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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

Mechanism-guided engineering of a minimal biological particle for genome editing

The widespread application of genome editing to treat and cure disease requires the delivery of genome editors into the nucleus of target cells. Enveloped delivery vehicles (EDVs) are engineered virally derived particles capable of packaging and delivering CRISPR-Cas9 ribonucleoproteins (RNPs). However, the presence of lentiviral genome encapsulation and replication proteins in EDVs has obscured the underlying delivery mechanism and precluded particle optimization. Here, we show that Cas9 RNP nuclear delivery is independent of the native lentiviral capsid structure. Instead, EDV-mediated genome editing activity corresponds directly to the number of nuclear localization sequences on the Cas9 enzyme. EDV structural analysis using cryo-electron tomography and small molecule inhibitors guided the removal of ~80% of viral residues, creating a minimal EDV (miniEDV) that retains full RNP delivery capability. MiniEDVs are 25% smaller yet package equivalent amounts of Cas9 RNPs relative to the original EDVs and demonstrated increased editing in cell lines and therapeutically relevant primary human T cells. These results show that virally derived particles can be streamlined to create efficacious genome editing delivery vehicles with simpler production and manufacturing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ambient energy for buildings: Beyond energy efficiency

The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during power outages. 3. National policies, incentives, and marketing should be enacted to promote ambient energy use. Federal administrative priorities should reflect the importance of ambient energy for buildings. Use of ambient energy should be encouraged through existing and new building codes and standards. 4. Ambient energy system design tools are needed for architects, engineers, builders, building scientists, realtors, appraisers, and consumers. PVWatts is used over 100 million times per year for photovoltaic system design. A similar, simple, and accessible tool for ambient design is crucial. 5. Training on ambient energy is needed throughout secondary, post-secondary, and continuing education for workforce development. Currently, only about 10% of colleges teach courses on passive heating and cooling systems. 6. Ambient-conditioned buildings should be demonstrated in all US climate zones. Performance should be monitored and reported, with quantitative case studies made widely available. 7. While current technology is sufficient to build high-performance ambient buildings now, research is needed to develop new technologies to harness ambient energy more effectively and more economically. Such advancements will facilitate adoption of ambient energy technologies in a wider range of buildings, including retrofits. Examples include windows with much lower thermal losses, use of the building shell as thermal storage, alternative light-weight thermal storage systems, sky radiation cooling systems, automated controls for solar gains and passive cooling, and ground coupling.

14 SOLAR ENERGY↗
DOE OSTI2024

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
DOE OSTI2024

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Vascular dysfunction in hemorrhagic viral fevers: opportunities for organotypic modeling

The hemorrhagic fever viruses (HFVs) cause severe or fatal infections in humans. Named after their common symptom hemorrhage, these viruses induce significant vascular dysfunction by affecting endothelial cells, altering immunity, and disrupting the clotting system. Despite advances in treatments, such as cytokine blocking therapies, disease modifying treatment for this class of pathogen remains elusive. Improved understanding of the pathogenesis of these infections could provide new avenues to treatment. While animal models and traditional 2D cell cultures have contributed insight into the mechanisms by which these pathogens affect the vasculature, these models fall short in replicating in vivo human vascular dynamics. The emergence of microphysiological systems (MPSs) offers promising avenues for modeling these complex interactions. These MPS or ‘organ-on-chip’ models present opportunities to better mimic human vascular responses and thus aid in treatment development. In this review, we explore the impact of HFV on the vasculature by causing endothelial dysfunction, blood clotting irregularities, and immune dysregulation. We highlight how existing MPS have elucidated features of HFV pathogenesis as well as discuss existing knowledge gaps and the challenges in modeling these interactions using MPS. Understanding the intricate mechanisms of vascular dysfunction caused by HFV is crucial in developing therapies not only for these infections, but also for other vasculotropic conditions like sepsis.

42 ENGINEERING↗
DOE OSTI2024

"A" is for Ammonia: Why and How Fertilizer May Power the Planet [Slides]

Ammonia (chemical formula NH 3 ) is so pervasive in our history that human beings simply wouldn't exist without it: 4 billion people on this planet are fed by food grown using ammonia fertilizer, but this powerful molecule consumes nearly 2% of the world's energy supply to be produced at an industrial scale. This talk will first explore the energy challenges of ammonia's current means of industrial production, followed by a new vision for its synthesis using only renewable electricity, air and water, and opportunities to use ammonia as a hydrogen source. Fertilizer may one day fuel more than just our mouths.

08 HYDROGEN↗
DOE OSTI2026

Environmental Contributions to Proton Sharing in Protein Low-Barrier Hydrogen Bonds

Hydrogen bonds (H-bonds) are central to biomolecular structure and dynamics. Although H-bonds are typically characterized by well-defined proton positions, proton delocalization has been proposed to play a role in facilitating enzyme catalysis and allostery in some systems. Experimentally locating protons is difficult, hampering the study of proton mobility in H-bonds. We used neutron crystallography, atomic resolution X-ray bond length analysis, and large quantum mechanics/molecular mechanics-Born–Oppenheimer molecular dynamics (QM/MM-BOMD) simulations to comprehensively characterize the shared proton/deuteron in a Glu–Asp low-barrier hydrogen bond (LBHB) in the bacterial protein YajL that is a conventional H-bond in the homologous disease-associated human protein DJ-1. X-ray bond length analysis of protiated and perdeuterated DJ-1 and YajL shows no significant effect of deuteron substitution on these carboxylic acid-carboxylate H-bonds but does reveal an effect at the active site glutamic acid near a cysteine thiolate. Residues in an H-bonded network that might favor LBHB formation in YajL were interrogated by the mutation of homologous residues in DJ-1. A distal DJ-1 substitution increases proton delocalization in the Glu–Asp H-bond, demonstrating that mutations within extended H-bond networks can modulate proton transfer barriers in carboxylic acid-carboxylate H-bonds. In addition, proton mobility in the H-bond is correlated with dimer-spanning motions in the QM/MM-BOMD simulations of YajL and DJ-1. Our results show that proton delocalization can be tuned using combined bioinformatic, structural, and computational information, opening the possibility of using engineered proton delocalization as a probe of H-bonding environments and as a tool to test hypotheses about LBHB function.

Lin, Jiusheng [University of Nebraska, Lincoln, NE↗
DOE OSTI2026

Elucidating biodegradation of dimethyl terephthalate by two Rhodococcus strains for its valorization applications

Dimethyl terephthalate (DMT) serves as the precursor in the production of polyethylene terephthalate, polytrimethylene terephthalate, and polybutylene terephthalate. The widespread use of DMT in the polymer industry and its ubiquitous existence in end products raise alarms about its potential harm to humans and animals. DMT can enter the environment through the degradation of polymers and their end products, and cause endocrine disruption, oxidative stress, and an elevated risk of cancer. In recent years, DMT has also gained renewed interest in its potential for plastic recycling and upcycling. In this study, we identified two strains of Rhodococcus that possess DMT-degrading capabilities and utilized transcriptomic analysis and gene knockout to elucidate the mechanisms of DMT degradation. R. opacus PD630 and R. jostii RPET were found to convert up to 1 g/L DMT into mono-methyl terephthalate (MMT). A putative DMTase (RS34275) was identified for this conversion. R. jostii RPET also demonstrates the ability to convert DMT into MMT and to utilize MMT for its cellular growth via the terephthalate pathway. A putative MMTase (RS21885) as the sole enzyme was identified for the conversion of MMT into terephthalate in the RPET strain. In addition, we successfully produced lycopene and lipids from an engineered RPET strain using DMT as a substrate. Our findings will facilitate future DMT bioremediation and bio-upcycling of DMT-associated plastics, enabling the production of value-added products.

Biodegradation↗
DOE OSTI2026

Poster: Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The rapid integration of artificial intelligence (AI) in the utility transmission and distribution (T&D) sector is revolutionizing traditional grid management practices. As utilities encounter complexities from evolving consumer behaviors and energy integration, AI becomes a critical solution for enhancing grid monitoring, fault detection, and operational optimization. However, increased reliance on interconnected technologies introduces significant cybersecurity risks, regulatory compliance challenges, and human factors concerns. This study proposes a strategic, responsible and consequence-driven approach to AI implementation, examining the dual nature of AI adoption by highlighting its transformative benefits for utilities and associated risks. It provides utilities with a framework for evaluating AI integration, enabling them to navigate challenges and capitalize on opportunities to achieve greater reliability, efficiency, and resilience in an increasingly complex energy landscape.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

"A" is for Ammonia: Why and How Fertilizer May Power the Planet

Ammonia (chemical formula NH3) is so pervasive in our history that human beings simply wouldn't exist without it: 4 billion people on this planet are fed by food grown using ammonia fertilizer, but this powerful molecule consumes nearly 2% of the world's energy supply to be produced at an industrial scale. This talk will first explore the energy challenges of ammonia's current means of industrial production, followed by a new vision for its synthesis using only electricity, air and water, and opportunities to use ammonia as a hydrogen source. Fertilizer may one day fuel more than just our mouths.

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

Isolation and characterization of IgG3 glycan-targeting antibodies with exceptional cross-reactivity for diverse viral families

Broadly reactive antibodies that target sequence-diverse antigens are of interest for vaccine design and monoclonal antibody therapeutic development because they can protect against multiple strains of a virus and provide a barrier to evolution of escape mutants. Using LIBRA-seq (linking B cell receptor to antigen specificity through sequencing) data for the B cell repertoire of an individual chronically infected with human immunodeficiency virus type 1 (HIV-1), we identified a lineage of IgG3 antibodies predicted to bind to HIV-1 Envelope (Env) and influenza A Hemagglutinin (HA). Two lineage members, antibodies 2526 and 546, were confirmed to bind to a large panel of diverse antigens, including several strains of HIV-1 Env, influenza HA, coronavirus (CoV) spike, hepatitis C virus (HCV) E protein, Nipah virus (NiV) F protein, and Langya virus (LayV) F protein. We found that both antibodies bind to complex glycans on the antigenic surfaces. Antibody 2526 targets the stem region of influenza HA and the N-terminal domain (NTD) region of SARS-CoV-2 spike. A crystal structure of 2526 Fab bound to mannose revealed the presence of a glycan-binding pocket on the light chain. Antibody 2526 cross-reacted with antigens from multiple pathogens and displayed no signs of autoreactivity. These features distinguish antibody 2526 from previously described glycan-reactive antibodies. Further study of this antibody class may aid in the selection and engineering of broadly reactive antibody therapeutics and can inform the development of effective vaccines with exceptional breadth of pathogen coverage.

Microbiology↗
DOE OSTI2026

Design and Integration of a Compact Mobile Outdoor Soil Sampling Agricultural Robot

The lack of feedback on soil management for crop systems necessitates the collection of soil samples to derive insights into prevailing soil conditions. Achieving an accurate model of these plantations requires a substantial number of soil samples, which is a labor-intensive process that can suffer from inconsistencies in both the methodology of collection and the locations from which samples are gathered. In addition, the close spacing of crop rows constrains the maneuverability of mobile agricultural equipment during sample collection. This article proposes the use of agricultural robotics to facilitate the acquisition of composite soil samples with minimal human intervention, allowing for precise data collection for a Populus plant system. More specifically, this article presents a case study on the design and construction of a compact agricultural robot for soil sample collection. The performance of the robot, including its soil collection efficacy, maneuverability, and positional accuracy, is evaluated.

42 ENGINEERING↗
DOE OSTI2025

"A" is for Ammonia: Why and How Fertilizer May Power the Planet [Slides]

Ammonia (chemical formula NH3) is so pervasive in our history that human beings simply wouldn't exist without it: 4 billion people on this planet are fed by food grown using ammonia fertilizer, but this powerful molecule consumes nearly 2% of the world's energy supply to be produced at an industrial scale. This talk will first explore the energy challenges of ammonia's current means of industrial production, followed by a new vision for its synthesis using only renewable electricity, air and water, and opportunities to use ammonia as a hydrogen source. Fertilizer may one day fuel more than just our mouths.

08 HYDROGEN↗
DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗
DOE OSTI2024

Computational multiphysics modeling of radioactive aerosol deposition in diverse human respiratory tract geometries

The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning

Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An end-to-end workflow for executing a classically bootstrapped variational quantum algorithm on an academic quantum computer

Academic quantum computing platforms often face unique challenges in executing quantum workloads due to fragmented software environments and limited engineering support. Unlike commercial ecosystems, academic devices typically evolve without full-stack integration in mind, making it difficult to run complex applications—such as variational quantum algorithms (VQA)—reliably and efficiently. Issues such as incompatible software layers and lack of automated job management significantly increase the overhead of theory-experiment collaboration. To address these challenges, we develop a modular, end-to-end workflow that decouples application-layer code from low-level hardware control, automates circuit submission and result collection, and supports fine-grained circuit-level job scheduling and recovery. The architecture employs a dual-end application programming interface (API) design, enabling robust operation across unstable or resource-constrained hardware backends. For practical use, the framework is lightweight and user-friendly, allowing rapid prototyping of full-stack workflows using basic Python tools. We validate this workflow on a high-fidelity trapped-ion quantum computer by demonstrating a variational quantum eigensolver (VQE) experiment with a classically bootstrapped ansatz initialization technique. The system successfully executed over 60,000 circuits across multiple molecular test cases with minimal human intervention, highlighting the framework’s effectiveness in enabling reproducible, resilient quantum experimentation in academic settings.

Clifford↗