto elusive methyl elimination channels leading to acyclic resonantly stabilized hexatetraenyl radicals: 1,2,4,5-hexatetraen-3-yl (CH 2 CC•CHCCH 2 ) and/or 1,3,4,5-hexatetraen-3-yl (CH 2 CHC•CCCH 2 ). These pathways are exclusive to the singlet potential energy surface, with the reaction initiated by the barrierless addition of dicarbon to one of the carbon-carbon double bonds in the diene. In combustion systems, both hexatetraenyl radicals can isomerize to the phenyl radical (C 6 H 5 ) through a hydrogen atom assisted isomerization – the crucial reaction intermediate and molecular mass growth species step toward the formation of polycyclic aromatic hydrocarbons (PAHs) and soot.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Combined Crossed Molecular Beam and Theoretical Investigation of the Elementary Reaction of Tricarbon (C 3 (X 1 Σ g + )) with Diacetylene (C 4 H 2 (X 1 Σ g + )): Gas Phase Formation of the Heptatriynylidyne Radical ( l -C 7 H(X 2 Π))

An elucidation of the underlying formation pathways to acyclic hydrocarbons such as polyynes (C n H 2 ), cumulenes (C n H 2 ), and linear resonantly stabilized linear radicals (l-C n H) is indispensable to understand the hydrocarbon chemistry in extreme low and high temperature environments. In this study, we exploited the crossed molecular beam technique to investigate the reaction of tricarbon C 3 (X 1 Σ g + ) with diacetylene (butadiyne; HCCCCH; X 1 Σ g + ) at a collision energy of 47 ± 1 kJ mol ⁻1 . The experimental data were merged with ab initio calculations of the singlet C 7 H 2 potential energy surface (PES) revealing that the reaction is initiated via the formation of an initial van der Waals reactant complex in the entrance channel. Subsequent rearrangements lead to various carbene-type and cyclic intermediates via ring-opening, ring-closure, and hydrogen migration processes eventually forming acyclic C 7 H 2 isomers prior to their barrierless unimolecular decomposition to the most stable linear isomer, heptatriynylidyne (C 7 H, X 2 Π) in an overall endoergic reaction (+57 kJ mol ⁻1 ). The reaction exhibits strong similarities to the tricarbon – acetylene (C 3 – C 2 H 2 ). Furthermore, the significant energy threshold suggests that the tricarbon reaction with (poly)acetylenes forming resonantly stabilized linear radicals are open in high-temperature environments such as combustion flames and circumstellar envelopes of carbon stars and planetary nebulae as their descendants; however, these reactions are closed in low-temperature environments as in cold molecular clouds and hydrocarbon-rich atmospheres of planets and their moons such as in Titan.

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

Mechanism and Reaction Energy Landscape for Apiose Cross-Linking by Boric Acid in Rhamnogalacturonan II

Rhamnogalacturonan II (RG-II)—the most complex polysaccharide known in nature—exists as a borate cross-linked dimer in the plant primary cell wall. Boric acid facilitates the formation of this cross-link on the apiosyl residues of RG-II’s side chain A. Here, we detail the reaction mechanism for the cross-linking process with ab initio calculations coupled with transition state theory. We determine the formation of the first ester linkage to be the rate-limiting step of the mechanism. Our findings demonstrate that the regio- and stereospecific nature of subsequent steps in the reaction itinerary presents four distinct energetically plausible reaction pathways. This has significant implications for the overall structure of the cross-linked RG-II dimer assembly. Finally, our transition state and reaction path analyses reveal key geometric insights that corroborate previous experimental hypotheses on borate ester formation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational Insights into Malononitrile-Based Carbanions for CO 2 Capture

Although anionic N and O sites have been widely used in chemisorption of CO 2 , carbanions are much less explored for CO 2 capture. Here, in this study, we employ ab initio calculations and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations to examine the interaction between CO 2 and the malononitrile carbanion, [CH(CN) 2 ] – . We have explored the potential energy surface of CO 2 binding by scanning the C–C distance between CO 2 and the central C site of the carbanion. We find that CO 2 prefers to bind to the nitrile group physically rather than to form a C–C bond via the carboxylation reaction at the sp 2 C site. Moreover, the two –CN groups can attract two CO 2 molecules at equal strength. The presence of an alkali metal ion enhances both physical and chemical interactions of CO 2 with the malononitrile carbanion. QM/MM MD simulations further confirm the preference of physical interaction in the condensed ionic liquid phase with a phosphonium cation. Our findings suggest that ionic liquids based on the malononitrile carbanion may have a high CO 2 solubility for carbon capture.

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

Empirically Optimized One-Electron Pseudopotential for the Hydrated Electron: A Proof-of-Concept Study

Mixed quantum-classical molecular dynamics simulations have been important tools for studying the hydrated electron. They generally use a one-electron pseudopotential to describe the interactions of an electron with the water molecules. Furthermore, this approximation shows both the strength and weakness of the approach. On the one hand, it enables extensive statistical sampling and large system sizes that are not possible with more accurate ab initio molecular dynamics methods. On the other hand, there has (justifiably) been much debate about the ability of pseudopotentials to accurately and quantitatively describe the hydrated electron properties. These pseudopotentials have largely been derived by fitting them to ab initio calculations of an electron interacting with a single water molecule. In this paper, we present a proof-of-concept demonstration of an alternative approach in which the pseudopotential parameters are determined by optimizing them to reproduce key experimental properties. Specifically, we develop a new pseudopotential, using the existing TBOpt model as a starting point, which correctly describes the hydrated electron vertical detachment energy and radius of gyration. In addition to these properties, this empirically optimized model displays a significantly modified solvation structure, which improves, for example, the prediction of the partial molar volume.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Substituted ALPO-5 Zeolites as Promising O 2 Sorption Pump Materials: A Density Functional Theory Study

Many chemical processes depend on having an environment that is low in oxygen partial pressure (P O2 < 100 Pa); sorption pumps are a promising route to establishing that environment by either oxygen pumping or oxygen separation from an inert gas. Near ambient sorption-based processes rely on either pressure or thermal swings, requiring no moving parts, no electricity, and neither very high nor very low temperatures. In this work, we use ab initio calculations to explore zeolites as a class of materials for sorption based oxygen pumping/separation. Our calculations indicate that while the neat ALPO-5 zeolite does not adsorb O 2 , O 2 does adsorb on zeolites selectively substituted with transition metals and metalloids and hence, can enable separation and pumping. ALPO-5 substituted with Si, Ge, Sn, Pd, Pt, Ti, V, Cr, Mn, Zr, Mo, Hf, W, Ce, and Pr provides adsorption energies ranging from -0.19 to -3.92 eV, (-) indicates exothermic process. Additionally, we provide a comprehensive understanding of what controls the adsorption energy: 1) the substi-tutions must be able to adopt an oxidation state that is more positive than the cation it replaces, and 2) the size of the pore into which the O 2 adsorbs to the wall. Additionally, we conduct a ther-modynamic analysis of a thermal swing cycle to approximate the optimal O 2 binding energy for 2 low energy O 2 pumping/separation. We find that the minimum energy cost likely occurs when the adsorption energy is in the range of 0.75 – 1.00 eV (72 – 97 kJ·mol -1 ), which corresponds to Ge, V, Pt, or Ce substituted ALPO-5.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Tuning the Electronic Properties of Graphane via Hydroxylation: An Ab Initio Study

The thermodynamic stability of hydroxylated graphane, that is, fully sp 3 graphene derivatives coordinated with -H and -OH groups, has been recently demonstrated by ab initio calculations. Within the density functional theory approach, we investigate the electronic property modifications of graphane by progressive hydroxylation, that is, by progressively substituting -H with -OH groups. When 50% of graphane is hydroxylated, the energy bandgap reaches its largest value of 6.68 eV. The electronic affinity of 0.8 eV for graphane can widely change in the 0.28–1.60 eV range depending on the geometric configuration. Hydroxylated graphane has two interfaces with vacuum, hence its electron affinity can be different on each interface with the formation of an intrinsic dipole perpendicular to the monolayer. We envisage the possibility of using hydroxylated graphane allotropes with tunable electronic affinity to serve as interfacial layers in 2D material-based heterojunctions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗