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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conformationally Adaptable Extractant Flexes Strong Lanthanide Reverse-Size Selectivity

Chemical selectivity is traditionally understood in the context of rigid molecular scaffolds with precisely defined local coordination and chemical environments that ultimately facilitate a given transformation of interest. By contrast, nature leverages dynamic structures and strong coupling to enable specific interactions with target species in otherwise complex media. Taking inspiration from nature, we demonstrate unconventional selectivity in the solvent extraction of light over heavy lanthanides using a conformationally flexible ligand called octadecyl acyclopa (ODA). This novel ligand forms pseudocyclic molecular complexes with lanthanide ions at organic/aqueous interfaces, revealed by vibrational sum frequency generation spectroscopy. These complexes are extracted into the organic phase, where femtosecond structural dynamics are probed by two-dimensional infrared spectroscopy and ab initio molecular dynamics simulations to mechanistically frame the macroscopic selectivity trends. We find larger-than-expected structural fluctuations and bond lengths for heavy Ln–ODA complexes that arise from an inability of ODA to contort around the smaller ions to satisfy all would-be bonding interactions, despite forming some individually strong bonds. This finding contrasts with the binding of ODA with lighter lanthanides where, despite individually weaker bonds, collective interactions manifest that minimize structural fluctuations and give rise to enhanced thermodynamic stability. Furthermore, these results point to a new paradigm where conformational dynamics and cumulative bonding interactions can be used to facilitate unconventional chemical transformations.

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

Fast extraction of nickel from aqueous media by using ionic metal-organic frameworks

As global demand for stainless steel rapidly increases, supply for minerals such as nickel, manganese, and chromium become more critical. To shift mineral peak production and delay scarcity of alloying minerals, recycling rate of the mineral needs to increase. Development of simple and cost-effective techniques for critical mineral production and recovery from industrial wastewater will lead to enhance the current recycling rate of the mineral and reduce potential hazards of industrial wastewater bearing high concentrations of minerals. Here, in this study, ionic metal-organic framework (iMOF)-based sorbents are successfully designed for critical metal ion extraction from aqueous solution. The iMOFs are highly stable in aqueous solution over wide pH ranges, indicating that they are suitable for use in industrial wastewater with harsh chemical environments. The sorption capacity of iMOFs towards Ni reaches 34.1 mg/g with a removal efficiency of >99.9%. Notably, complete extraction of Ni takes place within 5 min, which is much faster compared to other sorbents. Moreover, the iMOFs can simultaneously coextract multiple minerals, proving their effectiveness as general sorbents for critical mineral recovery.

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

Rapid Sensing to Facilitate Purification of Rare Earth Element-Containing Process Streams Produced Through Membrane-Assisted Solvent Extraction

The development of an economically competitive domestic supply of rare earth elements and yttrium (REY) is necessary for our nation’s economic growth and national security. The achievement of a secure domestic supply of REY requires not only the development of effective processes for recovery of REY from naturally occurring materials and/or recycled products, but also the development of downstream processes for the ultimate production of high-REY content solids. An impediment to the development of such processes is the scarcity of analytical methods that provide rapid determination of the process stream compositions. In this work, a membrane-based extraction process was used to selectively recover REYs from a dilute solution in the presence of much higher concentrations of Ca and Al. In tandem, the use of a portable spectrometer equipped with an immobilized zinc adeninate benzene tricarboxylate metal-organic framework sensing material makes possible the rapid detection of the presence of ppm concentrations of Tb and Eu in both weakly acidic and strongly acidic process streams within minutes. A solvent extraction processing time of 15-60 min maximized REY selectivity over gangue ions while achieving up to 80% REY and minimal gangue ion recovery. Taken together, these experiments highlight not only an innovative method for REY purification but also the importance of inexpensive, portable characterization methods for near real-time analysis of REY content.

Membrane-assisted solvent extraction↗
DOE OSTI2026

Final Scientific/Technical Report: Simultaneous Lithium Extraction and Thin-Film Deposition of Lithium Metal for Low-Cost, High-Energy Anodes from Brine Resources

This report describes the scale-up and pilot validation of Alpha-En's Reductive Lithium Extraction (RLE) process, which directly converts lithium ions from aqueous brine-derived feedstocks into thin-film lithium metal anodes, demonstrating greater than 50% extraction efficiency, battery performance matching or exceeding commercial lithium metal controls in coin and pouch cells, and continuous roll-to-roll production of a meter-scale lithium metal anode strip.

25 ENERGY STORAGE↗
NASA NTRS2018

ISRU Technology Development for Extraction of Water from the Mars Surface

Goals: Develop technologies to extract water from planetary regolith considering production rate vs: energy/power consumption (efficiency, yield, heat recuperation options); Mass and sizing: modularity, batch sizes, soil feed options, etc.; Ruggedness in terms of soil, environmental, and operational parameters; seals and component wear, etc.; Removal of product and disposal of spent material. Summary: Technology development is underway for several ISRU water extraction hardware concepts for Mars application - Hydrated minerals (Auger dryer, Microwave, Open Air), Subsurface Ice (Rodwell); Models are developed with experimental and breadboard efforts for use in larger ISRU system models; Each effort consists of a 3 year development plan, with the goal of integrating into a larger subsystem test in 2020 - Concurrent technology advance allows for flexibility in system design; depending on architecture decisions and progress of associated subsystems.

In-Situ Resource Utilization↗
NASA NTRS2026

Turbofan Engine Power Extraction Demonstration Final Report

As GE Aerospace advances toward a revolutionary step change in propulsion efficiency, the integration and demonstration of new engine architectures and technology systems are essential. The NASA Turbofan Engine Power Extraction Demonstration (PEx), conducted through the Hybrid Thermally Efficient Core (HyTEC) project, aims to develop and demonstrate megawatt-class hybrid electric capability on a modern commercial turbofan engine. The hybrid electric system is critical to meeting the needs of the U.S. aviation industry for next-generational propulsion systems with greater efficiency, durability, and range. This supports energy independence and helps ensure the security and resilience of one of America's largest export industries. The PEx project specifically targets three key objectives: mechanically integrating hybrid electric capability into a commercial turbofan engine, integrating electric machine control with turbofan control for advanced power management, and de-risking performance modeling of future hybrid electric architectures. To mature these technologies to Technology Readiness Level (TRL) 6, a series of electric power system component tests and a baseline engine performance test campaign were conducted. These efforts culminated in an integrated hybrid electric turbofan test campaign demonstrating power extraction, power insertion, and power transfer between spools. Tests of the electric power system were completed at GE Aerospace’s Electrical Power Integrated Systems Center in Dayton, Ohio and engine tests were completed at Peebles Test Operation in Peebles, Ohio. Hybrid electric trade studies extended the demonstrated capability to altitude using the validated cycle model from the PEx test campaigns, allowing for comments on expanded mission benefits not demonstrated in the ground campaign. The knowledge gained from PEx also supports GE Aerospace’s Compact Core Demonstrator as part of HyTEC Phase 2 and ultimately informs the implementation of hybrid electric systems in the next generation of GE Aerospace commercial engine products. This report provides a summary of the program background, test campaigns, trade studies, and insights into the technical maturation required to support future commercial products.

Hybrid Electric↗
DOE OSTI2024

Comprehensive review of combustion ion chromatography for the analysis of total, adsorbable, and extractable organic fluorine

Poly‐ and perfluoroalkyl substances (PFAS) are a class of persistent organic pollutants whose high stability and appreciable water solubility have led to near‐global contamination. PFAS are bioaccumulative toxins that have been linked to a myriad of disorders and have been detected nearly universally in human blood. Liquid chromatography‐tandem mass spectrometry is the most frequent method used for quantitation, though this typically only measures a few dozen of the >14 000 known PFAS and has been shown to account for a small portion of the total organic fluorine present. Sum parameter methods such as total, extractable, and adsorbable organic fluorine have emerged as alternative measurements for PFAS determination. Combustion ion chromatography has become the preferred method for organofluorine measurement where the sorbent or extract containing PFAS is combusted and the emitted hydrofluoric acid (HF) is a measure of the cumulative organofluorine present. Herein we critically review the types of organofluorine measurement, their separation from the sample matrix, and key parameters of the analytical instrument that affect sensitivity, reproducibility, and recovery with regards to PFAS analysis.

Chemistry↗
DOE OSTI2025

Selectively extracting lithium from single and mixed cathode materials

With the burgeoning reliance on lithium-ion batteries for sustainable energy solutions and electric transportation, the environmental and resource management associated with battery disposal are increasingly critical. Addressing these challenges necessitates innovative recycling techniques that recover valuable battery components, particularly lithium. This research introduces a universal, eco-friendly approach tailored for the efficient selective extraction of lithium from both single and mixed cathode materials, achieving impressive selective leaching efficiencies of lithium (99.51 % for LFP, 90 % for NMC, and 97.24 % for mixed cathode). Surprisingly, leaching efficiency of lithium from NMC can be significantly improved by introducing LFP since LFP can remove the dense transition-metal salts on the surface of NMC. The extracted lithium is recovered as lithium carbonate with battery-grade purity. This study also highlights the reuse of formic acid and the adoption of oxygen as an oxidizing agent to prevent wastewater production. Therefore, this method provides a robust foundation for sustainable lithium battery recycling.

economically and environmentally feasible↗
DOE OSTI2024

Residual resistance ratio measurement system for Nb 3 Sn wires extracted from Rutherford cables

Residual resistance ratio (RRR) of superconducting strands is an important parameter for magnet electrical stability. RRR serves as a measure of the low-temperature electrical conductivity of the copper within a conductor that has a copper stabilization matrix. For Nb 3 Sn, due to the need of a reaction heat treatment, the technical requirements for high quality measurements of strands extracted from Rutherford cables are particularly demanding. Quality of wire, cabling deformation, heat treatment temperature, heat treatment atmosphere, sample handling, and measurement methods can all affect the RRR. Therefore, as an integral part of the electrical quality control (QC) of Nb 3 Sn Rutherford cables manufactured at the Lawrence Berkeley National Laboratory, it was prudent that we established a RRR measurement system that can isolate the assessment of cable-fabrication-related impacts from sample preparation and measurement factors. Here we describe a bespoke cryocooler-based measurement system, capable of measuring RRR of over 80 samples in a single cooldown. The samples are mounted on custom-designed printed circuit boards that accommodate the shape of strands extracted from a Rutherford cable without added deformation, which we will show is critical in ensuring that the measurements accurately represent the RRR values of the conductor within the cable. Using this sample mounting solution, we routinely measure the overall RRR of the strand as well as individual intra-strand sections corresponding to both cable edges and cable broad faces with high reproducibility. Such measurements provide valuable information on the variation of RRR along the length of the strands as well as across strand productions and cable runs over time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Multioutput Convolutional Neural Network for Improved Parameter Extraction in Time-Resolved Electrostatic Force Microscopy Data

Time-resolved scanning probe microscopy methods, like time-resolved electrostatic force microscopy (trEFM), enable imaging of dynamic processes ranging from ion motion in batteries to electronic dynamics in microstructured thin film semiconductors for solar cells. Reconstructing the underlying physical dynamics from these techniques can be challenging due to the interplay of cantilever physics with the actual transient kinetics of interest in the resulting signal. Previously, quantitative trEFM used empirical calibration of the cantilever or feed-forward neural networks trained on simulated data to extract the physical dynamics of interest. Both these approaches are limited by interpreting the underlying signal as a single exponential function, which serves as an approximation but does not adequately reflect many realistic systems. Here, we present a multi-branched, multi-output convolutional neural network (CNN) that uses the trEFM signal in addition to the physical cantilever parameters as input. The trained CNN accurately extracts parameters describing both single-exponential and bi-exponential underlying functions, and more accurately reconstructs real experimental data in the presence of noise. This article demonstrates an application of physics-informed machine learning to complex signal processing tasks, enabling more efficient and accurate analysis of trEFM.

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

Toward Sustainable Lithium Recovery: A Universal Hydrothermal Approach for Lithium Extraction

The rapid growth of lithium-ion battery (LIB) deployment presents critical challenges in sustainable end-of-life management and raw material recovery. Conventional pyrometallurgical and hydrometallurgical methods suffer from high energy demand, lithium loss, and complex wastewater treatment. This study established a universal, highly efficient, and sustainable hydrothermal route for lithium extraction and material recovery from various spent lithium-ion battery cathodes using 1,2,4,5-benzenetetracarboxylic acid (BTCA). The optimized process achieved over 99% lithium leaching efficiency for lithium iron phosphate (LFP) and LiNi x Mn y Co 1–x–y O 2 (NMC), with transition metal coleaching below 1%. It was also broadly applicable to lithium manganese oxide, lithium cobalt oxide, and black mass, achieving 98.5%, 98.95%, and 94.06% leaching efficiencies, respectively. The extracted lithium was directly converted into battery-grade lithium sources, while transition metals were recovered as oxides. Unreacted BTCA was efficiently regenerated and reused without degradation. Electrochemical evaluation confirmed that cathode materials synthesized with recovered lithium exhibit comparable performance to commercial products. Compared to conventional hydrometallurgy, the BTCA-based process increased revenue by over 40% and reduced greenhouse gas emissions by up to 39%. This closed-loop, chemistry-agnostic strategy offered a scalable and economically viable solution for industrial LIB recycling, enabling resource circularity and reducing dependency on primary critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reactions of the ˙NO 3 radical with nuclear extraction ligands in alkane solution

Here, the reactivity of the nitrate radical (NO 3 ˙) with organophosphorus and amidic actinide and lanthanide complexing agents of interest to nuclear solvent extraction applications was measured, resulting in the first-ever reported bimolecular rate constants for this radicals’ reactions in dodecane solution. The order of reactivity for neutral organophosphorus compounds showed faster rate constants with increasing electron density on the phosphoryl phosphorus atom, indicating an increasing facility for electron abstraction reactions occurring in addition to H-atom abstraction from the ligand alkane chains. The only acidic organophosphorus compound investigated, HEH[EHP], showed low reactivity with the NO 3 ˙ radical, attributed to its dimerization in this non-polar solvent. Amide ligand reaction rates were faster than for organophosphorus molecules, suggesting more facile H-atom abstraction from carbonyl activated methylene and amyl groups. While all rate constants were slower than the diffusion-limited rate they were still rapid enough to result in significant oxidation of solvent extraction ligands in dodecane solution.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗
DOE OSTI2025

Dynamic in-context learning with conversational models for data extraction and materials property prediction

The advent of natural language processing and large language models (LLMs) has revolutionized the extraction of data from unstructured scholarly papers. However, ensuring data trustworthiness remains a significant challenge. In this paper, we introduce PropertyExtractor, an open-source tool that leverages advanced conversational LLMs such as Google gemini-pro and OpenAI gpt-4, blends zero-shot with few-shot in-context learning, and employs engineered prompts for the dynamic refinement of structured information hierarchies—enabling autonomous, efficient, scalable, and accurate identification, extraction, and verification of material property data. Our tests on material data demonstrate precision and recall that exceed 95% with an error rate of ∼9%, highlighting the effectiveness and versatility of the toolkit. Finally, databases for 2D material thicknesses, a critical parameter for device integration, and energy bandgap values are developed using PropertyExtractor. In particular, for the thickness database, the rapid evolution of the field has outpaced both experimental measurements and computational methods, creating a significant data gap. Our work addresses this gap and showcases the potential of PropertyExtractor as a reliable and efficient tool for the autonomous generation of various material property databases, advancing the field.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2025

Direct Extraction of Uranium-Lanthanide Oxides in Tributyl Phosphate

Abstract Direct extraction of used nuclear fuel (UNF) in an organic solution could be more efficient than the previous practice with aqueous solutions. However, the UNF would need to be treated via voloxidiation before being processed using solvent extraction. The voloxidation process can form oxide and/or nitrate compounds. This work investigated the dissolution of uranium/lanthanide oxides in 30 vol % TBP diluted in dodecane (pre-equilibrated with 4 M nitric acid) in a glass reactor with air sparging to ascertain the uranium/lanthanide oxide dissolution behavior prior to scaling the process. The uranium/lanthanide oxides were prepared by co-precipitating uranium/lanthanide nitrates with hydroxide and then calcined to form a mixed oxide. While the relative concentrations of the lanthanides are not representative of used nuclear fuel, the neodymium and erbium allowed ease of tracking dissolution with visible spectroscopy. Cerium was used as a surrogate for plutonium. The dissolution rate of the oxides was similar but incomplete. A miniscule amount of cerium, as cerium oxide, took several months to slowly dissolve; however, when co-precipitated with uranium and other lanthanides, a significant amount of cerium dissolved readily.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Bayesian Neural Network Variational Autoencoder Inverse Mapper (BNN-VAIM) and its application in Compton Form Factors extraction

Abstract We extend the Variational Autoencoder Inverse Mapper (VAIM) framework for the inverse problem of extracting Compton Form Factors (CFFs) from deeply virtual exclusive reactions, such as the unpolarized Deeply virtual exclusive scattering (DVCS) cross section. VAIM is an end-to-end deep learning framework to address the solution ambiguity issue in ill-posed inverse problems, which comprises of a forward mapper and a backward mapper to simulate the forward and inverse processes, respectively. In particular, we incorporate Bayesian Neural Network (BNN) into the VAIM architecture (BNN-VAIM) for uncertainty quantification. By sampling the weights and biases distributions of the BNN in the backward mapper of the VAIM, BNN-VAIM is able to estimate prediction uncertainty associated with each individual solution obtained for an ill-posed inverse problem. We first demonstrate the uncertainty quantification capability of BNN-VAIM in a toy inverse problem. Then, we apply BNN-VAIM to the inverse problem of extracting 8 CFFs from the unpolarized DVCS cross section.

Instruments & Instrumentation↗
DOE OSTI2025

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗