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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Anisotropic strength behavior of single-crystal TATB

High-rate strength behavior plays an important role in the shock initiation of high explosives, with plastic deformation serving to localize heat into hot spots and as a mechanochemical means to enhance reactivity. Recent simulations predict that detonation-like shocks produce highly reactive nanoscale shear bands in the layered crystalline explosive TATB (1,3,5-triamino-2,4,6-trinitrobenzene), but the thresholds leading to this response are poorly understood. We utilize molecular dynamics to simulate the high-rate compressive stress–strain response of TATB, with a focus on understanding flow behavior. Here, the dependence of strength on pressure and loading axis (crystal orientation) is explored. The deformation mechanisms fall broadly into two categories, with compression along crystal layers activating a buckling/twinning mode and compression normal to the layers producing nanoscale shear bands. Despite the complexity of the underlying mechanisms, the crystal exhibits relatively straightforward stress–strain curves. Most of the crystal orientations studied show rapid strain softening following the onset of yielding, which settles to a steady flow state. Trajectories are analyzed using five metrics for local states and structural order, but most of these metrics yield similar distributions for these deformation mechanisms. On the other hand, a recently proposed measure of intramolecular strain energy is found to most cleanly distinguish between these mechanisms, while also providing a plausible connection with mechanochemically accelerated decomposition kinetics. Localization of intramolecular strain energy is found to depend strongly on crystal orientation and pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predicting nepheline precipitation in waste glasses using ternary submixture model and machine learning

Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to its negative effect on chemical durability. Developing models to accurately predict nepheline precipitation from compositions is important to increase waste loading since existing models can be overly conservative. In this study, an expanded dataset containing 955 glasses was compiled from literature data, where 355 glasses are for high-level waste (HLW). Previously developed submixture models were refitted using the new dataset, where a misclassification rate of 7.8% was achieved. Nine machine learning (ML) algorithms (e.g., k-nearest neighbor, Gaussian process regression, artificial neural network, support vector machine, decision tree, etc.) were applied to evaluate their ability of predicting nepheline precipitation from compositions. Model accuracy, precision, recall/sensitivity, and F1 score were systemically compared between different ML algorithms and modeling protocols. Good model prediction with an accuracy ~0.9 (misclassification rate of ~10%) was observed with different algorithms under certain protocol. This study evaluated various ML models to predict nepheline precipitations in waste glasses, highlighting the importance of data preparation, modeling protocol, and their effect on model stability and reproducibility. The results provide insights into applying ML to predict glass properties and suggest areas for future research on modeling nepheline precipitations.

Lu, Xiaonan↗
DOE OSTI2021

Frequency–Magnitude Statistics of Laboratory Foreshocks Vary With Shear Velocity, Fault Slip Rate, and Shear Stress

Understanding the nucleation phase of earthquakes is key for advancing earthquake hazard assessment and improving earthquake early warning systems. However, little progress has been made in this area due to a poor understanding of nucleation processes and incomplete seismic and fault zone measurements. The ability to integrate measured fault zone properties with seismic data could significantly improve our understanding of how earthquakes begin and whether there are systematic variations in seismic properties preceding failure. In this work, we use high-resolution laboratory measurements of fault zone properties along with acoustic emission data to document temporal variations of foreshock properties. Our data show that foreshock size increases with shear stress, loading rate, and fault slip rate. We propose that the preseismic fault slip rate and fault zone thickness (i.e., porosity) work in concert to modulate foreshock properties.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Grain reorientation and stress-state evolution during cyclic loading of an α -Ti alloy below the elastic limit

Here, high-energy synchrotron x-rays are used to track grain-averaged lattice reorientation and stress-state evolution in Ti–7Al as it is cyclically loaded to 90% of its macroscopic yield stress. This evolution provides clear indication of accumulating plastic strain even though the sample never exceeded the elastic limit. The largest changes in lattice orientation and stress state are observed following the first cycle then evolution continues at a lower rate with subsequent cycles. Variation of the axes about which lattice reorientation occurs is found to be highly dependent on the maximum resolved shear stress and corresponding activation of various families of slip systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Impact of Operational Strategies and Load Fluctuations on Anion Exchange Membrane Water Electrolyzer Degradation

This study reports on the durability of anion exchange membrane water electrolyzers (AEMWEs) at the cell level in a supporting electrolyte (1 M) and the impact of operational profiles on cell degradation. While constant load shows significant voltage loss, including a current hold at 1 A cm −2 and a potential hold at 2 V, it generally occurs in the first 70 h of testing. These losses are likely due to passivation altering site reactivity and cell kinetics, and are largely recoverable upon load cycling and diagnostics at the end of test. Furthermore, square and triangular-wave cycling do not show cell degradation and indicate that AEMWEs are not vulnerable to load cycling. When operating outside of this potential window (1.45–2 V), cell voltage decay rates markedly increase and the losses are not recoverable. This includes a current density hold at 4.0 A cm −2 with high cell voltages (>2.4 V for test duration) and cycling between 0 and 2 V to simulate start–stop, where more than a 50% loss in current density occurs over 50 h. The findings presented here demonstrate the high durability of AEMWEs, particularly when operating with load fluctuations, and may allow for durability advantages compared to iridium and proton exchange membrane systems.

08 HYDROGEN↗
DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2023

Laboratory investigation of hydraulic fracturing in granitic rocks using active and passive seismic monitoring

SUMMARY Knowledge of the fracturing processes can be important for the optimization of pressurized fluid injection operations in the deep underground rock mass. Active and passive seismic monitoring techniques have been used in the field for tracking or mapping the propagating hydraulic fracture. Although both these monitoring techniques provide valuable information about the generated fracture network, it is difficult for either technique to comprehensibly identify the different processes associated with hydraulic fracturing. The combined active and passive monitoring has the potential for better characterization of the complex hydraulic fracturing phenomena. In this study, laboratory hydraulic fracturing experiments with combined active and passive seismic monitoring were conducted on true triaxially loaded Barre granite cubes with different fluid injection rates. The seismic inelastic fracturing was detected by 16 passive acoustic emission sensors, where 3678 and 2370 seismic source events were detected for the high and low injection rate experiments, respectively. For active monitoring, strong variations in the attributes of signals were observed which were transmitted through four source–receiver pairs, placed both perpendicular and parallel to the generated hydraulic fracture. Positive velocity changes were observed for active sensor pairs with ray paths passing through the generated hydraulic fracture indicating fluid permeation, whereas isolated dry deformation was characterized by a slight but permanent velocity decrease. Compared to velocity, the energy of the active signals was 1–2 orders of magnitude more sensitive to different hydraulic fracturing processes. However, the sensitivity and signatures of the active signal attributes were found to be dependent on the frequency range and direction of ray path with respect to the location of the generated fracture network. Using the coupled evaluation of the active and passive signals we were able to systematically identify various hydraulic fracturing processes including: (1) aseismic deformation, (2) fracture initiation and fluid permeation, (3) pressure build-up, (4) fracture propagation and (5) pressure release and leak-off. The results of this study showed that combining the respective advantages of active and passive seismic techniques and using both of them to monitor the failure processes can facilitate a more comprehensive understanding and better control of the hydraulic stimulations in subsurface operations.

Geochemistry & Geophysics↗
DOE OSTI2026

Durable Thin‐Film Porous Transport Electrodes for High Current Density PEM Water Electrolysis

Proton exchange membrane water electrolyzers rely on relatively expensive Ir-based catalysts for efficient and durable hydrogen production. To reduce system costs, Ir loadings can be reduced if performance and durability are maintained. Sputter deposition is a readily scalable method to synthesize uniform, low-loading catalyst layers with controlled composition. A catalyst applied directly to the porous transport layer can have advantages for performance, manufacturing simplicity, and catalyst recovery. Suitable porous transport layer porosity can minimize activity losses when reducing loadings. Here, methods are presented to deposit metallic Ir as well as amorphous and rutile Ir oxides. The activity and durability of these materials in the porous transport electrode architecture is evaluated. The metallic and amorphous forms have better initial activity, however, operation at 3 A cm −2 with 0.1 mg Ir cm −2 shows that only rutile IrO 2 maintains performance beyond 100 h with a 50 mV improvement after 700 h. A >10x reduced dissolution rate is shown for rutile IrO 2 . With a low-porosity transport layer and 0.4 mg Ir cm −2 , a steady-state voltage decay rate of 6 µV h −1 is achieved. The results demonstrate that sputter-deposited rutile IrO 2 porous transport electrodes with low Ir loading can be operated at high current density to reduce hydrogen production costs.

08 HYDROGEN↗
DOE OSTI2020

Enzyme interactions on lignocellulosic biomass structure

This chapter shows that, although well studied over the years, the cellulose enzymatic hydrolysis process has still many obstacles to be overcome or minimized. High enzyme loading and relatively long incubation periods are generally required for effective cellulose saccharification to be achieved. These limitations make the process unattractive from an economic perspective. Most studies show that the conversion rate of cellulose hydrolysis decreases over reaction time due to several factors that may inhibit, deactivate, or slow the work of enzymes. Some of these factors are inhibition by the product generated; inhibition/deactivation of enzymes by by-products generated during pretreatment (PT); limitation of mass transfer; shear stress by high stirring; air–liquid interfacial area; and unproductive adsorption on lignin or other compounds present in the biomass. The interaction between cellulases and the lignin present in these biomasses has a major negative impact on the process, with the source of the raw material and the type of PT used having a strong influence on it. Finally, the use of nonenzymatic proteins seems to be the best way to mitigate this problem.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

DROP DURABILITY ASSESSMENT OF ELECTRONIC ASSEMBLIES UNDER OFF-AXIS LOADING WITH SKEWED FIXTURES

This thesis studies drop durability of electronic assemblies when the acceleration vector is oriented at 45° to the out-of-plane direction of the circuit card. The off-axis drop tests are accomplished with a skewed fixture and are conducted as a proxy for multiaxial drop testing. Advanced shock testing and vibration test methods have been developed over the last few decades to better represent real-world field environments during ground-based laboratory testing. However, many of these test methods require expensive and specialized equipment not available in most laboratories. An alternative approach for approximating simultaneous loading along multiple axes on conventional equipment utilizes skewed fixtures which have seen use in off-axis random vibration and drop impact testing. These methods generally rely on the conversion of a uniaxial input load from the test equipment (using a uniaxial drop tower or shaker) into a multiaxial load when resolved in the reference frame of the test article (mounted on a skewed fixture). Skewed fixture design is presented and recommendations for conducting skewed angle drop testing are introduced based on local measurements along the skewed face of the fixture to accurately monitor the impact event. Characterization tests were performed with a skewed fixture, at simultaneous acceleration loads from 500 to 3,000 g in two (in-plane and out-of-plane) directions, while meeting standard time domain tolerances. Upon experimental characterization, drop shock durability tests were conducted on a printed circuit assembly (PCA). Mean drops-to-failure were measured and quantified with Weibull statistics. Dominant solder joint failure modes were identified via failure analysis. Prior work on inclined angle impact testing is limited, and the majority of solder joint interconnect level fatigue studies are conducted considering perpendicular loading normal the circuit card. Low-cycle fatigue curves are generated based on plastic strain and plastic work density within the solder joint. A multiscale nonlinear finite element model is used to relate board-level flexure to solder joint interconnect level plastic strain. A high strain rate solder constitutive model allows for accurate modeling of solder plasticity resulting from high-impact drop shock. Fatigue parameters are computed from the Coffin-Manson relation and Palmgren-Miner damage accumulation. This work serves to apply established low-cycle fatigue methods for conventional drop shock loading (impact normal to circuit card) to non-perpendicular loading with a skewed fixture.

Hower, Jonathan [Kansas City National Security Cam↗
DOE OSTI2023

Design of Dilute Palladium–Indium Alloy Catalysts for the Selective Hydrogenation of CO 2 to Methanol

Adding small amounts of a more reactive dopant metal to a more selective host metal is a well-known strategy for promoting the catalytic reactivity of the latter without sacrificing its selectivity. While substantial attention has been given to coinage metal hosts for activating individual C–H or O–H bonds, less attention has been given to more exotic metals, such as indium, which is highly selective in the complex hydrogenation of CO 2 to methanol. Herein, we describe the synthesis and properties of Pd–In alloys containing Pd in various states of aggregation (isolated atom, small clusters, and extended clusters) assessed through various characterization methods. These materials exhibit unique catalytic behaviors, with Pd promoting both the reaction rate and methanol selectivity in all cases, though its efficacy is highest when Pd is present in small clusters. Here, the inefficiency of high Pd loadings is due in part to losses in Pd accessibility, while the importance of aggregated vs isolated Pd is theorized to result from accelerated H 2 activation. Methods used to synthesize more conventional dilute-limit and single-atom alloy catalysts can, therefore, be extended to non-coinage metal hosts to promote and control more complex chemistries, though the roles of ensemble size may greatly differ.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems

Major technological advancements and recent policy support are improving the outlook for heavy-duty truck electrification in the United States. In particular, short-haul operations (=200 miles (=322 km)) are prevalent and early candidates for plug-in electric vehicles (EVs) given their short, predictable routes and return-to-base applications, which allows vehicles to recharge when off shift at their depots. Although previous studies investigated the impacts of added electrical loads on distribution systems, which included light-duty EVs, the implications for heavy-duty EV charging are underexplored. Here we summarize the causes, costs and lead times of distribution system upgrades anticipated for depot charging. We also developed synthetic depot charging load profiles for heavy-duty trucks from real-world operating schedules, and found that charging requirements are met at common light-duty EV charging rates (=100 kW per vehicle). Finally, we applied depot charging load profiles to 36 distribution real-world substations, which showed that most can accommodate high levels of heavy-duty EV charging without upgrades.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

3D–Integrated, Multi–Functional Carbon Fibers for Stable, High–Areal–Capacity Batteries

Increasing lithium-ion batteries' (LIBs) electrode areal capacity can boost energy density and lower manufacturing costs, but faces challenges in manufacturing, rate performance, and cycling stability. A conductive framework made of commercial micro-sized carbon fibers (Cfs) is presented that serves as a host for both the LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC 532) cathode and Cfs anode. The Cf framework has multiple functions that offer high electronic conductivity (270 mS cm –1 ), low tortuosity (1.7), low Li + diffusion resistance (22 Ω), and high thermal conductivity (200 W mK –1 ). Additionally, the Cf-integrated electrodes can have an extremely high mass loading of NMC 532 (70 mg cm –2 ) with a theoretical capacity of 14 mAh cm –2 . Thus, the practical full cells assembled with the Cfs-enabled electrodes exhibit an initial areal capacity of 4.1 mAh cm –2 and capacity retention of 90.4% at 500 cycles at a cycling rate of C/3, 1.5 mA cm –2 . Data collected from the operando isothermal microcalorimetry suggest that full cells utilizing the Cf anode experience less heat release from side reactions compared to cells utilizing a conventional graphite anode. Finally, this present approach is scalable and cost-effective and can fabricate practical LIBs that boast high areal capacity, rate performance, and a lengthy cycling lifetime.

25 ENERGY STORAGE↗
DOE OSTI2020

Effect of isotropic and anisotropic porous microstructure on electrochemical performance of Li ion battery cathodes: An experimental and computational study

Liquid electrolyte mass transport is a major limitation affecting high-power Li ion batteries. Fast discharging causes Li salt depletion in the current collector region of the cathode which produces overpotential in the electrolyte and consequently a drop of cell voltage to below the cut-off voltage, especially at higher electrode thickness and discharge rate. In this study, through experiment and simulation, we have investigated the effect of electrode thickness, mass loading, discharge rate and tortuosity on electrolyte mass transport and final derived areal capacity and specific energy for electrodes having isotropic (normal tape casting) and anisotropic (freeze tape casting) porous microstructure. Furthermore, the macroporous channels in freeze tape cast electrodes facilitate Li salt transport and reduce the Li salt mass transport limitations even at high electrode thickness and discharge rates, and high electrode tortuosity. In our results, computer simulations show that freeze tape cast electrodes may be fully discharged up to 750 μm thickness at 1 C rate compared to 300 μm for normal tape cast electrodes with the same mass loading. Freeze tape cast electrodes also show stable maximum areal capacity for C rates about double the maximum C rates of their normal tape cast electrode counterparts with the same mass loading.

25 ENERGY STORAGE↗
DOE OSTI2023

Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters

Abstract—Grid following inverter-based renewable generation has replaced conventional generation in recent years, resulting in lower system inertia. The frequency resilience in such a lower inertia system is critical for emergency mitigation. In this paper, we propose a resilience metric based on frequency recovery to quantitatively represent system resilience in terms of the rate of change of frequency. Application of grid-forming converters provides a means to improve system resilience by providing virtual inertia. An under-frequency load shedding strategy is applied to further support frequency recovery in cases with high penetration of grid-forming inverters. Case studies are designed and performed in a modified IEEE 9-bus test system using the PSCAD/EMTDC platform. Simulation results demonstrate the validity of the proposed resilience metric and the effectiveness of the strategy for reducing frequency excursion in inverter-based power systems. citation: J. Gui, H. Lei, T. R. McJunkin and B. K. Johnson, "Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters," 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1-5, doi: 10.1109/ISGT51731.2023.10066357.

14 SOLAR ENERGY↗
DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Anisotropic spall failure of additively manufactured 316L stainless steel

The dynamic high strain rate tensile (spall) failure of additively manufactured (AM) materials is an area of great interest but much less understood than material failure under other loading regimes. The research presented here examines the effects of microstructure anisotropy in 316L stainless steel fabricated by laser powder bed fusion (LPBF) on its spall failure and properties. In this work, plate-on-plate impact experiments were performed using an 80-mm gas gun to investigate the spall behavior of AM fabricated sample discs with impact along the perpendicular and parallel orientations relative to build directions. Experiments were also performed on wrought 316L stainless steel as baseline material with uniform equiaxed grain microstructure for comparison with the AM material of same composition. The spall experiments involved free-surface velocity profiles measured using Photon Doppler Velocimetry (PDV) to capture the spall pull-back signals, combined with post-mortem analysis of the microstructure of soft-recovered impacted samples. In the case of AM samples, spall failure initiated preferentially at melt pool boundaries in both impact directions. The spall plane location and spall strength, however, were both heavily influenced by the orientation of the impact direction relative to the build direction in the AM samples. The spall behavior is also observed to be more complex in the samples impacted perpendicular to the build (through-thickness) direction, due in large part to the orientation of the microstructural features such as melt pool boundaries, laser scan tracks, and general grain morphology.

36 MATERIALS SCIENCE↗