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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluating Technology Adoption Risks in Early-Stage Materials Research

Development of new technologies often begins with fundamental materials science research. Decisions at this stage can shape factors related to the eventual adoption readiness of the technology, such as process scalability or materials availability. Here we present the early-Stage Technology Evaluation for Adoption Risks (STEAR) framework as a method for qualitatively assessing metrics spanning four categories of adoption risks: value proposition, market acceptance, resource maturity, and license to operate. We conduct a case study applying STEAR to different methanol production processes at a range of technology readiness levels and demonstrate how the assessment identifies key challenges related to adoption readiness. Finally, we discuss efforts to expand the applicability and utility of STEAR, including focus group feedback and complementary quantitative analysis methods.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Stacking fault analysis for the early-stages of PVT growth of 4H-SiC crystals

Here, four types of stacking fault formation mechanisms are identified and discussed for early stage PVT growth of 4H-SiC crystals: Type 1: Shockley / double Shockley stacking fault formation inside the facet; Type 2: Stacking fault formation via 2D nucleation; Type 3: Frank + Shockley (S) stacking fault formation due to deflection of threading mixed dislocation (TMD) by macrosteps; Type 4: “Carrot” defect formation related to overgrowth of the terrace formed by separation of 3c/4 and c/4 step risers after deflection of a TMD by vicinal steps. The results help further reduction of defect generation in 4H-SiC substrates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Guideline for Characterizing and Evaluating a Candidate Project Site for Solar Thermal Applications

This document presents a structured procedure for characterizing and evaluating candidate project sites for concentrating solar power (CSP) and solar heat for industrial processes (SHIP) applications. The objective is to provide project developers, researchers, and other stakeholders with a consistent, technology-agnostic framework for early-stage site assessment, enabling informed decision-making prior to significant investment in project development. Site selection is a critical factor in project success or failure for both CSP and SHIP projects. Key factors such as solar resource availability, land characteristics, environmental and regulatory constraints, infrastructure availability, and community context are determined by the choice of project site and can materially impact project performance, cost, schedule, and overall viability. This procedure is designed to systematically evaluate these factors, identify potential fatal flaws, and prioritize the most favorable candidate sites for further development. The process begins with rapid screening-level evaluation, using publicly available data to assess solar resource, land availability and suitability, zoning and land-use compatibility, and exclusion zones such as protected lands or sensitive habitats. Sites that meet the minimum screening criteria advance to a more detailed characterization. Subsequent sections of this report provide guidance for a next-level assessment of the most important technical and environmental parameters, including: 1) Solar resource quality, variability, and uncertainty using multiyear datasets and, where appropriate, on-site measurement campaigns; 2) Meteorological conditions such as wind, temperature, extreme weather events, and soiling impacts; 3) Land characteristics including slope, shading, and geotechnical conditions; and 4) Environmental and regulatory considerations, including permitting processes, endangered species, cultural resources, and visual impacts. The procedure also addresses infrastructure and integration considerations, including: 1) Grid interconnection requirements for CSP power generation projects; 2) Electrical and operational integration for SHIP facilities; 3) Water availability, quality, and permitting constraints, which are particularly critical for CSP in arid regions; and 4) Site access, construction logistics, and availability of workforce and supporting services. Recognizing the importance of social and economic context, the procedure includes evaluation of community engagement factors, such as stakeholder sentiment, proximity to sensitive visual receptors, workforce development opportunities, and local economic incentives. The outputs of these assessments are synthesized in a cost and risk evaluation, translating site characteristics into expected impacts on capital cost, operating cost, schedule, and technical risk. This is complemented by screening-level performance modeling, including 8760 simulations and long-term projections, to quantify expected energy or thermal output, assess variability thereof, and support comparison between candidate sites. Finally, the procedure provides high-level guidance on a structured go/no-go decision framework, categorizing sites based on identified risks and constraints, and outlining a clear path forward to feasibility studies and front-end engineering design for viable projects. By standardizing the site characterization process across both CSP and SHIP applications, this guideline aims to: 1) Improve consistency and transparency in early-stage project evaluation; 2) Reduce development risk and avoid investment in nonviable project sites; 3) Support collaboration between developers, researchers, and public agencies; and 4) Accelerate successful deployment of concentrating solar technologies for both power generation and industrial process heat.

14 SOLAR ENERGY↗
DOE OSTI2026

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material↗
DOE OSTI2026

Agentic framework for programmatic crystal structure generation using a fine-tuned worker–supervisor large language model

Platinum group metals (PGMs) underpin many catalytic technologies but face severe supply constraints, motivating the search for alternative materials and computational methods to accelerate discovery. While atomistic simulation tools such as Pymatgen and ASE have streamlined structure manipulation, they require detailed inputs, limiting accessibility for experimentalists and slowing early-stage exploration. Here, in this study, we present an AI-driven agentic framework that orchestrates worker–supervisor large language models (LLMs). The worker translates natural-language prompts of varying abstraction into valid crystallographic structures using a compact LLM fine-tuned with low-rank adaptation on a curated text–code–CIF dataset, emphasizing energy-efficient training. Benchmarking against the baseline CodeGen-350M-mono model shows that fine-tuning reduces hallucination rates from 100% to as low as 5% and improves structural match accuracy to up to 82% for fully specified inputs. Accuracy declines with decreasing prompt detail but remains nontrivial even when only stoichiometry and space group are provided, underscoring the LLM’s capacity for crystallographic inference. The supervisor Claude LLM evaluates the outputs and triggers iterative refinement through the worker’s built-in structure manipulation capabilities (e.g., supercell scaling, strain, vacancy, and substitution operations). We further demonstrate use cases for technologically relevant catalysts, including IrO 2 , pyrochlore Pb 2 Ir 2 O 7 , Ni 2 FeO 4 , and Ni 3 Mo, where the framework generates physically consistent structures that can be refined via geometry optimization. This work introduces a low-energy, language-driven pathway for integrating human and machine intelligence in materials design, paving the way for AI-assisted synthesis planning and high-throughput screening of complex oxides.

AI agent↗
DOE OSTI2026

Techno-Economic Analysis of Recycling Strategies for Catalyst and Acid During Catalytic Graphitization

With the aim of meeting the urgent demand for active anode materials (AAM) in energy storage systems, bio-based graphite (biographite) emerges as an affordable solution to de-risk the turbulent supply chain of critical minerals. Anode grade biographite requires high crystallinity and purity, which can be achieved by catalytic graphitization with iron, followed by acid washing. Therefore, a well-conceived process integration that recycles catalyst can be the starting point to commercialization. This study evaluates closed-loop catalyst recovery, and byproducts valorization scenarios through a technoeconomic framework to help understand the scale-up potential of biographite. For the acid washing, three reactors in series meet the required biographite purity at 99.95%. Iron and acid recovery can reduce material consumption and waste generation by ~95%, albeit at the expense of ~80% increase in capital costs. Recovery scenarios present similar capital and operational expenses, yielding minimum selling prices (MSP) near $6 kg-1 of biographite. Monte Carlo methodology reveals that feedstock price accounts for ~60% of MSP variance, followed by plant capacity ~20%. The likelihood of reaching a competitive profit margin of 30% in the U.S. AAM market sits at 85% average for recovery scenarios, and 103% when iron oxide is sold as byproduct. Additionally, an IRR >= 15% can be achieved for half of Monte Carlo simulations, representing promising early-stage results. Biographite production offers a strategic pathway to stabilize the anode market beyond China by integrating established technologies for a scalable, economically viable, and sustainable process. The role of catalyst recovery and byproducts utilization is critical for advancing the biomaterials industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Staying Current: A Community Readiness Framework for Marine Energy Applied to River Current Energy in Alaska

Marine energy-including wave, tidal, and river current energy-can provide a local energy source for rural and remote communities. Marine energy has the potential to bolster self-sufficiency and create economic opportunities while preserving ecological integrity. Communities may be interested in deploying, testing, and advancing these early-stage technologies to meet their needs. However, limited capacity, workforce constraints, and other barriers can challenge development. To better understand a community's interest in and preparedness for marine energy, we developed a suite of 150 'metrics of readiness.' Organized across seven categories-technical, social, environmental, strategic, governance, economic, financial-and 29 subcategories, the metrics provide a holistic perspective beyond the technical aspects of an energy device. We conducted a desktop application of the metrics of readiness for Igiugig, Alaska. The metrics were applied retrospectively for two points in time: before (2009) and after (2018) in-stream testing of a river current energy device. By documenting changes among categories and subcategories of the metrics, our results show the evolving nature of community readiness for river current energy. They also illustrate how our interdisciplinary framework captures the investment in environmental effects research and commitment to strategic planning that occurred in Igiugig. In future applications, we envision the framework could be used to foster public engagement in marine energy, collaborate with communities in project development, shape capacity building activities, prioritize investments, and inform research needs. While our study focuses on enabling river current energy in Alaska, the metrics of readiness have the potential to inform implementation of other renewable technologies with communities in new geographies.

13 HYDRO ENERGY↗
DOE OSTI2026

Integrated geological, economic, and risk assessment of underground hydrogen storage

Underground hydrogen storage (UHS) is a promising option to buffer variable renewable power and support the hydrogen economy. Yet this technology is early-stage, and key uncertainties remain about how coupled processes such as geochemical and geomechanical impacts affect long-term storage security. In this paper, we seek to integrate the results from a large, multi-scale research program to quantify core feasibility metrics and situate these studies within ongoing efforts. Through this work, we evaluate hydrogen recoverability during storage by assessing diffusive losses, losses to geochemical interactions and their subsequent impact on geomechanical properties, and losses to residual saturation during injection and withdrawal. Molecular and laboratory studies show that lithologic heterogeneity, pore geometry, and mineral surface chemistry govern hydrogen–rock interactions, controlling loss pathways. High-pressure coreflooding is used to estimate relative permeabilities and measure parameters needed for reservoir-scale sensitivity analyses. These core-scale experiments found early hydrogen breakthrough at low saturations driven by capillary and viscous fingering, which limits pore-space utilization at early times, while repeated injection and withdrawal cycles improve deliverability over time. Technoeconomic factors and purity requirements for end uses are also considered as part of our comprehensive feasibility analysis. Finally, we underscore the importance of geophysical monitoring and tailored injection strategies to maintain integrity and efficiency. Together, these results provide a quantitative foundation for safe, scalable deployment of UHS and highlight priorities for future integrated studies.

08 HYDROGEN↗
DOE OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗
DOE OSTI2026

Electronic Trap-State Modulation in Sm-Doped SnO 2 Nanofibers Enables Ultrasensitive Hydrogen Sensing

The demand for sub-ppm hydrogen (H 2 ) sensing is growing across emerging applications such as environmental monitoring, breath-based disease diagnostics, and early-stage battery failure detection. However, achieving reliable ppb-level detection with chemiresistive metal oxide sensors remains challenging. At trace gas concentrations, resistance modulation is often insufficient, particularly in the absence of noble metal catalysts. Here, we report samarium-doped tin dioxide (Sm-SnO 2 ) nanofibers in which electronic trap-state modulation is exploited to enable ultrasensitive hydrogen sensing. The 2 at% Sm-doped SnO 2 nanofibers exhibited markedly enhanced H 2 sensitivity, achieving clear detection down to 25 ppb H 2 at 200 °C, with a theoretical limit of detection of 4.5 ppb, placing this material among the most sensitive noble-metal-free SnO 2 -based H 2 sensors reported to date. Mechanistic investigations through X-ray photoelectron spectroscopy and electron energy loss spectroscopy revealed that Sm 3+ doping introduces deep trap states associated with charge-compensating defect complexes. These states reduce free carrier density, increase baseline resistance, and enable trap-assisted charge release during H 2 exposure, thereby amplifying the sensing response. Trap-state engineering via rare-earth doping, exemplified by Sm-SnO 2 , provides an effective pathway for achieving ppb-level hydrogen detection in noble-metal-free chemiresistive sensors.

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

Chromium versus Aluminum: Impact of Nickel Alloy Composition and Interfacial Kinetics on High-Temperature Passivating Oxide Formation

High-temperature corrosion resistance depends critically on the formation of a passivating surface oxide, which is highly sensitive to alloy composition and structure. Such details often elude experimental investigation, and simplified analytical models fail to provide a truly chemical view of passivating oxide evolution. Here, we explicitly compare the fundamental chemistry of Cr and Al as prototypical passivating elements in Ni alloys by directly simulating competing reaction and diffusion processes within the oxide film using kinetic Monte Carlo and density functional theory. We find that the origin and expression of passivating behavior during early-stage thermal oxidation are qualitatively different between the two alloy systems. Ni–Cr alloys feature a sudden onset of passivation associated with a sharp phase transition upon Cr enrichment that directly couples oxidation kinetics to phase transformation behavior. In contrast, Ni–Al alloys display more continuous oxide phase variation with Al enrichment, ultimately resulting in a lower composition threshold for passivation and a thinner passivating layer. In addition, we elucidate the nonobvious role of metal exchange within the alloy near the oxide boundary, which fundamentally alters film composition and passivating behavior. Furthermore, our results have key implications for engineering improved corrosion-resistant alloys, both in terms of compositional variation and processing.

Alloys↗
DOE OSTI2026

Thermodynamic Control of Interface Directs MnO 2 Nucleation Chemistry for Dense and Conformal Electrodeposition

Manganese dioxide (MnO 2 ) is widely recognized as a promising material for high-energy-density energy storage systems due to its broad applicability and facile electrodeposition. However, achieving uniform, thin, and high-mass-loading MnO 2 coatings on high-surface-area electrodes remains a significant challenge. Conventional electrodeposition methods typically yield nonuniform, thick layers with poor conductivity and limited material utilization, restricting their practical use. Here, we uncover a thermodynamically engineered vanadyl/pervanadyl (VO 2+ /VO 2 + ) interface that fundamentally reshapes MnO 2 electrodeposition chemistry, enabling highly uniform and dense coatings. Here, combining in situ AFM measurement, Classical Nucleation Theory, and Johnson–Mehl–Avrami–Kolmogorov modeling, we show that this interface reduces early-stage detectable MnO 2 island size by 35-fold and shifts the MnO 2 growth from diffusion-limited to reaction-limited progressive nucleation. This thermodynamically controlled interface yields highly dense and conformal MnO 2 films with record-high mass loading of 241 mg cm –2 (1607 mg cm –3 ) on 3D-printed graphene aerogels, without compromising porosity or inducing thickness gradient. As a prototype demonstration, the resulting MnO 2 electrodes deliver record-setting volumetric performance in both capacitors (106 F cm –3 ) and Zn//MnO 2 pouch cells (162 mAh cm –3 ). Beyond energy storage, our findings demonstrate the significance of thermodynamic interface control in MnO 2 nucleation chemistry for achieving dense and uniform coatings on various substrates, with implications for electrocatalysis, semiconductor processing, and advanced materials manufacturing.

Batteries↗
DOE OSTI2026

Exponential crystallization in corals

Corals form their reef-building aragonite (CaCO 3 ) skeletons via transient precursor phases yet understanding of the dynamics of these early-stage transformations remains incomplete. Using time-independent myriad mapping (MM) at 50 nm resolution, we map five mineral phases near the skeleton surface of Stylophora pistillata corals grown in varying seawater pH. All precursors, crystalline and amorphous, exhibit a consistent exponential decay from the growth front, with a shared decay length of 0.7 ± 0.1 μm, independent of time, phase, or pH. This spatial decay, paired with the constant growth rate of the skeleton, reveals a decay time of 5.1 ± 0.5 minutes. The dominant precursor is not amorphous but crystalline: calcium carbonate hemihydrate (CCHH, CaCO₃·½H₂O). These results suggest that exponential crystallization kinetics govern coral biomineralization and may be a widespread feature in biogenic, geologic, and synthetic systems—traceable long after initial mineral deposition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗
DOE OSTI2026

Electrochemical carbon deposition from CO 2 in molten carbonates: substrate-dependent growth

Electrochemical carbon deposition from molten carbonate salts using inert electrodes and no additional catalyst is systematically examined. At sufficiently cathodic potentials, carbon formation occurs within 30 min and transitions from substrate-dependent nucleation to carbon-on-carbon growth. Although deposits formed on either mild-steel or graphite cathodes exhibit comparable thicknesses and salt contents, their macrostructures differ, reflecting differences in early-stage growth rates and surface chemistry. Characterization by ICP-OES, Raman spectroscopy, SEM/EDS, synchrotron powder X-ray diffraction, and C K-edge X-ray absorption near edge structure reveals that the as-deposited carbon is predominantly disordered sp 2 -bonded material. However, post-treatment reveals latent turbostratic ordering in select samples, indicating that short-range order is established during deposition but is obscured by an entrained electrolyte and kinetically formed amorphous phases. No anode-derived contamination is detected, and carbon grown on graphite cathodes shows minimal metallic impurities. These results clarify the role of cathode surface chemistry and provide pathways for controlling electrode-derived impurity incorporation and carbon structure in catalyst-free molten carbonate systems.

36 MATERIALS SCIENCE↗
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 OSTI2026

Ultrasonic Resonance Techniques for Materials Research

Mechanical resonances are directly related to the physical behavior of a system at the bulk and microscopic levels. In materials science, resonant ultrasound spectroscopy (RUS) has long been a preferred nondestructive method to study mechanical resonances of solids and precisely measure quantitative material properties, namely elasticity. In recent years, advances in computational power and hardware have enabled RUS to be relevant for an increasing range of applications, such as advanced manufacturing. An extension of this technique, nonlinear RUS (NRUS), has been demonstrated to provide unmatched sensitivity to early-stage damage. NRUS was originally developed to probe geologic materials but has become a vital tool in nondestructive evaluation and materials research, offering a powerful means of quantifying and characterizing microstructural nonlinearity in a broad range of materials. This review summarizes recent developments and growth opportunities in RUS and NRUS techniques, modeling, and applications across a wide range of material systems including metals, composites, geomaterials, and explosives.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Dynamic Facade Dashboard v0.1.0

The dashboard is a useful tool for early-stage building design decision-making and communication, as it can help users quickly compare the energy and non-energy related performance of various automated, integrated facade systems using a library of pre-computed data. Users can explore the impacts of various design choices by selecting different facade glazing and shading systems, facade control strategies, and lighting control strategies across multiple climate zones. The dashboard instantly visualizes key metrics, including energy usage in HVAC and lighting, peak cooling and heating load, and daylight availability, allowing immediate trade-off analysis to optimize building efficiency and comfort.

Yu, Tammie [Lawrence Berkeley National Laboratory ↗