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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 OSTI2013

Ab Initio Study of Molecular Interactions in Cellulose Iα

Biomass recalcitrance, the resistance of cellulosic biomass to degradation, is due in part to the stability of the hydrogen bond network and stacking forces between the polysaccharide chains in cellulose microfibers. In this paper, the fragment molecular orbital (FMO) method at the correlated Møller–Plesset second order perturbation level of theory was used on a model of the crystalline cellulose Iα core with a total of 144 glucose units. These computations show that the intersheet chain interactions are stronger than the intrasheet chain interactions for the crystalline structure, while they are more similar to each other for a relaxed structure. An FMO chain pair interaction energy decomposition analysis for both the crystal and relaxed structures reveals an intricate interplay between electrostatic, dispersion, charge transfer, and exchange repulsion effects. The role of the primary alcohol groups in stabilizing the interchain hydrogen bond network in the inner sheet of the crystal and relaxed structures of cellulose Iα, where edge effects are absent, was analyzed. Finally, the maximum attractive intrasheet interaction is observed for the GT-TG residue pair with one intrasheet hydrogen bond, suggesting that the relative orientation of the residues is as important as the hydrogen bond network in strengthening the interaction between the residues.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Molecular interactions with ice: Molecular embedding, adsorption, detection, and release

The interaction of atomic and molecular species with water and ice is of fundamental importance for chemistry. In a previous series of publications, we demonstrated that translational energy activates the embedding of Xe and Kr atoms in the near surface region of ice surfaces. In this paper, we show that inert molecular species may be absorbed in a similar fashion. We also revisit Xe embedding, and further probe the nature of the absorption into the selvedge. CF{sub 4} molecules with high translational energies (≥3 eV) were observed to embed in amorphous solid water. Just as with Xe, the initial adsorption rate is strongly activated by translational energy, but the CF{sub 4} embedding probability is much less than for Xe. In addition, a larger molecule, SF{sub 6}, did not embed at the same translational energies that both CF{sub 4} and Xe embedded. The embedding rate for a given energy thus goes in the order Xe > CF{sub 4} > SF{sub 6}. We do not have as much data for Kr, but it appears to have a rate that is between that of Xe and CF{sub 4}. Tentatively, this order suggests that for Xe and CF{sub 4}, which have similar van der Waals radii, the momentum is the key factor in determining whether the incident atom or molecule can penetrate deeply enough below the surface to embed. The more massive SF{sub 6} molecule also has a larger van der Waals radius, which appears to prevent it from stably embedding in the selvedge. We also determined that the maximum depth of embedding is less than the equivalent of four layers of hexagonal ice, while some of the atoms just below the ice surface can escape before ice desorption begins. These results show that energetic ballistic embedding in ice is a general phenomenon, and represents a significant new channel by which incident species can be trapped under conditions where they would otherwise not be bound stably as surface adsorbates. These findings have implications for many fields including environmental science, trace gas collection and release, and the chemical composition of astrophysical icy bodies in space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Protein–Mineral Interactions: Molecular Dynamics Simulations Capture Importance of Variations in Mineral Surface Composition and Structure

Molecular dynamics simulations, conventional and metadynamics, were performed to determine the interaction of model protein Gb1 over kaolinite (001), Na+-montmorillonite (001), Ca2+-montmorillonite (001), goethite (100), and Na+-birnessite (001) mineral surfaces. Gb1, a small (56 residue) protein with a well-characterized solution-state nuclear magnetic resonance (NMR) structure and having α-helix, four-fold β-sheet, and hydrophobic core features, is used as a model protein to study protein soil mineral interactions and gain insights on structural changes and potential degradation of protein. From our simulations, we observe little change to the hydrated Gb1 structure over the kaolinite, montmorillonite, and goethite surfaces relative to its solvated structure without these mineral surfaces present. Over the Na+-birnessite basal surface, however, the Gb1 structure is highly disturbed as a result of interaction with this birnessite surface. Unraveling of the Gb1 β-sheet at specific turns and a partial unraveling of the α-helix is observed over birnessite, which suggests specific vulnerable residue sites for oxidation or hydrolysis possibly leading to fragmentation.

Environmental Molecular Sciences Laboratory↗
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 OSTI2016

Dependence of the rate of LiF ion pairing on the description of molecular interaction

We present an analysis of the dynamics of ion-pairing of Lithium Fluoride (LiF) in aqueous solvent using both detailed molecular simulation as well as reduced models within a Gener- alized Langevin Equation (GLE) framework. We explored the sensitivity of the ion-pairing phenomena to the details of descriptions of molecular interaction, comparing two empirical potentials to explicit quantum based density functional theory. We find quantitative differences in the potentials of mean force for ion-pairing as well as time dependent frictions that lead to variations in the rate constant and reactive flux correlation functions. These details reflect differences in solvent response to ion-pairing between different representations of molecular interaction and influence anharmonicity of the dynamic response. We find that the short time anharmonic response is recovered with a GLE parameterization. Recovery of the details of long time response may require extensions to the reduced model. We show that the utility of using a reduced model leads to a straight forward application of variational transition state the- ory concepts to the condensed phase system. The significance of this is reflected in the analysis of committor distributions and the variation of planar hypersurfaces, leading to an improved understanding of factors that determine the rate of LiF ion-pairing. CJM and GKS are supported by the U.S. Department of Energy‘s (DOE) Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest Na- tional Laboratory (PNNL) is operated for the Department of Energy by Battelle. MDB is grateful for the support of Laboratory Directed Research and Development funding under the auspices of PNNL’s Laboratory Initiative Materials Synthesis and Simulation across Scales (MS3). Additional computing resources were generously allocated by PNNL’s Institutional Computing program. EP acknowledges support from PNNL’s Alternate Sponsored Fellowship program and IMPRS Dres- den.Support to P.J. from the Czech Science Foundation (grant P208/12/G016) and the Academy of Sciences (Praemium Academie award) is gratefully acknowledged.

Pluharova, Eva↗
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 OSTI2019

Molecular interactions of phospholipid monolayers with a model phospholipase

The intrinsic overexpression of secretory phospholipase A2 (sPLA 2 ) in various pro-inflammatory diseases and cancers has the potential to be exploited as a therapeutic strategy for diagnostics and treatment. To explore this potential and advance our knowledge of the role of sPLA 2 in related diseases, it is necessary to systematically investigate the molecular interaction of the enzyme with lipids. By employing a Langmuir trough integrated with X-ray reflectivity and grazing incidence X-ray diffraction techniques, this study examined the molecular packing structure of 1,2-palmitoyl- sn-glycero -3-phosphocholine (DPPC) films before and after enzyme adsorption and enzyme-catalyzed degradation. Molecular interaction of sPLA 2 (from bee venom) with the DPPC monolayer exhibited Ca 2+ dependence. DPPC molecules at the interface without Ca 2+ retained a monolayer organization; upon adsorption of sPLA 2 to the monolayer the packing became tighter. In contrast, sPLA 2 -catalyzed degradation of DPPC occurred in the presence of Ca 2+ , leading to disruption of the ordered monolayer structure of DPPC. Further, the interfacial film became a mixture of highly ordered multilayer domains of palmitic acid (PA) and loosely packed monolayer phase of 1-palmitoyl-2-hydroxy- sn-glycero -3-phosphocholine (lysoPC) that potentially contained the remaining un-degraded DPPC. The redistribution of lipid degradation products into the third dimension, which produced multilayer PA domains, damaged the structural integrity of the original lipid layer and may explain the bursting of liposomes observed in other studies after a latency period of mixing liposomes with sPLA 2 . A quantitative understanding of the lipid packing and lipid-enzyme interaction provides an intuitive means of designing and optimizing lipid-related drug delivery systems.

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.

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