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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effect of heat treatment paths on the aging and rejuvenation of metallic glasses

Here, this study explores the influence of heat treatment paths on the structural relaxation of metallic glasses (MGs) in the regime of fast dynamics. We create MG samples using various quenching rates, from 10 9 to 10 11 K/s, and expose these samples to near-T g heat treatments with assorted combinations of heating/cooling rates, from 5×10 10 to 5×10 12 K/s, and annealing durations, from 10 ps to 10 ns. Results show that the effect of the heating rate is intricately tied to the initial structure of the MG, while a decrease in the cooling rate invariably intensifies the aging process. Extending the annealing duration may induce either aging or rejuvenation, subject to the specific thermal history. To interpret these findings, we hypothesize that the memory effect, governed by the activation and annihilation of reversible and irreversible flow units, underpins the rejuvenation-aging competition in MGs. Moreover, we suggest viewing the cooling stage as an annealing phase controlled by gradient temperature and fine-tuning its rate to achieve the targeted active flow unit distributions. This study illuminates the role of fast dynamics during the glass relaxation process and offers practical strategies for tailoring heat treatments to optimize MG structures and mechanical performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrating Experiments and Well Logs to Predict Caney Shale Static Mechanical Properties During Production with Supervised Machine Learning

Caney shale is one of the emerging oil reservoirs in Oklahoma. Understanding the impact of effective stress on its mechanical properties is critical for predicting hydraulic fracture geometry and overall hydrocarbon production. The objective of our study is to evaluate the impact of effective stress on the dynamic Young’s modulus using ultrasonic velocity measurements for Caney shale samples. A triaxial cell was utilized to measure ultrasonic (P-wave and S-wave) velocities for ten downhole Caney shale samples under various effective stresses to indirectly assess the impact of pore pressure change. The dynamic Young’s moduli estimated from these measurements were integrated with available conventional well logs (excluding sonic logs) and triaxial test results from Benge et al. (2021) to predict the static Young’s modulus using Random Forest (RF) and Extreme Gradient Boosting (XGBoost) models. The results showed that the estimated dynamic Young’s moduli from ultrasonic measurements were higher than the corresponding static Young’s modulus of cores from the same vertical well at similar depths. With increasing effective stress, the dynamic Young’s modulus increased for all samples. The estimated dynamic-to-static correction factor tended to be higher in zones of high neutron porosity (PHIN) and low density compared to other zones. Finally, SHapley Additive exPlanations (SHAP) for RF and XGBoost models identified depth, gamma ray (GR), and PHIN as key features for predicting the static Young’s modulus. This study enhances our understanding of the dynamic and static Young’s moduli for the Caney shale interval, as a function of effective stress and conventional well logs. The findings from this study can improve predictions of production throughout the well's lifespan by offering insights into the mechanical property degradation resulting from pore pressure depletion.

Kholy, Sherif M.↗
DOE OSTI2021

Reinforcement learning in discrete action space applied to inverse defect design

Abstract Reinforcement learning (RL) algorithms that include Monte Carlo Tree Search (MCTS) have found tremendous success in computer games such as Go, Shiga and Chess. Such learning algorithms have demonstrated super-human capabilities in navigating through an exhaustive discrete action search space. Motivated by their success in computer games, we demonstrate that RL can be applied to inverse materials design problems. We deploy RL for a representative case of the optimal atomic scale inverse design of extended defects via rearrangement of chalcogen (e.g. S) vacancies in 2D transition metal dichalcogenides (e.g. MoS 2 ). These defect rearrangements and their dynamics are important from the perspective of tunable phase transition in 2D materials i.e. 2H (semi-conducting) to 1T (metallic) in MoS 2 . We demonstrate the ability of MCTS interfaced with a reactive molecular dynamics simulator to efficiently sample the defect phase space and perform inverse design—starting from randomly distributed S vacancies, the optimal defect rearrangement of defects corresponds a line defect of S vacancies. We compare MCTS performance with evolutionary optimization i.e. genetic algorithms and show that MCTS converges to a better optimal solution (lower objective) and in fewer evaluations compared to GA. We also comprehensively evaluate and discuss the effect of MCTS hyperparameters on the convergence to solution. Overall, our study demonstrates the effectives of using RL approaches that operate in discrete action space for inverse defect design problems.

42 ENGINEERING↗
DOE OSTI2024

Perspective on Integrative Simulations of Bioenergetic Domains

Bioenergetic processes in cells, such as photosynthesis or respiration, integrate many time and length scales, which makes the simulation of energy conversion with a mere single level of theory impossible. Just like the myriad of experimental techniques required to examine each level of organization, an array of overlapping computational techniques is necessary to model energy conversion. Here, in this work, a perspective is presented on recent efforts for modeling bioenergetic phenomena with a focus on molecular dynamics simulations and its variants as a primary method. An overview of the various classical, quantum mechanical, enhanced sampling, coarse-grained, Brownian dynamics, and Monte Carlo methods is presented. Example applications discussed include multiscale simulations of membrane-wide electron transport, rate kinetics of ATP turnover from electrochemical gradients, and finally, integrative modeling of the chromatophore, a photosynthetic pseudo-organelle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

TARGET: A multi-channel digitizer chip for very-high-energy gamma-ray telescopes

The next-generation very-high-energy (VHE) gamma-ray observatory, the Cherenkov Telescope Array, will feature dozens of imaging atmospheric Cherenkov telescopes (IACTs), each with thousands of pixels of photosensors. To be affordable and reliable, reading out such a mega-channel array requires event recording technology that is highly integrated and modular, with a low cost per channel. We present the design and performance of a chip targeted to this application: the TeV Array Readout with GSa/s sampling and Event Trigger (TARGET). This application-specific integrated circuit (ASIC) has 16 parallel input channels, a 4096-sample buffer for each channel, adjustable input termination, self-trigger functionality, and tight window-selected readout. We report the performance of TARGET in terms of sampling frequency, power consumption, dynamic range, current-mode gain, analog bandwidth, and cross talk. The large number of channels per chip allows a low cost per channel ($10 to $20 including front-end and back-end electronics but not including photosensors) to be achieved with a TARGET-based IACT readout system. In addition to basic performance parameters of the TARGET chip itself, we present a camera module prototype as well as a second-generation chip (TARGET 2), both of which have been produced.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Geometric and energetic considerations of surface fluctuations during ion transfer across the water-immiscible organic liquid interface

Molecular dynamics simulations and umbrella sampling free energy calculations are used to examine the thermodynamics, energetics, and structural fluctuations that accompany the transfer of a small hydrophilic ion (Cl{sup −}) across the water/nitrobenzene interface. By examining several constrained interface structures, we isolate the energetic costs of interfacial deformation and co-transfer of hydration waters during the ion transfer. The process is monitored using both energy-based solvation coordinates and a geometric coordinate recently introduced by Morita and co-workers to describe surface fluctuations. Our simulations show that these coordinates provide a complimentary description of the water surface fluctuations during the transfer and are necessary for elucidating the mechanism of the ion transfer.

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

Probing Pore Size and Connectivity in Porous Silicas Using 13C MAS NMR Spectroscopy of Supercritical Methane

Measuring the pore size and pore-size distributions and exploring the fluid-exchange dynamics between different types of pores in porous materials remains a significant experimental challenge but is critical to understanding catalysis, chromatography, nutrient cycling, and a whole range of geochemical phenomena, including shale gas and tight gas extraction. Here, we present the results of 1D 13 C NMR and 2D exchange spectroscopy (EXSY) NMR investigations of a porous silica using supercritical methane (scCH 4 ) as a direct probe of pore size and fluid exchange between pore types. The results show that the 13 C chemical shift of scCH 4 adsorbed in nanometer-scale silica pores becomes more negative with increasing pore diameter, in agreement with trends reported for gas hydrates, zeolites, MOFs, and clays and other microporous (<10 nm pores) geochemical materials. These 13 C chemical shifts follow a natural log–linear trend with pore size in the vacuum-dried porous silicas studied here, allowing one to predict pore size based on the 13 C chemical shift in dry silica nanopores. The EXSY and 1D 13 C NMR results both show that CH 4 exchanges between pore and bulk fluid environments over rate scales from 0.01 to 1 kHz in vacuum-dried samples and that exchange dynamics must be considered when interpreting 13 C NMR of pore-adsorbed CH 4 . Introducing H 2 O to the system causes the 13 C chemical shift to become more negative with increasing H 2 O content as a result of H 2 O preferentially filling small pores, forcing CH 4 to occupy larger pores that are better connected to the bulk environment. Likewise, the 1D 13 C data show a decreased distribution of exchange rates between pore-adsorbed and bulk CH 4 in the presence of H 2 O.

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

Confinement effects and acid strength in zeolites

Chemical reactivity and sorption in zeolites are coupled to confinement and—to a lesser extent—to the acid strength of Brønsted acid sites (BAS). In presence of water the zeolite Brønsted acid sites eventually convert into hydronium ions. The gradual transition from zeolite Brønsted acid sites to hydronium ions in zeolites of varying pore size is examined by ab initio molecular dynamics combined with enhanced sampling based on Well-Tempered Metadynamics and a recently developed set of collective variables. While at low water content (1–2 water/BAS) the acidic protons prefer to be shared between zeolites and water, higher water contents (n > 2) invariably lead to solvation of the protons within a localized water cluster adjacent to the BAS. At low water loadings the standard free energy of the formed complexes is dominated by enthalpy and is associated with the acid strength of the BAS and the space around the site. Conversely, the entropy increases linearly with the concentration of waters in the pores, favors proton solvation and is independent of the pore size/shape.

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

A k-mer based approach for classifying viruses without taxonomy identifies viral associations in human autism and plant microbiomes

Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples, even if they do not have a taxonomy. To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses to create a database of metagenomic viruses. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. We then integrated the viral classification database with databases created with genomes from NCBI for use with ParaKraken (a parallelized version of Kraken provided in Supplemental Zip 1), a metagenomic/transcriptomic classifier. To illustrate the breadth of our utility for classifying metagenome viruses, we analyzed data from a plant metagenome study identifying genotypic and compartment specific differences between two Populus genotypes in three different compartments. We also identified a significant increase in abundance of eight viral sequences in post mortem brains in a human metatranscriptome study comparing Autism Spectrum Disorder patients and controls. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we validate the accuracy of viral classification with NCBI databases containing viruses with taxonomy to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples. Our method represents the compulsory first step in better understanding the role of viruses in the microbiome by allowing for a more complete identification of sequences without taxonomy. Better classification of viruses will improve identifying associations between viruses and their hosts as well as viruses and other microbiome members. Despite the lack of taxonomy, this database of metagenomic viruses can be used with any tool that utilizes a taxonomy, such as Kraken, for accurate classification of viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Confinement-controlled selective CO 2 insertion into a dicopper dihydride core: A multiscale mechanistic study

CO 2 is an abundant C 1 feedstock for fuel and chemical synthesis. We have previously demonstrated experimentally a stepwise insertion of CO 2 into a [Cu 2 H 2 ] core via a solid–gas in crystallo reaction, forming formate species that are unstable and inaccessible under solution-phase conditions. This work elucidates how structural confinement within the crystal lattice enables such selective reactivity. In particular, co-crystallized tetrahydrofuran molecules induce site asymmetry around the [Cu 2 H 2 ] unit, modulating both the local electronic environment and CO 2 diffusion pathways. Using a multiscale computational approach that combines classical molecular mechanics, hybrid quantum mechanics/molecular mechanics molecular dynamics, and enhanced-sampling free energy calculations, we demonstrate how site asymmetry affects CO 2 binding affinities and reaction pathways. These results provide detailed mechanistic insight into CO 2 insertion and hydride transfer, highlighting key differences between crystal- and solution-phase pathways and offering a general framework for understanding how lattice confinement shapes chemical reactivity.

Chemical bonding↗
DOE OSTI2024

Effects of Ligand Chemistry on Ion Transport in 2D Hybrid Organic–Inorganic Perovskites

2D hybrid organic–inorganic perovskites are potentially promising materials as passivation layers that can enhance the efficiency and stability of perovskite photovoltaics. The ability to suppress ion transport is proposed as a stabilization mechanism, yet an effective characterization of relevant modes of halide diffusion in 2D perovskites is nascent. In light of this knowledge gap, molecular dynamics simulations with enhanced sampling and experimental validation to systematically characterize how ligand chemistry in seven (R-NH 3 ) 2 PbI 4 systems impacts halide diffusion, particularly in the out-of-plane direction is combined. It is found that increasing stiffness and length of ligands generally inhibits ion transport, while increasing ligand polarization generally enhances it. Structural and energetic analyses of the migration pathways provide quantitative explanations for these trends, which reflect aspects of the disorder of the organic layer. Overall, this mechanistic analysis greatly enhances the current understanding of halide migration in 2D hybrid organic–inorganic perovskites and yields insights that can inform the design of future passivation materials.

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

Investigating Lignin Aggregation and Interactions with Solvents during γ-Valerolactone (GVL) Pretreatment: A Combined Small Angle Neutron Scattering and Molecular Simulations Study

The strong tendency of lignin to aggregate in solution, coupled with limited understanding of how its molecular structure governs this behavior, hinders its effective utilization in biorefineries. Here, in this study, we investigated the solution behavior of lignin extracted from poplar using γ-valerolactone/water (GVL/H2O, 9:1 wt/wt) through combined small-angle neutron scattering (SANS) and molecular dynamics (MD) simulations. Lignin samples obtained at 100 °C (L100) and 120 °C (L120) differed in β–O–4 content, hydroxyl distribution, and S/G ratio, enabling direct assessment of how molecular composition governs solvation and aggregation. SANS showed that L120 formed rigid and elongated cylindrical aggregates at 25 °C that transitioned to more flexible spheroidal structures by 50 °C and remained stable up to 80 °C, whereas L100 adopted globular aggregates that progressively collapsed with increasing temperature. MD simulations reinforced these observations by showing that S-rich (L120-like) oligomers had larger radii of gyration, stronger solvent coordination driven by methoxy groups, and fewer lignin–lignin contacts. In contrast, G-rich (L100-like) oligomers displayed persistent aggregation and lower solubility. Collectively, these results reveal that increased aromatic methoxylation enhances lignin–solvent interactions and suppresses self-association, whereas reduced methoxylation and higher β–O–4 content promote persistent aggregation into colloid-like structures with restricted solvent penetration into the aggregate interior.

biorefinery pretreatment↗
DOE OSTI2025

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗
DOE OSTI2019

Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer

Molecular dynamics (MD) simulations must take very small (femtosecond) integration steps in simulation-time to avoid numerical errors. Efficient use of parallel programming models and accelerators in state-of-the art MD programs now is pushing Moore’s limit for time-per-MD step. As a result, directly simulating timescales beyond milliseconds will not be attainable directly, even at exascale. However, concepts from statistical physics can be used to combine many parallel simulations to provide information about longer timescales and to adequately sample the simulation space, while preserving details about the dynamics of the system. Implementing such an approach requires a workflow program that allows adaptable steering of task assignments based on extensive statistical analysis of intermediate results. Here we report the implementation of such an adaptable workflow program to drive simulations on the Summit IBM Power System AC922, a pre-exascale supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). We compare to experiences on Titan, Summit’s predecessor, report the performance of the workflow and its components, and describe the porting process. We find that using a workflow program managed by a Mongo database can provide the fault tolerance, scalable performance, task dispatch rate, and reconfigurability required for robust and portable implementation of ensemble simulations such as are used in enhanced-sampling molecular dynamics. This type of workflow generator can also be used to provide adaptive steering of ensemble simulations for other applications in addition to MD.

Ossyra, John R.↗
DOE OSTI2017

Propagation of a finite-amplitude elastic pulse in a bar of Berea sandstone: A detailed look at the mechanisms of classical nonlinearity, hysteresis, and nonequilibrium dynamics: Nonlinear propagation of elastic pulse

Here, we study the propagation of a finite-amplitude elastic pulse in a long thin bar of Berea sandstone. In previous work, this type of experiment has been conducted to quantify classical nonlinearity, based on the amplitude growth of the second harmonic as a function of propagation distance. To greatly expand on that early work, a non-contact scanning 3D laser Doppler vibrometer was used to track the evolution of the axial component of the particle velocity over the entire surface of the bar as functions of the propagation distance and source amplitude. With these new measurements, the combined effects of classical nonlinearity, hysteresis, and nonequilibrium dynamics have all been measured simultaneously. We then show that the numerical resolution of the 1D wave equation with terms for classical nonlinearity and attenuation accurately captures the spectral features of the waves up to the second harmonic. But, for higher harmonics the spectral content is shown to be strongly influenced by hysteresis. This work also shows data which not only quantifies classical nonlinearity but also the nonequilibrium dynamics based on the relative change in the arrival time of the elastic pulse as a function of strain and distance from the source. Finally, a comparison is made to a resonant bar measurement, a reference experiment used to quantify nonequilibrium dynamics, based on the relative shift of the resonance frequencies as a function of the maximum dynamic strain in the sample.

58 GEOSCIENCES↗
DOE OSTI2019

Dynamic Wetting of High-Al Steel by CaO-SiO{sub 2}- and CaO-Al{sub 2}O{sub 3}-Based Mold Fluxes

Wetting of steel by mold fluxes affects the surface quality of steel products. Reaction between [Al] and mold fluxes in the continuous casting of high-Al steel leads to a dynamic interfacial phenomenon. This work investigated the wetting of the high-Al steel substrate by CaO-SiO{sub 2}-based and CaO-Al{sub 2}O{sub 3}-based mold fluxes. The interfacial tensions were estimated and related to their high-temperature structures. The interface morphology revealed that CaO-SiO{sub 2}-based mold flux and CaO-Al{sub 2}O{sub 3}-based mold flux with CaO/Al{sub 2}O{sub 3} = 1 exhibited deep reaction zones in the steel substrates and irregular flux/steel interfaces, while CaO-Al{sub 2}O{sub 3}-based mold fluxes with CaO/Al{sub 2}O{sub 3} = 2 and 3 showed smooth interfaces and superficial reaction zones. The sedation of dynamic wetting behavior in Samples 3 and 4 was related to the high viscosity in the flux droplet after the initial composition change, which led to the stabilization of the interface.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Investigation of Compatibility Between M-Cr-Al-X Thermal Spray Coatings and Third Generation γ-TiAl Alloys

In this work, the physical and chemical compatibility of cast Ti-Al-Nb-Cr-Zr and Ti-Al-Nb-Cr-Zr-B-La alloys was investigated with oxidation-resistant M-Cr-Al-X thermal spray coatings. Ti and Al are main alloy elements to form γ-TiAl and α{sub 2}-Ti{sub 3}Al phases. To obtain coatings, we used air plasma spray and high-velocity oxygen fuel equipment. Four commercially available M-Cr-Al-X powders, including Ta-containing, were used as starting materials. Our investigation of compatibility between M-Cr-Al-X thermal spray coatings and γ-TiAl alloys consists of isothermal annealing in air muffle furnace during 100 h at 920 °C, followed by samples investigation. Oxidation products formed at coatings surface were studied by XRD analysis with Rietveld refinement. Interdiffusion between coatings and alloys was studied by means of cross-sectional SEM with EDX analysis. Plots were made to show concentration of each main element at the end of experiments. Samples were subjected to dynamic mechanical thermal analysis in order to determine the effect of high-temperature exposure on complex elastic modulus. Finally, burner rig cycling test was performed to estimate the thermal shock resistance of M-Cr-Al-X coatings.

36 MATERIALS SCIENCE↗