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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 631 records · Page 35
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DOE OSTI2021

Unraveling Local Structure of Molten Salts via X-ray Scattering, Raman Spectroscopy, and Ab Initio Molecular Dynamics

In this work, we resolve a long-standing issue concerning the local structure of molten MgCl 2 by employing a multimodal approach, including X-ray scattering and Raman spectroscopy, along with the theoretical modeling of the experimental spectra based on ab initio molecular dynamics (AIMD) simulations utilizing several density functional theory (DFT) methods. We demonstrate the reliability of AIMD simulations in achieving excellent agreement between the experimental and simulated spectra for MgCl 2 and 50 mol % MgCl 2 + 50 mol % KCl, and ZnCl 2 , thus allowing structural insights not directly available from experiment alone. A thorough computational analysis using five DFT methods provides a convergent view that octahedrally coordinated magnesium in pure MgCl 2 upon melting preferentially coordinates with five chloride anions to form distorted square pyramidal polyhedra that are connected via corners and to a lesser degree via edges. This is contrasted with the results for ZnCl 2 , which does not change its tetrahedral coordination on melting. Although the five-coordinate MgCl 5 3– complex was not considered in the early literature, together with an increasing tendency to form a tetrahedrally coordinated complex with decreasing the MgCl 2 content in the mixture with alkali metal chloride systems, current work reconciles the results of most previous seemingly contradictory experimental studies.

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

Machine Learning-Accelerated First-Principles Molecular Dynamics Reveals C–C Coupling Mechanisms toward Ethylene on Cu(100)

Here, the Cu(100) termination has been identified as the most effective facet for converting CO and CO 2 into ethylene. To enhance both the activity and selectivity of ethylene production, we perform machine-learning-accelerated, first-principles molecular dynamics simulations at 298 K in an explicit solvent at pH 7 to elucidate the C–C coupling mechanism─the critical reaction step in forming C 2+ products. Among the six potential C–C coupling pathways, the most feasible are CO* dimerization and CO – CHO* and CHO* – CHO* couplings. Using the computational hydrogen electrode method, we demonstrate that all three pathways are equally accessible at −0.6 V vs RHE. At a potential below −1.0 V vs RHE, the thermodynamic barriers for the CO – CHO* and CHO* – CHO* pathways become negligible. Our computational findings explain the experimental observations, particularly the absence of C 2+ products above −0.4 V vs RHE and the peaks in ethylene production near −0.6 and −1.0 V vs RHE. Since CHO* acts as a key intermediate common to both C–C coupling and CH 4 formation, we propose that suppressing CHO* hydrogenation would inhibit CH 4 pathways, thereby maximizing ethylene selectivity.

CO2 reduction↗
DOE OSTI2023

Toward Quantum Chemical Free Energy Simulations of Platinum Nanoparticles on Titania Support

Platinum nanoparticles (Pt-NPs) supported on titania surfaces are costly but indispensable heterogeneous catalysts because of their highly effective and selective catalytic properties. Therefore, it is vital to understand their physicochemical processes during catalysis to optimize their use and to further develop better catalysts. However, simulating these dynamic processes is challenging due to the need for a reliable quantum chemical method to describe chemical bond breaking and bond formation during the processes but, at the same time, fast enough to sample a large number of configurations required to compute the corresponding free energy surfaces. Density functional theory (DFT) is often used to explore Pt-NPs; nonetheless, it is usually limited to some minimum-energy reaction pathways on static potential energy surfaces because of its high computational cost. In this work, we report a combination of the density functional tight binding (DFTB) method as a fast but reliable approximation to DFT, the steered molecular dynamics (SMD) technique, and the Jarzynski equality to construct free energy surfaces of the temperature-dependent diffusion and growth of platinum particles on a titania surface. In particular, we present the parametrization for Pt-X (X = Pt, Ti, or O) interactions in the framework of the second-order DFTB method, using a previous parametrization for titania as a basis. The optimized parameter set was used to simulate the surface diffusion of a single platinum atom (Pt 1 ) and the growth of Pt 6 from Pt 5 and Pt 1 on the rutile (110) surface at three different temperatures (T = 400, 600, 800 K). The free energy profile was constructed by using over a hundred SMD trajectories for each process. We found that increasing the temperature has a minimal effect on the formation free energy; nevertheless, it significantly reduces the free energy barrier of Pt atom migration on the TiO 2 surface and the transition state (TS) of its deposition. In a concluding remark, the methodology opens the pathway to quantum chemical free energy simulations of Pt-NPs’ temperature-dependent growth and other transformation processes on the titania support.

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

Unraveling the Heterogeneous but Ordered Microstructure of the Nonionic Deep Eutectic Solvent Formed by Lauric Acid and N -Methylacetamide

The nonionic deep eutectic solvent, formed by lauric acid (LA) and N-methylacetamide (NMA), has been shown to have a heterogeneous molecular structure in which the LA and NMA form nonpolar and polar domains, respectively. Previous vibrational spectroscopy experiments demonstrated that the ability of the LA domains to solvate compounds was limited to long carbon chains, whereas other nonpolar molecules, such as W(CO) 6 , were found to be solvated by both LA and NMA. These experiments were not fully compatible with the previously proposed micelle-like structure of the nonpolar domains of the LA-NMA DES. In this work, the modeling of the DES molecular structure is pursued using classical molecular dynamics simulations. The new classical model reproduces both the SAXS structural factors and the previously experimentally derived interaction map for these LA-NMA DESs. In addition, the simulation also shows that LA-NMA DESs form highly organized LA aggregates that are difficult to disorganize. Further evidence of the correct description provided by the newly derived model is obtained using a moderately polar probe: chloroform-d. Computations using the classical model have a good agreement with the solvation behavior of the probe derived from experiments, in which the location of the probe is found to be mostly within the polar domain of the DES. The computational model also demonstrates that the probe solvation is a consequence of the tightly packed LA structure, which causes nonpolar molecules to be located at the interphase of the DES nonpolar domains.

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

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Multiscale Concurrent Atomistic-Continuum (CAC) modeling of multicomponent alloys

We report strengthening in complex multicomponent systems such as solid solution alloys is controlled primarily by the dynamic interactions between dislocation lines and heterogeneously distributed solute species. Modeling of extended defect length scales in such multicomponent systems becomes prohibitively expensive, motivating the development of reduced order approaches. This work explores the application of the Concurrent Atomistic-Continuum (CAC) method to model dislocation mobility in random alloys at extended length scales. By employing recently developed average-atom interatomic potentials, the average “bulk” material response in coarse-grained regions interacts with true random solute species in the atomistic-scale domain. We demonstrate that spurious stresses in domain resolution transition regions are eliminated entirely due to the CAC formulation. Simultaneously, the key details of local stress fluctuation due to randomness in the dislocation core region are captured, and fluctuating stress smoothly decays to the long-range dislocation stress field response. Dislocation mobility calculations, for line lengths over 400 nm, are computed as a function of alloy composition in the model FeNiCr system and compared to full molecular dynamics (MD). The results capture the composition-dependent trends, while reducing degrees of freedom by nearly 40%. This approach can be readily extended to any system described by an EAM potential and facilitates the study of large-scale defect dynamics in complex solute environments to support computational alloy design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Water dissociation at the water–rutile TiO 2 (110) interface from ab initio-based deep neural network simulations

The interaction of water with TiO 2 surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO 2 –water interface has a critical role in the surface chemistry of TiO 2 , but is difficult to determine both experimentally and computationally. Among TiO 2 surfaces, rutile TiO 2 (110) is of special interest as the most abundant surface of TiO 2 ’s stable rutile phase. While surface-science studies have provided detailed information on the interaction of rutile TiO 2 (110) with gas-phase water, much less is known about the TiO 2 (110)–water interface, which is more relevant to many applications. In this work, we characterize the structure of the aqueous TiO 2 (110) interface using nanosecond timescale molecular dynamics simulations with ab initio-based deep neural network potentials that accurately describe water/TiO 2 (110) interactions over a wide range of water coverages. Simulations on TiO 2 (110) slab models of increasing thickness provide insight into the dynamic equilibrium between molecular and dissociated adsorbed water at the interface and allow us to obtain a reliable estimate of the equilibrium fraction of water dissociation. We find a dissociation fraction of 22 ± 6% with an associated average hydroxyl lifetime of 7.6 ± 1.8 ns. These quantities are both much larger than corresponding estimates for the aqueous anatase TiO 2 (101) interface, consistent with the higher water photooxidation activity that is observed for rutile relative to anatase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effect of Domain Size, Boundary, and Loading Conditions on Mechanical Properties of Amorphous Silica: A Reactive Molecular Dynamics Study

Mechanical properties are very important when choosing a material for a specific application. They help to determine the range of usefulness of a material, establish the service life, and classify and identify materials. The size effect on mechanical properties has been well established numerically and experimentally. However, the role of the size effect combined with boundary and loading conditions on mechanical properties remains unknown. In this paper, by using molecular dynamics (MD) simulations with the state-of-the-art ReaxFF force field, we study mechanical properties of amorphous silica (e.g., Young’s modulus, Poisson’s ratio) as a function of domain size, full-/semi-periodic boundary condition, and tensile/compressive loading. We found that the domain-size effect on Young’s modulus and Poisson’s ratio is much more significant in semi-periodic domains compared to full-periodic domains. The results, for the first time, revealed the bimodular and anisotropic nature of amorphous silica at the atomic level. We also defined a “safe zone” regarding the domain size, where the bulk properties of amorphous silica can be reproducible, while the computational cost and accuracy are in balance.

bimodular materials↗
DOE OSTI2025

Separation of Linear and Cyclic Siloxanes in Pure Silica Zeolites

We present a computational assessment of pure-silica zeolites for separating linear and cyclic siloxanes. We developed a force field (FF) for pure silica zeolites, when combined with our previously developed FF for siloxanes using standard Lorentz–Berthelot combining rules, shows good agreement with dispersion-corrected density functional theory calculations. We used molecular dynamics simulations to investigate diffusion of siloxanes in pure silica zeolites and identified a pure silica zeolite with the structure code FAU that enables kinetic separation of linear and cyclic siloxanes. FAU allows the diffusion of linear siloxanes (L2–L6) while excluding cyclic siloxanes. D4 siloxane does not diffuse in any of the investigated zeolites, eliminating the potential of pure silica zeolites to achieve equilibrium-based separations of linear and cyclic siloxanes.

adsorption↗
DOE OSTI2022

Energy, angle, and temperature dependencies of the sticking of D atoms on Li surfaces

Detailed experimental and computational information on the response of lithium surfaces to irradiation by slow hydrogenic particles (ions, atoms, molecules) is sparse and mainly speculative. In this work, we present a computational study of the reflection and retention of deuterium (D) atoms at crystalline and amorphous lithium surfaces at 300 and 500 K, where the D atoms have an impact energy in the range of 0.025–5 eV and incident angles of 0° (perpendicular incidence) or 85° (near-grazing incidence). Classical molecular dynamics simulations are performed with the reactive bond-order force field (ReaxFF) potentials. This study provides quantitative information on the deuterium sticking probability and recycling coefficient for lithium surfaces. Further, our results support the ongoing work at the Lithium Tokamak eXperiment-β fusion experiment as well as relevant experiments in the laboratory setting.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

An analytic and complete equation of state for condensed phase materials

Analytic equations of state (EOS) are intended to reproduce theoretical and experimental data in a single phase portion of the thermodynamic space. We devise a complete and thermodynamically consistent model with four distinct features: (1) a reference isotherm that remains thermodynamically stable, (2) a flexible specific heat model based on a fourth-order rational polynomial, (3) a Grüneisen parameter that depends on specific volume and temperature, and (4) pressure and internal energy functions that can be inverted analytically in temperature. The model aims to improve the accuracy of existing equations of state while remaining computationally efficient. To demonstrate its features, we include calibrations for single-crystal pentaerythritol tetranitrate (PETN), liquid nitromethane (NM), and hexagonal close-packed beryllium (Be) metal. The parameter optimization uses the specific heat capacity, Grüneisen parameter, and static compression curves obtained from density functional theory for the crystalline solids and molecular dynamics simulations for liquid NM. We also present a velocity autocorrelation function that yields accurate phonon densities of states for the EOS calibration from the molecular dynamics trajectories. Each of the three calibrations is constrained to enforce the ambient state from experimental measurements and validated against experimental Hugoniot data from multiple sources. We also include one-dimensional hydrodynamic simulations of the isentropic compression experiments for beryllium conducted at the Z facility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Multiscale molecular simulations for the solvation of lignin in ionic liquids

Lignin, the second most abundant biopolymer found in nature, has emerged as a potential source of sustainable fuels, chemicals, and materials. Finding suitable solvents, as well as technologies for efficient and affordable lignin dissolution and depolymerization, are major obstacles in the conversion of lignin to value-added products. Certain ionic liquids (ILs) are capable of dissolving and depolymerizing lignin but designing and developing an effective IL for lignin dissolution remains quite challenging. To address this issue, the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) model was used to screen 5670 ILs by computing logarithmic activity coefficients (ln(γ)) and excess enthalpies (H E ) of lignin, respectively. Based on the COSMO-RS computed thermodynamic properties (ln(γ) and H E ) of lignin, anions such as acetate, methyl carbonate, octanoate, glycinate, alaninate, and lysinate in combination with cations like tetraalkylammonium, tetraalkylphosphonium, and pyridinium are predicted to be suitable solvents for lignin dissolution. The dissolution properties such as interaction energy between anion and cation, viscosity, Hansen solubility parameters, dissociation constants, and Kamlet–Taft parameters of selected ILs were evaluated to assess their propensity for lignin dissolution. Furthermore, molecular dynamics (MD) simulations were performed to understand the structural and dynamic properties of tetrabutylammonium [TBA] + -based ILs and lignin mixtures and to shed light on the mechanisms involved in lignin dissolution. MD simulation results suggested [TBA] + -based ILs have the potential to dissolve lignin because of their higher contact probability and interaction energies with lignin when compared to cholinium lysinate.

09 BIOMASS FUELS↗
DOE OSTI2022

The “good,” the “bad,” and the “hidden” in neutron scattering and molecular dynamics of ionic aqueous solutions

We characterize a concentrated 7.3 m CaCl 2 solution, combining neutron diffraction with chloride isotopic substitution (Cl-NDIS) in null water and molecular dynamics (MD) simulations. We elucidate the solution structure, thermodynamic properties, and extent of ion pairing previously suggested as concentration-dependent and often not observed at lower concentrations. Our Cl-NDIS measurements designate the solvent-shared ion pairing as dominant and the contact ion pairing (CIP) as insignificant even under conditions close to the solubility limit. The MD models parameterized against neutron diffraction with calcium isotopic substitution (Ca-NDIS) overestimate CIP despite successfully reproducing most of the Cl-NDIS signal. This drawback originates from the fact that Ca 2+ –Cl - interactions were primarily “hidden” in the Ca-NDIS signal due to overlapping with Ca 2+ –O w and Ca 2+ –H w contributions to the total scattering. Contrary, MD models with moderate CIP and possessing generally good performance at high concentrations fail to reproduce the NDIS measurements accurately. Therefore, the electronic polarization, introduced in most of the recent MD models via scaling ionic charges, resolves some but not all parameterization drawbacks. We conclude that despite improving the quality of MD models “on average,” the question “which model is the best” has not been answered but replaced by the question “which model is better for a given research.” An overall “good” model can still be inappropriate or, in some instances, “bad” and, unfortunately, produce erroneous results. Additionally, the accurate interpretation of several NDIS datasets, complemented by MD simulations, can prevent such mistakes and help identify the strengths, weaknesses, and convenient applications for corresponding computational models.

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

Recent Advances in X-ray Absorption Near Edge Structure (XANES) Simulation for Catalysis: Theories and Applications

X-ray absorption spectroscopy (XAS) is a powerful spectroscopic technique for characterizing catalytic active sites. In particular, X-ray Absorption Near Edge Structure (XANES) provides insights into the oxidation state and local coordination environment of the absorbing atom, shedding light on the catalytic structure. Computational XANES simulations provide one-on-one correspondence between the molecular structure and their corresponding spectra, making them an effective approach for interpreting experimental XANES features. This work outlines various theories used to simulate XANES spectra and highlights recent advancements in computational XANES applications for homogeneous, heterogeneous, and single-atom catalysts focusing on identifying the active site structures, the site heterogeneity, and the dynamic evolution of catalysts.

Xu, Jiayi↗
DOE OSTI2021

Exploring the impacts of conformer selection methods on ion mobility collision cross section predictions

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50,000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire dataset. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property—the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good tradeoff between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Nielson, Felicity F.↗
DOE OSTI2025

Evaluating the Structural Response of Amphiphilic Monolayers to Environmental Stimuli

Amphiphilic monolayers composed of end groups with distinct polar and nonpolar functional groups offer rapid and reversible interfacial adaptation in response to environmental stimuli such as a change in interfacial medium polarity. We have synthesized and characterized a suite of monolayers with functional groups of competing polarity designed to reconfigure their interfacial chemical composition in response to solvent polarity. In these films, the end group is designed to be able to reorient and expose the functional groups that minimize the interfacial free energy between the film and the environment. Using a combination of spectroscopic, computational, and wettability studies, we have investigated the responsive interfacial behavior of different end groups upon exposure to environments with varying polarities. Contact angle measurements across a series of polar and dispersive probe liquids reveal trends that reflect the underlying molecular flexibility and composition. Vibrational sum frequency generation (SFG) spectroscopy and atomistic molecular dynamics (MD) simulations confirm solvent-driven reorientation of the end groups, with restructuring observed at the interface. To quantify these effects, we have developed a surface energy calculation model that incorporates solvent-induced surface rearrangements into the estimations. Our findings reveal a strong dependence of surface energy and switching behavior on the length and flexibility of the functionalities in the end group, which affects the exposure of certain interfacial compositions under different solvents. These results offer new insights into the design of adaptive monolayers and provide a framework for evaluating solvent-responsive surfaces.

functional groups↗
DOE OSTI2022

Hit Expansion of a Noncovalent SARS-CoV-2 Main Protease Inhibitor

Inhibition of the SARS-CoV-2 main protease (M pro ) is a major focus of drug discovery efforts against COVID-19. Here we report a hit expansion of non-covalent inhibitors of M pro . Starting from a recently discovered scaffold (The COVID Moonshot Consortium. Open Science Discovery of Oral Non-Covalent SARS-CoV-2 Main Protease Inhibitor Therapeutics. bioRxiv 2020.10.29.339317) represented by an isoquinoline series, we searched a database of over a billion compounds using a cheminformatics molecular fingerprinting approach. We identified and tested 48 compounds in enzyme inhibition assays, of which 21 exhibited inhibitory activity above 50% at 20 μM. Among these, four compounds with IC 50 values around 1 μM were found. Interestingly, despite the large search space, the isoquinolone motif was conserved in each of these four strongest binders. Room-temperature X-ray structures of co-crystallized protein–inhibitor complexes were determined up to 1.9 Å resolution for two of these compounds as well as one of the stronger inhibitors in the original isoquinoline series, revealing essential interactions with the binding site and water molecules. Molecular dynamics simulations and quantum chemical calculations further elucidate the binding interactions as well as electrostatic effects on ligand binding. The results help explain the strength of this new non-covalent scaffold for M pro inhibition and inform lead optimization efforts for this series, while demonstrating the effectiveness of a high-throughput computational approach to expanding a pharmacophore library.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A silicate dynamo in the early Earth

The Earth’s magnetic field has operated for at least 3.4 billion years, yet how the ancient field was produced is still unknown. The core in the early Earth was surrounded by a molten silicate layer, a basal magma ocean that may have survived for more than one billion years. Here we use density functional theory-based molecular dynamics simulations to predict the electrical conductivity of silicate liquid at the conditions of the basal magma ocean: 100–140 GPa, and 4000–6000 K. We find that the electrical conductivity exceeds 10,000 S/m, more than 100 times that measured in silicate liquids at low pressure and temperature. The magnetic Reynolds number computed from our results exceeds the threshold for dynamo activity and the magnetic field strength is similar to that observed in the Archean paleomagnetic record. We therefore conclude that the Archean field was produced by the basal magma ocean.

54 ENVIRONMENTAL SCIENCES↗