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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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DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Li Stripping Behavior of Anode‐Free Solid‐State Batteries Under Intermittent‐Current Discharge Conditions

Anode‐free manufacturing holds promise to enable high energy densities and lower Lithium (Li)‐metal solid‐state batteries (LMSSBs). Nevertheless, in contrast to thick Li foil (>50 µm), the stripping capacity of in situ‐formed Li (10–30 µm) is limited due to diminished creep flow, resulting in reduced accessible capacity. This study explores the correlation between stripping capacity and surface roughness of garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte. The results reveal that stripping capacity can be enhanced through the surface modification of solid electrolytes. Additionally, this study scrutinizes the stripping behavior of in situ Li under intermittent‐current discharge conditions, which are more relevant to the operational conditions of electric vehicles (EVs). It is demonstrated that, when compared to constant‐current stripping, intermittent‐current stripping effectively suppresses void formation and enhances the stripping capacity of in situ Li by 40%. It is considered that the intermittent current inhibits the accumulation of Li vacancies, thereby delaying the void formation. These findings provide valuable insights into the development of high‐performance anode‐free LMSSBs for EVs.

25 ENERGY STORAGE↗
DOE OSTI2025

Design Strategies Based on Electronic Interactions for Effective Catalysts in Lithium–Sulfur Batteries

Abstract Lithium–sulfur batteries (LSBs) are considered promising next‐generation batteries due to their high energy density (>500 W h kg −1 ). However, LSBs exhibit an unsatisfactory energy density (<400 W h kg −1 ) and cycle life (<300 cycles) because of the shuttle effect caused by soluble lithium polysulfide (LiPS) intermediates and the sluggish conversion reaction kinetics caused by insulating sulfur (S 8 ) and lithium sulfide (Li 2 S). Although various types of catalysts, including metal‐based compounds to single‐atom catalysts, have been reported to address these issues, most catalysts exhibited limited catalytic activity under practical lean electrolyte conditions (<5 µL mg −1 ). A comprehensive understanding of the synthetic strategy and catalytic mechanism of catalysts is essential for their design, but understanding the electronic effects of the catalysts and LiPS is more important. Furthermore, the electronic design of these catalysts is not well understood. In this review, we introduce the catalytic mechanisms in LSBs and discuss catalyst design strategies in terms of electronic effects on the interactions between reactants and catalysts, with a primary focus on heterogeneous catalytic systems. We additionally consider how the electronic property of homogeneous systems, particularly redox mediators, affects catalytic behavior under lean electrolyte conditions and propose future research directions for catalyst development in LSBs.

Chemistry↗
DOE OSTI2026

Optical transparency of LiF (100) shock compressed to ∼360 GPa

High-purity [100] lithium fluoride (LiF) is the most widely used optical window in dynamic compression experiments due to its wide bandgap and well-characterized mechanical response. Recent plate-impact experiments established the [100] LiF Hugoniot to ∼230 GPa and demonstrated shock-induced melting onset at 182 GPa with complete melting by 195 GPa; theoretical models predict LiF optical transparency to nearly 900 GPa. To experimentally examine the optical transparency of [100] LiF at higher pressures and in the liquid state, laser-driven shock experiments were performed at peak stresses ranging from 223 to 363 GPa. Optical response was examined by measuring the particle velocity histories at the Kapton/LiF interface using laser interferometry at 532 and 1550 nm wavelengths; in-material particle velocities were obtained using established refractive-index corrections. Continuous photonic Doppler velocimetry fringes were observed across the entire stress range, demonstrating that LiF remains transparent to 1550 nm light throughout the multi-megabar regime investigated. At 532 nm, fringe visibility depended on the reflector coating: aluminum mirrors provided signals to ∼235 GPa, while gold mirrors extended this limit to 270.5 GPa, indicating that the shorter-wavelength response is likely sensitive to experimental configuration rather than to the loss of LiF transparency. Continued optical transparency to at least 360 GPa indicates that shock-melted LiF does not display bandgap closure over the stress range explored. Furthermore, these results provide direct experimental constraints on the high-pressure optical response and establish LiF (100) as a robust optical window material for laser-driven dynamic compression experiments approaching 400 GPa.

Renganathan, P. [Argonne National Laboratory (ANL)↗
DOE OSTI2025

Transforming Windows from Energy Liabilities to Zero-Energy Assets: Next-Generation Solutions for Buildings

Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is achievable across diverse climate zones, with specific regional requirements. Most climate zones from 3-8 can achieve ZEW with specific configurations, while some warm climates (1-2) appear challenging for ZEW implementation. Climate zones 4-6 consistently allow for zero energy window implementation, offering multiple pathways through either static or dynamic window technologies. Colder climate zones (7-8) ZEW products allow for higher SHGC values while requiring low U-values.

Yu, Lili↗
DOE OSTI2026

Unveiling field-transverse spin anisotropy in the spin liquid candidate α-RuCl3 via spin Hall magnetoresistance

α-RuCl3 has emerged as a possible candidate for a quantum spin liquid (QSL) that promises exotic quasiparticles relevant for fault-tolerant quantum computation. Here, we report spin-sensitive transport measurements using a proximal spin Hall metal, platinum (Pt), to probe magnetic moments in the insulator α-RuCl3. We observe spin Hall magnetoresistance (SMR), where both the transverse and longitudinal resistivities exhibit angular oscillations between the in-plane magnetic field and the current, driven by the interplay between the spin Hall effect in Pt and local magnetic moments in α-RuCl3. These oscillations occur from 1.5 to 18 T, covering the zigzag antiferromagnetic, putative QSL, and supposedly partially field-polarized phases. The phase of the SMR oscillations suggests that the local moments, whether static or fluctuating, develop spin anisotropy with a quantization axis in-plane and largely transverse to the magnetic field across all fields from 1.5 to 18 T. Temperature dependence indicates that the spin anisotropy operates at an energy scale similar to that of the reported QSL signatures in α-RuCl3.

Idzuchi, Hiroshi [Tohoku University, Japan]↗
DOE OSTI2026

Green Era Anaerobic Digester

Green Era Educational NFP constructed and commissioned the Green Era Renewable Energy & Urban Farming Campus in Chicago’s Auburn Gresham neighborhood. The project transformed a long-vacant brownfield site into a commercial-scale anaerobic digestion facility that converts food waste into renewable natural gas and nutrient-rich material for agricultural use. The facility can process up to 80,000 wet tons of food waste annually and supports approximately 15 permanent jobs while advancing food waste diversion, renewable energy production, nutrient recovery and community revitalization.

03 NATURAL GAS↗
DOE OSTI2026

Vapor-phase pillarization of MXenes for engineering hierarchical interlayer porosity

MXenes, a family of two-dimensional (2D) multilamellar materials, possess excellent thermal and electronic properties for a range of applications. Their use in heterogeneous catalysis, however, is limited by the low surface area resulting from stacked layers. Pillarization with inorganic oxides can create more open, mesoporous MXene structures, improving accessibility for guest species to diffuse, reside or react in the space between 2D layers. A previous liquid-phase pillarization method, however, involves excessive use of solvent-based precursors and multiple processing steps. Here, we report a vapor-phase pillarization (VPP) strategy to introduce pillars, exemplified by silica pillars, with high pillar precursor usage efficiency and a simplified processing workflow. The resulting silica-pillared mesoporous MXene exhibits significantly increased surface area and porosity. These textural properties can be easily tuned by the VPP synthesis conditions. When applied as a ruthenium (Ru) catalyst support for the hydrogenolysis of low-density polyethylene (LDPE), the silica-pillared MXene enabled high Ru dispersion and catalytic activity. This study highlights the potential of the VPP method for engineering mesoporous, 2D MXene materials and demonstrates the effectiveness of mesoporous MXene as a catalyst support in overcoming mass transport and active-site accessibility challenges in heterogeneous catalysis involving bulky substances, such as plastics upcycling.

Luo, Song [University of Delaware, Newark, DE (Uni↗
DOE OSTI2025

Advancements in nanocomposites for enhancing the performance of rechargeable lithium-ion batteries

The benefits of nanotechnology have been realized in almost every component of lithium-ion batteries. From electrodes to electrolytes, the incorporation of nanoparticles as dopants and coatings has shown marked improvements in cell cycle life, efficiency, mechanical and thermal stabilities, and lithium-ion transport. The improvements realized depends on several factors, from processing methods, nanoparticle type, structure, and concentration, to the material into which the nanoparticulate will be incorporated. Regardless of these many factors, nanotechnology has vastly improved the performance of secondary lithium-ion batteries. Here we will highlight some of the works that demonstrate these improvements and the quantitative benefits of nanotechnology.

25 ENERGY STORAGE↗
DOE OSTI2026

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗
DOE OSTI2026

A Unified Scaling Framework for Comparative Analysis of Major Electrical Machine Topologies

This paper presents a unified framework for comparing major electrical machine topologies under identical output and thermal constraints, with emphasis on supply-chain-aware selection among rare-earth-intensive, reduced-rare-earth, and rare-earth-free solutions. Using power factor and air-gap flux density as the principal descriptors, the framework links topology choice to relative size, copper demand, magnet dependence, cost sensitivity, and inertia. To support robust early-stage screening, the deterministic scaling model is combined with uncertainty representation, Monte Carlo scenario propagation, and hesitationaware ranking. The results show that rare-earth-rich machines remain compact and dense, whereas reduced-rare-earth and rare-earth-free alternatives become more attractive under specific material-risk and cost scenarios.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
DOE OSTI2025

De Novo Design of High‐Affinity Miniprotein Binders Targeting Francisella Tularensis Virulence Factor

Abstract Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella‐like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well‐defined binding pockets and structural information on native interactions has hindered structure‐guided ligand discovery against Flpp3. Here, we used a combination of physics‐based and deep‐learning methods to design high‐affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24–110 nM. For the second site, an initial binder showed a dissociation constant ( K D ) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub‐nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X‐ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (Cα root‐mean‐square deviation (RMSD): 0.9 Å). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

Gokce‐Alpkilic, Gizem [Molecular Engineering and S↗
DOE OSTI2026

Enhanced Recovery of Critical Minerals and Geological Hydrogen in The Mine of the Future

invited perspective article: The rapid demand for critical minerals (CMs) and hydrogen (H2) necessitates innovative solutions beyond conventional mining. This study explores enhanced mineral recovery (EMR) and geological hydrogen production (GeoH2) by leveraging the Earth’s subsurface as a reactive platform. Using ultramafic rocks and engineered fluids, the approach simultaneously mobilizes critical resources and produces H2 through natural processes like serpentinization. This paradigm offers a transformative pathway to secure essential materials and diversify energy resources, setting a foundation for the Terrestrial Mine of the Future

Yan, Keju↗
DOE OSTI2026

Estimating Return on Investment for Energy Technical Assistance Programs

The U.S. Department of Energy's Office of State and Community Energy Programs engaged the National Laboratory of the Rockies to assess the return on investment (ROI) of technical assistance (TA) programs that support state, local, and Tribal energy planning. Although TA delivers value through capacity building, stakeholder engagement, and knowledge transfer, these benefits are often intangible and challenging to monetize. This study reviews existing ROI frameworks and synthesizes the most relevant elements into a hybrid approach tailored to energy TA programs. The proposed framework integrates monetary and non-monetary outcomes through early logic model development, baseline data collection, and the use of proxies for intangible benefits. As a case study, this paper applies this approach to the Communities Local Energy Action Program (Communities LEAP), demonstrating how ROI can inform program design, data strategy, and performance assessment. Findings underscore that ROI should be applied selectively and planned from the outset to ensure data alignment and attribution accuracy. The framework offers TA practitioners a structured approach that can be leveraged for future programs to evaluate and communicate the multifaceted value of TA investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Solvent-Mediated Control of Nanocellulose Dispersion: An Integrated Computational and Experimental Investigation

Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.

cellulose↗
DOE OSTI2024

RMCProfile7 : reverse Monte Carlo for multiphase systems

This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.

Chemistry↗
DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗