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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 OSTI2022

Hydration Free Energies of Polypeptides from Popular Implicit Solvent Models versus All-Atom Simulation Results Based on Molecular Quasichemical Theory

Calculating the hydration free energy of a macromolecule in all-atom simulations has long remained a challenge, necessitating the use of models wherein the effect of the solvent is captured without explicit account of solvent degrees of freedom. This situation has changed with developments in the molecular quasi-chemical theory (QCT)-an approach that enables calculation of the hydration free energy of macromolecules within all-atom simulations at the same resolution as is possible for small molecular solutes. The theory also provides a rigorous and physically transparent framework to conceptualize and model interactions in molecular solutions and thus provides a convenient framework to investigate the assumptions in implicit solvent models. In this study, we compare the results using molecular QCT versus predictions from EEF1, ABSINTH, and GB/SA implicit solvent models for polyglycine and polyalanine solutes covering a range of chain lengths and conformations. The hydration free energies or the differences in hydration free energies between conformers obtained from the implicit solvent models do not agree with explicit solvent results, with the deviations being largest for the group additive EEF1 and ABSINTH models. GB/SA does better in capturing the qualitative trends seen in explicit solvent results. Finally, analysis founded on QCT reveals the critical importance of the cooperativity of hydration that is inherent in the hydrophilic and hydrophobic contributions to hydration-physics that is not well captured in additive models but somewhat better accounted for by means of a dielectric in the GB/SA approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

All-Atom Simulation of 3D Hot Spot Formation in Shocked TATB Explosive

TATB is an insensitive high explosive (IHE) critical to the stockpile that is challenging to model at the continuum scale. Advanced detonation models in the Cheetah high explosive chemistry code require validation though subscale simulations. High explosive initiation is determined by micron-scale physics of hot spots formed a shock-collapsed pores. Pore sizes between 100 nm and 1 μm are believed to be the most important for determining the shock sensitivity of TATB. This range of pore sizes is difficult to access at the atomic scale through allatom molecular dynamics (MD) simulations, even with Sierra-class computers. Quasi-2D simulations are widely used and allow much larger pore sizes (up to 400 nm) to be studied, but the applicability of 2D simulations to the actual 3D pore response is not understood. Resolving these uncertainties through “full physics” MD modeling is key for generalizing, parameterizing, and validating the kinds of continuum models used to inform design, safety, and performance. This work was a continuation of FY20 efforts pushing simulations to full 3D with the largest-ever all-atom simulations of an explosive. These were the first all-atom full-3D simulations of large hot spots thought to govern explosive detonation and required over a billion atoms. Simulations were performed using LAMMPS, an open SNL science code. MD explosive models present unique challenges, even for established codes such as LAMMPS. Their model forms are more complex than typical models for metals, while simulating high temperature-pressure conditions is demanding and increases computational cost. Scaling problems in GPU-enabled MD algorithms initially limited simulations to <100 million atoms but were resolved through collaboration with SNL. An overall 24x speedup was obtained relative to CPU machines. Specialized analysis of these simulations required a bottom-up refactoring and algorithm parallelization of in-house codes and application of computer vision algorithms to extract meaningful information.

36 MATERIALS SCIENCE↗
DOE OSTI2021

ATOMIC Simulations and Experimental Data for CaCO3 Mixtures

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [1] and are used to develop a statistical characterization of matrix effects. Our overall suite of simulations includes contains several sets of simulations: training and validation sets of simulations for three and four element mixtures of calcium, carbon, oxygen, and nitrogen (included to account for atmosphere) along with simulations of the individual elements. The 4-element simulations include the mixture of all four elements mentioned and for each of the four individual elements. The 3-element simulations include output for the mixture of calcium, carbon, oxygen and for these three individual elements. The training data were produced using a 600-run design, shown in Figure 1, that varies input parameters temperature (T), electron density (Ne), and proportion of the elements calcium, carbon, oxygen, and nitrogen (Ca; C; O; N) for the 4 element output. The 3-element output includes all parameters except for the proportion of nitrogen. The element proportions (all the variables but T and Ne) sum to one and are unused in the single-element simulations. The validation data was produced with a 80-run design shown in Figure 2. The training and validation simulation outputs for the 4-element simulations for the mixture and for the single element calcium are shown as sample simulations in Figures 3 and 4 respectively. The simulations produce spectra over a range of 190nm - 950nm that roughly mimics the range collected by the SciAps Z-300 LIBS instrument that was used for the experimental data. The measured spectra for a CaCO3 (which may include contribution from Earth's atmosphere) in the experiment is shown in in Figure 5. All files are kept in directories whose names indicate the elemental composition (CaCO3, Ca, C, O, or N), number of elements (3 or 4), and purpose (training, which is not labeled in the file name, or validation) with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file. [1] J Colgan, EJ Judge, DP Kilcrease, and JE Barefield II. Ab-initio modeling of an iron laser-induced plasma: Comparison between theoretical and experimental atomic emission spectra. Spectrochimica Acta Part B: Atomic Spectroscopy, 97:65{73}, 2014.

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

ATOMIC Simulations and Experimental Data for Sodium and Copper Mixtures

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [1]. Our overall suite of simulations contains 12 sets of simulations: training and validation sets of simulations for each of two resolutions of each of sodium, copper, and mixtures of the two. The training data were produced using a 500-run design that varies input parameters temperature (T), electron density (Ne), proportion of sodium (pNa), and proportion of copper (pCu). The latter two variables sum to one and are unused in the single-element simulations. The validation data was produced with a 25-run design. The coarse simulations produce spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. The fine resolution simulations produce spectra over a range of 550nm to 600nm and were produced to mimic the included experimental results. The experimental results cover four mixtures of sodium and copper. All data sets are kept in zip files whose names indicate the elemental composition (NaCu, Na, or Cu), resolution (coarse or fine), and purpose (training or validation) with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file. See attached abstract for figures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

ATOMIC Simulations and Experimental Data for Basalt-like Compounds

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [-7,-4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Atomic Diffusion, Segregation, and Grain Boundary Migration in Nickel-Based Alloys from Molecular Dynamics Simulations

Grain boundary diffusion and metal mobility in alloys control material performance in many applications and yet remain poorly understood at a mechanistic level. With advances in accessible time and length scales for computational molecular simulations, and recent force field developments, we now possess tools to help unravel those mechanisms. Using large-scale molecular dynamics simulations, here we examined vacancy-mediated diffusion processes in Ni-5Cr alloy with low and high-energy grain boundaries. We show that atomic diffusion inside the grain boundary plane is about four times higher than bulk diffusion, at any temperature, and exhibits a typical Arrhenius behavior with a very small energy barrier (0~.8 eV for Cr and 0.7 eV for Ni within 1300-1600 K). Additionally, the fastest diffusing species inverts; Cr diffusion was faster than Ni in the bulk but slower in the grain boundaries. This is attributed to the creation of high cohesive energy clusters of Cr at the grain boundary. Grain boundary migration was also observed to be temperature dependent and appears to be two times higher in the 5% Cr alloy than in pure Ni, highlighting the important role of the alloying element on grain boundary motion.

Simonnin, Pauline GN↗
DOE OSTI2023

Simulating Atomic Dark Matter in Milky Way Analogs

Dark sector theories naturally lead to multicomponent scenarios for dark matter where a subcomponent can dissipate energy through self-interactions, allowing it to efficiently cool inside galaxies. We present the first cosmological hydrodynamical simulations of Milky Way analogs where the majority of dark matter is collisionless cold dark matter (CDM) but a subcomponent (6%) is strongly dissipative minimal atomic dark matter (ADM). The simulations, implemented in GIZMO and utilizing FIRE-2 galaxy formation physics to model the standard baryonic sector, demonstrate that the addition of even a small fraction of dissipative dark matter can significantly impact galactic evolution despite being consistent with current cosmological constraints. We show that ADM gas with roughly standard model–like masses and couplings can cool to form a rotating “dark disk” with angular momentum closely aligned with the visible stellar disk. The morphology of the disk depends sensitively on the parameters of the ADM model, which affect the cooling rates in the dark sector. The majority of the ADM gas gravitationally collapses into dark “clumps” (regions of black hole or mirror star formation), which form a prominent bulge and a rotating thick disk in the central galaxy. These clumps form early and quickly sink to the inner ∼kiloparsec of the galaxy, affecting the galaxy’s star formation history and present-day baryonic and CDM distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Comparing the Expense and Accuracy of Methods to Simulate Atomic Vibrations in Rubrene

Atomic vibrations can inform about materials properties from hole transport in organic semiconductors to correlated disorder in metal–organic frameworks. Currently, there are several methods for predicting these vibrations using simulations, but the accuracy–efficiency tradeoffs have not been examined in depth. In this work, rubrene is used as a model system to predict atomic vibrational properties using six different simulation methods: density functional theory, density functional tight binding, density functional tight binding with a Chebyshev polynomial-based correction, a trained machine learning model, a pretrained machine learning model called ANI-1, and a classical forcefield model. The accuracy of each method is evaluated by comparison to the experimental inelastic neutron scattering spectrum. All methods discussed here show some accuracy across a wide energy region, though the Chebyshev-corrected tight-binding method showed the optimal combination of high accuracy with low expense. We then offer broad simulation guidelines to yield efficient, accurate results for inelastic neutron scattering spectrum prediction.

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

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. In this work, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (~98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ~1.5 million atoms is discussed in the context of MuMMI.

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

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

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

All-Atom Simulations Uncover Structural and Dynamical Properties of STING Proteins in the Membrane System

Recent studies have shown that the stimulator of interferon gene (STING) protein plays a central role in the immune system by facilitating the production of type I interferons in cells. The STING signaling pathway is also a prominent activator of cancer-killing T cells that initiate a powerful adaptive immune response. Since biomolecular signaling pathways are complicated and not easily identified through traditional experiments, molecular dynamics (MD) has often been used to study structural and dynamical responses of biological pathways. In this work, we carried out MD simulations for full-length chicken and human STING (chSTING and hSTING) proteins. Specifically, we investigated ligand-bound closed (holo) and ligand-unbound open (apo) forms of STING in the membrane system by comparing their conformational and dynamical differences. Our research provides clues for understanding the mechanism of the STING signaling pathway by uncovering detailed insights for the examined systems: the residues from each chain in the binding pocket are strongly correlated to one another in the open STING structure compared with those in the closed STING structure. Ligand-bound closed STING displays ~174° rotation of the ligand-binding domain (LBD) relative to the open STING structure. The dynamical analysis of residue Cys148 located in the linker region of hSTING does not support the earlier hypothesis that Cys148 can form disulfide bonds between adjacent STING dimers. We also demonstrate that using the full-length proteins is critical, since the MD simulations of the LBD portion alone cannot properly describe the global conformational properties of STING.

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

Optimization of Ag Electrocatalyst Performance for CO2 to CO Conversion: Pairing Atomic Simulations with Experiments

Density-functional theory- based calculations that complement our series of experimental efforts on optimizing Ag electrocatalyst performance for CO2 to CO conversion were presented. Three key findings are drawn out from the combined UHV surface science, STM and electrochemical measurements: (1) Using a series of Ag nanoparticles with 2-6 nm average diameters, CO2 reduction reaction (CO2RR) activity increases, with particle between 2 nm and ∼4 nm demonstrating the highest combination of activity and selectivity; (2) Electronic metal−support interactions (EMSIs) between Ag and C dramatically improve CO2RR performance as evidenced by a scaling relationship between particle size and the relative Ag−C EMSIs strength, which improves the CO2-to-CO Faradaic efficiency of sub-2 nm Ag particles from 2 to ∼100% and increases the CO turnover frequency ∼15-fold compared with similarly sized bare Ag particles; (3) The performance Ag electrocatalysts is improved when supported on S-doped C materials. Computational modeling of 1−10 nm Ag particles predicts a nearly identical size-dependent trend with maximum CO2RR activity predicted for 3.7nm particles. The calculations support the promotional effect of C materials, showing a large charge transfer of 1.02 e from Ag clusters to defective C and a 0.41 eV less endergonic step of forming COOH intermediate on Ag/defective-C compared to the Ag/C system. Calculations indicate a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, consistent with experiments.

CO2 utilization↗
DOE OSTI2022

Modeling of deposit formation in mesoporous substrates via atomic layer deposition: Insights from pore‐scale simulation

Atomic layer deposition (ALD) has been a promising technique in fabricating membranes and tuning their properties with a precision at the atomic level. Fabrication of zeolitic imidazolate framework (ZIF) membranes using the ligand-induced permselectivation (LIPS) method starts with the formation of an oxide in a mesoporous substrate by ALD and is followed by the transformation of this oxide to ZIF using imidazolate vapor treatment. The objective of the ALD step is to block the mesopores with a thin deposit, that is, one with small penetration depth and small thickness on the top surface of the substrate. Unlike typical ALD on nonporous substrates, where all available sites react per ALD cycle, thin deposit formation in a mesoporous substrate requires that only a small fraction of the available deposition sites (i.e., close to the substrate surface) is subjected to ALD. Consequently, reactant dosing and duration of pulses are important process variables which, together with diffusion and reaction kinetics determine the deposit structure. Quantitative understanding of the interplay of these variables and phenomena can enable the rational design of ALD within mesoporous substrates. Here, we extend our earlier modeling effort considering the coexistence of ALD both inside the pores and on the external surface of the substrate. Finite-volume based models were developed and validated to simulate the two distinct modes of deposition cycle by cycle. The total mass uptake of the substrate with ALD cycles can be predicted using the combined surface deposition and pore reaction–diffusion models as affirmed by in situ quartz crystal microbalance experimental data. The ALD reactor model combined with the deposition model can accurately capture the number of ALD cycles needed to block the pores of the substrate. Based on the model, we designed a modified ALD process and examined the performance of the corresponding LIPS membranes. Furthermore, the present modeling work provides a new understanding of the deposit formation via ALD within mesoporous substrates for a variety of membrane applications.

atomic layer deposition↗