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Results for “molecular dynamic (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.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Molecular dynamics simulations of the secondary-binding site in disaccharide-modified glycopeptide antibiotics

Oritavancin is a semisynthetic glycopeptide antibiotic used to treat severe infections by multidrug-resistant Gram-positive pathogens. Oritavancin is known to be a thousand times more potent than vancomycin against Gram-positive bacteria due to the additional interactions with bacterial peptidoglycan (PG) facilitated by a secondary-binding site. The presence of this secondary-binding site is evident in desleucyl-oritavancin, an Edman degradation product of oritavancin, still retaining its potency against Gram-positive bacteria, whereas desleucyl-vancomycin is devoid of any antimicrobial activities. Herein, using explicit solvent molecular dynamics (MD) simulations, steered MD simulations, and umbrella sampling, we show evidence of a secondary-binding site mediated by the disaccharide-modified hydrophobic sidechain of oritavancin interactions with the pentaglycyl-bridge segment of the PG. The interactions were characterized through comparison to the interaction of PG with chloroeremomycin, vancomycin, and the desleucyl analogs of the glycopeptides. Our results show that the enhanced binding of oritavancin to PG over the binding of the other complexes studied is due to an increase in the hydrophobic effect, electrostatic and van der Waals interactions, and not the average number of hydrogen bonds. Our ranking of the binding interactions of the biomolecular complexes directly correlates with the order based on their experimental minimum inhibitory concentrations. The results of our simulations provide insight into the modification of glycopeptides to increase their antimicrobial activities or the design of novel antibiotics against pathogenic Gram-positive bacteria.

60 APPLIED LIFE SCIENCES↗
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 OSTI2019

Effect of Domain Size, Boundary, and Loading Conditions on Mechanical Properties of Amorphous Silica: A Reactive Molecular Dynamics Study

Mechanical properties are very important when choosing a material for a specific application. They help to determine the range of usefulness of a material, establish the service life, and classify and identify materials. The size effect on mechanical properties has been well established numerically and experimentally. However, the role of the size effect combined with boundary and loading conditions on mechanical properties remains unknown. In this paper, by using molecular dynamics (MD) simulations with the state-of-the-art ReaxFF force field, we study mechanical properties of amorphous silica (e.g., Young’s modulus, Poisson’s ratio) as a function of domain size, full-/semi-periodic boundary condition, and tensile/compressive loading. We found that the domain-size effect on Young’s modulus and Poisson’s ratio is much more significant in semi-periodic domains compared to full-periodic domains. The results, for the first time, revealed the bimodular and anisotropic nature of amorphous silica at the atomic level. We also defined a “safe zone” regarding the domain size, where the bulk properties of amorphous silica can be reproducible, while the computational cost and accuracy are in balance.

bimodular materials↗
DOE OSTI2023

Impact of organic solutes on capillary phenomena in water-CO2-quartz systems

Hypothesis: The migration of supercritical CO2 (scCO2) injected into underground reservoirs as part of carbon capture and storage is influenced by organic contamination affecting mineral wettability. Molecular dynamics (MD) simulations of relevant systems that incorporate representative organic solutes allow detailed investigation of changes in fundamental interfacial and capillary properties. Experiments: We use MD simulations to explore the effects of four organic solutes (quinoline, decanoic acid, coronene, sorgoleone) on the wettability of quartz by water in the presence of scCO2. We examine the impacts of polar, alkyl, and aromatic moieties as well as fluid flow velocity at elevated temperatures and pressures. Findings: Organic molecules accumulate at the water-CO2 interface, where they distribute according to their size and functional groups. Certain organics penetrate the adsorbed water film at the quartz-CO2 interface, revealing two modes of hydrogen bonding between polar organic functional group, water, and quartz surface –OH groups. Interfacial energies and contact angles are minimally impacted by organic adsorption at the water-CO2 interface, possibly due to simultaneous CO2 desorption. Non- equilibrium MD simulations reveal that flow-induced redistribution of organic compounds modulates the radii of curvature of the advancing and receding water-CO2 interfaces. Our results indicate that organic adsorption on water surfaces is likely ubiquitous during multi-phase flow in soils and sedimen- tary rocks, with implications for the mobilization and transport of organic compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular mechanism of biased signaling at the kappa opioid receptor

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

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

Relating Geometric Nanoconfinement and Local Molecular Environment to Diffusion in Ionic Polymer Membranes

Understanding structure-diffusion relationships in ionic polymer membranes not only illuminates fundamental mechanisms for membrane transport, but also informs further membrane development. In this study, we employ NMR diffusometry and molecular dynamics (MD) simulations to investigate diffusion coefficients and activation energies of diffusion (Ea) for both a lithium-form perfluorosulfonic acid membrane and aqueous solutions of lithium triflate. NMR shows that, at high water/ion molar ratio (?), Ea for water diffusion is slightly lower in the membrane than in solution. Conversely, membrane transport exhibits much higher Ea at low hydration as compared to solutions. MD simulations of a model system consisting of carbon nanotubes with varying diameter reveal that Ea of diffusion clearly relates to both the geometric nanoconfinement of the hydrophilic pathways in the membrane as well as the local molecular environment. These results demonstrate that Ea of diffusion can serve as a revelatory tool for the study of molecular transport processes and the coupling of morphology with transport at the nanoscale. This study thus provides new insights and new experimental and computational models for understanding transport in a wide range of polymer membranes, such as those used in molecular separations applications.

Zhang, Rui↗
DOE OSTI2021

Understanding the plasticity contributions during laser-shock loading and spall failure of Cu microstructures at the atomic scales

A hybrid atomic-scale and continuum modeling framework is used to study the microstructural evolution during the laser-induced shock deformation and failure (spallation) of copper microstructures. A continuum two-temperature model (TTM) is used to account for the interaction of Cu atoms with a laser in molecular dynamics (MD) simulations. The MD-TTM simulations study the effect of laser loading conditions (laser fluence) on the microstructure (defects) evolution during various stages of shock wave propagation, reflection, and interaction in single-crystal (sc) Cu systems. In addition, the role of the microstructure is investigated by comparing the defect evolution and spall response of sc-Cu and nanocrystalline (nc) Cu systems. The defect (stacking faults and twin faults) evolution behavior in the metal at various times is further characterized using virtual in situ selected area electron diffraction and x-ray diffraction during various stages of evolution of microstructure. Here, the simulations elucidate the uncertain relation between spall strength and strain-rate and the much stronger relation between the spall strength and the temperatures generated due to laser shock loading for the small Cu sample dimensions considered here.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A spall and diffraction study of nanosecond pressure release across the iron ε-α phase boundary

The extreme response of polycrystalline iron at high pressures and high strain rates is revealed by means of high-power laser pulses. The compression portion of the pulse coupled with x-ray diffraction identifies the expected body-centered cubic (α) to hexagonal close packed (ε) displacive transformation. Upon release, observation shows that the complete reverse transformation takes approximately 8 ns and that the structure returns to its initial microstructural configuration, in a reversible transformation path. This is in good agreement with molecular dynamics (MD) simulations which predict an inverse dependence between transformation time and strain rate. The grain size is reduced from μm to nm range during compression and begins increasing back to the original grain size on decompression. The kinetics of the transition is dictated by heterogenous nucleation as it follows the Johnson-Mehl-Avrami-Kolmogorov equation with the appropriate time exponent of ~1. This is confirmed by MD simulations which also identify profuse twinning and dislocation generation. Here, the tensile pulse generated upon reflection at the free surface is captured by time-resolved free surface velocity measurements from which a peak tensile stress of 7 GPa is obtained, in stark contrast with its quasi-static value of ~200 MPa. At these strain rates, the strength of grain interiors, which is determined by twinning and slip exceeds the strength of the boundaries, and failure initiates preferentially in the latter.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Implementing a neural network interatomic model with performance portability for emerging exascale architectures

The two main thrusts of computational science are increasingly accurate predictions and faster calculations; to this end, the zeitgeist in molecular dynamics (MD) simulations is pursuing machine learned and data driven interatomic models, e.g. neural network potentials, and novel hardware architectures, e.g. GPUs. Current implementations of neural network potentials are orders of magnitude slower than traditional interatomic models and while looming exascale computing offers the ability to run large, accurate simulations with these models, achieving portable performance for MD with new and varied exascale hardware requires rethinking traditional algorithms, using novel data structures, and library solutions. We re-implement a neural network interatomic model in CabanaMD, an MD proxy application, built on libraries developed for performance portability. Our implementation shows significantly improved thread scaling in this complex kernel as compared to a current LAMMPS implementation, across both strong and weak scaling. Our single-source solution enables simulations up to 20 million atoms on a single CPU node and 4 million atoms with improved performance on a single GPU. Furthermore, we also explore parallelism and data layout choices (using flexible data structures called AoSoAs) and their effect on performance, seeing up to ~50% and ~5% improvements in performance on a GPU by choosing the right level of parallelism and data layout respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Computational studies reveal Fluorine based quinolines to be potent inhibitors for proteins involved in SARS-CoV-2 assembly

World is witnessing one of the worst pandemics of this century caused by SARS-CoV-2 virus which has affected millions of individuals. Despite rapid efforts to develop vaccines and drugs for COVID-19, the disease is still not under control. Chloroquine (CQ) and Hydroxychloroquine (HCQ) are two very promising inhibitors which have shown positive effect in combating the disease in preliminary experimental studies, but their use was reduced due to severe side-effects. Here, we performed a theoretical investigation of the same by studying the binding of the molecules with SARS-COV-2 Spike protein, the complex formed by Spike and ACE2 human receptor and a human serine protease TMPRSS2 which aids in cleavage of the Spike protein to initiate the viral activation in the body. Both the molecules had shown very good docking energies in the range of -6kcal/mol. Subsequently, we did a high throughput screening for other potential quinoline candidates which could be used as inhibitors. From the large pool of ligand candidates, we shortlisted the top three ligands (binding energy -8kcal/mol). We tested the stability of the docked complexes by running Molecular Dynamics (MD) simulations where we observed the stability of the quinoline analogues with the Spike-ACE2 and TMPRSS2 nevertheless the quinolines were not stable with the Spike protein alone. Thus, although the inhibitors bond very well with the protein molecules their intrinsic binding affinity depends on the protein dynamics. Moreover, the quinolines were stable when bound to electronegative pockets of Spike-ACE2 or TMPRSS2 but not with Viral Spike protein. We also observed that a Fluoride based compound: 3-[3-(Trifluoromethyl)phenyl]quinoline helps the inhibitor to bind with both Spike-ACE2 and TMPRSS2 with equal probability. The molecular details presented in this study would be very useful for developing quinoline based drugs for COVID-19 treatment.

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

Quantifying Membrane Structure and Dynamics during Bioproduct Production in Zymomonas mobilis by Molecular Simulation

The conversion of lignocellulosic biomass into biofuels and bioproducts by microbial biorefineries is central to a sustainable chemical industry. Zymomonas mobilis is one such biorefinery chassis and is resistant to ethanol stress, leading to its use in biomass conversion to biofuels and bioproducts. However, Z. mobilis growth is often inhibited by organic acids, aldehydes, alcohols, ketones, and amides found in biomass hydrolysate. The resulting slow growth inhibits production and as a result drives up the price for the resulting products. One hypothesis is that these molecules interact with or disrupt the bacterial membrane, triggering stress responses and hindering growth. To test this hypothesis at the molecular level, we employ all-atom molecular dynamics (MD) simulations to investigate lignocellulose-derived small molecules and their impact on a biologically relevant Z. mobilis membrane model. Simulations were conducted across a range of inhibitor concentrations from 0 to 2.5 mol %, analyzing key membrane properties such as area per lipid (APL), membrane thickness, lipid-order parameter (−S CH ), lateral diffusion coefficient (D xy ), and permeability coefficient (Pm). From simulation, we observed altered membrane structure and dynamics at these modest small molecule concentrations commonly found in hydrolysates. Generally, the membranes become thinner, with a higher area per lipid and lower-order parameter as the small molecule concentration increases. These trends are stronger for more hydrophobic molecules with greater hydrophobic bulk, as isobutanol, propanol, and propanoic acid showed greater membrane perturbations as the concentration increased compared to other small molecules. Tracking small molecule distributions directly in our equilibrium simulations allows us to determine concentration-dependent free energy profiles for these molecules. While the trends are noisy, generally the barriers to crossing the membrane decrease as the concentration increases, indicating that the membranes become leakier as small molecule concentrations rise. Comparing between native Z. mobilis membranes with hopanoids and membranes sharing the same phospholipid composition but without hopanoids, hopanoids stabilize and order the membrane for smaller molecules to maintain membrane structure but appear insufficient for larger hydrophobic molecules like isobutanol. These findings provide a mechanistic understanding of how small molecules found in biomass degradation streams interact with the Z. mobilis membrane, offering valuable insights for future strain engineering efforts to optimize biofuel and bioproduct synthesis from biomass feedstocks by highlighting limits to small molecule tolerance. This knowledge can guide the modification of membrane composition to develop more robust microbes, thereby improving microbial survival and yields in industrial contexts.

Singh, Nitin Kumar [Michigan State Univ., East Lan↗
DOE OSTI2021

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. Additionally, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. Finally, the capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

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

Effect of free surfaces on localized plastic deformation in single-crystal nickel containing helium bubbles and radiation-induced self-interstitial atom clusters

This paper presents molecular dynamics (MD) simulations of plastic deformation in single-crystal Ni models containing internal distributions of helium (He) bubbles and self-interstitial atom (SIA) clusters corresponding to experimental characterization of ex-service Inconel X-750 components. Here, we simulate single crystals with and without free surfaces at room temperature and 588K, the latter temperature corresponding to the Inconel X-750 service conditions. Both models are deformed under multiple slip to a maximum deviatoric strain of ~10 %. A dislocation slip band forms in the model without free surfaces, but not in the model with free surfaces. However, the latter exhibits nano-twin nucleation from surfaces. Helium (He) bubbles that overlap with a slip band or a nano-twinned region deform more severely than other bubbles in the model. Nevertheless, the bubbles do not link up and do not form configurations that resemble incipient cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Breaking the mold: Overcoming the time constraints of molecular dynamics on general-purpose hardware

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms have, however, failed to provide strong scaling for MD, as scale-out central processing unit (CPU) and graphics processing unit (GPU) platforms that provide substantial increases to spatial scale do not lead to proportional increases in temporal scale. Important scientific problems therefore remained inaccessible to direct simulation, prompting the development of increasingly sophisticated algorithms that present significant complexity, accuracy, and efficiency challenges. While bespoke MD-only hardware solutions have provided a path to longer timescales for specific physical systems, their impact on the broader community has been mitigated by their limited adaptability to new methods and potentials. In this work, we show that a novel computing architecture, the Cerebras wafer scale engine, completely alters the scaling path by delivering unprecedentedly high simulation rates up to 1.144 M steps/s for 200 000 atoms whose interactions are described by an embedded atom method potential. This enables direct simulations of the evolution of materials using general-purpose programmable hardware over millisecond timescales, dramatically increasing the space of direct MD simulations that can be carried out. In this paper, we provide an overview of advances in MD over the last 60 years and present our recent result in the context of historical MD performance trends.

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

Extreme Metastability of Diamond and its Transformation to the BC8 Post-Diamond Phase of Carbon

Diamond possesses exceptional physical properties due to its remarkably strong carbon–carbon bonding, leading to significant resilience to structural transformations at very high pressures and temperatures. Despite several experimental attempts, synthesis and recovery of the theoretically predicted post-diamond BC8 phase remains elusive. Through quantum-accurate multimillion atom molecular dynamics (MD) simulations, we have uncovered the extreme metastability of diamond at very high pressures, significantly exceeding its range of thermodynamic stability. We predict the post-diamond BC8 phase to be experimentally accessible only within a narrow high pressure–temperature region of the carbon phase diagram. The diamond to BC8 transformation proceeds through premelting followed by BC8 nucleation and growth in the metastable carbon liquid. Here we propose a double-shock compression pathway for BC8 synthesis, which is currently being explored in experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗