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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

InteraChem: Virtual Reality Visualizer for Reactive Interactive Molecular Dynamics

Interactive molecular dynamics in virtual reality (IMD-VR) simulations provide a digital molecular playground for students as an alternative or complement to traditional molecular modeling kits or 2D illustrations. Previous IMD-VR studies have used molecular mechanics to enable simulations of macromolecules such as proteins and nanostructures for the classroom setting with considerable success. Here, we present the InteraChem molecular visualizer, intended for reactive IMD-VR simulation using semiempirical and ab initio methods. InteraChem visualizes not only the molecular geometry but also (1) isosurfaces such as molecular orbitals and electrostatic potentials and (2) two-dimensional graphs of time-varying simulation quantities such as kinetic/potential energy, internal coordinates, and user-applied force. Additionally, InteraChem employs speech recognition to facilitate user interaction and introduces a novel “atom happiness” visualization using emojis to indicate the energetic feasibility of a particular bonding arrangement. Furthermore, we include a set of accompanying exercises that we have used to teach chemical reactivity in small molecular systems.

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

I ntera C hem : Exploring Excited States in Virtual Reality with Ab Initio Interactive Molecular Dynamics

InteraChem is an ab initio interactive molecular dynamics (AI-IMD) visualizer that leverages recent advances in virtual reality hardware and software, as well as the graphical processing unit (GPU)-accelerated TeraChem electronic structure package, in order to render quantum chemistry in real time. We introduce the exploration of electronically excited states via AI-IMD using the floating occupation molecular orbital-complete active space configuration interaction method. The optimization tools in InteraChem enable identification of excited state minima as well as minimum energy conical intersections for further characterization of excited state chemistry in small- to medium-sized systems. We demonstrate that finite-temperature Hartree–Fock theory is an efficient method to perform ground state AI-IMD. InteraChem allows users to track electronic properties such as molecular orbitals and bond order in real time, resulting in an interactive visualization tool that aids in the interpretation of excited state chemistry data and makes quantum chemistry more accessible for both research and educational purposes.

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

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2026

Long-Range Fit: A Software Package for the Representation and Study of Long-Range Molecular Interactions

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions─with electrostatic, induction, and dispersion as the main components─play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via a multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed long-range-fit (LRF), an interactive and user-friendly software package designed to automate the generation and fitting of long-range interaction terms for arbitrary molecules in nondegenerate (ground or excited) electronic states. We have derived and implemented all terms up to 15th order, without approximations, via a spherical tensor representation, with symmetry adaptation to all molecular point-group symmetries. The resulting potential energy surface is compatible with most representations of the close interaction region.

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

Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions

A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.

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

Molecular interactions in short-chain perfluoroalkyl carboxylic acids and aqueous solutions

The presence of short-chain per- and polyfluoroalkyl substances in water poses a major health and environmental challenge. Here, we have performed high-energy small- and wide-angle X-ray scattering measurements on CF 3 [CF 2 ] n COOH (where n = 1, 2, 3 represents the chain length) and their aqueous solutions at 10% mole concentrations to characterize their molecular interactions at the atomic and nanometer length scales. The experimental wide-angle structure factors have been modelled using Empirical Potential Structural Refinement. The oxygen–oxygen partial X-ray pair distribution functions show that the coordination number between the hydroxyl oxygen on the acid and surrounding oxygen water molecules increases significantly with acid chain length, rising from 3.2 for n = 1 to 4.1 for n = 3. The small-angle scattering is dominated by a sharp, high-intensity peak at Q 1 ~ 0.2 Å -1 and a smaller peak at Q 2 = 1.2 Å -1 for n = 3, both of which decrease with decreasing chain length. The Q 2 peak is attributed to groups of adjacent non-bonded acid molecules, and Q 1 has contributions from both correlations between acid molecules and water–water interactions. In all cases, the models show nanoscale aggregation occurs in the form of denser channels of winding hydrogen-bonded chains, approximately 20 water molecules in length, surrounding clusters of acid molecules.

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

Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles

The aldol reaction of p-nitrobenzaldehyde in amino-catalyzed mesoporous silica nanoparticles (MSN) has revealed varying catalytic activity with the size of the pores of MSN. The pore size dependence related to the reactivity indicates that the diffusion process is important. A detailed molecular-level analysis for understanding diffusion requires assessment of the noncovalent interactions of the molecular species involved in the aldol reaction with each other, with the solvent, and with key functional groups on the pore surface. Such an analysis is presented here based upon the effective fragment potential (EFP). The EFP method can calculate the intermolecular interactions, decomposed into Coulomb, polarization, dispersion, exchange-repulsion, and charge-transfer interactions. In this study, the potential energy surfaces corresponding to each intermolecular interaction are analyzed for homo- and hetero-dimers with various configurations. The monomers that compose dimers are five molecules such as p-nitrobenzaldehyde, acetone, n-hexane, propylamine, and silanol. The results illustrate that the dispersion interaction is crucial in most dimers.

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

Roles of kaolinite-oil-gas molecular interactions in hydrogen storage within depleted reservoirs

Hydrogen is a clean alternative to fossil fuels, emitting only water vapor during combustion. In a future hydrogen economy, large-scale storage will be an important component of the supply chain. Due to its low volumetric density, conventional surface storage methods are inadequate. Underground hydrogen storage (UHS) offers a viable solution, enabling the storage of millions of cubic meters. Among potential geological sites, including salt caverns, aquifers, and depleted gas reservoirs, depleted oil reservoirs show promise. Studying hydrogen interactions with residual oil and reservoir minerals is vital for understanding the properties of hydrogen and the reservoir post-injection. In this work, we employed molecular dynamics simulations to gain molecular-level insights into these interactions. We investigated hydrogen dissolution in oil, adsorption at kaolinite/oil interfaces, the role of CO 2 as a cushion gas, and the influence of kaolinite’s hydrophobicity on H 2 behavior. The main findings include: (1) hydrogen dissolves more in oil than in water, (2) the introduction of CO 2 suppresses hydrogen dissolution in oil and reduces the interfacial tension (IFT) between oil and gas, (3) CO 2 decreases H 2 partitioning near kaolinite surfaces due to its strong affinity for the hydrophilic gibbsite surface of kaolinite, and (4) CO 2 is more effective than H 2 in reducing IFT between kaolinite and the oil–gas mixture. These findings emphasize the effectiveness of CO 2 as a cushion gas and the important role of clay hydrophobicity in UHS, providing insights that are challenging to obtain experimentally.

08 HYDROGEN↗
DOE OSTI2022

Scanning the RBD-ACE2 molecular interactions in Omicron variant

The emergence of new SARS-CoV-2 variants poses a threat to the human population where it is difficult to assess the severity of a particular variant of the virus. Spike protein and specifically its receptor binding domain (RBD) which makes direct interaction with the ACE2 receptor of the human has shown prominent amino acid substitutions in most of the Variants of Concern. Here, in this work, by using all-atom molecular dynamics simulations we compare the interaction of Wild-type RBD/ACE2 receptor complex with that of the latest Omicron variant of the virus. We observed a very interesting diversification of the charge, dynamics and energetics of the protein complex formed upon mutations. These results would help us in understanding the molecular basis of binding of the Omicron variant with that of SARS-CoV-2 Wild-type.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Tuning Molecular Interactions between Peptoids and Substrates to Achieve Surface-Agnostic Coating

Achieving programmable and robust coatings that maintain functionality while adhering to various surface types with molecular-level tunability and programmable features remains challenging. In this study, we develop adaptable and stable surface-agnostic coatings (SACs) based on crystalline peptoid membranes by tuning interpeptoid and peptoid-substrate interactions. We utilize two complementary methods: (1) surfaceinduced assembly, where peptoid membranes form directly on substrates, and (2) depositing preformed peptoid crystalline membranes via an aqueous layer-by-layer (LbL) assembly technique. These strategies are applied to substrates with diverse surface chemistries and topographies, including mica, highly ordered pyrolytic graphite (HOPG), MoS 2 , sapphire, and porous membranes like porous alumina and polysulfide. Atomic force microscopy confirms the formation of peptoid coatings and reveals differences in assembly behavior across surfaces. Moisture vapor transport measurements serve as a proof-of-concept test for membrane continuity and tunable permeance. Together, these findings demonstrate the adaptability and programmability of peptoid-based SACs, enabling rational coating design on surfaces with diverse chemical and topographical features. Furthermore, this work opens pathways for using peptoid membranes as programmable surface modifiers in functional interfaces, protective coatings, and membrane platforms.

biomimetic polymers↗
DOE OSTI2024

Mapping TpPa-1 covalent organic framework (COF) molecular interactions in mixed solvents via atomistic modeling and experimental study

Complex solvent environments continue to limit the widespread adoption of organic solvent nanofiltration (OSN) in many chemical industry applications. In this paper we employ a commercially available covalent organic framework (COF), TpPa-1, and force field models to molecularly map separation performance of TpPa-1 membrane in mixed solvents. To minimize time and length scale mismatch between atomistic modeling and experiments, solvent permeance was normalized with water in modeling and experimental results to enable direct comparison. Model outputs, such as organic solvent permeance and solute rejection rate, matched well with filtration results. Since the atomistic models assume that all mass transfer is via through-pore transport, the discrepancies between modeling and experimental results provide insights on the effect of linear polymer defects, adsorption and interstitial mass transfer on polycrystalline COF membrane performance. In sum, force field models can serve as digital twins of COF membranes to simulate separation processes while capturing the effects of COF structure, chemistry, and crystallinity on membrane performance in complex organic solvent environments. Finally, this approach will provide insight into future COF design and synthesis for persisting separation challenges.

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

Molecular interactions that drive morphological and mechanical stabilities in organic solar cells

Morphological and mechanical stabilities of organic solar cells (OSCs) are of paramount importance to ensure long-lived devices. However, the fundamental drivers of these stability metrics and their competing relationship have yet to be well defined. Here, in this work, several high-performance polymers and small molecule acceptors (SMAs) are considered to assist in the development of a comprehensive view of the molecular drivers of, and interrelationships between, morphological and mechanical stabilities. We find that the SMAs drive much of the embrittlement and diffusion characteristics in the blend films. However, the heterointeraction of the SMA and polymer, probed through dynamic mechanical analysis, is a key contributing factor to the film toughness. The heterointeraction energy is ideally maximally negative (i.e., repulsive), deviating from the geometric mean of the homointeraction energy. These findings assist in introducing a framework to understand the active layer stability and highlight material properties that lead to morphologically stable and physically robust OSCs.

14 SOLAR ENERGY↗
DOE OSTI2026

Selectivity in gas–liquid interactions: Molecular beam scattering of CD 4 and ND 3 from an aqueous flat liquid jet

The dynamics of polar and nonpolar molecules colliding with an aqueous surface are characterized by scattering molecular beams of deuterated methane and ammonia, CD 4 and ND 3 (E i = 28.9 and 30.3 kJ mol −1 , respectively), from a flat liquid jet of cold salty water (8 m LiBr, 230 K). Translational energy distributions of scattered species collected as a function of collision geometry probe both impulsive scattering (IS) and thermal desorption (TD) mechanisms. Here, we find that CD 4 scattering is dominated by IS and exhibits a super-specular angular distribution. The fraction of TD scattering events is notably smaller for cold salty water than for dodecane, consistent with a higher free energy of solvation for CD 4 in the water jet. In contrast, no scattering signal is seen for ND 3 from the water jet, a result attributed to the high solubility and efficient protonation of ND 3 in liquid water. The IS channel for CD 4 was analyzed using a soft-sphere model, yielding a higher internal energy (E int ) and lower effective surface mass (m eff ) than was seen for Ne/water; the higher value of E int is attributed to rotational excitation of the scattered CD 4 . These findings demonstrate that the outcomes of a gas–liquid collision—scattering trajectory, surface adherence, and energy transfer—are directed at the molecular level by both the gaseous scatterer and liquid surface.

Foreman, Madison M. [University of California, Ber↗