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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 OSTI2025

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗
DOE OSTI2025

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

2023 Roadmap on molecular modelling of electrochemical energy materials

New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as empowered by machine learning techniques can help us to understand, control and design electrochemical energy materials at atomistic precision. Therefore, this roadmap, which is a collection of authoritative opinions, serves as a gateway for both the experts and the beginners to have a quick overview of the current status and corresponding challenges in molecular modelling of electrochemical energy materials for batteries, supercapacitors, CO 2 reduction reaction, and fuel cell applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Early Career Researcher Support for Foundations of Molecular Modeling and Simulation Conference

This project enabled 14 early career researchers, including graduate students and postdocs, to attend the 8th triennial conference on Foundations of Molecular Modeling and Simulation (FOMMS 2022), which took place in Delavan, WI (Lake Geneva area), from July 17 to 21, 2022. Molecular-level modeling and simulation, which serve as critical tools for advancing science and engineering in a myriad of applications, were at the forefront of discussions. These ranged from the design of new materials for various energy applications to insights into the interaction between drug molecules and protein receptors within the body.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Modeling Molecular Hydrogen in Low-metallicity Galaxies

We use a suite of hydrodynamics simulations of the interstellar medium (ISM) within a galactic disk, which includes radiative transfer, a nonequilibrium model of molecular hydrogen, and a realistic model for star formation and feedback, to study the structure of the ISM and H 2 abundance as a function of local ISM properties. We show that the star formation rate and structure of the ISM are sensitive to the metallicity of the gas with a progressively smoother density distribution with decreasing metallicity. In addition to the well-known trend of the H I–H 2 transition shifting to higher densities with decreasing metallicity, the maximum achieved molecular fraction in the ISM drops drastically at Z ≲ 0.2 Z ⊙ as the formation time of H 2 becomes much longer than a typical lifetime of dense regions of the ISM. We present accurate fitting formulae for both volumetric and projected ƒ H 2 measured on different scales as a function of gas metallicity, UV radiation field, and gas density. We show that when the formulae are applied to the patches in the simulated galaxy, the overall molecular gas mass is reproduced to better than a factor of ≲1.5 across the entire range of metallicities and scales. We also show that the presented fit is considerably more accurate than any of the previous ƒ H 2 models and fitting formulae in the low-metallicity regime. The fit can thus be used for modeling molecular gas in low-resolution simulations and semi-analytic models of galaxy formation in the dwarf and high-redshift regimes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Critical behavior in a chiral molecular model

Understanding the condensed-phase behavior of chiral molecules is important in biology as well as in a range of technological applications, such as the manufacture of pharmaceuticals. Here, we use molecular dynamics simulations to study a chiral four-site molecular model that exhibits a second-order symmetry-breaking phase transition from a supercritical racemic liquid into subcritical D-rich and L-rich liquids. We determine the infinite-size critical temperature using the fourth-order Binder cumulant, and we show that the finite-size scaling behavior of the order parameter is compatible with the 3D Ising universality class. We also study the spontaneous D-rich to L-rich transition at a slightly subcritical temperature of T = 0.985Tc, and our findings indicate that the free energy barrier for this transformation increases with system size as N2/3, where N is the number of molecules, consistent with a surface-dominated phenomenon. The critical behavior observed herein suggests a mechanism for chirality selection in which a liquid of chiral molecules spontaneously forms a phase enriched in one of the two enantiomers as the temperature is lowered below the critical point. Furthermore, the increasing free energy barrier with system size indicates that fluctuations between the L-rich and D-rich phases are suppressed as the size of the system increases, trapping it in one of the two enantiomerically enriched phases. Such a process could provide the basis for an alternative explanation for the origin of biological homochirality. We also conjecture the possibility of observing nucleation at subcritical temperatures under the action of a suitable chiral external field.

Chemistry↗
DOE OSTI2024

Molecular Models of Atomically Dispersed Uranium at MoS 2 Surfaces Reveal Cooperative Mechanism of Water Reduction

Single atoms of uranium supported on molybdenum sulfide surfaces (U@MoS 2 ) have been recently demonstrated to facilitate the hydrogen evolution reaction (HER) through electrocatalysis. Theoretical calculations have predicted uranium hydroxide moieties bound to edge-sulfur atoms of MoS 2 as a proposed transition state involved in the HER process. However, the isolation of relevant intermediates involved in this process remains a challenge, rendering mechanistic hypotheses unverified. The present work describes the isolation and characterization of a uranium-hydroxide intermediate on molybdenum sulfide surfaces using [(Cp* 3 Mo 3 S 4 )UCp*], a molecular model of a reduced uranium center supported at MoS 2 . Mechanistic investigations highlight the metalloligand cooperativity with uranium involved in the water activation pathway. The corresponding uranium-oxo analogue, [(Cp* 3 Mo 3 S 4 )Cp*U(═O)], was also accessed from the hydroxide cluster via hydrogen atom transfer and from [(Cp* 3 Mo 3 S 4 )UCp*] through an alternative direct oxygen atom transfer. These results provide an atomistic perspective on the reactivity of low-valent uranium at molybdenum sulfide surfaces toward water, modeling key intermediates associated with the HER of U@MoS 2 catalysts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model

We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Molecular Modeling of Surfactant Interaction on Phospholipid Bilayers Mimicking Corneal Epithelium

Surfactants found in consumer products can compromise eye corneal membrane integrity upon accidental exposure. Traditional in vitro and in vivo approaches to evaluate membrane–surfactant interaction pose experimental limitations such as species variability, reproducibility, and most often do not provide the overall picture. These limitations motivate the use of in silico models to study phenomena like cellular disruption assays caused by surfactants at the molecular scale. In this work, coarse-grained molecular dynamics simulations have been employed to investigate how nonionic alcohol ethoxylate (AE) and anionic surfactant alcohol ethoxy sulfate (AES) interact with lipid bilayer liposomes that mimic corneal epithelial cell membranes. The spherical liposome is composed of 1,2-dihexadecanoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-di(9Z-octadecenoyl)-sn-glycero-3-phosphoethanolamine (DOPE), 1,2-di(9Z-octadecenoyl)-sn-glycero-3-phospho-l-serine (DOPS), and cholesterol, resembling the composition of the corneal epithelial cells’ membrane bilayer. The simulation consisted of varying degrees of representative surfactant compositions and two initial types of surfactant configurations within or outside the liposome. Our results reveal that both surfactants induce outer leaflet bulging, agreeing with membrane solubilization models. The more highly ethoxylated surfactant, AE, caused more consistent inner leaflet disruption than AES, resulting in significantly more water permeation and membrane thinning. In addition, both surfactants increase the lateral diffusion of lipids within the membrane layers, with higher ethoxylated AE showing a stronger effect than AES. This study demonstrates how surfactant structure and localization influence bilayer membrane integrity, offering mechanistic insights into the irritation potential, thus guiding the rational design of effective surfactant-based formulations.

Lipids↗
DOE OSTI2023

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On-lattice kinetic Monte Carlo approaches for modeling molecular anisotropy in resveratrol crystallization

Stilbenes are a class of organic compounds with broad-ranging pharmaceutical and agricultural applications, which are typically isolated and purified through recrystallization. We are motivated by reducing experimental waste and optimizing yield via developing predictive simulations for processing-dependent crystal morphologies. Using resveratrol as a model stilbene system, we have developed an approach for simulating crystallization with molecular resolution using on-lattice kinetic Monte Carlo. In this work, we highlight modifications to the Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) software package, which were essential to this application. Key enhancements include the incorporation of non-orthogonal cell shapes and monomer anisotropy approximations using bound hard spheres. This new SPPARKS application has been applied to resveratrol with attachment energy libraries obtained from density functional theory, resulting in excellent agreement with experimental morphology prediction.

crystallization↗
DOE OSTI2026

A High-Fidelity Molecular Model of the Cu(111) Repeating Unit

Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.

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

Molecular model of TFIIH recruitment to the transcription-coupled repair machinery

Transcription-coupled repair (TCR) is a vital nucleotide excision repair sub-pathway that removes DNA lesions from actively transcribed DNA strands. Binding of CSB to lesion-stalled RNA Polymerase II (Pol II) initiates TCR by triggering the recruitment of downstream repair factors. Yet it remains unknown how transcription factor IIH (TFIIH) is recruited to the intact TCR complex. Combining existing structural data with AlphaFold predictions, we build an integrative model of the initial TFIIH-bound TCR complex. We show how TFIIH can be first recruited in an open repair-inhibited conformation, which requires subsequent CAK module removal and conformational closure to process damaged DNA. In our model, CSB, CSA, UVSSA, elongation factor 1 (ELOF1), and specific Pol II and UVSSA-bound ubiquitin moieties come together to provide interaction interfaces needed for TFIIH recruitment. STK19 acts as a linchpin of the assembly, orienting the incoming TFIIH and bridging Pol II to core TCR factors and DNA. Molecular simulations of the TCR-associated CRL4CSA ubiquitin ligase complex unveil the interplay of segmental DDB1 flexibility, continuous Cullin4A flexibility, and the key role of ELOF1 for Pol II ubiquitination that enables TCR. Collectively, these findings elucidate the coordinated assembly of repair proteins in early TCR.

Paul, Tanmoy↗
DOE OSTI2023

EXPERIMENTAL AND MODELING STUDY OF MOLECULAR TRANSPORT PHENOMENA IN COMPLEX LIQUID MIXTURES USING COVALENT ORGANIC FRAMEWORK MEMBRANES

Currently, 10-15% of the world’s energy is consumed by chemical separations, and more than 80% of that is used to purify organic liquids and recover rare earth elements and critical minerals. Membrane nanofiltration presents an energy-efficient, cost-effective, and eco-friendly alternative to current separation technologies. These complex liquid environments require high- performance, chemically-resistant membrane materials. Recently discovered Covalent Organic Frameworks (COFs) possess desirable properties as membrane materials for complex liquid separations. COFs are highly crystalline, chemically and thermally stable, with tunable size and charge. COFs, especially two-dimensional highly crystalline COFs, possess narrow pore-size distribution and controlled porous structures. Two-dimensional COFs are also resistant to swelling, another feature beneficial in complex liquid separations. Molecular interactions in complex liquid systems often dictate final membrane performance, resulting in a discrepancy between designed and apparent COF properties. Understanding and resolving this discrepancy is critical in utilizing COF membranes as a viable alternative to energy-intensive separations. The primary objective of this thesis was to use a commercially available COF TpPa-1 as a platform to investigate how mixed solvent environment affects COF membrane performance via experimental and molecular modeling studies. Specifically, the effects of solution pH, solvent- solvent-solute interactions in mixed solvents, and COF chemistry were carefully examined on apparent TpPa-1 pore size and permeability and targeted solute rejection of COF membranes for neat and mixed solvents. Experimental COF filtration performance was compared and corroborated with modeling predication. Findings from this study will provide guidance for future COF design, synthesis, and desired functional COF membrane performance.

Barnes, Anastasia↗
DOE OSTI2024

Development of Transformational Solvents for CO2 Separations

The primary objective of this CRADA activity is to use a combined molecular modeling and experimental validation approach to refine and develop transformational solvents for carbon capture. PNNL’s role on this project is currently funded by the Department of Energy’s (DOE) Office of Fossil Energy (OFE). PNNL is developing advanced molecular modeling based on their CO2BOLs solvent platform as a demonstration solvent for the activity; the model was developed and compared against measured data for CO2BOL derivatives. Here, a CRADA with PNNL and GE will leverage their current molecular models and apply them to solvent classes that operate on carbamate chemistry, specifically GE’s aminosilicone solvent class. The molecular models will be used to predict physical and thermodynamic properties, such as viscosity, as a means to predict advanced formulations with reduced viscosity compared to current aminosilicone derivatives, enabling optimized thermodynamic and kinetic metrics for economical carbon capture for this class of materials. Together, PNNL and GE will develop a comprehensive means of linking molecular modeling parameters to intermediate physical properties as a means to improve solvent performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗