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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Godiva IV central cavity neutron environment characterization with threshold neutron detectors

Godiva IV is a cylindrical fast burst reactor comprised of approximately 65 kg of highly enriched uranium that is operated by Los Alamos National Laboratory and sited at the National Criticality Experiments Research Center at the Nevada National Security Site in Nevada in the United States. Godiva IV is typically operated at delayed critical and in the regime spanning from sub-prompt to super-prompt bursts. Godiva IV is used for sample irradiations, criticality safety demonstrations, dosimetry studies, and for studying super-prompt behavior. In preparation for both an upcoming experiment to reduce uncertainties in the prompt fission spectrum for 235U using threshold neutron detectors, and for future research using Godiva IV, it was desired to exercise the process of the selection of threshold neutron detectors/activation foils, radiation metrology, and the subsequent adjustment of the neutron spectrum. For this exercise, nine high purity threshold neutron detectors/activation foils were irradiated in a Godiva IV burst. The foils were then analyzed using a high-purity germanium detector in the NCERC counting laboratory to determine end of irradiation specific activities for available IRDFF-II reactions. This work summarizes the Godiva IV foil irradiation, radiation metrology results, and adjusted neutron spectrum. The results of this exercise ultimately characterized the neutron environment inside the sample irradiation cavity inside Godiva IV to a higher degree than previously performed, informed decisions for the upcoming larger scale experiment, and will inform future neutron spectrum characterizations at NCERC.

Whitman, Nicholas H.↗
DOE OSTI2024

Photoinduced Carbon Dioxide Release via a Metastable Photoacid in a Nonaqueous Environment

Capturing and concentrating carbon dioxide (CO 2 ) from the atmosphere is an important modern scientific and technological challenge. CO 2 can be captured by forming a carbamate bond with amines, most notably monoethanolamine (MEA). Regenerating MEA by releasing the captured CO 2 requires heating the carbamate solution, which is energy-demanding and wasteful. Recently, photoacids were used to convert light input into pH change, which in turn released CO 2 from aqueous carbonate solutions. Here, we report a merocyanine photoacid that releases CO 2 from a non-aqueous carbamate solution of MEA, thereby extending the utility of this concept to a wider range of capture agents and environments. Based on the absorption spectra of the photoacid in the presence of acids and CO 2 , we show that the photoacid cycle and the CO 2 capture of MEA are two separate equilibria that are coupled to each other via protons. Then, we demonstrate that irradiating 405 nm light on the sample can induce release of CO 2 which we detect using an in-line mass spectrometer. This work highlights an alternative path for optimizing a photo-induced CO 2 capture and release system.

Amines↗
DOE OSTI2024

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗
DOE OSTI2025

A Comparison of Novel Woodstove Catalytic Combustors to Improve Low Temperature Light off and Catalyst Stability at High Temperatures and Corrosive Environments, Including Stability of Catalytic Combustors used in Coastal Environments

Wood heaters with catalytic combustors often emit higher levels of particulate matter (PM) and volatile organic compounds (VOCs) at startup before the catalytic combustor is at operational temperature. This project aims to advance wood heater catalytic combustor technology by studying degradation mechanisms in failed field catalysts and using those insights to develop an improved catalytic combustor. Findings will provide critical insights into the degradation mechanisms of wood heater catalytic combustors and inform the design of catalysts that deliver improved efficiency, durability, and performance compared to current commercial products. The outcomes of this project will not only improve catalytic combustor technology but also contribute to operational guidelines to extend catalyst lifetimes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2024

Fungal diversity and function in metagenomes sequenced from extreme environments

Fungi are increasingly recognized as key players in various extreme environments. Here we present an analysis of publicly-sourced metagenomes from global extreme environments, focusing on fungal taxonomy and function. The majority of 855 selected metagenomes contained scaffolds assigned to fungi. Relative abundance of fungi was as high as 10% of protein-coding genes with taxonomic annotation, with up to 289 fungal genera per sample. Despite taxonomic clustering by environment, fungal communities were more dissimilar than archaeal and bacterial communities, both for within- and between-environment comparisons. Relatively abundant fungal classes in extreme environments included Dothideomycetes, Eurotiomycetes, Leotiomycetes, Pezizomycetes, Saccharomycetes, and Sordariomycetes. Broad generalists and prolific aerial spore formers were the most relatively abundant fungal genera detected in most of the extreme environments, bringing up the question of whether they are actively growing in those environments or just surviving as spores. More specialized fungi were common in some environments, such as zoosporic taxa in cryosphere water and hot springs. Relative abundances of genes involved in adaptation to general, thermal, oxidative, and osmotic stress were greatest in soda lake, acid mine drainage, and cryosphere water samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Mil-Std-464C and Mil-Std-464D Electromagnetic Radiation Environment Evaluation

Many systems derive their electromagnetic radiation (EMR) environments from Mil-Std-464C or Mil-Std-464D, Electromagnetic Environmental Effects Requirements for Systems. This standard defines several EMR environments based on the type of system and expected application. Many nuclear weapon (NW) systems reference the ordnance environments as the starting point for their functional EMR requirements, since any item intended to go into Department of Defense (DOD) custody is expected to be certified hazards of electromagnetic radiation to ordnance (HERO) safe when exposed to the environments listed in Mil-Std-464 Table 9. This environment is defined as the envelope of all sources any system in DOD custody may ever encounter, however, and may include sources that are not relevant for a particular system. This document is intended to provide additional clarity on the Mil-Std-464C and Mil-Std-464D EMR environments, specifically the driving sources for the maximum ordnance levels. This supplementary information may be used to guide tailoring of relevant environments or application to different systems with the additional consideration of any shielding that may reduce the external environments defined in the military standard.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments

Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

DNA copy number variations↗
DOE OSTI2026

Characterizing degraded visual environments with scanning lenses to improve contrast recovery

Atmospheric aerosols, such as fog and smoke, degrade optical signals via the scattering and absorption of light, making it difficult to recover information from the surrounding environment. Here, we present a technique that measures the angular distribution of light in scattering environments to help recover these degraded optical signals. This is done by passing a collimated beam through the aerosol environment and collecting the scattered and unscattered light with an f-theta scan lens. The lens transforms the angular distribution of the scattered light into the linear domain, mapping the collected light onto a detector. The measured angular scattering distribution is then used to estimate the point spread function of the environment at an arbitrary stand-off distance. This point spread function can be used to deconvolve images blurred by the aerosol environment in which the angular scattering distribution was initially measured. With this approach, we demonstrate improvements in the effective resolution of deblurred images up to 26% over a 120-cm stand-off distance. Experimentation was performed in the Sandia National Laboratories tabletop fog chamber, a platform that generates aerosol environments analogous to real-world fogs. We intend to leverage this technique in future work to develop a low-SWaP system for the in situ characterization of aerosol environments.

Aerosols↗
DOE OSTI2024

TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) Report, Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. Under the TRUST work package, there are five testbeds and their associated engineering analysis baseline models (EABMs): 1. Contact Thermal Conductivity (CTC), 2. Nonlinear Dynamics (ND), 3. Sensors in Environments: Accelerometers (SE-A), 4. Sensors in Environments: Fiber Optic Displacement Gauges (SE-FOD), and 5. Sensors in Environments: Thermocouples (SE-TC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental, modeling and simulation, and analysis efforts conducted in FY24 relevant to the TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) testbed.

42 ENGINEERING↗
DOE OSTI2026

Beyond Mass and Multiscale Environments: What Shapes Low Surface Brightness Galaxies? Evidence from MaNGA

The origin of low surface brightness (LSB) galaxies remains a key open question in galaxy formation, reflecting the balance between internal mechanisms and environmental influence. Using MaNGA integral-field spectroscopy, we investigate whether LSB and high surface brightness (HSB) galaxies of comparable stellar mass (9 < logM * < 10) occupy distinct environments or differ primarily through internal evolution. Our late-type sample comprises 113 central and 29 satellite LSB galaxies, and 374 central and 142 satellite HSB galaxies. We characterize environments on scales from ∼100 kpc to 10 Mpc, analyzing radial profiles of stellar mass surface density (Σ * ), star formation activity, and gas-phase metallicity. Central LSB and HSB galaxies inhabit similarly low-density large-scale (>200 kpc) environments, but LSB galaxies are more isolated on small scales (∼100 kpc). Even after matching in stellar mass and environment, LSB galaxies show systematically lower Σ * , Σ SFR , and metallicities, often hosting diffuse, weakly star-forming bulges embedded in extended disks. These results indicate that LSB structure and star formation are not primarily governed by a large-scale environment or halo mass. While secondary halo properties such as spin, concentration, or gas accretion history are often invoked, their environmental dependence appears weak. Instead, LSB–HSB differences for centrals likely reflect divergent assembly or interaction histories and internal processes—such as angular momentum-driven disk evolution or inefficient gas conversion—largely decoupled from a large-scale environment. Nonetheless, the environment still influences the observed star formation and chemical differences between central and satellite LSB galaxies.

Shen, Mengting [Xiamen University (China); SDSS Co↗
DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗
DOE OSTI2025

Passive Environment-Assisted Quantum Communication with GKP States

Bosonic pure-loss channel, which represents the process of photons decaying into a vacuum environment, has zero quantum capacity when the channel’s transmissivity is less than 50%. Modeled as a beam splitter interaction between the system and its environment, the performance of bosonic pure-loss channel can be enhanced by controlling the environment state. We show that by choosing the ideal Gottesman-Kitaev-Preskill (GKP) states for the system and its environment, perfect transmission of quantum information through a beam splitter is achievable at arbitrarily low transmissivities. Our explicit constructions allow for experimental demonstration of the improved performance of a quantum channel through passive environment assistance, which is potentially useful for quantum transduction where the environment state can be naturally controlled. In practice, it is crucial to consider finite-energy constraints, and high-fidelity quantum communication through a beam splitter remains achievable with GKP states at the few-photon level.

Wang, Zhaoyou [Univ. of Chicago, IL (United States↗
DOE OSTI2025

Competition and cooperation: The plasticity of bacterial interactions across environments

Bacteria live in diverse communities, forming complex networks of interacting species. A central question in bacterial ecology is whether species engage in cooperative or competitive interactions. But this question often neglects the role of the environment. Here, we use genome-scale metabolic networks from two different open-access collections (AGORA and CarveMe) to assess pairwise interactions of different microbes in varying environmental conditions (provision of different environmental compounds). By computationally simulating thousands of environments for 10,000 pairs of bacteria from each collection, we found that most pairs were able to both compete and cooperate depending on the availability of environmental resources. This modeling approach allowed us to determine commonalities between environments that could facilitate the potential for cooperation or competition between a pair of species. Namely, cooperative interactions, especially obligate, were most common in less diverse environments. Further, as compounds were removed from the environment, we found interactions tended to degrade towards obligacy. However, we also found that on average at least one compound could be removed from an environment to switch the interaction from competition to facultative cooperation or vice versa. Together our approach indicates a high degree of plasticity in microbial interactions in response to the availability of environmental resources.

Biochemistry & Molecular Biology↗