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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reticular Materials and AI-Driven Computer Simulations for Seawater Mining of Valuable Metals (Final Technical Report)

This Final Technical Report describes our exploratory efforts that combine reticular materials synthesis (hydrolytically robust metal–organic frameworks, MOFs) with AI‑enabled molecular simulations to develop mechanistic, quantitative design rules for recovering lithium and other alkali-metal ions from highly dilute, competitive aqueous resources (e.g., seawater). The central outcome is a joint experimental–computational study of ion uptake in MOF‑808 (Chemical Science, 2025) that quantifies both thermodynamics and kinetics of Li + , Na + , and K + uptake and identifies how pore size, pore hydration state, dehydration penalties, and pore-window transport barriers govern selectivity. Guided by these insights, we synthesized and tested functionalized MOF‑808 and multivariate MOFs incorporating ion-recognition motifs (including carboxylates and crown-ether linkers) and evaluated uptake in synthetic seawater, highlighting framework topology and pore chemistry as levers for improved Li + /Na + discrimination. We also developed transferable simulation models, enhanced-sampling protocols, and automated workflows that enable systematic screening of porous sorbents.

42 ENGINEERING↗
DOE OSTI2026

Life Cycle Inventories and Data Gap Analysis for Rare Earth Elements: Neodymium and Dysprosium from Mining to Magnets

The United States demand for Neodymium-Iron-Boron (NdFeB) magnets, produced from rare earth elements (REEs) such as (Nd) and Dysprosium (Dy), far exceeds its nascent domestic production capacity, rendering it reliant on vulnerable global supply chains dominated by China. To guide research and development investments in securing U.S. REE supply, defensible benchmark metrics across environmental, economic, and social dimensions are needed. In this study, we built globally-representative, process-based cradle-to-cradle life cycle inventories for Nd and Dy in NdFeB magnets lifecycles, encompassing primary material acquisition, beneficiation, smelting and refining, metal processing, specialty alloy and chemical transformation, subcomponent manufacturing, consumer application (use phase) and end-of-life management. We carried out detailed literature review, and applied process engineering principles to build industry-representative upscaled life cycle inventories for both metals. We used these models to conduct bottom-up literature review and gap analysis on existing literature, compilation of data sources for each life cycle stage (and transformations where necessary), and a preliminary technoeconomic analysis (TEA)/life cycle costing analysis (LCCA). Findings from this work emphasize the need for metal specific, representative REE LCIs to establish robust benchmarks for advancing sustainable REE technologies and guiding R&D in REE supply chains.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Mining Product Reviews for Important Product Features of Refurbished iPhones

Problem: Remanufacturers want to increase consumer interest in refurbished products, which motivates the need to understand which product features are important to buyers of refurbished products such as mobile phones. Research Questions: This study addresses two questions. First, which product features are most important for buyers of refurbished iPhones? Second, how do those preferences differ from the preferences of buyers of new iPhones? Methods: Online reviews of iPhones are obtained and converted into a document–term matrix. Using this text model, three subsets of features are identified using statistical analysis of frequency of mention: most frequent, average, and least frequent. A logistic regression (LR) model is then used to identify which features are most predictive of whether a review is for a new or refurbished phone. Results: Buyers of refurbished phones mention battery health, screen/display, shell condition, and brand significantly more often than other features. Directly contrasting reviews of refurbished versus new phones shows that shell condition, brand, speaker, and charger are found to be the most predictive product features indicated in reviews for refurbished phones. Of those, the shell condition is significantly more predictive than the others. Implications: The results identify product features that remanufacturers of iPhones can emphasize to increase customer demand.

Anisi, Atefeh↗
DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗