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At least 1,585 records · Page 88

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Sulfonated polybenzimidazole membrane with graphene oxide additive for 2,3-butanediol/water separation: A molecular simulation

Membrane separation for 2,3-butanediol (2,3-BDO) recovery from fermentation broth is highly valued for sustainable and renewable processes, but it requires efficient membrane materials. Here, this work evaluates the sulfonated polybenzimidazole (sPBI) and its graphene oxide (GO) doped composite membrane for separating 2,3-BDO and water via atomistic simulations. Density functional theory calculations are applied to identify various forms of sPBI structures and quantify their binding interactions with 2,3-BDO and water. Classical molecular dynamic simulations are used to evaluate the structural changes, diffusivity, and selectivity of 2,3-BDO and water in different sPBI models, GO surfaces, and GO-doped sPBI composite models. Our results suggest that sPBI slightly increases the crystallinity of the membrane structures, enhances the adsorption strength for both 2,3-BDO and water, and improves the water/2,3-BDO selectivity by 2–3 times. The GO surfaces display a maximum selectivity at a surface coverage of 0.1–0.15 for both hydroxyl and epoxy surface groups. The addition of GO flakes to sPBI creates new interaction sites for 2,3-BDO and water at the interface of sPBI and GO, and the water/2,3-BDO selectivity of GO-doped sPBI models is further increased up to 3 times. This work illustrates how the integrated addition of sPBI and GO flakes offers a promising approach to selective separation of 2,3-BDO and water, providing theoretical guidance for polybenzimidazole-based membranes in the potential application of 2,3-BDO recovery.

2,3-butanediol↗

NASA NTRS1989

Simulating The Gamma-Ray Observatory Spacecraft

Gamma-Ray Observatory (GRO) spacecraft constitutes major advance in gamma-ray astronomy by offering first opportunity for comprehensive observations in range of 0.1 to 30,000 MeV. GRO Attitude Dynamics Simulator (GROSS) computer program designed to simulate mission. Consists of three separate programs: stand-alone profile program; simulator program, containing simulation control input/output (SCIO) subsystem, truth model (TM) subsystem, and on-board computer (OBC) subsystem; and postprocessor program. Written in FORTRAN 77.

Garrick, J.↗

DOE OSTI2026

Molecular Dynamics Investigation of Oil Wetting on Synthetic Polymer Substrates

Understanding the interaction of polymer surfaces with nonpolar, low surface tension liquids, or whether a substrate is oleophobic versus oleophilic, is critical for applications ranging from antifingerprint coatings to oil–water separation membranes and oil spill remediation. Despite its technological importance, the molecular mechanisms underpinning polymer–oil wetting are not well characterized. Here, we employ molecular dynamics simulations to investigate the behavior of n-hexadecane in contact with chemically distinct polymer surfaces, spanning eight constitutional unit chemistries as well as amorphous and crystalline morphologies. This permits a critical examination of both thermodynamic and dynamic descriptors of oleophobicity, including oil contact angle, dewetting free energy, interfacial diffusivity, and a proposed “ghost probe energy,” which does not require explicit simulation of oil–polymer interactions. We find that the oil contact angle does not reliably distinguish oleophobic behavior across polymer chemistries, whereas other metrics provide clearer and more consistent differentiation. Analysis of the results reveals that polymer–oil wetting behavior is primarily governed by interfacial van der Waals interactions and modulated by surface flexibility and morphology. Collectively, this work establishes a computational framework for characterizing oil wetting and provides additional insight into what molecular-level factors dictate trends in oleophobicity.

lipids↗

DOE OSTI2025

Absorbing boundary conditions in material point method adopting perfectly matched layer theory

This study focuses on solving the numerical challenges of imposing absorbing boundary conditions for dynamic simulations in the material point method (MPM). To attenuate elastic waves leaving the computational domain, the current work integrates the Perfectly Matched Layer (PML) theory into the implicit MPM framework. The proposed approach introduces absorbing particles surrounding the computational domain that efficiently absorb outgoing waves and reduce reflections, allowing for accurate modeling of wave propagation and its further impact on geotechnical slope stability analysis. The study also includes several benchmark tests to validate the effectiveness of the proposed method, such as several types of impulse loading and symmetric and asymmetric base shaking. The conducted numerical tests also demonstrate the ability to handle large deformation problems, including the failure of elasto-plastic soils under gravity and dynamic excitations. The findings extend the capability of MPM in simulating continuous analysis of earthquake-induced landslides, from shaking to failure.

58 GEOSCIENCES↗

DOE OSTI2021

Cs retention and diffusion in C-S-H at different Ca/Si ratio

Cement and concrete are commonly used in the construction of repository sites for radioactive wastes. The correct isolation of those contaminants requires good adsorption and low diffusion rates. Both parameters are highly affected by many factors, such as pH, temperature or composition. The large variability of experimental conditions and formulations makes it extraordinarily difficult to tackle the influence of each of them independently in experimental samples. To this effect, molecular dynamics simulations have been employed in this study to investigate the role of the composition in the capacity to retain Cs and diffusivity of these ions in calcium silicate hydrate (C-S-H) gel pores. The results indicate that the adsorption of Cs ions is worsened at high Ca/Si ratios due to a lower interaction of the cations with the C-S-H surface, while hydrophilicity of the C-S-H nanopore rises, resulting in higher long-range ordering and lower diffusion coefficients of Cs ions.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Atomic understanding of structural deformations upon ablation of graphene

We investigate the atomic rearrangement in graphene under femtosecond pulse illumination with reactive molecular dynamics simulations and compare with ultra-fast laser ablation experiments. To model the impact of the laser pulse irradiation, heat is locally applied to a selected area of the graphene layer and the resulting structural deformation is simulated as a function of time, providing a detailed understanding of the bond breaking process under laser illumination and subsequent re-equilibration afterAQ3 the pulse is turned off. Analysis of the atomic dynamics indicates that the types of defects formed depend on the pulse energy and exposure duration. By varying the exposed area, we determine that the shape of the ablated area is not only a function of the pulse energy, but also of the beam spot size and pulse repetition. Furthermore, we apply a machine learning approach to extrapolate our simulated data to experimental length scales and reproduce the trends in ablated area as a function of temperature. Furthermore, our study provides a first step towards understanding the design parameters for graphene nano-patterning.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

Ion and Water Dynamics in the Transition from Dry to Wet Conditions in Salt-Doped PEG

The influence of the water content on ion and water transport mechanisms in polymer membranes under low to moderate hydration conditions remains poorly understood. In this study, we combine ion and water diffusivity (PFG-NMR) measurements with atomistic molecular dynamics simulations to better understand transport processes in hydrated salt-doped poly(ethylene glycol). Above the water percolation threshold, the experimental and simulated diffusivities are in good agreement with the free volume transport models. At low hydration levels, unlike dry systems, ion diffusion cannot be described by polymer segmental dynamics alone. We rationalize such observations by the interplay between ion–water and ion–polymer solvation of cations and between ion–water and cation–anion interactions for anions. Further, we demonstrate that a two-state model combining ion–water solvation and free volume transport can describe water dynamics across the entire hydration range of interest. Here, our findings provide a more encompassing analysis of ion and water transport in hydrated polyelectrolytes, specifically in the low hydration regime.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Reversible motions and disordered structure of soft particles in amorphous solids

In amorphous solids, soft vibrational modes derived from normal mode analysis can be utilized to identify the soft particles that are prone to irreversible rearrangements. However, the normal mode analysis approach cannot explain why the spatial distributions of clustered soft particles do not change over time. We define a softness parameter based on the vibrational density of states calculated directly from molecular dynamics simulations with both the harmonic vibrations and anharmonic relaxations being properly captured at finite temperatures. This parameter spontaneously correlates with the real space atomic motions and the dynamics heterogeneity. Using the softness parameter, we show that the softest particles are confined within rigid cages. These particles keep rearranging reversibly without long-range diffusion. The moderately soft particles rearrange irreversibly, and the hard particles mainly participate in vibrations without rearrangement. Here, we also show that the soft particles form locally disordered structures, while the hard particles present strong ordering. These findings confirm the defective nature of soft particles, and provide insights on the nature of softness as the ability to rearrange, but not necessarily irreversibly.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Efficient Simulation of Cascading Outages Using an Energy Function-Embedded Quasi-Steady-State Model

Here, this paper proposed an energy function-embedded quasi-steady-state model for efficient simulation of cascading outages on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation. Cascading outage simulation using the proposed model conducts three steps for each disturbance such as a line outage. First, it performs time-domain simulation for a short term to obtain a post-disturbance trajectory. Second, along the trajectory, the system state with the local maximum potential energy is found and used as the initial point to search for a relevant unstable equilibrium by Newton's method. Third, the transient energy margin is estimated based on this unstable equilibrium to predict an out-of-step condition with generators. The proposed energy function-embedded quasi-steady-state model is tested in terms of its accuracy and time performance on an NPCC 140-bus power system and compared to a quasi-steady-state model embedding transient stability simulation.

Guo, Zhenping [Univ. of Tennessee, Knoxville, TN (↗

DOE OSTI2023

A Joint Modeling/Experimental Approach to Characterize Ionization and Fragmentation of SOA Molecules with CIMS

The Molecular Dynamics technique Collective variable hyperdynamics (CVHD) interfaced with density functional tight-binding at the GFN1-xTB and GFN2-xTB levels of electronic structure theory has been applied to the H + GAG positively charged peptide system to explore the fragmentation of this simple tripeptide under relatively low temperature/energy conditions. Unlike conventional chemical dynamics simulations which can only be performed up to hundreds of picoseconds when coupled with semi-empirical Hamiltonians, CVHD is able to capture the long-time dynamics of multiple proton hopping, the formation of reversible ring structures, and ester rearrangement of the H + GAG system prior to fragmentation. The CVHD method applied to H + GAG is also able to uncover alternative fragmentation pathways not considered previously such as glycine fragmentation on the N-terminal side of the charged peptide and new cyclic cationic species. These findings in the H + GAG case have implications for other peptide systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2016

Towards an Aero-Propulso-Servo-Elasticity Analysis of a Commercial Supersonic Transport

This paper covers the development of an aero-propulso-servo-elastic (APSE) model using computational fluid dynamics (CFD) and linear structural deformations. The APSE model provides the integration of the following two previously developed nonlinear dynamic simulations: a variable cycle turbofan engine and an elastic supersonic commercial transport vehicle. The primary focus of this study is to provide a means to include relevant dynamics of a turbomachinery propulsion system into the aeroelastic studies conducted during a vehicle design, which have historically neglected propulsion effects. A high fidelity CFD tool is used here for the integration platform. The elastic vehicle neglecting the propulsion system serves as a comparison of traditional approaches to the APSE results. An overview of the methodology is presented for integrating the propulsion system and elastic vehicle. Static aeroelastic analysis comparisons between the traditional and developed APSE models for a wing tip detection indicate that the propulsion system impact on the vehicle elastic response could increase the detection by approximately ten percent.

aeroservoelasticity↗

NASA NTRSDate not supplied

Use of CFD in the Design of the 10- by 10-Foot Supersonic Wind Tunnel Characterization Array

At the 10- by 10-Foot Supersonic Wind Tunnel at the NASA Glenn Research Center, a future full test section characterization generated an ideal opportunity to design and build new characterization hardware to improve the understanding of the flow field, including flow quality, uniformity, and uncertainty in primary variables of interest. An array of flow sensing probes, referred to as the Characterization Array, was designed and built to replace 1960’s-era test section characterization hardware. Many references exist to guide wind tunnel characterization practitioners in the design of new hardware to properly measure various aspects of the flow within their wind tunnel facilities. Although reliable sources of information, these references tend to be over 30 years old and are not exhaustive. In scenarios where design decisions needed to be validated, computational simulations of the flow field around the characterization hardware were used. Decisions regarding probe location, probe spacing, and performance of various probes were justified using computational fluid dynamic simulations and rules-of-thumb from the legacy resources available in literature. This paper is intended to serve as an example of the benefits from integrating CFD into the design of wind tunnel hardware, particularly hardware for wind tunnel characterization.

CFD↗

NASA NTRSDate not supplied

Use of CFD in the Design of the 10- by 10-Foot Supersonic Wind Tunnel Characterization Array

CFD↗

DOE OSTI2023

Atomistic simulation of brittle-to-ductile transition in silicon carbide embedded with nano-sized helium bubbles

In this study, the tensile response of cubic silicon carbide (SiC) bulk containing cavities (voids and He bubbles) has been investigated using molecular dynamic simulations. The formation of cavities in SiC leads to a significant degradation in the mechanical properties of SiC with more influence on material fracture than initial elastic deformation. The brittle-to-ductile transition occurs in cavity-embedded SiC as the pressure in He bubbles increases. This is associated with the deformation mechanism that bond breaking at a low He bubble pressure transfers to extensive dislocation activities at a higher He bubble pressure. The cavities can effectively concentrate stress around them in the direction perpendicular to the tension, which leads to preferred cracking in the region with a higher tensile stress. The failure mechanism as revealed by this study improves understanding of property degradation in SiC that may be useful for applications of SiC in advanced nuclear energy systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators

Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

High-Fidelity Simulations of HyMETS Arc-Jet Flows for PICA-N Modeling

Arc-jet testing is a fundamental tool in the screening of thermal protection systems under atmospheric entry conditions. In this work, high-fidelity computational fluid dynamics simulations coupled with machine learning methods for the Hypersonic Materials Environmental Test System arc-jet facility have been carried out. This effort improves the MEDLI-2 data reconstruction fidelity by understanding the impact of the NuSil coating over the PICA thermocouple plugs. Thermochemical non-equilibrium models are employed to simulate the flows inside the arc-jet nozzle and chamber and machine learning techniques are used to calibrate the arc-jet inflow conditions. The material response is simulated with the recession and in-depth numerical results compared to experimental measurements.

STMD↗

DOE OSTI2021

Spatial correlations of entangled polymer dynamics

The spatial correlations of entangled polymer dynamics are examined by molecular dynamics simulations and neutron spin-echo spectroscopy. Due to the soft nature of topological constraints, the initial spatial decays of intermediate scattering functions of entangled chains are, to the first approximation, surprisingly similar to those of an unentangled system in the functional forms. However, entanglements reveal themselves as a long tail in the reciprocal-space correlations, implying a weak but persistent dynamic localization in real space. Furthermore, comparison with a number of existing theoretical models of entangled polymers suggests that they cannot fully describe the spatial correlations revealed by simulations and experiments. In particular, the strict one-dimensional diffusion idea of the original tube model is shown to be flawed. The dynamic spatial correlation analysis demonstrated in this work provides a useful tool for interrogating the dynamics of entangled polymers. Lastly, the failure of the investigated models to even qualitatively predict the spatial correlations of collective single-chain density fluctuations points to a possible critical role of incompressibility in polymer melt dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Data-driven prediction of α IIb β 3 integrin activation paths using manifold learning and deep generative modeling

The integrin heterodimer is a transmembrane protein critical for driving cellular process and is a therapeutic target in the treatment of multiple diseases linked to its malfunction. Activation of integrin involves conformational transitions between bent and extended states. Some of the conformations that are intermediate between bent and extended states of the heterodimer have been experimentally characterized, but the full activation pathways remain unresolved both experimentally due to their transient nature and computationally due to the challenges in simulating rare barrier crossing events in these large molecular systems. An understanding of the activation pathways can provide new fundamental understanding of the biophysical processes associated with the dynamic interconversions between bent and extended states and unveil new putative therapeutic targets. In this work, we apply nonlinear manifold learning to coarse-grained molecular dynamics simulations of bent, extended, and two intermediate states of αI I b β3 integrin to learn a low-dimensional embedding of the configurational phase space. We then train deep generative models to learn an inverse mapping between the low-dimensional embedding and high-dimensional molecular space and use these models to interpolate the molecular configurations constituting the activation pathways between the experimentally characterized states. Furthermore, this work furnishes plausible predictions of integrin activation pathways and reports a generic and transferable multi-scale technique to predict transition pathways for biomolecular systems.

97 MATHEMATICS AND COMPUTING↗