Search NASA⌕ Search

SEARCH · Search NASA

Results for “STRESS AND LOAD”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Characterizing electrical demand and load diversity of low-power water and space heating appliances in US homes

Home renovation and remodeling projects can involve costly and time consuming electrical infrastructure upgrades at the household level. From the grid perspective they also lead to costly replacement of local infrastructure, such as transformers, and can add stress to the grid at peak times. The emergence of innovative, power-efficient household appliances offers a way to minimize these problems. These appliances are designed for lower power consumption, simplifying installation through standard plug-in connections, reducing the need for new electric circuits/panels/service, and minimizing the peak power demand for the home. Key examples include low-power heat pump water heaters (HPWHs) and cold climate window heat pumps that operate on standard 120V outlets. To assess the real-world impact of these solutions, we compiled and analyzed power metering data from several US field studies. This data provides insights into the effects on peak power demand of selecting lower-power appliances. Our analysis focuses on several key metrics, including the maximum power demand of individual appliances, their operational runtime, continuous operation and load diversity. While individual low-power 120V space and water heating appliances offer significant peak demand reductions compared to 240V heat pump or resistance alternatives, their longer runtimes might increase the likelihood of operation during whole-dwelling peak events, albeit at lower power levels.

Less, Brennan↗
DOE OSTI2025

Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot

This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level. Using charging data from over 4,600 EV drivers, the study analyzed SCM’s impact on the distribution systems of BGE and Pepco, which consists of over 2000 feeders. Unlike prior research that focused on system-wide trends or synthetic feeders, this analysis offers granular, feeder-level insights based on real-world operational data. It highlights how transformer density, load profiles, and infrastructure constraints influence smart charging performance. Results show feeder-level conditions play a crucial role in SCM effectiveness, with most feeders benefiting more from LB, while TOU-based SCM may be sufficient for others. By 2035, LB reduced peak charging loads by 27% on average, compared to 23% under TOU-based SCM, though some feeders saw reductions exceeding 35%, while others experienced minimal impact. Feeders with higher transformer utilization and limited capacity benefited more from LB, which more effectively distributed charging demand during off-peak hours. Beyond reducing grid constraints, SCM offers long-term operational and financial benefits. By shifting EV charging demand strategically, utilities can optimize asset utilization, delay infrastructure investments, and enhance grid performance. In terms of infrastructure upgrade deferrals, at the feeder level, LB consistently reduced peak charging loads and resulting infrastructure upgrade costs, particularly in high EV enrollment areas, decreasing the number of overloaded transformers by up to 35%, while TOU-based SCM achieved 20-30% reductions depending on feeder characteristics. At the system level, LB has the potential to defer total upgrade costs by $\$$186 million for BGE, compared to $\$$159 million under TOU-based SCM. For Pepco, TOU-based SCM performed slightly better, deferring upgrade costs by $\$$30 million, compared to $\$$29 million under LB. Section 4.5 reviews some of the system differences between BGE and Pepco. However, as EV adoption scales, TOU-based SCM will introduce secondary peak charging loads, reinforcing the need for more advanced, adaptive SCM approaches to prevent new grid challenges. As EV adoption continues to grow, feeder-level managed charging strategies will be essential for mitigating grid stress, improving infrastructure efficiency, and maintaining energy affordability for consumers. This report provides critical insights for utilities, Public Utility Commissions (PUCs), and state agencies on the role of feeder-specific smart charging in infrastructure planning, policy development, and grid modernization. The findings underscore the importance of tailored, data-driven SCM solutions that align with local grid conditions, ensuring a resilient, cost-effective transition to increasing EV adoption while safeguarding distribution system performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Unveiling the structural transformations in glassy solid electrolyte adapted to high-stress cycles

Brittleness of glass–ceramic and ceramic ion conductors is considered as a main roadblock for their implementation as electrolytes in solid-state batteries where the fractures often occur due to the pressure exerted by metallic lithium. In this regard, nano- and micro-scale ductility of the solid electrolyte allows reducing such pressure without formation of cracks. Among different types of solid state ion conductors, phosphate invert glasses seem to be promising in achieving such ductility. We report the mechanical behavior of lithium phosphorous oxynitride (LiPON) invert glass probed by static and cyclic nanoindentation. Repeated application of high intensity stress results in densification and shear deformation of material allowing LiPON to accommodate the ~ 22% nominal strain imposed by the nanoindenter without cracking. Ability to do this under repeated loading indicates robustness of LiPON when used in lithium metal batteries under cyclic charge and discharge. Using Raman spectroscopy with unsupervised K-means clustering we reveal pressure-induced formation of P 2 O 7 units which migrate to the periphery of the residual hardness impressions with cycling resulting in surface morphology of LiPON superficially similar to that of deformed bulk metallic glass.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Photo-oxidation of semicrystalline polymers: Effect of stress triaxiality on ductility

The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned ex situ using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

FEM Analysis of Hybrid LTS/HTS Cos-Theta Dipole Magnet With Heterogeneous Cable Model

The Lawrence Berkeley National Laboratory (LBNL) and the National High Magnetic Field Laboratory (NHMFL) have published results on Bi-2212 superconductive magnets realized and tested in the canted cosine-theta and solenoid designs, respectively. Fermilab is now preparing for the assembly of the first Bi-2212 stress-managed cosine-theta insert magnet. The insert will be part of the first hybrid cosine-theta magnet made of Nb$_3$Sn outer layers within the US-MDP effort to reach a 20 T bore field. This paper presents the analytical analysis of the cosine-theta Nb$_3$Sn/Bi-2212 hybrid magnet. We report the parameters, logic, and implementation method of the 2D electromagnetic and mechanical FEM analysis of the LTS/HTS hybrid magnet. Results from a detailed heterogeneous model are compared to the homogeneous model implemented in the past. A Python code has been developed to simulate the current degradation due to stresses in the detail-modeled conductor areas. The current degradation has been introduced in the simulation dynamics for the HTS conductor as an iteration process, updating the input load of Lorentz forces of the energization at each step. The magnetic and mechanical analysis results of the 2D cosine-theta LTS/HTS dipole magnet have been described and analyzed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

High tensile alloy of copper to mitigate current collector deformation in silicon electrodes for lithium-ion batteries

The volumetric changes of silicon electrodes, along with the strong adhesive properties of certain binders, can lead to plastic deformation of the current collector and create damage in the electrode coating. Here, in this study, we report a detailed study of silicon coatings on a high-tensile alloy (HTA) foil of copper with strength over twice that of conventional copper foils. The HTA current collectors with high mechanical strength can mitigate plastic deformation upon continuous cycling. At moderate areal capacities (2.5–3 mAh cm −2 ), conventional copper foils show significant wrinkling after only a few electrochemical cycles, whereas the HTA foils remain intact. We demonstrate viability of the HTA foils in large format xx6395 pouch cells, in which the HTA current collectors remain intact even at an areal capacity of 4.5 mAh cm −2 ; in contrast, wrinkles form in conventional copper current collectors increasing the likelihood of lithium plating. Computational studies show that stresses generated during cycling of silicon electrodes are very high in the current collector and at the current collector-coating interface, explaining the wrinkling of conventional Cu foils. Our studies highlight importance of current collector to solve the electrochemical and chemo-mechanical performance challenges associated with high-loading silicon electrodes.

Chemo-mechanical degradation↗
DOE OSTI2025

Atomic Energy Accuracy of Neural Network Potentials: Harnessing Pretraining and Transfer Learning

Machine learning-based interatomic potentials (MLIPs) have transformed the prediction of potential energy surfaces (PESs), achieving accuracy comparable to ab initio calculations. However, atomic energy predictions, often assumed to lack physical meaning, remain underexplored. In this study, we demonstrate that inaccuracies in atomic energy predictions reduce the robustness and transferability of Neural Network Potentials (NNPs) and atomic energy error can be masked in total energy predictions due to error cancellation. Here, we validate this finding using challenging configurations involving deformation and failure under tensile loading. By pretraining atomic energy predictions using empirical potentials and applying transfer learning with density functional theory (DFT) data, we achieve notable improvements in the accuracy of total energy, forces, and stress predictions. Furthermore, this approach enhances the robustness and transferability of NNPs, emphasizing the importance of atomic energy predictions in developing high-quality and reliable MLIPs.

Active Learning↗
DOE OSTI2025

SAN-Based Block Polymers as a Platform for Manufacturing Strong Isoporous Membranes

Ultrafiltration (UF) membranes are ubiquitous in water purification and bioprocessing. However, co-designing their mechanical and transport properties remains challenging because of the broad pore size distributions at the surface and within the bulk that result from nonsolvent-induced phase separation (NIPS) – their typical manufacturing process. These distributions influence the hydrodynamic resistance to water flow and the stress concentrations around the pores. Developing advanced UF membranes requires innovative molecular designs that offer control over the surface and bulk pores, as well as the mechanical properties of the load-bearing, polymer. Here, we introduce a platform for designing UF membranes by leveraging solution self-assembly of block polymers and chain architectures with pendant polar groups. The block polymers consist of a poly(styrene-co-acrylonitrile) hydrophobic block, which is known for its strength, and a poly(4-vinyl pyridine) hydrophilic block, which drives solution self-assembly. We focus on a series of block polymers with constant molecular weight, M n ≈ 115 kDa, SAN fraction, 75 wt.%, and varying acrylonitrile content, 0 to 40 mol%, to demonstrate that: (i) RAFT dispersion copolymerization of acrylonitrile and styrene provides a facile route to synthesize strong block polymers, (ii) incorporation of acrylonitrile into the hydrophobic block enhances membrane strength by facilitating chain entanglements and dipole-dipole interactions, and (iii) acrylonitrile alters the balance between membrane permeance and rejection, even when the membranes feature similar surface and bulk pores. Overall, our results provide insights into the molecular design of UF membranes with enhanced mechanical and separation properties, contributing to the development of materials for water and energy technologies.

deformation↗
DOE OSTI2024

Multifunctional Heat Pump with Energy Storage Capability

Replacing gas furnaces with heat pumps on a large scale can pose challenges to the electrical grid. It will significantly increase the demand, strain the electrical grid, especially during peak usage times. To ensure that heat pumps contribute to reducing emissions, it's essential to increase the share of renewable energy in the grid. However, the supply of renewable energy is unstable. Large scale of electrification must address the concern of grid resilience to meet necessary heating/cooling demands and shift peak electric load. All these require future heat pumps having energy storage capability. These systems can store excess energy during low-demand periods and release it during high-demand periods, reducing stress on the grid. This paper will introduce an innovative configuration, control, and laboratory investigations of a multifunctional packaged heat pump. In addition to the original indoor and outdoor air coils, the heat pump has a parallel hydronic loop with a brazed plate heat exchanger (BHP). The hydronic loop circulates hot/chilled water to store heating/cooling energy in phase change material (PCM). It is capable of space cooling, space heating, cooling energy storage/defrosting, water heating/heating energy storage with outdoor air source or indoor air source, and cooling/heating energy free discharge. The laboratory studies and breadboard unit are presented. Additionally, building energy simulation demonstrates utility cost reduction potential via charging PCM panels/ceilings during off-peak hours and releasing the energy during peak hours to mitigate the peak power consumption.

Shen, Bo↗
DOE OSTI2025

Conceptual Designs for Irradiation Creep Testing of SiC in HFIR

Understanding irradiation creep of nuclear fuel cladding is important to properly size the initial fuel-cladding gap and understand when pellet-cladding contact is expected to occur due to a combination of fuel swelling and cladding creep-down. Irradiation creep also plays a role in relaxing stresses that develop in-pile. Silicon carbide fiber–reinforced silicon carbide matrix (SiC/SiC) composites are the leading long-term accident-tolerant fuel cladding concept for light-water reactors (LWRs). Although some limited data are available regarding irradiation creep of the individual constituents (fibers, matrix), data regarding irradiation creep of SiC/SiC composites are currently insufficient. Additional data regarding irradiation creep compliance and the rupture lifetime (combination of creep and slow crack growth) are needed to understand material limitations. This work describes the design and development of two irradiation vehicles that are being pursued for testing SiC/SiC concepts in the High Flux Isotope Reactor (HFIR). The first is a passive experiment, referred to as the PRECISE experiment, that leverages the constant coolant pressure of HFIR to compress a metallic bellows and provide a well-characterized load to drive creep in a SiC/SiC dog bone specimen. The total creep strain would be quantified post-irradiation by measuring dimensional changes of the specimen length as well as local dimensional changes within the gauge region. Non-stressed specimens would also be irradiated under the same conditions to provide an indication of dimensional changes due to radiation-induced swelling in the absence of creep. A second, more complex experiment, referred to as the INSITE experiment, is being designed in parallel that would use pneumatics to pressurize a metal bellows and linear variable differential transformers (LVDTs) to measure the specimen displacement in situ during irradiation. Such an experiment would provide significantly more data regarding the evolution of the creep compliance as a function of dose and applied stress within a single experiment but would require significantly more development time and cost to execute. The primary concern with the INSITE experiment is the accuracy, reliability, and expected lifetime of the LVDTs during irradiation at elevated temperatures. Efforts are being made to adjust the experiment design and operating procedure to limit LVDT temperatures and mitigate or otherwise compensate for uncertainties due to factors such as temperature fluctuations, creep in the surrounding structural materials, and drift of the LVDTs. This work describes the experiment designs, thermal and structural analysis that were performed to ensure that the desired temperature and stress conditions can be achieved, some initial sensitivity analyses to predict the evolution of the radiation-induced specimen displacements, and potential sources of uncertainty in the measurements. Out-of-pile testing is being performed in parallel to confirm that the test trains achieve the expected stress states in the specimens and do not result in prohibitive stress concentrators (e.g., in the grip regions) that might risk pre-mature failure. The PRECISE experiments are proceeding toward fabrication and assembly with HFIR insertion planned during fiscal year 2026. The INSITE experiment is progressing toward out-of-pile demonstrations, which will provide more conclusive evidence regarding the feasibility of executing these tests in HFIR or whether alternative displacement monitoring techniques may need to be considered.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Mechanics of pore array collapse and interaction in shock-compressed polymethyl methacrylate (PMMA)

Recent studies on dynamic pore collapse have revealed significant development of shear localization, which can lead to material failure in porous structures and hot spot generation in energetic materials. These findings have dramatically improved the understanding of failure mechanisms during pore collapse but also prompt further investigation of realistic porous materials. In particular, porous media consist of many pores and porous networks. Even in low-porosity materials, pores can form in close proximity during the manufacturing process, leading to the critical question of pore–pore interaction during collapse under dynamic loading conditions. This study investigates, via plate impact experiments coupled with high-speed internal digital image correlation and shadowgraphy techniques, the collapse of two pores in shock-compressed PMMA at stresses between 0.4 and 1 GPa. The results of these experiments provide new insights into shear localization in pore collapse, in addition to distinct interactions between pores. Shadowgraphy measurements reveal novel, direct visualization of shear band development and crack evolution from pore surfaces. Spacing between adiabatic shear bands is measured over a range of impact stresses and is predicted accurately by the Grady–Kipp model. Pore interactions are found to effect a transition in the impact stress threshold at which different failure mechanisms initiate and are also found to possibly influence preferential sites for shear cracking. Throughout the study, numerical and theoretical models are leveraged to understand shear localization behavior. The role of baroclinicity and wave interactions between the pores is used to elucidate interaction mechanisms between pores.

Lawlor, Barry P. [California Institute of Technolo↗
DOE OSTI2024

STRUCTURAL MODELING TO SUPPORT POST-YIELD ACCEPTANCE CRITERIA FOR SPENT NUCLEAR FUEL CLADDING

Spent nuclear fuel (SNF) is evaluated for structural failure during storage and transportation scenarios. The U.S. Department of Energy’s Spent Fuel and Waste Science and Technology (SFWST) program has sponsored significant research in quantifying mechanical loads on SNF during storage and transportation scenarios using experimental and modeling methods. The SFWST program has also performed significant research on measuring the mechanical behavior of irradiated SNF as defueled cladding segments and cladding with fuel pellets to measure composite behavior. This paper considers some of the key material data from the Sibling Pin testing and uses structural modeling and analysis methods that have been informed by testing to consider post-yield acceptance criteria for SNF cladding structural analysis. Test data published by Oak Ridge National Laboratory (ORNL) and Pacific Northwest National Laboratory (PNNL) are the foundation for informing the material behavior of the models developed in this study. In particular, four-point bend (4PB) tests of fueled and defueled cladding segments provide significant information about the bending failure mode of SNF. ORNL’s 4PB test data is on fueled cladding segments, so the composite behavior of SNF is demonstrated. This paper describes PNNL’s coincident beam model that was developed to approximate the composite behavior of SNF. This paper also presents PNNL’s structural dynamic finite element models of a cask tip-over scenario, which is predicted to cause the strongest mechanical loads on SNF of all postulated storage and transportation scenarios. SNF bending loads predicted in the cask tip-over scenario and cladding acceptance criteria beyond yield are considered, with justification based on the Sibling Pin test data. ASME Boiler and Pressure Vessel code stress intensity limits are also considered. The ultimate goal of this work is to aid in the justification of structural acceptance criteria for SNF cladding beyond the cladding’s irradiated yield strength for use in structural analysis of all storage and transportation scenarios.

Klymyshyn, Nicholas A.↗
DOE OSTI2024

Dynamic Modeling and Characterization of Nuclear-grade Graphite

Idaho National Labs serves as the spearhead for many innovative energy solutions to the world's energy crisis. One such solution is the INL's Microreactor which is designed to deploy to extreme/remote environments where other sources of power are either unavailable or unreliable. In order to best design these energy solutions for their operational environments, it is crucial to understand how the design, components, and materials will respond to the environmental conditions. One key material in these innovative designs is a nuclear-grade graphite known as PCEA. This study examines the behavior of PCEA graphite under dynamic loading, similar to that which may occur in extreme environments. The objective is to characterize the dynamic behavior and produce an accurate, reliable constitutive model suitable for use in simulation tools such as INL's MOOSE. Graphite specimens were tested using a Split Hopkinson Pressure Bar (SHPB) to administer the dynamic compressive load. The SHPB was charged at various pressures to produce a range of strain rates on the material in compression. Data was acquired via strain gauges on the SHPB setup, from which stress, strain, and time data were collected. Analysis revealed the stress-strain behavior of the material as well as insights into the material behavior's relationship to strain rate. Further work must continue to characterize the various other dynamic behaviors of the material which will combine to create a substantially trustworthy constitutive model for this grade of nuclear-grade graphite. Ultimately, this will allow for realistic simulation of the material in reactor designs, allowing for prediction of design weaknesses and leading to improved designs for increased resilience, security, and reliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗
DOE OSTI2026

Pilot Development Progress to Demonstrate Electric Thermal Energy Storage (ETES) Using Low-Cost Particles

The rapid growth of future energy demand increases the need to economically store electrical energy over durations up to several days in long-duration energy storage (LDES) applications. LDES can reduce the grid stress for improving the resilience of the grid. The integration of renewable power and storage has several significant and positive impacts including expanding the renewable energy portion of electricity generation, meeting peak-load demand, and coordinating supply and demand. Several energy storage approaches including mechanical, chemical and electrochemical methods are currently deployed or under development. However, LDES requirements pose unique challenges for scalability, energy capacity, and cost. Thermal energy storage (TES) has the ability to store a large capacity of energy with improved site flexibility compared to incumbent LDES technologies (i.e., pumped hydro) and has attracted significant interest. Our development in TES technology using solid particles as the storage medium has shown feasibility and potential in serving LDES purposes. Particle TES has various advantages over commercialized molten nitrate salt TES and has emerged as a promising storage technology originating from Generation 3 concentrating solar power (CSP) development. Stable, inexpensive silica sand produced in the Midwestern U.S. was identified as a suitable storage medium and has been validated through lab heating and cycling tests. We have successfully developed particle TES for bidirectional electric energy storage to broaden the applications for TES beyond CSP technologies and into standalone electric-thermal energy storage (ETES) systems. Key component designs and performance were verified with prototype testing and model simulations. The ETES system uses high-temperature, low-cost particle thermal energy storage coupled with a unique pressurized fluidized bed heat exchanger that supports a high-efficiency, air-Brayton combined power cycle. At times of low energy demand or high renewable production, an electric particle heater heats large quantities of solid particles to high temperatures in excess of 1100 degrees C. The particles are stored in internally insulated silos. At times of high electricity demand, the hot particles are gravity-fed through the heat exchanger where stored thermal energy is transferred to the power cycle working fluid to drive the gas turbine power generation system, thereby converting the thermal energy back into electricity for the grid. The cold particles leaving the heat exchanger are returned to the storage silos by a well-insulated particle conveyor. This ETES technology using particle TES can be sited anywhere and is predicted to be economic and efficient. Moreover, this ETES technology could be co-located with a retired coal or gas plant to leverage existing power generation and grid infrastructure. Our work has focused on the development of each of the key components (e.g., the electric particle heater, particle storage silos, and the particle-to-gas pressurized fluidized bed heat exchanger) through conceptual designs, prototype testing, and computational modeling. These developments demonstrate technological feasibility and are an important step towards the next phase of development of this promising LDES technology. This presentation will show the progress in developing a pilot demonstration of the ETES system on a commercially relevant scale.

25 ENERGY STORAGE↗
DOE OSTI2026

Sparsely Dispersed CeO x ‑Stabilized Pt Nanoparticles Overcome Pt Loading–Durability Trade-Off for Highly Durable Heavy-Duty Fuel Cells

Proton-exchange-membrane fuel cells (PEMFCs) are clean and sustainable mobile power sources for transportation. Recently, their deployment in heavy-duty vehicles (HDVs) has attracted growing interest owing to their high energy scalability and lower infrastructure requirements. However, to meet the stringent requirements for efficiency and long-term durability for HDV applications, PEMFCs typically employ a relatively high platinum group metal (PGM) loading (>0.2 mg PGM /cm 2 ). This elevated PGM loading significantly increases the stack and system costs, surpassing the U.S. Department of Energy (DOE) target of $\$ 60$/kW for commercial viability. Reducing PGM loading while maintaining performance and durability remains a central challenge for HDV fuel cells. Here we exploit metal oxide–Pt interactions and utilize the strong CeO x –Pt interaction to design a CeO x @Pt catalyst structure with exceptional durability. At a low total PGM loading (0.1 mg PGM /cm 2 ), the CeO x @Pt/C catalyst demonstrates high fuel cell performance (8.8 kW/g PGM ) and stability (power retention >90%) after the challenging HDV durability testing (90,000 accelerated-stress-test cycles). With the CeO x @Pt/C catalyst, we showcase over 70% reduction in Pt cost from the M2FCT target (to $\$ 9$/kW), highlighting its promising potential for enabling stable and cost-effective fuel cell systems for heavy-duty applications.

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

Integrating AI Data Centers with the Power Grid

The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Relative molecular orientation can impact the onset of plasticity in molecular crystals

Abstract Creating or moving dislocations is the first step to dissipating mechanical energy via plastic deformation under contact loading. In molecular crystals there is both a lattice that defines crystal orientation and a relative orientation of the basis of the molecules. We define a normalization parameter which relates strain at yield, the hardness of the bulk crystal, and a distance parameter analogous to a Burgers vector that nominally predicts the relative ease of initiating plasticity in this broad class of materials. Analyzing the yield behavior of 10 different molecular crystals of varying space groups shows the inter-molecular orientation predicts the experimentally observed applied stress needed to nucleate dislocations. When molecules are oriented ‘parallel’ relative to one another the normalized maximum shear stress at the onset of plasticity is on the order of 3–5 times lower than when molecules within the crystal are ‘anti-parallel’, and molecules with a more equiaxed shape fall in between these bounds. This provides an initial indication of a structural feature which predicts the relative ease of initiating plasticity during contact loading in molecular crystals.

36 MATERIALS SCIENCE↗