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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Numerical and experimental analysis of mechanically induced failure in electric vehicle battery modules

Mitigating thermal runaway and cell-to-cell propagation is essential for improving the safety of electric and hybrid vehicles. Enhancing digital twin capabilities to predict battery mechanical abuse is particularly critical for automotive and aerospace applications, where crashworthiness is a key concern. Understanding failure conditions and propagation in battery modules during mechanical abuse is complex due to interactions between structural deformation, heat transfer, electrochemical processes, exothermic reactions and mechanical fracture. While prior studies have focused on modeling cell-level behavior, extending these models to module or pack level is necessary for a system level understating of electric vehicle safety. This study develops coupled large deformation finite element models that simultaneously solve for electrochemistry, material failure, internal short circuit and thermal runaway propagation. The models account for mechanical and thermal interactions between lithium-ion cells and other battery components while the contact interfaces are evolving with time. Model-predicted voltage, temperature and force responses are compared with experimental data for validation. The results demonstrate that the approach captures key failure mechanisms, including thermal propagation through heat transfer, electrical propagation from short circuits in parallel-connected cells, and mechanical propagation via penetration and crack formation. These findings show that computational models are valuable tools for understanding battery module failure and providing insight that can reduce the need for extensive experimental testing.

25 ENERGY STORAGE↗
DOE OSTI2026

Development of Machine-Learned Interatomic Potentials to Predict Structure, Transport, and Reactivity in Platinum-Based Fuel Cells

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent systems remains a challenge. In this work, we train an MLIP to describe hydrated Nafion ionomers and platinum catalysts, which are important components of fuel cells, by constructing a diverse training set to describe the bulk polymer and interfacial catalyst–polymer interactions well. We use our trained MLIP to study the properties of the platinum–Nafion system, including polymer structure, proton mobility in a bulk Nafion polymer and near a platinum-Nafion interface, and reactions near and far from the interface, finding excellent results for structure and reactions contained within our training set. Transport seems to be well described, with both vehicular transport and Grotthuss hopping captured, although converged calculations of diffusivities were not computed because they require calculations of tens of nanoseconds that are challenging with current state-of-the-art MLIPs. The combined insights that this model provides can be leveraged to optimize fuel cell performance, and the approach can be applied to other chemical processes and devices where structure, transport, and reactivity all contribute to the overall observed performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Overview of the OECD-NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established in 1989 to facilitate collaboration in nuclear data activities. Over its thirty year history, different Subgroups have been created to address topics in nearly every aspect of nuclear data, including: experimental measurements, evaluation, validation, model development, quality assurance of databases and the development of software tools. WPEC has recently completed activities on fission yield evaluation, the general nuclear database structure (GNDS) to replace the ENDF-6 format, methods to provide feedback to evaluation, studies of specific capture cross sections, new methods in thermal scattering kernel evaluation and the Collaborative International Evaluated Library Organisation (CIELO) Pilot Project. Ongoing activities in GNDS application programming interface (API) development, methods for covariance evaluation and quality assurance in nuclear data validation using the International Criticality Safety Benchmark Evaluation Project (ICSBEP) database are complemented by the work of two Expert Groups that oversee the High-Priority Request List (HPRL) for Nuclear Data and the continuous development of the GNDS. New activities on the use of integral experiments for nuclear data validation and adjustment, as well as the use of the Shielding Integral Benchmark Archive and Database (SINBAD) for validation have begun and will be coordinated alongside future Subgroups. After three decades we will review the status of WPEC, how it integrates other collections and activities organised by the NEA and how it dovetails with the initiatives of the IAEA and other bodies to effectively coordinate international activities in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Deformation and fracture characteristics of zirconium plate produced via ultrasonic additive manufacturing

Abstract The microstructural evolution, deformation modes, and fracture mechanisms of zirconium plate produced using ultrasonic additive manufacturing (UAM) are presented. In addition to conventional tensile testing techniques, digital image correlation captured highly variable strain accumulation in specimens loaded perpendicular or parallel to the build height (Z). When tested in parallel to Z, delamination at prior foil/foil interfaces creates strain localization noticeable in strain rate maps, whereas specimens loaded perpendicular to Z illustrate conventional strain hardening until necking accelerates delamination. Although bond strengths are statistically and spatially variable, in situ electron backscattering diffraction tests illustrate the ability for grains near interfaces to accommodate strain with twinning and slip modes consistent with conventionally produced zirconium alloys. Finally, mixtures of ductile and delamination-induced fracture highlight the interface-driven failure modes of UAM zirconium plate in the as-built condition. Graphic abstract

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling deformation and failure in AlSi-polyester abradable sealcoating material using microstructure-based finite element simulation

A plasma-sprayed aluminum-silicon (AlSi)/polyester coating is applied in modern gas turbine engines as an abradable sealcoating to maintain tight clearances between the rotating blades and the static casing. While running the engine, the rotating blades “rub” with the abradable coating, which results in extreme strain rate (up to 10 6 ) dynamics and a high-temperature environment. Due to the difficulty of collecting direct measurements, predictive computational models are important for analyzing the deformation and failure of the abradable material, to help meet the design target of avoiding damage to the blade tip and maintaining high fuel efficiency. In this research, a microstructure-based finite element (FE) computational model was developed to capture the complex mechanical behavior of the AlSi/polyester microstructure. The model is based on a virtual representative-volume-element (RVE) of a metal-polymer microstructure, reconstructed from x-ray computed tomography. It models the plastic deformation of, and damage to, each AlSi and polyester constituents, as well as the failure at their interface. The model was calibrated and validated with uniaxial tension and compression experiments, conducted at two temperatures (298 K and 533 K) at an applied strain rate of 10 3 - 10 4 s -1 . The material exhibited strongly asymmetric tension-compression behavior and a sensitivity to temperature, which was well captured by the model. The model was further applied to investigate changes in mechanical behavior due to variations in constituents’ volume fractions, which provides guidance to the microstructural design of AlSi/polyester abradable materials. The model is expected to facilitate the development of improved abradable materials by bypassing the conventional trial-and-error approach and extensive testing requirements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Mechanistic Insight into Photocatalytic Pathways of MIL-100(Fe)/TiO 2 Composites

The integration of metal organic frameworks (MOFs) with semiconductors has attracted mounting attention for photocatalytic applications. However, more efforts are needed to unravel the interface structure in MOF/semiconductor composites and its role in charge transfer. In this paper, a MIL-100(Fe)/TiO 2 composite was synthesized as a prototypical photocatalyst and studied systematically to explore the interface structure and unravel the charge transfer pathways during the photocatalytic processes. The composite was fabricated by growing MIL-100(Fe) crystals on TiO 2 using surface-coated FeOOH as the precursor. The as-prepared MIL-100(Fe)/TiO 2 exhibited significantly improved photocatalytic performance over pristine TiO 2 , which was mainly because of the enhanced charge separation as confirmed by transient absorption spectroscopy analysis. This enhancement partially arose from the special chemical structure at the interface, where the Fe-O-Ti bond was formed. As verified by the density functional theory calculation, this distinct structure would create defect energy levels adjacent to the valence band maximum of TiO 2 . During the photocatalytic processes, the defect energy levels serve as sinks to capture excited charge carriers and retard the recombination, which subsequently leads to the increased charge density and promoted photocatalytic efficiency. Meanwhile, the intimate interactions between MIL-100(Fe) and TiO 2 would also help to improve the charge separation by transferring photo-induced holes through the ligands to Fe-O clusters. Lastly, these findings would advance the fundamental understanding of the interface structure and the charge transfer pathways in MOF/semiconductor composite photocatalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ab initio metadynamics calculations reveal complex interfacial effects in acetic acid deprotonation dynamics

Acid-base reactions play a central role in solution chemistry, with carboxylic acids being particularly important in atmospheric chemical processes. In this work, we harness metadynamics calculations with Born-Oppenheimer molecular dynamics (BOMD) simulations to understand deprotonation dynamics of acetic acid (CH 3 COOH) in both bulk and air-water interfacial environments. Collective variables are carefully chosen in our well-tempered metadynamics simulations to capture the deprotonation process in various aqueous configurations. Herein, our findings show that the free energy barrier for deprotonation of acetic acid at the air-water interface is lower than in the bulk, in accordance with the available experimental data. Furthermore, our well-tempered metadynamics calculations suggest that the variations in free energy are primarily due to intricate solvation shell effects.

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

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.

Wolfe, Bradley T. (ORCID:0000000268301614)↗
DOE OSTI2022

(U) SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, k eff , α , and Subcritical Multiplication Using PARTISN

SENSMG is a tool for computing first-order sensitivities of neutron reaction rates, reaction-rate ratios, leakage, k eff , α, and subcritical multiplication using the PARTISN multigroup discrete-ordinates code. SENSMG computes sensitivities to all of the transport cross sections and data (total, fission, a nu, chi, and all scattering moments), two edit cross sections (absorption and capture), and the density for every nuclide and energy group. It also computes sensitivities to the mass density for every material and derivatives with respect to all interface locations and outer boundaries. It computes sensitivities to user specified reactions whose cross sections are available in a user-supplied NJOY output file. The tool can be used for one-dimensional spherical and slab (r) and two-dimensional cylindrical (r-z) geometries. The tool can be used for fixed-source and eigenvalue problems. For most responses, the tool implements Generalized Perturbation Theory (GPT) as discussed by Williams and Stacey. The tool is thus limited to computing sensitivities only for GPT-allowable responses. For subcritical multiplication, the tool implements sensitivities derived by O’Brien and Clark. SENSMG has a similar role as the old SWANLAKE (Ref. 8), FORSS (Ref. 9), and SENSIT (Ref. 10) codes. It has capabilities similar to those of SUSD3D (Refs. 11 and 12), which also uses PARTISN. Section II of this report describes the theory behind adjoint-based sensitivities, gives the equations that SENSMG solves, and defines the sensitivities that are output. Section III describes the user interface, including the input file and command line options. Section IV describes the output. Section V gives some notes about the coding that may be of interest. Section VI presents some sample problems and discusses verification, which is ongoing. Section VII lists needs and ideas for future work. Appendix A lists most of the input files whose results are presented in Sec. VI. Appendix B provides some useful details on one of the cross-section libraries that SENSMG supports.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Measuring Vibronic Coupling and Ultrafast Charge Delocalization on Nanocrystal Surfaces Using Ligand-Specific Vibrational Probes

The primary goal of this proposal was to measure and quantify how vibronic ligand-exciton interactions at the inorganic-organic interface of semiconductor nanocrystals (NCs) govern femtosecond non-radiative relaxation and charge delocalization mechanisms as a function of nanocrystal and ligand structures – including NC size, shape, and ligand identity. Molecular-scale chemical and physical properties and interactions of surface ligands dictate nanocrystal exciton dynamics on the femto-to-microsecond timescales. Improvements in synthesis, experimental, and theoretical characterizations have enhanced our understanding of NC photophysics. However, quantitative descriptions of complex ligand-exciton interactions at the NC surface have remained elusive, which limits elucidation of relaxation mechanisms that determine overall carrier transfer dynamics at the exciton-ligand interface. Thus, the central motivation for this proposal was to fill a significant knowledge gap for judicious selection of ligand-functionalized nanocrystals for targeted isolation and capture of charge carriers to drive selective organic photocatalytic transformations in NC photocatalysts and NC-assembled photonic materials. Our unique two-pronged experimental approach combining nanocrystal synthesis and ligand-specific nonlinear spectroscopy has resulted in (i) four peer-reviewed publications; (ii) 12+ invited and contributed posters and talks at national and international scientific meetings and seminars, (iii) two completed PhD theses, (iv) training of two postdoctoral researchers, three PhD students, and two undergraduate students, and (v) two manuscripts under preparation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Back-surface recombination, electron reflectors, and paths to 28% efficiency for thin-film photovoltaics: A CdTe case study

As thin-film and silicon solar technologies mature, questions emerge about the upper bounds of thin-film solar performance and realistic experimental paths to reach them. Directions include increasing absorber hole density and bulk lifetime, improving the junction interface, reducing back-surface recombination, and implementing a back-surface electron reflector. Textbook solutions of idealized p-n junctions create a powerful conceptualization of solar cells as predominantly minority-carrier-driven devices. We demonstrate that thin films are distinct, and models often fail to capture the important role of majority-carrier lifetime, leading to contradictions with lifetime measurements and overestimates of potential device improvement from back-surface passivation and/or reflectors. Furthermore, we identify methods to probe majority-carrier lifetime and re-examine the degree to which back-surface passivation and electron reflectors can increase efficiency for a range of common thin-film interface and absorber properties, using current and emerging CdTe technology as an example. Here, the results indicate that a practical approach is to focus first on improving front-interface recombination velocity and the absorber properties, and then on implementing the back-surface passivation or reflector, which can ultimately allow thin-film solar technology to reach 28% efficiency.

14 SOLAR ENERGY↗
DOE OSTI2018

Structures of the fungal dynamin-related protein Vps1 reveal a unique, open helical architecture

Dynamin-related proteins (DRPs) are large multidomain GTPases required for diverse membrane-remodeling events. DRPs self-assemble into helical structures, but how these structures are tailored to their cellular targets remains unclear. We demonstrate that the fungal DRP Vps1 primarily localizes to and functions at the endosomal compartment. We present crystal structures of a Vps1 GTPase–bundle signaling element (BSE) fusion in different nucleotide states to capture GTP hydrolysis intermediates and concomitant conformational changes. Using cryoEM, we determined the structure of full-length GMPPCP-bound Vps1. The Vps1 helix is more open and flexible than that of dynamin. This is due to further opening of the BSEs away from the GTPase domains. A novel interface between adjacent GTPase domains forms in Vps1 instead of the contacts between the BSE and adjacent stalks and GTPase domains as seen in dynamin. Disruption of this interface abolishes Vps1 function in vivo. Hence, Vps1 exhibits a unique helical architecture, highlighting structural flexibilities of DRP self-assembly.

Varlakhanova, Natalia V.↗
DOE OSTI2019

Relating Structural and Microstructural Evolution to the Reactivity of Cellulose and Lignin during Alkaline Thermal Treatment with Ca(OH) 2 for Sustainable Energy Production Integrated with CO 2 Capture

The transition toward a low carbon economy necessitates the implementation of a wide range of negative emissions technologies, including bioenergy integrated with CO 2 capture and storage. Advancing large-scale or modular technologies for bioenergy with carbon capture and storage requires a fundamental understanding of chemo-morphological coupling in these material systems. In this context, integrated chemical pathways such as alkaline thermal treatment (ATT) of biomass which involves the production of bio-H 2 while converting and storing CO 2 as solid carbonates provides promising potential for integrating bioenergy with carbon capture and storage. We elucidate the structural and morphological changes when biomass feedstocks such as cellulose and lignin are reacted with calcium hydroxide to capture, convert, and store CO 2 as calcium carbonate while producing energy carrier such as H 2 . These structural and morphological changes were monitored using synchrotron based in operando multiscale X-ray scattering measurements. Enhanced CO 2 capture at temperatures above 375 °C was evident from the significant growth of the calcium carbonate phase at these conditions. Increase in the surface area and porosity of cellulose was noted compared to lignin due to the relatively fast decomposition of cellulose. Pore–solid interfaces in Ca(OH) 2 + cellulose system became smoother in the temperature range of 500–700 °C compared to Ca(OH) 2 + lignin system, where the interfaces became rougher. Enhanced roughness of the pore–solid interfaces in the presence of lignin is attributed to the simultaneous slow decomposition of lignin and formation of calcium carbonate.

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

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain–affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. Further, the integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Multifidelity computing for coupling full and reduced order models

Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a multifidelity problem sharing an interface between various formulations or heterogeneous computational entities. To this end, we present a robust hybrid analysis and modeling approach combining a physics-based full order model (FOM) and a data-driven reduced order model (ROM) to form the building blocks of an integrated approach among mixed fidelity descriptions toward predictive digital twin technologies. At the interface, we introduce a long short-term memory network to bridge these high and low-fidelity models in various forms of interfacial error correction or prolongation. The proposed interface learning approaches are tested as a new way to address ROM-FOM coupling problems solving nonlinear advection-diffusion flow situations with a bifidelity setup that captures the essence of a broad class of transport processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Robust Dissimilar Metal Friction Welded Spool for Enhanced Capability for Steam Power Components (Final Program Report)

This project successfully demonstrated the feasibility and advantages of producing durable, friction-welded dissimilar-metal spools, both with and without transition pieces, as well as the use of advanced oxidation-protective coatings for steam power applications. The work encompassed the optimization and full-scale production of NFA tubing, overcoming manufacturing and processing challenges to achieve enhanced strength, creep, and fatigue properties validated by extensive microstructural characterization. Optimized welding techniques were developed and refined for joining dissimilar materials, resulting in defect-free welds optimized for both low- and high-pressure boiler circuits. Systematic evaluation of welding parameters, coupled with heat treatments, ensured reliable performance and minimized weld defects such as banding and cracking. Comprehensive mechanical and non-destructive testing, including tensile, bend, fatigue, and CT scanning, confirmed the superior integrity and durability of the friction-welded joints under representative service conditions. To address oxidation-related degradation, a range of protective alloy coatings—such as IN625, APMT, Duplex 2507, and FeCrAlY—were selected and evaluated for their ability to counteract oxide notch formation at dissimilar metal interfaces. These coatings demonstrated improved oxidation resistance and long-term stability under thermal cycling, thereby extending weld service life. Thermal cyclic testing and long-term studies captured the phase stability and diffusion behavior of coated and uncoated configurations. Validated models for low-cycle fatigue (LCF), creep, and thermal mechanical fatigue (TMF) were developed to predict component life and failure modes. These models confirmed that friction-welded configurations exhibited significantly enhanced performance compared to conventional gas-tungsten arc welding (GTAW), with up to 7× improvement in creep resistance and at least 2× enhancement in fatigue properties. The introduction of a tailored transition piece further reduced thermally induced strains, enhancing fatigue life. The results demonstrate a robust pathway for retrofitting existing steam fleet components and upgrading future equipment to deliver substantially improved cold-start cycling behavior and reduction of unplanned outages due to premature weld failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Qualification of a multi-diagnostic detonator-output characterization procedure utilizing PMMA witness blocks

In this study, experiments were conducted to qualify a multi-diagnostic characterization procedure for the performance output of a detonator when fired into a poly(methyl methacrylate) (PMMA) witness block. A suite of optical diagnostics were utilized in combination to both bound the shock wave interaction state at the detonator/PMMA interface and characterize the nature of the shock wave decay in PMMA. The diagnostics included the Shock Wave Image Framing Technique (SWIFT), a photocathode tube streak camera, and photonic Doppler velocimetry (PDV). High-precision, optically clear witness blocks permitted dynamic flow visualization of the shock wave in PMMA via focused shadowgraphy. SWIFT-and streak-imaging diagnostics captured the spatiotemporally evolving shock wave, providing a two-dimensional temporally discrete image set and a one-dimensional temporally continuous image, respectively. PDV provided the temporal velocity history of the detonator output along the detonator axis. Lastly, through combination of the results obtained, a bound was able to be placed on the interface condition and a more-physical profile representing the shock wave decay in PMMA for an exploding-bridgewire detonator was achieved.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

A scalable Euler–Lagrange approach for multiphase flow simulation on spectral elements

Multiphase flow can be difficult to simulate with high accuracy due to the wide range of scales associated with various multiphase phenomena. These scales may range from the size of individual particles to the entire domain of interest. Traditionally, large scale systems can only be simulated using averaging approaches that filter out the locations of individual particles. In this work, the Euler–Lagrange method is used to simulate large-scale dense particle systems in which each individual particle is tracked. In order to accomplish this, the highly scalable spectral element code nek5000 has been extended to handle the multiple levels of multiphase coupling in these systems. These levels include what has been called one-, two-, and four-way coupling. Here, each level has been separated to detail the computational impact of each stage. A binned ghost particle algorithm has also been developed to efficiently handle the challenges of two- and four-way coupling in a parallel processing context. The algorithms and their implementations are then shown to scale to 65,536 Message Passing Interface (MPI) ranks in both the strong and weak limits. After this, validation is performed through simulation of a small-scale fluidized bed. Lastly, a large-scale fluidized bed is simulated with 65,536 MPI ranks and is able to capture the unique physics of the onset of fluidization.

Computer Science↗