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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID , toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5′-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.

Methanosarcina acetivorans↗
DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Edgecomb, Joseph↗
DOE OSTI2025

Measuring the flatband potential in 2D semiconductors: Pitfalls and a possible SECCM solution

The flatband potential (V fb ) is a critical parameter in semiconductor electrochemistry, defining the potential at which no excess charge exists at the semiconductor/electrolyte interface. It serves as a key reference for interpreting charge transfer kinetics and current–voltage behavior. However, conventional methods like Mott–Schottky analysis fail for atomically thin 2D materials due to the breakdown of the depletion approximation. This perspective examines the limitations of traditional V fb measurements for 2D semiconductors and the experimental challenges that arise. To address these issues, we propose using scanning electrochemical cell microscopy (SECCM) to spatially resolve the potential of zero charge (V pzc ), equivalent to V fb . This approach mitigates sample heterogeneity issues, such as pinholes or multilayer defects, and offers a pathway to more accurate electrochemical characterization. Ultimately, this method will enhance understanding of current–potential behavior in 2D materials, supporting the design of advanced systems for photoelectrocatalysis, energy conversion, and sensing.

2D semiconductors↗
DOE OSTI2024

Structural Characterization of Disulfide-Linked p53-Derived Peptide Dimers

Disulfide bonds provide a convenient method for chemoselective alteration of peptide and protein structure and function. We previously reported that mild oxidation of a p53-derived bisthiol peptide (CTFANLWRLLAQNC) under dilute non-denaturing conditions led to unexpected disulfide-linked dimers as the exclusive product. The dimers were antiparallel, significantly α-helical, resistant to protease degradation, and easily reduced back to the original bisthiol peptide. Here, in this work, we examine the intrinsic factors influencing peptide dimerization using a combination of amino acid substitution, circular dichroism (CD) spectroscopy, and X-ray crystallography. CD analysis of peptide variants suggests critical roles for Leu6 and Leu10 in the formation of stable disulfide-linked dimers. The 1.0 Å resolution crystal structure of the peptide dimer supports these data, revealing a leucine-rich LxxLL dimer interface with canonical knobs-into-holes packing. Two levels of higher-order oligomerization are also observed in the crystal: an antiparallel “dimer of dimers” mediated by Phe3 and Trp7 residues in the asymmetric unit and a tetramer of dimers mediated by Trp7 and Leu10. In CD spectra of Trp-containing peptide variants, minima at 227 nm provide evidence for the dimer of dimers in dilute aqueous solution. Importantly, and in contrast to the original dimer model, the canonical leucine-rich core and robust dimerization of most peptide variants suggests a tunable molecular architecture to target various proteins and evaluate how folding and oligomerization impact various properties, such as cell permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Preventing native oxide formation in niobium thin films through platinum encapsulation

Superconducting transmon qubits are a key technology in quantum computing, with niobium (Nb) widely used due to its favorable superconducting properties and compatibility with scalable fabrication. However, the performance of Nb-based qubits is hindered by two-level systems (TLS), which arise predominantly from native oxide layers at surfaces and interfaces. These oxides and suboxides form rapidly in air and contribute significantly to decoherence by introducing dielectric losses. While various mitigation strategies, including thermal-annealing, chemical-etching, and nitrogen plasma treatment, have been explored, many are challenging to integrate into large-scale manufacturing due to complexity and instability in ambient conditions. In this study, we investigate the structural, chemical, and superconducting properties of room-temperature sputtered Nb thin films grown on sapphire substrates. We focus on a surface protection strategy using noble metal encapsulation with platinum (Pt) to suppress oxides and reduce TLS-related losses. Structural and chemical characterization were performed using X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy. Superconducting properties were measured using a physical property measurement system. Results demonstrate that Pt encapsulation effectively suppresses surface oxidation and mitigates its detrimental impact on superconducting performance. In conclusion, this approach offers a promising path toward enhancing the coherence of Nb-based qubits while remaining compatible with scalable-fabrication processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties). To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties).To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

UNLOQ: UNderstanding coherence in Light-matter interfaces for Quantum Science (Final Technical Report)

The general goal of this project is to prepare next-generation quantum systems for novel quantum information science applications. Decades of research on quantum optics have provided revolutionary systems for manipulating atomic and photonic quantum coherence in transformative ways. Our hypothesis is that the next-generation quantum systems will come from nano-molecular quantum optics. Specifically, we are interested in coupling the electronic states of molecules or nanoparticles to the quantized radiation field inside an optical cavity to create a set of new photon-matter hybrid excitations, called polaritons. As opposed to atoms, the vibrational modes of molecules and nanoparticles provide new degrees of freedom to mediate the quantum transduction between electronic and photonic states, offering new ways to tune and ultimately control the quantum coherence of the integrated system. In this project we are interested in designing, fabricating, and characterizing the polaritons that arise from coupling CdSe nanoplatelets (NPLs) to a Fabry-Pérot optical cavity. Specific attention was paid to parameters of the system (cavity mode volume, quality factor, etc.) that would maximize the collective coupling strength. Through a combined theoretical and experimental approach, we were able to make important contributions to understanding NPL exciton-polariton photophysics including how to use cavity loss as a tunable parameter in order to manipulate the populations of the upper and lower polariton states. Finally, using state-of-the-art theoretical methods, we were able to show how the collective coupling of many molecular excitons in a cavity can protect polariton coherence from vibrationally-induced decoherence. In particular, for NPL-cavity polaritonic systems, the quantum coherence can be extended by over an order of magnitude at room temperature.

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

Complex polycation redox material interfaced with renewable porous carbon for asymmetric supercapacitors

Mixed polycation transition metal ferrites are known to exhibit unique and superior characteristics for structural, electrical, magnetic, and optical applications. Although a few binary transition metal ferrites are found to be suitable for electrochemical energy storage application, ternary transition metal ferrites are not investigated for asymmetric supercapacitors (ASCs). Mixed polycation oxides are expected to have increased active sites that can facilitate proton and electron transfer impacting the redox reactions. Specific crystal structure and associated lattice parameters as well as surface and morphological characteristics can also influence the energy storage properties. This study for the first time reports a novel complex polycation redox material, (Cu p Mn q Zn r ) x Fe y O z and renewable pinewood (PW) derived porous carbon (POC) as electrodes for ASC. Both (Cu p Mn q Zn r ) x Fe y O z and PW-POC are subjected to electrochemical characterization and used in ASC configuration with aqueous KOH electrolyte. It is anticipated that the Faradaic characteristics of (Cu p Mn q Zn r ) x Fe y O z will make it to serve as a cathode while PW-POC with capacitive behavior will act as anode in ASCs. Relatively higher specific capacitance of > 200 F/g is observed for the (Cu p Mn q Zn r ) x Fe y O z reference electrode and fabricated ASCs. Capacitance retention rate is tested in 10,000 cycles for the working electrodes whereas for ASC, the stability tests are performed over 100 charging-discharging cycles exhibiting relatively higher capacitance retention. (Cu p Mn q Zn r ) x Fe y O z appears to be a promising material for a supercapacitor.

(CupMnqZnr)xFeyOz↗
DOE OSTI2025

Spontaneous sodium ion storage behaviors of reduced graphene oxide anodes exceeding 100% Coulombic efficiency by modulated ion solvation

Rechargeable batteries are essential energy storage devices that power portable devices and electrical vehicles throughout the world. In general, it is thought that the electrochemical performance of rechargeable batteries is mostly determined by the electrodes within them and that the electrolyte plays a relatively passive role. However, ion transport and storage can be greatly influenced by the electrolyte solution structure, specifically, ion solvation within the bulk and ion desolvation across the electrode/electrolyte interfaces. Herein, we studied the role of the electrolyte as an active component of electrochemical energy storage devices. We found that with an appropriate electrolyte formulation, ion storage in disordered carbonaceous anode materials can occur spontaneously without externally supplied electrical energy. Reduced graphene oxide (RGO) in an ether-based electrolyte demonstrates ‘spontaneous' ion storage behaviors of adsorbing and inserting the solvated ions utilizing facilitated permeability and wettability of RGO, which results in Coulombic efficiency of ~145% due to additional charging capacity of ~180 mAh g -1 during electrochemical processes. The unexpected spontaneous ion storage behavior was extensively investigated using a combination of electrochemical analyses and diagnostics, advanced characterizations, and computational simulation. In conclusion, we believe the spontaneous ion storage behavior offers a new way to further improve the energy efficiency of practical rechargeable batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

End-to-End Automated Segmentation Framework for Four-Dimensional Scanning Transmission Electron Microscopy Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) is powerful for rapidly characterizing arrays of nanoparticles produced via high-throughput synthesis. However, such 4D-STEM datasets typically contain thousands of nanoparticles, each characterized by thousands of diffraction patterns spatially distributed across the nanoparticle, necessitating efficient and comprehensive analysis. We propose an end-to-end segmentation framework to automatically segment each nanoparticle into regions with distinct composition/orientation of crystal grains, using only the 4D-STEM data. Bragg disk information is extracted in a physics-informed manner from the diffraction patterns at each spatial location and combined with the real space coordinates to form feature vectors. These feature vectors are then used as inputs to a Gaussian mixture model (GMM) to segment the nanoparticle into distinct regions. We also develop two visualization tools based on the GMM outputs to infer the interface transition and the degree of superposition. Our framework comprehensively integrates machine learning tools and physics knowledge, and provides a basis for substantially compressing enormous 4D-STEM datasets, e.g., by replacing the full 4D-STEM dataset for each nanoparticle with only a single set of Bragg disk features for each distinct crystal grain identified in the nanoparticle. In this article, we demonstrate the power of our framework by presenting results for real, complex datasets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Conformational free energy landscape of a glutamate transporter and microscopic details of its transport mechanism

Removing glutamate from the synaptic cleft is vital for proper function of the brain. Excitatory amino acid transporters mediate this process by uptaking the neurotransmitter from the synaptic cleft back to the cell after its release. The archaeal homolog, Glt Ph , an aspartate transporter fromPyrococcus horikoshii, presents the best structurally characterized model for this family of transporters. In order to transport, Glt Ph undergoes elevator-like conformational changes between inward-facing (IF) and outward-facing (OF) states. Here, we characterize, at an atomic level, the OF⇌IF transition of Glt Ph in differentapo/bound states using a combination of ensemble-based enhanced sampling techniques, employing more than two thousand of coupled simulation replicas of membrane-embedded Glt Ph . The resulting free-energy profiles portray the transition ofapo/bound states as a complex four-stage process, while sodium binding alone locks the structure in one of its states. Along the transition, the transport domain (TD) disengages from the scaffold domain (SD), allowing it to move as a piston sliding vertically with respect to the membrane during the elevator-like motion of TD. Lipid interactions with residues comprising the SD–TD interface directly influence the large-scale conformational changes and, consequently, the energetics of transport. Structural intermediates formed during the transition leak water molecules and may correlate to the uncoupled Cl − ion conductance observed experimentally in both prokaryotic and mammalian glutamate transporters. Mechanistic insights obtained from our study provide a structural framework for better development of therapeutic for neurological disorders.

Science & Technology - Other Topics↗
DOE OSTI2024

Intrinsic exchange bias from interfacial reconstruction in an epitaxial Ni x Co y Fe 3– x – y O 4 (111)/α-Al 2 O 3 (0001) thin film family

Intrinsic exchange bias is known as the unidirectional exchange anisotropy that emerges in a nominally single-component ferro-(ferri-)magnetic system. In this work, with magnetic and structural characterizations, we demonstrate that intrinsic exchange bias is a general phenomenon in (Ni, Co, Fe)-based spinel oxide films deposited on α-Al 2 O 3 (0001) substrates, due to the emergence of a rock-salt interfacial layer consisting of antiferromagnetic CoO from interfacial reconstruction. We show that in Ni x Co y Fe 3–x–y O 4 (111)/α-Al 2 O 3 (0001) films, intrinsic exchange bias and interfacial reconstruction have consistent dependences on Co concentration y, while the Ni and Fe concentration appears to be less important. This work establishes a family of intrinsic exchange bias materials with great tunability by stoichiometry and highlights the strategy of interface engineering in controlling material functionalities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2024

Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics

In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity $\overline{k_{L}}$, where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts $\overline{k_{L}}$ = α o Sc -1/2 ($v\bar{ϵ}$) 1/4 , where Sc is the molecular Schmidt number, $v$ is the water kinematic viscosity, and $\bar{ϵ}$ is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While α o = 0.39 - 0.46 has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous ϵ around $\bar{ϵ}$, a mechanism that was not previously considered. As the coefficient of variation (CV e ) in ϵ increases, α o must be adjusted by a multiplier (1 = CV e 2 ) -3/32 that was derived from a log‐normal model for the probability density function of ϵ. Reported variations in α o with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in ϵ. Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of ϵ. That α o varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade.

Batchelor scale↗
DOE OSTI2024

Embedded symmetric positive semi-definite machine-learned elements for reduced-order modeling in finite-element simulations with application to threaded fasteners

Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Advanced Diagnosis and Accelerated Testing of Balance of System Components for Utility Scale PV Installations: October 1, 2022-September 30, 2024

A study of the durability of PV Balance of System components was performed. Specifically, wire cable jackets and cable connectors were examined within the direct current (DC) PV Power Transmission Chain (PTC). Degraded and failed samples have been obtained from utility PV installations to provide feedback on the degradation modes and the related damage-enabling considerations in today's PV systems. An industry interface group (including system owners, system inspectors, component manufacturers, and test labs) was used to help identify and obtain field-failed samples, for feedback (including samples and experimental design), and to facilitate the subsequent dissemination of the results of this study. Samples were empirically studied using accelerated stress testing with steady-state conditions (cable jackets) in addition to combined-accelerated stress testing (cable jackets, connectors and uncapped connectors). Steady-state accelerated testing has been performed using at least one applied stressor (e.g. UV light) to aid understanding of jacket durability relative to its application. Component- and material-focused failure analysis was conducted to develop an understanding and advise the PV industry. In-depth characterization will be applied selectively to field- and artificially aged-samples, to gain scientific understanding of the structural, chemical, electrical, mechanical, and thermal properties enabling degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗