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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A New Shutdown Dose Rate Benchmark Problem for Representative Fusion Applications

Here, this work introduces a new benchmark problem for calculating shutdown dose rates (SDDRs) aimed at fusion reactor applications. The model is designed to represent a simplified version of a typical ITER port plug. The responses of interest include neutron flux, gamma flux, and gamma SDDR at 12 different locations scattered throughout the port. This article outlines the geometry specifications of the problem, provides material definitions for the components, specifies the required responses to be calculated, and presents the source definition information. The need for this benchmark arises from the limited availability of publicly accessible references, with only one benchmark representing the typical dimensions and materials found in fusion systems. This existing benchmark has been cited extensively, reflecting the demand within the scientific community to test both established and novel workflows for SDDR calculations. However, since its presentation at a conference in 2011, the results have become increasingly well known. Moreover, the absence of formal publication and peer review has led to the details of this benchmark being extracted from secondary sources, such as subsequent studies that reference it. As a result, analysts are left with significant flexibility in interpreting the key parameters, which can be adjusted to account for unknown systematic errors, ultimately reproducing the already well-known responses. This new benchmark serves as an updated version of that earlier work, with the aim of providing a more reliable description of the materials and their impurities, which is crucial for assessing activation and subsequent gamma emission. Additionally, it seeks to provide a geometry that more closely represents an ITER port plug. The improvements in the problem definition will lead to a more reproducible benchmark problem, while also presenting the radiation transport community with a completely new challenge. The results will be published in a future article to allow analysts adequate time to analyze this problem independently.

Benchmark↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗
DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗
DOE OSTI2026

Recyclable Materials for Resource Constrained Environments

In-space manufacturing exhibits severe limitations in resources as astronauts are only afforded with the materials that are brought on-board the space craft. Consequently, the use of recyclable and re-usable materials is paramount. Researchers at NLR leverage their expertise in polymer and recycling chemistry to develop material systems capable of high performance applications with intentional consideration on multi-life use through chemical recycling, mechanical recycling, bio-degradation, and thermoforming. Disclosed within this poster presentation are highlighted projects that illustrate several recyclable by design material systems that have been developed.

09 BIOMASS FUELS↗
DOE OSTI2025

Highly textured metal anodes for stable aqueous batteries: Fabrication and characterization

We report a purely mechanical “cold-compression flow” method for fabricating Zn, Sn, and In substrates with tunable crystallographic textures. Using textured Zn as a model system, we investigate Zn electrocrystallization and demonstrate correlated growth of crystalline films with correlation lengths from tens to hundreds of micrometers. At 5 milliamperes per square centimeter (mA/cm 2 ), capacities between 20 and 82 milliampere hours per square centimeter (mA·hour/cm 2 ) are achieved depending on substrate texture level. At higher currents (40 mA/cm 2 ), capacities reach up to 604 mA·hour/cm 2 . Rotating disk electrode studies show that dominantly (002) textured Zn substrates exhibit enhanced corrosion resistance and reduced interphase passivation. We introduce an effective Damköhler number (Da*) to concisely describe morphological evolution during electrocrystallization across substrates with different textures. High-texture (002) Zn substrates substantially enhance performance in high-capacity (~20 mA·hour/cm 2 ) symmetric Zn||Zn cells and full cells (Zn||δ-MnO 2 and Zn||I 2 ), enabling fast-charging and prolonged energy storage in coin and pouch rechargeable Zn battery formats.

Science & Technology - Other Topics↗
DOE OSTI2025

Multi-Ion Complexes and Competition from Bulky BArF – Anions for Chloride Binding in Ion Pairing Conditions

Cationic charges have long been used to enhance anion binding. Embedding charge introduces strong ion pairing for target anions but also for off-target ions, ultimately generating a mixture of multi-ion species that are hard to identify and quantify. While many sidestep this problem using polar solvents and weakly coordinating ions, these approaches exclude a substantial cross-section of conditions found in applications spanning recognition, assembly, separations, templation, and catalysis. To confront this complexity, we study the binding of an anion to a cationic receptor featuring low shape complementarity in a low-polarity solvent to maximize ionic interactions. We prepared the receptor as a salt of the weakly coordinating tetrakis­[3,5-bis­(trifluoromethyl)­phenyl]­borate (BArF – ) anion and studied the binding of small chloride (Cl – ) and medium-sized iodide (I – ) anions. Surprisingly, the use of the bulky BArF – anion does not suppress ion pairing interactions, with 65% of the receptor being paired at 0.5 mM in dichloromethane. We observe multi-ion receptor-Cl – complexes (2:1, 1:1, 1:2), reinforcing the complexity that emerges when working in low-polarity media. Here, we reveal the dependence of affinity on anion charge density and size and that bulky BArF – counteranions compete for chloride binding. These studies reveal the noninnocence of BArF – anions and strategies to quantify multi-ion species.

Ion pairing↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
DOE OSTI2026

A Unified Beam-Dynamics and Hardware Design Framework for Hybrid Nonlinear-Kicker Injection in NSLS-II

Nonlinear kickers (NLKs) enable off-axis injection in ultralow-emittance storage rings by providing a strong kick to the injected beam while remaining nearly transparent to the stored beam. In hybrid schemes, a conventional four-kicker bump defines the injected trajectory, and the NLK reduces the first-turn action under constrained beam offset and optics conditions. Effective operation additionally requires stable and reproducible first-turn injection trajectories. We develop a compact action–angle framework that expresses NLK dynamics in terms of Courant–Snyder invariants and yields an analytical bound on achievable action reduction. This formulation provides direct design rules for NLK placement, phase advance, injected-beam offset, and kicker field profile. Within this framework, we identify the 8-wire NLK as a practical baseline and extend its design by relaxing the square-geometry constraint, enabling inward shifting of the off-axis field peak while preserving on-axis field and gradient cancellation. Application to the NSLS-II lattice shows how aperture, pulsed-power, and mechanical constraints combine to determine a coupled design solution. Multi-turn tracking confirms that candidate NLK locations maintain sufficient stay-clear (aperture-clearance) margin, while the optimized wire geometry reduces the required current and Lorentz force load. The results establish a unified approach for NLK-assisted injection design and provide a practical pathway for upgrades in diffraction-limited storage rings.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electronegativity-Guided Site Differentiation in High-Entropy Alloy for pH-universal Hydrogen Evolution Reactions

Enhancing the intrinsic activity of transition metal catalysts for the hydrogen evolution reaction (HER) remains a critical challenge in sustainable energy conversion. Herein, we report an electronegativity-guided site differentiation strategy in a single-phase CoNiCuMoW high-entropy alloy (HEA) via electrodeposition by incorporating high-electronegativity 4d/5d orbital transition metals (Mo, W) into the face-centered cubic (fcc) matrix (CoNiCu). The as-synthesized HEA demonstrates exceptional HER performance in all pH conditions, delivering an outstanding overpotential of 65 mV (alkaline), 28 mV (acidic), and 155 mV (neutral) at a current density of 100 mA cm−2, showing performance comparable to commercial Pt/C and has excellent long-term stability at high current density (1 A cm−2, 1000 h). X-Ray absorption spectroscopy (XAS) and density functional theory (DFT) calculations reveal that the incorporation of Mo/W simultaneously alters the local coordination environment and induces element-dependent charge redistribution, accompanied by a system-level d-band center downshift, thereby optimizing the hydrogen binding strength across multimetallic sites. Meanwhile, oxophilic Mo/W sites lower the water dissociation energy barrier. These synergistic effects collectively enable efficient and durable pH-universal HER performance.

Wu, Yutong↗
DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗
DOE OSTI2026

Development of in-situ polymerized intrinsically conductive resin and low-cost carbon pigments offering high conductivity for sensing, EMI shielding and lighting protection

Electrically conductive composites are emerging across diverse industries such as electronic, automotive, aerospace, advanced air mobility, biomedical, infrastructure, defense and security offering static charge dissipation, electromagnetic interference shielding, lighting protection, sensing, dicing, corrosion monitoring, etc. Conductivity enhanced composites provide several advantages compared to conventional metals including weight reduction, corrosion resistance, energy efficient processability, tunable properties and multifunctionality. Polymers are typically insulating in nature and require conducting filler for electron transport. However, dispersion and polymer-filler interphases are critical and often disrupt conducting pathways. Besides, conductive fillers such as graphene, carbon nanotube, MXene, silver nanowire, etc. are expensive, limiting their wide adoption in composite industry. On the other hand, a limited number of intrinsically conductive polymers are available among which polyaniline (PANI) has been widely studied due to its high conductivity, thermal and chemical stability. However, PANI is difficult to process and exhibits weak mechanical properties. In brief, there is a significant demand for electrically conductive polymer formulation with cost-effective conducting fillers that offer processability in scale to expand the market of conductivity enhanced materials.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2026

PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow With Continual Learning

Solving the alternating current power flow equations in real time is essential for secure grid operation, yet classical Newton–Raphson solvers can be slow under stressed conditions. Existing graph neural networks for power flow are typically trained on a single system and often degrade on different systems. We present PowerModelsGAT-AI, a physics-informed graph attention network that predicts bus voltages and generator injections. The model uses bus-type-aware masking to handle different bus types and balances multiple loss terms, including a power-mismatch penalty, using learned weights. We evaluate the model on 14 benchmark systems (4 to 6,470 buses) and train a unified model on 13 of these under contingency conditions with up to two branch outages, achieving an average normalized mean absolute error of 0.89% for voltage magnitudes and R 2 >0.99 for voltage angles. We also show continual learning: when adapting a base model to a new 1,354-bus system, standard fine-tuning causes severe forgetting with error increases exceeding 1000% on base systems, while our experience replay and elastic weight consolidation strategy keeps error increases below 2% and in some cases improves base-system performance. Interpretability analysis shows that learned attention weights correlate with physical branch parameters (susceptance: r=0.38 ; thermal limits: r=0.22 ), and feature importance analysis supports that the model captures established power flow relationships.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Heliostat sizing methodology for concentrating solar thermal industrial process heat projects

This study presents a method to obtain a heliostat size that minimizes the levelized cost of heat (LCOH) of a heliostat-based concentrating solar thermal system for applications of solar heating for industrial processes at operating temperatures from 565 to 1550°C. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model to supplement the previously developed cost models, which we update to reflect current pricing trends. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWh th . Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the LCOH, producing a characteristic U-shaped trend with a robust near-optimal window of 7-20 m 2 ; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats being deployed at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗
DOE OSTI2026

Case Study of Integrating High-Temperature Heat Pump with LiBr-H2O Absorption Chiller for Data Center Liquid Cooling

Data centers (DCs) are physical infrastructures that support artificial intelligence workloads. The rapid growth of artificial intelligence is putting substantial pressure on the US power grid. Most of electricity consumed by IT equipment, accounting for 50%-60% of total DC power, ultimately becomes waste heat. This heat is dissipated by DC’s cooling facilities, accounting for an additional 30%-40% of total DC power. Recovering and repurposing this waste heat offers a significant opportunity to enhance energy efficiency and reduce operating costs of DCs. One potential pathway is converting heat to cold using thermal-driven absorption chillers, therefore, reducing the power consumption in DC cooling facilities. Existing studies mainly demonstrate the technical and economic feasibility of repurposing DC’s waste heat for cooling applications but provide limited technical details on how to integrate the thermal-driven absorption chillers with DC cooling systems. In addition, the low-grade waste heat available from DCs must be upgraded to higher temperatures suitable for absorption chillers. This paper presents a case study on integrating high-temperature heat pumps with a LiBr-H2O absorption chiller to use DC waste heat for cooling. A thermodynamic model of single-effect, LiBr-H2O absorption chiller and an empirical model of high-temperature heat pumps were built. The case study considers ASHRAE W17 liquid-cooled DC, with facility service water supplied at 17.0℃ and returned at 25.3℃. The thermal behaviors of absorption chiller components were predicted for the generation temperature ranging from 75.0℃ to 115.0℃. Based on the available waste heat in the integrated system, two waste heat recovery strategies were evaluated: a facility service water-based strategy and cooling water-based strategy. Results indicated that the cooling water-based strategy achieves higher Coefficient of Performance (COPs) than the facility service water-based strategy. The relatively low cooling COPs of single-effect LiBr-H2O absorption chillers could be offset by high heating COP of high temperature heat pumps. The maximum cooling COP of absorption chiller and the overall COP of integrated systems occur at lower generation temperatures, but these conditions also yield lower cooling capacities. In practice, system operation should balance the trade-off between the COP and cooling capacity

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗
DOE OSTI2025

Characterizing and modeling the mechanical behavior of an anion exchange membrane for carbon capture applications

A new direct air capture (DAC) technology uses a moisture swing (MS) process with anion exchange membranes, potentially offering a more energy-efficient way to remove CO₂ from the air. In this MS process, the membrane absorbs CO₂ as it dries and releases it when water is added. Understanding the mechanical behavior of these membranes is essential for improving the design and efficiency of DAC systems and prolonging sorbent lifetime. This study tested one anion exchange membrane, Fumasep’s FAA-3, under mechanical loading and various temperature and humidity conditions to measure its swelling, stiffness, strength, plastic deformation, and stress relaxation. Experimental results were used to identify a mechanical model for FAA-3 that can be used to predict the material’s nonlinear viscous behavior under various loads and environments. Unlike prior studies that assumed linear elastic behavior, this work incorporates humidity-dependent swelling, thermal expansion, and nonlinear viscoelasticity of FAA-3 in both the experiments and the model.

Direct air capture↗
DOE OSTI2026

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry↗
DOE OSTI2026

Thin Film Synthesis of SrZn2P2 with SrI2 Post-Annealing for Enhanced Crystallinity and Optoelectronic Quality

Ternary Zintl phosphides are promising light-absorbing semiconductors for thin-film optoelectronic applications, but strategies for controlling their microstructure and optoelectronic quality remain underexplored. Here, we report the synthesis of phase-pure SrZn2P2 thin films using radio-frequency co-sputtering in a PH3 + Ar atmosphere and investigate the impact of post-growth processing on their structural and optical properties. Grazing-incidence X-ray scattering and Raman spectroscopy confirm the formation of crystalline SrZn2P2 films over a finite compositional window. Optical measurements reveal clear absorption near the direct-band-gap energy (~1.8 eV) and near-band-edge photoluminescence. Further, we have studied the effects of chemically compatible halide-assisted annealing. It is found that SrI2 treatments lead to pronounced grain growth and reduced diffraction peak broadening while preserving phase purity, in contrast to rapid thermal or forming-gas annealing. Notably, annealing with SrI2 at 450 degrees C significantly enhances both the intensity and spatial uniformity of the photoluminescence, thus connecting the observed microstructural consolidation with improved radiative recombination. Our study demonstrates that halide-assisted annealing provides an effective pathway for microstructural control in SrZn2P2 thin films and highlights a generalizable processing strategy for advancing Zintl phosphide semiconductors toward optoelectronic applications.

14 SOLAR ENERGY↗