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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Error-mitigated nonorthogonal quantum eigensolver via shadow tomography

We present a shadow-tomography-enhanced nonorthogonal quantum eigensolver (NOQE) for more efficient and accurate electronic structure calculations on near-term quantum devices. By integrating shadow tomography into the NOQE, the measurement cost scales linearly rather than quadratically with the number of reference states, while also reducing the required qubits and circuit depth by half. This approach enables extraction of all matrix elements via randomized measurements and classical postprocessing. We analyze its sample complexity and show that, for small systems, it remains constant in the high-precision regime, while for larger systems, it scales linearly with the system size. We further apply shadow-based error mitigation to suppress noise-induced bias without increasing quantum resources. Demonstrations on the hydrogen molecule in the strongly correlated regime achieve chemical accuracy under realistic noise, showing that our method is both resource-efficient and noise-resilient for practical quantum chemistry simulations in the near term.

quantum algorithms & computation↗
DOE OSTI2024

Simulation of open quantum systems via low-depth convex unitary evolutions

Simulating physical systems on quantum devices is one of the most promising applications of quantum technology. Current quantum approaches to simulating open quantum systems are still practically challenging on NISQ-era devices, because they typically require ancilla qubits and extensive controlled sequences. In this work, we propose a hybrid quantum-classical approach for simulating a class of open system dynamics called random-unitary channels. These channels naturally decompose into a series of convex unitary evolutions, which can then be efficiently sampled and run as independent circuits. The method does not require deep ancilla frameworks and thus can be implemented with lower noise costs. We implement simulations of open quantum systems up to dozens of qubits and with large channel ranks. Published by the American Physical Society 2024

Peetz, Joseph (ORCID:0000000274458028)↗
DOE OSTI2025

High-Throughput Discovery Illuminates Design Principles and Limits for Long-Lived Charged Species in Organic Electrolytes

The chemical stability of charged molecules in all-organic redox flow batteries (RFBs) is required for the prolonged operation of these devices. Molecular engineering and electrolyte optimization are used to mitigate parasitic reactions and extend the lifetimes of the charge carriers. However, how much can structural variation extend the lifetime? To probe this query, we designed a high-throughput kinetic study of the radical cation of N-methylphenothiazinium, guided by statistical sampling and learning algorithms. Using Argonne’s autonomous discovery facility, we conducted over 6,000 kinetic experiments with robotic sample preparation, parallel kinetic measurements, and machine learning inputs, testing 188 solvent molecules selected from a space of over 540 candidates from 11 chemical classes. Algorithmic selections guided us to stable solvent candidates, which were further tested in high concentration with and without supporting electrolyte. Our findings reveal the inherent difficulty of exceeding the current state of the art through solvent variation. The desired stability is statistically rare and poorly predictable. Among the many tested, only three solvents significantly outperformed our baseline, acetonitrile─and none by more than a factor of 3─suggesting a general challenge in achieving the necessary techno-economic targets. Furthermore, we suggest that self-discharge through solvent homolysis is the cause of the observed limitations. Several structural motifs contribute to >1,000 h half-life stability including molecular simplicity, symmetry, oxidation complement, and strategic fluorination. Importantly, this workflow establishes effective assays for diagnosing and predicting oxidative stress for highly stable liquid electrolytes in all batteries.

Batteries↗
DOE OSTI2025

Cybersecurity Enhancement in Digital Substations: Hidden Markov Model-Based Smart Cyber Switching and Threat Response

The rising incidence of cyber-attacks on critical infrastructure and power grids poses significant threats to the stability and reliability of electrical substations, with potentially devastating consequences such as extended blackouts. This paper introduces an advanced cybersecurity framework aimed at safeguarding IEC 61850-based substations through the integration of software-defined networking (SDN) and digital twin (DT) technologies. The proposed DT-based framework employs smart cyber switching (SCS) for proactive threat mitigation and concurrent intelligent electronic device (CIED) for swift system restoration, thereby maintaining continuous operational integrity and robust cybersecurity defenses. Central to this framework is the adaptive port controller (APC), which enables dynamic port management to adapt to evolving threats, and an intrusion detection system (IDS) designed to detect and neutralize malicious attacks on IEC 61850-based sampled value (SV) and generic object-oriented substation event (GOOSE) messages within the substation’s communication network. Further, novel predictive intrusion detection and response (PIDR) algorithm is implemented on a digital substation (DS) to predict the best route to be taken by the attacker. The efficacy of these comprehensive cybersecurity frameworks is validated through rigorous simulations and a hardware-in-the-loop (HIL) testbed, showcasing the system’s ability to sustain substation operations amidst cyber-attacks.

Digital substation↗
DOE OSTI2025

Characterization of fluorite-structured ferroelectrics using transmission electron microscopy: Techniques, challenges, and recent advances

Fluorite-structured ferroelectrics, such as hafnium oxide and its alloyed variants, are key candidates for next-generation memory devices. Yet, fundamental questions about switching mechanisms, domain dynamics, and phase evolution remain open. Transmission electron microscopy (TEM) provides unique capabilities to address these challenges by simultaneously resolving the positions of anions and cations, chemical variations, and structural transformations. Recent advances—including in situ heating, electron beam-induced switching, electron energy loss spectroscopy, and differential phase contrast imaging—have revealed critical insights into phase transitions, potential switching pathways, and oxygen vacancy behavior. However, experimental barriers such as TEM sample-preparation-induced artifacts, high coercive fields, and imaging constraints persist, especially for polycrystalline films. By offering a focused overview of current TEM developments in fluorite ferroelectrics, this work outlines how TEM contributes to understanding key phenomena and proposes a roadmap for future studies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Strain Relaxation and Relative Defect Density with Thickness in MBE-Grown Ge 0.85 Sn 0.15 on Ge(001)

Germanium–tin (GeSn) alloys are emerging as promising materials for mid-infrared optoelectronics and silicon-compatible photonic devices, owing to their tunable direct bandgap. However, the growth of high-quality GeSn films with high Sn content remains challenging due to strain-induced defect formation. In this study, we investigate the role of film thickness on strain-induced relaxation, defect density, and Sn segregation. A series of five samples with varying thicknesses and ∼15% Sn-containing GeSn layers were grown, ranging from the critical thickness for strain relaxation to the onset of Sn segregation. All GeSn samples were analyzed using X-ray diffraction reciprocal space mapping (XRD-RSM) to explore the evolution of strain-induced relaxation as a function of thickness. Photoluminescence measurements reveal that increasing the GeSn thickness enhances strain relaxation while reducing defect-related emission, indicating a decrease in effective defect density prior to reaching the threshold thickness of GeSn layer. At a thickness of ∼150 nm, the GeSn layer shows the onset of Sn segregation, evident in the XRD-RSM spectrum, marking the threshold thickness for Sn segregation. This work defines an effective growth window in terms of thickness (35 to 150 nm) for fabricating relaxed, defect-suppressed GeSn layers with 15% Sn content. These findings emphasize the crucial role of thickness control in balancing strain relaxation and defect suppression, advancing the fabrication of high-quality, high Sn-content relaxed GeSn using molecular beam epitaxy.

Defects↗
DOE OSTI2025

Nanoscale control of LaAlO 3 /SrTiO 3 conductance beyond the polar catastrophe

Conductive atomic force microscope (c-AFM) lithography can be utilized to create a wide range of LaAlO 3 /SrTiO 3 (LAO/STO)-based nanoelectronic devices in a reconfigurable manner. Experiments were generally performed with intrinsically insulating LAO/STO heterostructures, with LAO thickness less than the critical value at which a polar catastrophe takes place [<4 unit cell (u.c.)]. Here, we use inductively coupled plasma reactive ion etching (ICPRIE) to fabricate c-AFM “canvases” on intrinsically conducting LAO/STO samples with ≥4 u.c. LAO. We observe that its interfacial two-dimensional electron gas (2DEG) can be pinched off and then switched back on by c-AFM lithography. Nanowires created with initially conductive LAO/STO interfaces have an order-of-magnitude longer lifetime in ambient conditions, when compared to an identically created 3.4 u.c. LAO/STO nanowire. We also demonstrate key nanoscale properties such as ballistic transport in a quasi-one-dimensional electron waveguide at a 5 u.c. LAO/STO interface. This approach frees c-AFM-written nanodevice designs from time constraints in air associated with <4 u.c. LAO/STO heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SDN-Based Smart Cyber Switching (SCS) for Cyber Restoration of a Digital Substation

In recent years, critical infrastructure and power grids have increasingly been targets of cyber-attacks, causing widespread and extended blackouts. Digital substations are particularly vulnerable to such cyber incursions, jeopardizing grid stability. This paper addresses these risks by proposing a cybersecurity framework that leverages software-defined networking (SDN) to bolster the resilience of substations based on the IEC- 61850 standard. The research introduces a strategy involving smart cyber switching (SCS) for mitigation and concurrent intelligent electronic device (CIED) for restoration, ensuring ongoing operational integrity and cybersecurity within a substation. The SCS framework improves the physical network’s behavior (i.e., leveraging commercial SDN capabilities) by incorporating an adaptive port controller (APC) module for dynamic port management and an intrusion detection system (IDS) to detect and counteract malicious IEC-61850-based sampled value (SV) and generic object-oriented system event (GOOSE) messages within the substation’s communication network. The framework’s effectiveness is validated through comprehensive simulations and a hardware-in-the-loop (HIL) testbed, demonstrating its ability to sustain substation operations during cyber-attacks and significantly improve the overall resilience of the power grid.

Liu, Chen-Ching (ORCID:0000000289417958)↗
DOE OSTI2025

A Modified Model Dielectric Function for Analyzing Optical Spectra of InGaN Nanofilms on Sapphire Substrates

Due to a lower InN bandgap energy Eg~0.7 eV, InxGa1−xN/Sapphire epifilms are considered valuable in the development of low-dimensional heterostructure-based photonic devices. Adjusting the composition x and thickness d in epitaxially grown films has offered many possibilities of light emission across a wide spectral range, from ultraviolet through visible into near-infrared regions. Optical properties have played important roles in making semiconductor materials useful in electro-optic applications. Despite the efforts to grow InxGa1−xN/Sapphire samples, no x- and d-dependent optical studies exist for ultrathin films. Many researchers have used computationally intensive methods to study the electronic band structures Ejk→, and subsequently derive optical properties. By including inter-band transitions at critical points from Ejk→, we have developed a semiempirical approach to comprehend the optical characteristics of InN, GaN and InxGa1−xN. Refractive indices of InxGa1−xN and sapphire substrate are meticulously integrated into a transfer matrix method to simulate d- and x-dependent reflectivity RE and transmission TE spectra of nanostructured InxGa1−xN/Sapphire epifilms. Analyses of RE and TE have offered accurate x-dependent shifts of energy gaps for InxGa1−xN (x = 0.5, 0.7) in excellent agreement with the experimental data.

Talwar, Devki N. (ORCID:0000000202723195)↗
DOE OSTI2025

UV-Enabled Defect Engineering in Multilayer GaSe and InSe and UV Writing of the Grating Pattern

III–VI post-transition-metal chalcogenides are layered semiconductor materials that exhibit direct band gaps in multilayers. Defect engineering is essential in 2D layered semiconductors for functional devices. Here, in this work, we report defect engineering in multilayer gallium selenide (GaSe) and indium selenide (InSe), where defects generated by ultraviolet (UV, 325 nm) laser irradiation result in an additional photoluminescence (PL) line. The additional PL line is due to defect-bound excitons. Characteristics of the defect emission are similar in GaSe and InSe samples subjected to UV irradiation, air annealing, and hydrostatic pressure. Two-beam UV interference was applied to create grating patterns with a periodic array of low and high densities of defects in GaSe. Density functional theory has identified the defect type in GaSe. The results provide valuable insights into defect generation and UV scribing of photonic circuits in 2D Se-based multilayers for optical integration in a 2D platform.

2D multilayered materials↗
DOE OSTI2024

Long-distance decay-less spin transport in indirect excitons in a van der Waals heterostructure

AbstractIn addition to its fundamental interest, the long-distance spin transport is essential for spintronic devices. However, the spin relaxation caused by scattering of the particles carrying the spin limits spin transport. We explored spatially indirect excitons (IXs) in van der Waals heterostructures composed of atomically thin layers of transition-metal dichalcogenides as spin carries. We observed the long-distance spin transport: the spin polarized excitons travel over the entire sample, ~10 micron away from the excitation spot, with no spin density decay. This transport is characterized by the 1/e decay distances reaching ~100 micron. The 1/e decay distances are extracted from fits over the ~10 micron sample size. The emergence of long-distance spin transport is observed at the densities and temperatures where the IX transport decay distances and, in turn, scattering times are strongly enhanced. The suppression of IX scattering suppresses the spin relaxation and enables the long-distance spin transport.

Science & Technology - Other Topics↗
DOE OSTI2025

ZnGa 2 Te 4 thin-film absorbers for photoelectrochemical CO 2 reduction

Photoelectrochemical (PEC) carbon dioxide reduction reaction (CO 2 RR) has been considered as a promising route to convert and store solar energy into chemical fuels. It is crucial to find suitable photoelectrode materials that are photo-catalytically active and exhibit excellent photochemical stability. One of the promising contenders is ZnTe with the ∼2.26 eV band gap and prolonged stability under CO 2 RR PEC conditions. Herein, a new telluride based thin-film ZnGa 2 Te 4 photocathode with lower band gap and stronger visible light absorption compared to ZnTe is synthesized and characterized using a combinatorial sputtering technique. A two-step annealing method with excess Te supply is implemented to synthesize nearly stoichiometric ZnGa 2 Te 4 absorber material with a zincblende-derived tetragonal crystal structure confirmed by synchrotron X-ray and electron diffraction. Theoretical calculations show that ZnGa 2 Te 4 has suitable direct bandgap (∼1.86 eV) and high absorption coefficient ∼10 5 cm −1 , in agreement with experimentally prepared films. Transient absorption spectroscopy reveals the biexponential decay dynamics, with time constants, τ 1 ∼ 0.04, and τ 2 ∼ 0.65 μs in microsecond time scales and provides the optical transition pathways for this semiconductor thin film. PEC measurements show that the ZnGa 2 Te 4 photocurrent densities are comparable to the widely investigated ZnTe photocathodes or even surpass it under simulated sunlight condition. ZnGa 2 Te 4 samples demonstrate promising photoelectrochemical stability, maintaining consistent performance under illumination. The inclusion of diaryliodonium additive substantially increases its CO 2 RR selectivity to ∼60%. These findings open a new avenue for the synthesis of telluride-based thin-film photocathodes for further exploration and will motivate future research to integrate this potential photocathode material into PEC devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nm-scale electrical resistance imaging on CdTe by scanning spreading resistance microscopy

Local resistance imaging can provide information on nm-scale carrier distribution in semiconductor devices. Scanning spreading resistance microscopy (SSRM), an atomic force microscopy-based nm-scale resistance mapping technique, has been developed for carrier delineation in Si microdevices. We report on the development and validation of SSRM on CdTe materials, by testing on molecular beam epitaxy (MBE) grown CdTe films. The probe/CdTe contact resistance was suppressed sufficiently below sample's spreading resistance by pressing the probe into the sample with ∼mN contact force and applying a large sample/probe forward bias voltage (V s ), which was understood by analyzing current-voltage (I-V) involving a serially connected insulating top layer with underlying spreading resistance. The carrier concentration as deduced from the resistance measurement, using a single mobility value, is consistent with Hall measurement with a standard deviation of 14% based on a set of MBE films with carrier concentrations in the range of 10 15 –10 16 /cm 3 . The doping polarity was readily identified by flipping V s polarity, where the resistance with reverse V s is orders of magnitude larger than forward V s . While focusing on the SSRM technique validation, we also show an example on an As-doped Cd(Se,Te) polycrystalline thin film of a high-performance CdTe solar cell, which illustrates the local resistance nonuniformity with up to two orders of magnitude differences, indicating if local mobility is roughly constant, local carrier concentration can have significant nonuniformity.

14 SOLAR ENERGY↗
DOE OSTI2026

Spray-Coated Silver as Backside Metal for III–V Photovoltaic Devices on GaAs and Ge Substrates

The accelerated increase in demand for III-V space photovoltaics on GaAs and Ge substrates, as well as growing interests in terrestrial applications, motivate the development of cost-effective, high-throughput processing routes of these materials. Here, in this study, we assess spray-coated silver (Ag) back contact metallization as a substitute for electron-beam-evaporated metals currently used in industry. We find that the spray-coated Ag films are dense and continuous. By means of quantum efficiency, dark current-voltage, and illuminated current-voltage characterizations, we show that spray-coated GaAs and Ge solar cells perform similarly to baseline devices with electroplated Au, including under high current densities. We estimate that the thresholds for specific contact resistance below which back contacts do not significantly contribute to resistive loss are 2.1 x 10 -1 Ω•cm 2 for GaAs and 4.7 x 10 -2 Ω•cm 2 for Ge. We experimentally confirm that our spray-coated samples meet these requirements. Peel tests show that the adhesion of plain spray-coated Ag films to the back of p-type Ge substrates used in III-V solar cells is currently insufficient, whereas adhesion to p-type GaAs substrates is outstanding and requires no further optimization.

14 SOLAR ENERGY↗
DOE OSTI2025

Monocrystalline CdSeTe/MgCdTe Double‐Heterostructure Solar Cells

This article reports monocrystalline CdSeTe/MgCdTe double‐heterostructure (DH) solar cells with varying Se compositions in the absorber layers that are grown on InSb substrates by using molecular beam epitaxy. The Se composition in the samples studied is determined to be 4%–11% through high‐resolution X‐ray diffraction (XRD) and photoluminescence measurements. Increased Se incorporation induces higher defect density attributed to increased lattice mismatch, and mixed‐phase formation due to the small difference in formation energies between the wurtzite and zinc blende phases of CdSe, which causes stacking faults and grain boundaries. Devices are fabricated by directly depositing an n‐type indium tin oxide (ITO) layer on the CdSeTe/MgCdTe DHs followed by Ag metal contacts. Reduced bandgap is observed in solar cells with increased Se composition. The devices with an absorber containing 4% Se exhibit an average open‐circuit voltage ( V OC ) of 0.925 V, a short‐circuit current density ( J SC ) of 23.4 mA/cm 2 , a fill factor ( FF ) of 0.650 and an efficiency of 14.1% without anti‐reflection coating. Absorbers with higher Se compositions result in poor device performance, mainly attributed to high defect density in the materials.

Ju, Zheng [Center for Photonics Innovation Arizona↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Confocal Raman Microscopy as an In Situ Probe of Volume Change in Hydration-Sensitive Polymer Membranes

An approach is described for measuring hydration-induced volume change within ion conductive polymer membranes and thin films by adapting the technique of confocal Raman microscopy. With careful consideration of factors that affect excitation and scattering within the confocal probe volume region, material swelling and deswelling were estimated from the intensities of polymer matrix spectral features. A high numerical aperture oil-immersion objective was used to achieve tight focusing within samples and the efficient collection of Raman scattered light. The approach is demonstrated for a fluorinated cation-exchange ionomer (Nafion) and the hydrocarbon anion-exchange ionomer Sustainion. Samples were monitored while under a nitrogen atmosphere that was cycled between dry and humid (∼50% relative humidity, RH) states. The volume changes estimated from the Raman spectra were in close agreement with those derived from conventional measurements. The reported work advances understanding needed to adapt confocal Raman microscopy for quantitative in situ and operando studies of ionomers within electrochemical devices, such as polymer electrolyte membrane fuel cells and electrolyzers, and lays a foundation for broader applications in the study of hydration-induced polymer swelling and the associated molecular level water and polymer framework structural changes.

Absorption↗