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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The damage Mechanics challenge Results: Participant predictions compared with experiment

In this article, We present results from a recent exercise where participating organizations were asked to provide model-based blind predictions of damage evolution in 3D-printed geomaterial analogue test articles. Participants were provided with a range of data characterizing both the undamaged state (e.g., ultrasonic measurements) and damage evolution (e.g., 3-point bending, unconfined compression, and Brazilian testing) of the material. In this paper, we focus on comparisons between the participants’ predictions and the previously secret challenge problem experimental observations. We present valuable lessons learned for the application of numerical methods to deformation and failure in brittle-ductile materials. The exercise also enables us to identify which specific types of calibration data were of most utility to the participants in developing their predictions. Further, we identify additional data that would have been useful for participants to improve the confidence of their predictions. Consequently, this work improves our understanding of how to better characterize a material to enable more accurate prediction of damage and failure propagation in natural and engineered brittle-ductile materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The kinetics of SARS-CoV-2 infection based on a human challenge study

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Overcoming Challenges to Nuclear-Maritime Applications

This report is the fifth deliverable in a series of reports set forth by the Department of Energy (DOE), led by the American Bureau of Shipping (ABS), for the research award titled “Accelerating Commercial Maritime Demonstration Projects for Advanced Nuclear Reactor Technologies.” The report highlights guidance to bridge the gaps between innovative nuclear technologies and their practical implementation in maritime environments. The previous reports discussed specific technical, economic and regulatory challenges that may be expected when developing and establishing advanced nuclear technologies for commercial maritime applications. This report supports the mission of the U.S. National Reactor Innovation Center (NRIC) to demonstrate projects with industry and acts as a resource for the various stakeholders associated with the development of novel applications for advanced reactors. The previous reports discuss the interest in nuclear technology applications for decarbonized energy and identify the potential demands in nuclear energy supply and price. The work in these reports supports the recently issued nuclear Executive Orders (EOs). Specifically, EO 14299, “Deploying Advanced Nuclear Reactor Technologies for National Security”, and EO 14300, “Ordering the Reform of the Nuclear Regulatory Commission,” by ensuring the rapid development, deployment, and use of advanced nuclear technologies; and increasing the deployment of new nuclear reactor technologies, such as Generation III+ and IV reactors, modular reactors, and microreactors to support America leading the commercialization of affordable and abundant nuclear energy.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

IBR Bulk System Protection Issues and Modeling Challenges

Issue to be Address: Difficulty in predicting Inverter (IBR) generation dynamic response characteristics. Main challenges are unavailability of proprietary control details for modeling and the aggregate mixed IBRs with different dynamic response characteristics all contributing during system faults. Framework for Discussion: Identifying issues by sharing experience Reviewing options to improve IBR modeling accuracy, computation speed, use of test results. Presenting related research by EPRI and PG&E (DOE project) Desired Outcomes: Provide technical update for participants Get feedback and suggestions for ongoing research Improve research collaboration

IBR, Protection Challenges, dynamic response, IBR ↗
DOE OSTI2025

Challenges and Opportunities for Rechargeable Aqueous Sn Metal Batteries

Rechargeable aqueous batteries based on metallic anodes hold tremendous potential of high energy density enabled by the combination of relatively low working potential and large capacity while retaining the intrinsic safety nature and economical value of aqueous systems; However, the realization of these promised advantages relies on the identification of an ideal metal anode chemistry with all these merits. In this review, the emerging Sn metal anode chemistry is examined as such an anode candidate in both acidic and alkaline media, where the inertness of Sn toward hydrogen evolution, flat low voltage profile, and low polarization make it a unique metal anode for aqueous batteries. From a panoramic viewpoint, the key challenges and detrimental issues of Sn metal batteries are discussed, including dead Sn formation, self‐discharge, and electrolyte degradation, as well as strategies for mitigating these issues by constructing robust Sn anodes. New design approaches for more durable and reliable Sn metal batteries are also discussed, with the aim of fully realizing the potential of Sn anode chemistry.

Sn metal↗
DOE OSTI2025

Demonstration of the Reproducibility Challenges in the Sintering Behavior of Lithium‐Stuffed Garnets in Scaling up Synthesis

Lithium-stuffed garnets, such as Li 7 La 3 Zr 2 O 12 (LLZO), are promising candidates for next-generation solid-state batteries because of their high room-temperature ionic conductivity and chemical stability against lithium metal anodes, which are crucial for achieving higher energy density. However, realizing LLZO's potential in practical devices requires synthesis methods that can be scaled reliably to large batch sizes for manufacturing. Herein, we investigate the sintering reproducibility of LLZO synthesized at larger scales using ultrasonic spray pyrolysis, a cost-effective and scalable synthesis route. Two 100 g batches of Al-doped LLZO are prepared and their sintering behavior is examined in detail. Both Al-LLZO batches contain over 90 wt.% cubic-phase LLZO, and both batches exhibit room temperature conductivities greater than 1 × 10 −4 S cm −1 at a relative density above 0.8. However, variations in secondary phases and subtle differences in Al content lead to significant differences in densification and microstructure. These results demonstrate that LLZO's sintering behavior is highly sensitive to small changes in secondary phases and Al content, creating reproducibility challenges when moving from laboratory- to manufacturing-scale synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Current Advances in i‐MAX Phases and their Two Dimensional Derivative i‐MXenes: Challenges and Opportunities (Adv. Electron. Mater. 21/2025)

The discovery of quaternary (M′ 2/3 M′′ 1/3 ) 2 AX phases has introduced newly ordered i-MAX phases in the MAX phase community. These atomically layered solids display in-plane chemical ordering of M′ and M′′, featuring a frustrated triangular lattice overlaid on an M′ honeycomb arrangement and an A Kagomé lattice. This unique structure gives rise to novel electronic and magnetic properties, paving the way for diverse applications and the creation of new MXenes. Both experimental and theoretical research have confirmed that these i-MAX phases can be chemically exfoliated into single- or multilayered and vacancy-ordered 2D transition metal carbides, known as i-MXenes. These 2D i-MXenes exhibit intriguing optical, electrochemical, piezoelectric, and magnetic properties, which are decidedly reliant on the surface functional groups (-F, -OH, -O). This review encompasses all available theoretical and experimental studies on i-MAX and i-MXenes, with a focus on their fundamental properties, organized in multiple sections. Along with the experimental investigation, significant attention is also directed toward theoretical predictions of potential i-MAX phases and i-MXenes, including their structural, vibrational, electronic, optical, magnetic, mechanical, piezoelectric, and electrochemical properties. This article provides a comprehensive understanding of vital properties of these materials by providing a review of foundational literature with existing challenges, limitations, and future perspectives.

electrochemical, electronic↗
DOE OSTI2026

A Dendrite-Resistant Sodium/Porous-Carbon Anode for Solid-State Batteries – Strategies and Challenges for Low-Pressure Operation

Sodium solid-state batteries (Na-SSB) have gained interest recently due to the abundance of Na over Li, but they still tend to fail due to dendrites under practical current densities and cycling capacities. To overcome this, Na-SSBs are frequently tested with impractically high applied pressure. In this work, a porous carbon interfacial layer is utilized in conjunction with Na-ß”-Al2O3 solid electrolytes to enable Na-cycling at milder cell pressures. This sodium/porous carbon layer enables improved solid-state Na cycling in symmetric cells, up to a current density of 10 mA cm-2 at 25 °C. Cycling up to 1 mAh cm-2 is challenging with low pressure, but 1 mAh cm-2 capacity can be reliably cycled at 1 mA cm-2 at an elevated temperature of 60 °C in symmetric cells. Finally, the evolution of the interface and sodium/carbon anode is evaluated with cryogenic ion-milling and cross-sectional imaging revealing that, depending on testing temperature, pressure, current density, and capacity, void formation, Na-extraction from porous carbon, delamination of the porous carbon matrix, or a combination of these occurs at the interface between Na-metal and BASE. Despite this, excellent dendrite resistance is achieved, and a full-cell design utilizing a Na-transition metal oxide cathode is still able to achieve an areal capacity of ~ 2.7 mAh cm-2 at 0.125 mA cm-2. This work demonstrates an alternative pathway toward a Na-metal anode for Na-SSBs without the requirement of excessive stack pressure.

low-cost↗
DOE OSTI2026

Materials Studies of Niobium Thin Films for Quantum Circuit Applications: Progress and Challenges

Niobium (Nb) films have emerged as a crucial material in the development of superconducting qubits, which are key components in quantum computing technology. Here, this review provides a comprehensive examination of Nb films from a materials perspective, focusing on their intrinsic properties, fabrication methods/techniques, and their influence on qubit performance, particularly through surface and interface driven loss mechanisms. We discuss the key material properties that are essential for qubit operation. Various deposition techniques for Nb thin films, such as sputtering, evaporation, molecular beam epitaxy, and atomic layer deposition, are explored, alongside their impact on film quality, uniformity, and qubit performance. Additionally, the influence of surface roughness, thin-film thickness, and substrate materials on quantum coherence is analyzed. Challenges such as defects and material degradation in Nb films are reviewed, along with strategies to mitigate these issues. Finally, we present the latest advancements and future directions in Nb film research, including potential improvements to enhance qubit coherence and scalability for large-scale quantum computing systems. Ultimately, a deeper understanding of surface and interface phenomena is essential for pushing the limits of qubit performance and realizing next-generation quantum technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Modeling of Precipitation over Africa: Progress, Challenges, and Prospects

In recent years, there has been an increasing need for climate information across diverse sectors of society. This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change. Likewise, this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa. By leveraging a large volume of climate model outputs, numerous studies have investigated the model representation of African precipitation as well as underlying physical processes. These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies. This paper provides a review of the progress in precipitation simulation over Africa in state-of-the-science climate models and discusses the major issues and challenges that remain.

CMIP6↗
DOE OSTI2024

Challenges, progress, and future perspectives for cyanobacterial polyhydroxyalkanoate production

Polyhydroxyalkanoates (PHA) are a promising bio-based alternative to traditional plastics derived from petroleum. Cyanobacteria are photosynthetic organisms that produce PHA from CO 2 and sunlight, which can potentially reduce production costs and environmental footprint in comparison to heterotrophic bacteria cultures because (1) they utilize inorganic carbon sources for growth and (2) they do not require intensive aeration for oxygenation. Moreover, supplementing precursors such as propionate, acetate, valerate, etc., can be used to obtain various copolymers with plastic customizable properties in comparison to the classical homopolymers, such as polyhydroxybutyrate, PHB. This critical review covers the latest advances in PHA production, including recent discoveries in the metabolism interplay between PHA and glycogen production, and new insights into cultivation strategies that enhance PHA accumulation, and purification processes. This review also addresses the challenges and suggests potential solutions for a viable industrial PHAs production process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

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

A critical review of electrochemical heat pump technologies: Status, challenges, and perspectives

The development of advanced heat pump technologies is critical for reducing global energy consumption in the building sector, where space heating and cooling account for nearly 50% of energy use. Electrochemical heat pumps (EHPs) offer a promising alternative to vapor compression systems by enabling direct electrochemical-to-thermal energy conversion, often with environmentally benign working fluids that exhibit low or zero global warming potential (GWP). Prior literature has predominantly focused on chemically reactive heat pumps, while comprehensive assessments of electrochemical mechanisms remain limited. Here, this review addresses this gap by systematically evaluating the underlying principles, architectures, and performance metrics of EHP systems. Compared to conventional vapor compression systems, EHPs can achieve 10%-30% higher energy efficiency, with reported cooling coefficients of performance (COP c ) ranging from 3.5 to 14.3 under standard operating conditions. Despite these advantages, widespread adoption is hindered by challenges including membrane degradation, electrode fouling, sluggish redox kinetics, and elevated system-level capital costs. To address these limitations, the review outlines three research priorities: (i) the development of advanced membranes, catalysts, and electrode materials with enhanced chemical and mechanical stability; (ii) the application of molecular-level simulations for the rational design of high-performance redox-active working fluids; and (iii) the integration of advanced diagnostic techniques for real-time monitoring and sustained operation of EHPs. By consolidating recent advances and explicitly identifying technological and scientific gaps, this work uniquely contributes a comprehensive framework for guiding future electrochemical heat pump research and facilitating the transition to sustainable thermal management technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A framework for challenges and solutions in biodesign research

The bioeconomy represents an advanced economic paradigm that builds upon previous agricultural, industrial, and digital economic models. It seeks to tackle critical global challenges such as resource scarcity, escalating healthcare demands, and environmental degradation. At the heart of the bioeconomy is biomanufacturing, which uses natural or engineered enzymes or cell factories built from ​biological components like promoters, terminators, regulatory sequences, reporters, and functional genes into various chassis hosts (including animal, microbial, plant, and de novo systems) to create products such as food, energy, medicine, materials, chemicals, and engineered tissue/organs. An enabler of biomanufacturing is biodesign – also known as biosystems design and closely related to synthetic biology or engineering biology. This interdisciplinary field aims to understand and predictably modify existing life forms or create entirely new biological entities/systems using rational engineering strategies and automated design tools. Through these capabilities, biodesign supports the discovery, optimization, and creation of efficient platforms for biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine learning in materials research: Developments over the last decade and challenges for the future

The number of studies that apply machine learning (ML) to materials science has been growing at a rate of approximately 1.67 times per year over the past decade. In this review, I examine this growth in various contexts. First, I present an analysis of the most commonly used tools (software, databases, materials science methods, and ML methods) used within papers that apply ML to materials science. The analysis demonstrates that despite the growth of deep learning techniques, the use of classical machine learning is still dominant as a whole. It also demonstrates how new research can effectively build upon past research, particular in the domain of ML models trained on density functional theory calculation data. Next, I present the progression of best scores as a function of time on the matbench materials science benchmark for formation enthalpy prediction. In particular, a dramatic improvement of 7 times reduction in error is obtained when progressing from feature-based methods that use conventional ML (random forest, support vector regression, etc.) to the use of graph neural network techniques. Finally, I provide views on future challenges and opportunities, focusing on data size and complexity, extrapolation, interpretation, access, and relevance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗