SEARCH · Search NASA

Results for “MD simulation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture

Abstract Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li 7 P 3 S 11 , a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

Chemistry↗

DOE OSTI2021

Lessons from combined experimental and theoretical examination of the FTIR and 2D-IR spectroelectrochemistry of the amide I region of cytochrome c</em

Amide I difference spectroscopy is widely used to investigate protein function and structure changes. In this article, we show that the common approach of assigning features in amide I difference signals to distinct secondary structure elements in many cases may not be justified. Evidence comes from Fourier transform infrared (FTIR) and 2D-IR spectroelectrochemistry of the protein cytochrome c in the amide I range, in combination with computational spectroscopy based on molecular dynamics (MD) simulations. This combination reveals that each secondary structure unit, such as an alpha-helix or a beta-sheet, exhibits broad overlapping contributions, usually spanning a large part of the amide I region, which in the case of difference absorption experiments (such as in FTIR spectroelectrochemistry) may lead to intensity-compensating and even sign-changing contributions. We use cytochrome c as the test case, as this small electron-transferring redox-active protein contains different kinds of secondary structure units. Upon switching its redox-state, the protein exhibits a different charge distribution while largely retaining its structural scaffold. Our theoretical analysis suggests that the change in charge distribution contributes to the spectral changes and that structural changes are small. However, in order to confidently interpret FTIR amide I difference signals in cytochrome c and proteins in general, MD simulations in combination with additional experimental approaches such as isotope labeling, the insertion of infrared labels to selectively probe local structural elements will be required. In case these data are not available, a critical assessment of previous interpretations of protein amide I 1D- and 2D-IR difference spectroscopy data is warranted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Relaxation Dynamics and Ion Conduction of Poly(Ethylene Carbonate/Ethylene Oxide) Copolymer-Based Electrolytes

Poly(ethylene carbonate/ethylene oxide) P(EC/EO) copolymer was synthesized from EC monomer as a new matrix component of solid polymer electrolytes (SPEs), and the correlation between polymer dynamics and ionic conductivity in the P(EC/EO)-based SPEs at various lithium salt weight fractions (w Li ) was investigated by dielectric spectroscopy, rheology, and molecular dynamics (MD) simulations. With the addition of lithium salt, the molecular motions at various scales (i.e., from local to segmental and global motion scales) were found to change as follows: (i) the local motion of P(EC/EO) was slightly accelerated, and at w Li ≥ 0.22, it was separated into two relaxation modes, one faster and the other slower than that of P(EC/EO), (ii) the segmental motion of P(EC/EO) became significantly slower with the addition of lithium salt, and (iii) the global terminal relaxation became slightly slower with the increase of w Li . Thus, the motion of P(EC/EO) at various scales in SPEs changed with different trends with increasing lithium salt. It was also found that the temperature dependence of the ionic conductivity was described by a Vogel–Fulcher–Tammann-type function, which was correlated with the segmental motion, as is known in other SPE systems. Furthermore, from MD simulations, lithium ions are coordinated with the EC units more likely and with a closer distance than EO units in P(EC/EO), and the coordination number of oxygens around one lithium ion was estimated as 6–7 at the distance of 0.30 nm. Here, these results suggest that the coordination structure of the oxygens around the lithium ion is slightly disrupted due to the presence of EC units compared to the chelating structure of pure PEO electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Strongly Anisotropic Thermomechanical Response to Shock Wave Loading in Oriented Samples of the Triclinic Molecular Crystal 1,3,5-Triamino-2,4,6-trinitrobenzene

All-atom molecular dynamics (MD) simulations were used to study shock wave loading in oriented single crystals of the highly anisotropic triclinic molecular crystal 1,3,5-triamino-2,4,6-trinitrobenzene (TATB). The crystal structure consists of planar hydrogen-bonded sheets of individually planar TATB molecules that stack into graphitic-like layers. Shocks were studied for seven systematically prepared crystal orientations with limiting cases that correspond to shock propagation exactly perpendicular and exactly parallel to the graphitic-like layers. The simulations were performed for initially defect-free crystals using a reverse-ballistic configuration that generates explicit, supported shocks. Final longitudinal stress components are between ≈8.5 and ≈10.5 GPa for the 1.0 km s –1 impact speed studied. Orientation-dependent properties are reported including shock speeds, stresses, temperatures, compression ratios, and local material strain rates. Spatiotemporal maps of the temperature, stress tensor, material flow, and molecular orientations reveal complicated processes that arise for specific shock directions. Furthermore, the results indicate that TATB shock response is highly sensitive to crystal orientation, with significant qualitative differences for the time evolution of the stress tensor and temperature, elastic/inelastic compression response, defect formation and growth, critical von Mises stress, and strain rates during shock rise that span nearly an order of magnitude. A variety of inelastic deformation mechanisms are identified, ranging from crumpling of graphitic-like layers to dislocation-mediated plasticity to intense shear strain localization. To our knowledge, these are the first systematic MD simulations and analysis of explicit shock wave propagation along nontrivial crystal directions in a triclinic molecular crystal.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Integrating solvation shell structure in experimentally driven molecular dynamics using x-ray solution scattering data

In the past few decades, prediction of macromolecular structures beyond the native conformation has been aided by the development of molecular dynamics (MD) protocols aimed at exploration of the energetic landscape of proteins. Yet, the computed structures do not always agree with experimental observables, calling for further development of the MD strategies to bring the computations and experiments closer together. Here, we report a scalable, efficient MD simulation approach that incorporates an x-ray solution scattering signal as a driving force for the conformational search of stable structural configurations outside of the native basin. We further demonstrate the importance of inclusion of the hydration layer effect for a precise description of the processes involving large changes in the solvent exposed area, such as unfolding. Utilization of the graphics processing unit allows for an efficient all-atom calculation of scattering patterns on-the-fly, even for large biomolecules, resulting in a speed-up of the calculation of the associated driving force. The utility of the methodology is demonstrated on two model protein systems, the structural transition of lysine-, arginine-, ornithine-binding protein and the folding of deca-alanine. We discuss how the present approach will aid in the interpretation of dynamical scattering experiments on protein folding and association.

Hsu, Darren J.↗

DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Origin of Unusual Acidity and Li+ Diffusivity in a Series of Water-in-Salt Electrolytes.

Superconcentrated aqueous electrolytes ("water-in-salt" electrolytes, or WiSEs) enable various aqueous battery chemistries beyond the voltage limits imposed by the Pourbaix diagram of water. However, their detailed structural and transport properties remain unexplored and could be better understood through added studies. Here, we report on our observations of strong acidity (pH 2.4) induced by lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) at superconcentration (at 20 mol/kg). Multiple nuclear magnetic resonance (NMR) and pulsed-field gradient (PFG) diffusion NMR experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations reveal that such acidity originates from the formation of nanometric ion-rich structures. The experimental and simulation results indicate the separation of water-rich and ion-rich domains at salt concentrations >= 5 m and the acidity arising therefrom is due to deprotonation of water molecules in the ion-rich domains. As such, the ion-rich domain is composed of hydrophobic -CF3 (of TFSI-) and hydrophilic hydroxyl (OH-) groups. At 20 m concentration, the tortuosity and radius of water diffusion channels are estimated to be similar to 10 and similar to 1 nm, respectively, which are close to values obtained from hydrated Nafion membranes that also have hydrophobic polytetrafluoroethylene (PTFE) backbones and hydrophilic channels consisting of SO3- ion cluster networks providing for the transport of ions and water. Thus, we have discovered the structural similarity between WiSE and hydrated Nafion membranes on the nanometer scale.

Han, Kee Sung↗

DOE OSTI2023

Microphysics of liquid water in sub-10 nm ultrafine aerosol particles

Abstract. Ultrafine aerosol particles with sizes smaller than 50 nm have been shown in recent studies to serve as a large source of cloud condensation nuclei that can promote additional cloud droplet formation under supersaturation conditions. Knowledge of the microphysics of liquid water in these droplets remains limited, particularly in the sub-10 nm particle size range, due to experimental and theoretical challenges associated with the complexity of aerosol components and the small length scales of interest (e.g., difficulty of precisely sampling the liquid–air interface, questionable validity of mean-field theoretical representations). Here, we carried out molecular dynamics (MD) simulations of aerosol particles with diameters between 1 and 10 nm and characterized atomistic-level structure and water dynamics in well-mixed and phase-separated systems with different particle sizes, NaCl salinities, and pimelic acid (PML) organic surface loadings as a function of distance from the time-averaged Gibbs dividing interface or instantaneous water–air interface. We define a sphericity factor (ϕ) that can shed light on the phase-mixing state of nanodroplets, and we reveal an unexpected dependence of mixing state on droplet size. Our results also evidence an ion concentration enhancement in ultrafine aerosols, which should modulate salt nucleation kinetics in sub-10 nm droplets, and provide detailed characterization of the influence of droplet size on surface tension and on water self-diffusivity near the interface. Analysis of water evaporation free energy and water activity demonstrates the validity of the Kelvin equation and Köhler theory at droplet sizes larger than 4 nm under moderate salinities and organic loadings and the need for further extension to account for ion concentration enhancement in sub-10 nm aerosols, droplet-size-dependent phase separation effects, and a sharp decrease in the cohesiveness of liquid water in sub-4 nm droplets. Finally, we show that an idealized fractional surface coating factor (fs) can be used to categorize and reconcile water accommodation coefficients (α*) observed in MD simulations and experimental results in the presence of organic coatings, and we resolve the droplet size dependence of α*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Modeling laser interactions with aluminum and tantalum targets using a hybrid atomistic-continuum model

A hybrid atomistic-continuum method can model the microstructure evolution of metals subjected to laser irradiation. This method combines classical molecular dynamics (MD) simulations with the two-temperature model (TTM) to account for the laser energy absorption and heat diffusion behavior. Accurate prediction of the temperature evolution in the combined MD-TTM method requires reliable accuracy in electron heat capacity, electron thermal conductivity, and electron–phonon coupling factor across the temperatures generated. This study uses the electronic density of states (DOS) obtained from first-principle calculations. The calculated electron temperature-dependent parameters are used in MD-TTM simulations to study the laser metal interactions in FCC and BCC metals and the phenomenon of laser shock loading and melting. This study uses FCC Al and BCC Ta as model systems to demonstrate this capability. When subjected to short pulsed laser shocks, the dynamic failure behavior predicted using temperature-dependent parameters is compared with the experimentally reported single-crystal and nanocrystalline Al and Ta systems. The MD-TTM simulations also investigate laser ablation and melting behavior of Ta to compare with the ablation threshold reported experimentally. In conclusion, this manuscript demonstrates that integrating the temperature-dependent parameters into MD-TTM simulations leads to the accurate modeling of the laser–metal interaction and allows the prediction of the kinetics of the solid–liquid interface.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The carboxylation status of osteocalcin has important consequences for its structure and dynamics

The carboxylation status of Osteocalcin (Ocn) not only influences formation and structure in bones but also has important endocrine functions affecting energy metabolism and expenditure. In this study, the role of γ-carboxylation of the glutamate residues in the structure-dynamics-function relationship in Ocn is investigated. Three forms of Ocn, differentially carboxylated at the Glu-17, 21 and 24 residues, along with a mutated form of Ocn carrying Glu/Ala mutations, are modeled and simulated using molecular dynamics (MD) simulation in the presence of calcium ions. Characterization of the global conformational dynamics of Ocn, described in terms of the orientational variations within its 3-helical domain, highlights large structural variations in the non-carboxylated osteocalcin (nOcn). The bi-carboxylated Ocn (bOcn) and tri-carboxylated (tOcn) species, in contrast, display relatively rigid tertiary structures, with the dynamics of most regions strongly correlated. Radial distribution functions calculated for both bOcn and tOcn show long-range ordering of the calcium ion distribution around the carboxylated glutamate (γGlu) residues, likely playing an important role in promoting stability of these Ocns. Additionally, the same calcium ions are observed to coordinate with neighboring γGlu, better shielding their negative charges and in turn stabilizing these systems more than do the singly coordinating calcium ions observed in the case of nOcn. bOcn is also found to exhibit a more helical C-terminal structure, that has been shown to activate its cellular receptor GPRC6A, highlighting the allosteric role of Ocn carboxylation in modulating the stability and binding potential of the active C-terminal. Furthermore, the carboxylation status of Ocn as well and its calcium coordination appear to have a direct influence on Ocn structure and dynamics, possibly leading to the known differences in Ocn biological function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Modular Approach for the Synthesis of Bottlebrush Diblock Copolymers from Poly(Glycidyl Methacrylate)-block-Poly(Vinyldimethylazlactone) Backbones

A strategy that enables the facile synthesis of bottlebrush block copolymers with flexible backbones was developed. A demonstration of the strategy’s utility was carried out by grafting end-functionalized polymethylmethacrylate (PMMA) and polystyrene (PS) to the dually reactive block copolymer, poly(glycidyl methacrylate)-block-poly(vinyldimethylazlactone) (PGMA-b-PVDMA). Five different bottlebrush diblock copolymers were investigated by size-exclusion chromatography (SEC), 1H NMR, Fourier transform infrared (FT-IR), differential scanning calorimetry (DSC), X-ray scattering methods, atomic force microscopy (AFM), rheology and computational simulations using molecular dynamics (MD), and self-consistent field theory (SCFT). A relationship between the glass transition temperature and the fraction of chain ends was demonstrated by DSC and highlights the potential of this synthetic method to tailor polymer properties. All five samples were found to be in a disordered phase exhibiting multiscale structures revealed by two broad peaks in small-angle X-ray scattering (SAXS) that can be attributed to graft-to-graft and backbone-to-backbone density correlations using MD simulations. The SCFT-based simulations justify the observation of a disordered phase due to its stabilization by the grafts. Additionally, this modular approach can be easily extended to other grafts, including responsive, conducting, and charged polymers with the prerequisite end groups. The versatility and ease of assembling these functional bottlebrushes constitute a powerful “toolbox” method for the rapid and scalable synthesis of novel bottlebrush block copolymers with desired properties.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Computational and experimental study of different brines in temperature swing solvent extraction desalination with amine solvents

Rapid global urbanization and high-salinity wastewater disposal from industrial activities have exerted significant pressure on water resources. Over the past few years, temperature swing solvent extraction (TSSE) has been identified as a promising technique to desalinate hypersaline brines. Despite its potential, the TSSE desalination literature has been mainly based on empirical insights, and the limited molecular simulation studies have primarily focused on NaCl brines. Herein, we use molecular dynamics (MD) simulations to study the TSSE desalination of four different brines, namely, KCl, KBr, NaCl, and NaBr using diisopropylamine as the solvent. Based on both bulk and interfacial brine-diisopropylamine MD results, here we investigate the qualitative and quantitative performance of the simulations by benchmarking these results against our experimental evaluations of these same systems. MD results provide satisfactory qualitative agreement with the experimental data of water solubilization in the organic phase and amine solubilization in the aqueous phase for the KBr, KCl, and NaBr brines. Also, the molecular mechanism of solvation of ionic species by water molecules over diisopropylamine suggested by the MD simulations is in agreement with our experimental data. However, larger qualitative and quantitative deviations were observed for the NaCl brines, and this is likely due to polarization and charge transfer effects, as quantified by our quantum chemical calculations.

42 ENGINEERING↗

DOE OSTI2021

Effects of nanoconfinement and surface charge on iron adsorption on mesoporous silica

Here, we present a combined molecular dynamics (MD) simulation and X-ray absorption fine structure (XAFS) spectroscopic investigation of aqueous iron adsorption on nanoconfined amorphous silica surfaces. The simulation models examine the effects of pore size, pH (surface charge), iron valency, and counter-ion (chloride or hydroxide). The simulation methods were validated by comparing the coordination environment of adsorbed iron with coordination numbers and bond lengths derived from XAFS. In the MD models, nanoconfinement effects on local iron coordination were investigated by comparing results for unconfined silica surfaces and in confined domains within 2 nm, 4 nm, and 8 nm pores. Experimentally, coordination environments of iron adsorbed onto mesoporous silica with 4 nm and 8 nm pores at pH 7.5 were investigated. The effect of pH in the MD models was included by simulating Fe(II) adsorption onto negatively charged SiO 2 surfaces and Fe(III) adsorption on neutral surfaces. The simulation results show that iron adsorption depends significantly on silica surface charge, as expected based on electrostatic interactions. Adsorption on a negatively charged surface is an order of magnitude greater than on the neutral surface, and simulated surface coverages are consistent with experimental results. Pore size effects from the MD simulations were most notable in the adsorption of Fe(II) at deprotonated surface sites (SiO - ), but adsorption trends varied with concentration and aqueous Fe speciation. The coordination environment of adsorbed iron varied significantly with the type of anion. Considerable ion pairing with hydroxide anions led to the formation of oligomeric surface complexes and aqueous species, resulting in larger iron hydroxide clusters at higher surface loadings.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Deep potential molecular dynamics simulations of low-temperature plasma-surface interactions

Machine learning approaches to potential generation for molecular dynamics (MD) simulations of low-temperature plasma-surface interactions could greatly extend the range of chemical systems that can be modeled. Empirical potentials are difficult to generalize to complex combinations of multiple elements with interactions that might include covalent, ionic, and metallic bonds. This work demonstrates that a specific machine learning approach, Deep Potential Molecular Dynamics (DeepMD), can generate potentials that provide a good model of plasma etching in the Si-Cl-Ar system. Comparisons are made between MD results using DeepMD models and empirical potentials, as well as experimental measurements. Pure Si properties predicted by the DeepMD model are in reasonable agreement with experimental results. Simulations of Si bombardment by Ar + ions demonstrate the ability of the DeepMD method to predict sputtering yields as well as the depth of the amorphous-crystalline interface. Etch yields as a function of flux ratio and ion energy for simultaneous Cl 2 and Ar + impacts are in good agreement with previous simulation results and experiment. Predictions of etch yields and etch products during plasma-assisted atomic layer etching of Si-Cl 2 -Ar are shown to be in good agreement with MD predictions using empirical potentials and with experiment. Finally, good agreement was also seen with measurements for the spontaneous etching of Si by Cl atoms at 300 K. Further, the demonstration that DeepMD can reproduce results from MD simulations using empirical potentials is a necessary condition to future efforts to extend the method to a much wider range of systems for which empirical potentials may be difficult or impossible to obtain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Exceptionally high spallation strength for a high-entropy alloy demonstrated by experiments and simulations

High-entropy alloys are materials with an increasing number of technological applications. Amongst them, the Cantor alloy, FeMnCoCrNi, shows desirable mechanical properties at normal loading conditions. In this study we focus on the performance of the Cantor alloy at the ultra-high deformation rates of shock waves. We study shock-induced spallation using both experiments and atomistic simulations. Experimental loading is achieved using high power laser, with VISAR to obtain velocity profiles and spall strength, followed by transmission electron microscopy of the recovered samples. Molecular Dynamics (MD) simulations of shock-induced spallation are compared with experiments. Both experiments and simulations show a high spall strength which would be beneficial for certain applications, with experiments giving ~8 GPa at ~10 7 s -1 and MD giving almost ~30 GPa at ~10 9 s -1 . The difference between experiments and simulations can be explained by the difference in strain rate. Post-mortem analysis of the experimental samples shows nanotwins near the spall plane, while MD simulations show a highly disordered region giving rise to void nucleation and spall during loading.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Challenges of conventional iterative all-atom and coarse-grained multiscale molecular dynamics

In this work, we evaluate the biomolecular dynamics behaviors when conventionally iterating between all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations over multiple cycles. We implemented the workflow to iterate between AA and CG in OpenMM, namely the iterative multiscale MD (iMMD) simulation workflow. In particular, we aim to identify practical applications for iterating between AA and CG simulations in a conventional manner without any constraints or model modifications. We evaluate the iMMD workflow on four representative systems, spanning folding of two soluble proteins and protein-protein as well as protein-lipid interactions of two membrane proteins. We observe that iteration between AA and CG representations could help the soluble proteins exit undesirable metastable states to fold, resulting from random protein structural distortions due to cycling. Consequently, the most reliable use of iterative AA and CG simulations appears to be to accelerating complex lipid mixing for membrane-bound protein systems rather than sampling protein conformational space. Our work explores the practical usages and limitations for iterative AA and CG simulations using readily available AA and CG force fields. The evaluated iMMD workflow in OpenMM is made available at https://github.com/lanl/iMMD.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗

DOE OSTI2022

Surface Interactions and Nanoconfinement of Methane and Methane plus CO2 Revealed by High-Pressure Magic Angle Spinning NMR Spectroscopy and Molecular Dynamics

This study explores the fundamental, molecular- to microscopic-level behavior of methane gas confined into nanoporous silica proxies with different pore diameters and surface-to-volume (S/V) ratios. Surfaces and pore walls of nanoporous silica matrices are decorated with hydroxyl (-OH) groups, resembling natural heterogeneity. High-pressure MAS NMR was utilized to characterize the interactions between methane and the engineered nanoporous silica proxies under various temperature and pressure regimes. There was a change in the chemical shift position of confined methane slightly in the mixtures with nanoporous silica up to 393 K, as shown by high-pressure 13C-NMR. The 13C-NMR chemical shift of methane was changed by pressure, explained by the densification of methane inside the nanoporous silica materials. The influence of pore diameter and S/V of the nanoporous silica materials on the behaviors and dynamics of methane were studied. The presence of CO2 in mixtures of silica and methane needs analysis with caution because CO2 in a supercritical state and gaseous CO2 change the original structure of nanoporous silica and change surface area and pore volume. According to simulation, the picosecond scale dynamics of methane confined in larger pores of amorphous silica is faster. In the 4 nm pore, the diffusivity obtained from MD simulations in the pore with a higher S/V ratio is slower due to the trapping of methane molecules in adsorbed layers close to the corrugated pore surface. In contrast, relaxation measured with NMR for smaller pores (higher S/V) exhibits larger T1, indicating slower relaxation.

03 NATURAL GAS↗