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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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DOE OSTI2023

Utah FORGE 4-2541: Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design - Workshop Presentation

This is a presentation on the Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design at Utah FORGE project by Fervo Energy, presented by Sireesh Dadi. The project's objective was to develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system. These factors include: achieving sufficient injectivity to support high cross-well flow rates, distributing flow evenly across the wellbore and reservoir, and overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

FY2022 Status Update: A Probabilistic Model for Stress Corrosion Cracking of SNF Dry Storage Canisters

Understanding the potential risk of stress corrosion cracking of spent nuclear fuel dry storage canisters has been identified as a knowledge gap for determining the safety of long-term interim storage of spent nuclear fuel. To address this, the DOE is funding a multi-lab DOE effort to understand the timing, occurrence, and consequences of potential canister SCC. Sandia National Laboratories has developed a probabilistic model for canister penetration by SCC. This model has been continuously updated at SNL since 2014. Model uncertainties are treated using a nested loop structure, where the outer loop accounts for uncertainties due to lack of data and the inner aleatoric loop accounts for uncertainties due to variation in nature. By separating uncertainties into these categories, it is possible to focus future work on reducing the most influential epistemic uncertainties. Several experimental studies have already been performed to improve the modeling approach through expanded process understanding and improved model parameterization. The resulting code is physics-based and intended to inform future work by identifying (1) important modeling assumptions, (2) experimental data needs, and (3) necessary model developments. In this document, several of the sub-models in the probabilistic SCC model have been exercised, and the intermediate results, as the model progresses from one sub-model to the next, are presented. Evaluating the sub-models in this manner provides a better understanding of sub-model outputs and has identified several unintended consequences of model assumptions or parameterizations, requiring updates to the modeling approach. The following updates have been made, and future updates have been identified.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Real-Time Partitioning of Diurnal Stem CO 2 Efflux into Local Stem Respiration and Xylem Transport Processes

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO 2 efflux (E S_CO2 ) to net stem O 2 influx (E S_O2 ), offers insights into the balance between local respiratory CO 2 production and CO 2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO 2 and O 2 molecules to continuously measure E S_CO2 , E S_O2 , and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between E S_CO2 and E S_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning E S_CO2 into local respiration and xylem-transported CO 2 indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO 2 exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO 2 flux components to improve our understanding of whole-tree carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Stochastic noise can be helpful for variational quantum algorithms

Saddle points constitute a crucial challenge for first-order gradient descent algorithms. In notions of classical machine learning, they are avoided, for example, by means of stochastic gradient descent methods. In this work, we provide evidence that the saddle-points problem can be naturally avoided in variational quantum algorithms by exploiting the presence of stochasticity. We prove convergence guarantees and present practical examples in numerical simulations and on quantum hardware. We argue that the natural stochasticity of variational algorithms can be beneficial for avoiding strict saddle points, i.e., those saddle points with at least one negative Hessian eigenvalue. This insight that some levels of shot noise could help is expected to add a new perspective to notions of near-term variational quantum algorithms. Published by the American Physical Society 2025

Liu, Junyu↗
DOE OSTI2024

Properties of V-defect injectors in long wavelength GaN LEDs studied by near-field electro- and photoluminescence

The efficiency of multiple quantum well (QW) light emitting diodes (LEDs) to a large degree depends on uniformity of hole distribution between the QWs. Typically, transport between the QWs takes place via carrier capture into and thermionic emission out of the QWs. In InGaN/GaN QWs, the thermionic hole transport is hindered by the high quantum confinement and polarization barriers. To overcome this drawback, hole injection through semipolar QWs located at sidewalls of V-defects had been proposed. However, in the case of the V-defect injection, strong lateral emission variations take place. In this work, we explore the nature of these variations and the impact of the V-defects on the emission spectra and carrier dynamics. The study was performed by mapping electroluminescence (EL) and photoluminescence (PL) with a scanning near-field optical microscope in LEDs that contain a deeper well that can only be populated by holes through the V-defects. Applying different excitation schemes (electrical injection and optical excitation in the far- and near-field), we have shown that the EL intensity variations are caused by the lateral nonuniformity of the hole injection. We have also found that, in biased structures, the PL intensity and decay time in the V-defect regions are only moderately lower that in the V-defect-free regions thus showing no evidence of an efficient Shockley-–Read–Hall recombination. In the V-defect regions, the emission spectra experience a red shift and increased broadening, which suggests an increase of the In content and well width in the polar QWs close to the V-defects.

Electroluminescence↗
DOE OSTI2021

Mutations in artificial self-replicating tiles: A step toward Darwinian evolution

Significance In nature, mutation is the first step of evolution, where it provides the genetic variation for the natural selection to act. Here we take a system of artificial self-replicating tiles, DNA origami, that exhibit templated reproduction. We can generate a small fraction of mutations by introducing a mismatch in hybridization between parent and daughter. We can modify the origami functionality to affect the growth rate of the mutated species, giving it less or more evolutionary advantage, and to become dominant in several generations. The introduction of mutations into an artificial self-replicating system provides new directions for research into self-assembly processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Association mapping across a multitude of traits collected in diverse environments in maize

Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genetic Basis of Non–Photochemical Quenching and Photosystem II Efficiency Responses to Chilling in the Biomass Crop Miscanthus

Miscanthus holds a promise as a biocrop due to its high yield, perenniality and ability to grow on infertile soils. However, the current commercial biomass production of Miscanthus is mostly limited to a single sterile triploid clone of M. × giganteus. Nevertheless, parental species of M. × giganteus, Miscanthus sacchariflorus and Miscanthus sinensis contain vast genetic diversity for crop improvement. With M. sacchariflorus having a natural geographic distribution in cold-temperate northeast China and eastern Russia, we hypothesised that it has substantial variation in physiological response to chilling. Using a semi-high-throughput method, we phenotyped 209 M. sacchariflorus genotypes belonging to six genetic groups for non-photochemical quenching (NPQ) and photosystem II efficiency (ΦPSII) kinetics under warm and chilling treatments in three growing seasons. In response to the chilling treatment, all genetic groups exhibited an increase in NPQ induction rate indicating faster activation of NPQ in light. Notably, under chilling, the Korea/NE China/Russia 2x and N China 2x groups stood out for the highest NPQ rate in light and the highest steady-state NPQ in light. This NPQ phenotype may contribute adaptation to chilling during bright, cold mornings of spring and early autumn in temperate climates, when faster NPQ would better protect from oxidative stress. Such enhanced adaptation could expand the growing season and thus productivity at a given location or expand the range of economically viable growing locations to higher latitudes and altitudes. A genome-wide association study identified 126 unique SNPs associated with NPQ and ΦPSII traits. Among the identified candidate genes were enzymes involved in the ascorbate recycle and shikimate pathway, gamma-aminobutyric acid and cation efflux transporters. Identifying natural variation and genes involved in NPQ and ΦPSII kinetics considerably enlarges the toolbox for breeding and/or engineering Miscanthus with optimised photosynthesis under warm and chilling conditions for sustainable feedstock production for bioenergy.

09 BIOMASS FUELS↗
DOE OSTI2022

Measuring sub-surface spatially varying thermal conductivity of silicon implanted with krypton

The thermal properties of semiconductors following exposure to ion irradiation are of great interest for the cooling of electronic devices; however, gradients in composition and structure due to irradiation often make the measurement difficult. Furthermore, the nature of spatial variations in thermal resistances due to spatially varying ion irradiation damage is not well understood. In this work, we develop an advancement in the analysis of time-domain thermoreflectance to account for spatially varying thermal conductivity in a material resulting from a spatial distribution of defects. We then use this method to measure the near-surface (≲1 μm) thermal conductivity of silicon wafers irradiated with Kr + ions, which has an approximate Gaussian distribution centered 260 nm into the sample. Our numerical analysis presented here allows for the spatial gradient of thermal conductivity to be extracted via what is fundamentally a volumetric measurement technique. We validate our findings via transmission electron microscopy, which is able to confirm the spatial variation of the sub-surface silicon structure, and provide additional insight into the local structure resulting from the effects of ion bombardment. Thermal measurements found the ion stopping region to have a nearly 50x reduction in thermal conductivity as compared to pristine silicon, while TEM showed the region was not fully amorphized. Our results suggest this drastic reduction in silicon thermal conductivity is primarily driven by structural defects in crystalline regions along with boundary scattering between amorphous and crystalline regions, with a negligible contribution being due to implanted krypton ions themselves.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Attaining the promise of plant gene editing at scale

Crop improvement relies heavily on genetic variation that arises spontaneously through mutation. Modern breeding methods are very adept at combining this genetic variation in ways that achieve remarkable improvements in plant performance. Novel traits have also been created through mutation breeding and transgenesis. The advent of gene editing, however, marks a turning point: With gene editing, synthetic variation will increasingly supplement and, in some cases, supplant the genetic variation that occurs naturally. We are still in the very early stages of realizing the opportunity provided by plant gene editing. At present, typically only one or a few genes are targeted for mutation at a time, and most mutations result in loss of gene function. New technological developments, however, promise to make it possible to perform gene editing at scale. RNA virus vectors, for example, can deliver gene-editing reagents to the germ line through infection and create hundreds to thousands of diverse mutations in the progeny of infected plants. With developmental regulators, edited somatic cells can be induced to form meristems that yield seed-producing shoots, thereby increasing throughput and shrinking timescales for creating edited plants. As these approaches are refined and others developed, they will allow for accelerated breeding, the domestication of orphan crops and the reengineering of metabolism in a more directed manner than has ever previously been possible.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Strangers in a foreign land: ‘Yeastizing’ plant enzymes

Abstract Expressing plant metabolic pathways in microbial platforms is an efficient, cost‐effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour‐intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost‐effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data‐driven machine learning framework designed to extract ‘yeastizing’ rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design‐build‐test cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Magnetic Field Strength from Turbulence Theory. I. Using Differential Measure Approach

The mean plane-of-sky magnetic field strength is traditionally obtained from the combination of polarization and spectroscopic data using the Davis–Chandrasekhar–Fermi (DCF) technique. However, we identify the major problem of the DCF technique to be its disregard of the anisotropic character of MHD turbulence. On the basis of the modern MHD turbulence theory we introduce a new way of obtaining magnetic field strength from observations. Unlike the DCF technique, the new technique uses not the dispersion of the polarization angle and line-of-sight velocities, but increments of these quantities given by the structure functions. To address the variety of astrophysical conditions for which our technique can be applied, we consider turbulence in both media with magnetic pressure higher than the gas pressure, corresponding, e.g., to molecular clouds, and media with gas pressure higher than the magnetic pressure, corresponding to the warm neutral medium. We provide general expressions for arbitrary admixtures of Alfvén, slow, and fast modes in these media and consider in detail particular cases relevant to diffuse media and molecular clouds. We successfully test our results using synthetic observations obtained from MHD turbulence simulations. We demonstrate that our differential measure approach, unlike the DCF technique, can be used to measure the distribution of magnetic field strengths, can provide magnetic field measurements with limited data, and is much more stable in the presence of induced large-scale variations of nonturbulent nature. Furthermore, our study uncovers the deficiencies of earlier DCF research.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Variation in morpho-physiological and metabolic responses to low nitrogen stress across the sorghum association panel

Abstract Background Access to biologically available nitrogen is a key constraint on plant growth in both natural and agricultural settings. Variation in tolerance to nitrogen deficit stress and productivity in nitrogen limited conditions exists both within and between plant species. However, our understanding of changes in different phenotypes under long term low nitrogen stress and their impact on important agronomic traits, such as yield, is still limited. Results Here we quantified variation in the metabolic, physiological, and morphological responses of a sorghum association panel assembled to represent global genetic diversity to long term, nitrogen deficit stress and the relationship of these responses to grain yield under both conditions. Grain yield exhibits substantial genotype by environment interaction while many other morphological and physiological traits exhibited consistent responses to nitrogen stress across the population. Large scale nontargeted metabolic profiling for a subset of lines in both conditions identified a range of metabolic responses to long term nitrogen deficit stress. Several metabolites were associated with yield under high and low nitrogen conditions. Conclusion Our results highlight that grain yield in sorghum, unlike many morpho-physiological traits, exhibits substantial variability of genotype specific responses to long term low severity nitrogen deficit stress. Metabolic response to long term nitrogen stress shown higher proportion of variability explained by genotype specific responses than did morpho-pysiological traits and several metabolites were correlated with yield. This suggest, that it might be possible to build predictive models using metabolite abundance to estimate which sorghum genotypes will exhibit greater or lesser decreases in yield in response to nitrogen deficit, however further research needs to be done to evaluate such model.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Three-Dimensional, Thermodynamically and Variationally Consistent, Fully Coupled, Electro-Chemo-Thermo-Mechanical Model of Solid-State Batteries

Here we present a theoretical framework for high fidelity modeling of three-dimensional electro-chemo-thermo-mechanical coupled systems such as solid-state batteries. The framework provides a useful means of utilizing molecular level information to predict the overall performance of the system at the continuum level. The central statement of the theoretical framework is a thermodynamically consistent inf-sup problem. The total potential of the coupled system consists of the Helmholtz free energy, the electrical kinetic potential, the chemical potential, the Fourier potential, the chemical reaction potential, and the external power expenditure. All governing equations derive from variational principles. We also show that the resulting initial-boundary-value problem (IBVP) is consistent with existing, widely adopted equations for modeling batteries. Moreover, the IBVP can be naturally discretized using the (variational) finite element method to simulate practical solid-state batteries with arbitrary geometries. Several examples illustrate multiphysics coupling between pairs of the physical field equations, culminating in a comprehensive three-dimensional model of charge-discharge in a solid state battery.

25 ENERGY STORAGE↗
DOE OSTI2025

Natural isotopic compositions of titanium, iron, and nickel observed in commercial fuel pellets – Promising candidate elements for stable isotope tagging

Stable isotope taggants would constitute unique identifiers for nuclear fuel cycle materials, resulting in expedited timelines and high confidence provenance assessments for nuclear forensics investigations. However, reliably identifying and interpreting stable isotope taggants in nuclear materials recovered from outside of regulatory control will largely be predicated on the assumption that the taggant element intrinsic to the untagged nuclear material exhibits natural isotopic ratios. Here, we present high-precision Ti, Fe, and Ni isotope compositions in 13 commercial low-enriched uranium (LEU) fuel pellets to assess the suitability of these transition metals as stable isotope taggants. Our investigations reveal limited isotope variations among the fuel pellets in all three elements, which are consistent with small mass-dependent isotope fractionations, comparable to variations previously reported for natural samples. In practice, isotopically tagged nuclear materials are expected to fall along isotopic mixing lines, since intrinsic background levels of taggant elements dilute the taggant towards natural isotope compositions. Furthermore, the observation that Ti, Fe, and Ni isotope compositions in a suite of LEU fuel pellets are close to or indistinguishable from estimates for the Bulk Silicate Earth demonstrates that a two end-member mixing assumption would be valid for these transition metals, indicating that all three are promising candidate elements for stable isotope tagging. Finally, we present mass balance calculations to quantify isotopic perturbations expected from admixing isotopically anomalous Ti, Fe, and Ni taggants to assess the interplay between elemental and taggant concentrations and find favorable compromises for facilitating successful taggant identification with current analytical methods.

Intentional forensics↗
DOE OSTI2023

Contrasting patterns of sequence variation in steelhead populations reflect distinct evolutionary processes

Abstract Multiple evolutionary processes influence genome‐wide allele frequencies and quantifying effects of genetic drift, and multiple forms of selection remain challenging in natural populations. Here, we investigate variation at major effect loci in contrast to patterns of neutral drift across a wide collection of steelhead ( Oncorhynchus mykiss ) populations that have declined in abundance due to anthropogenic impacts. Whole‐genome resequencing of 74 populations of steelhead revealed genome‐wide patterns (~8 million SNPs) consistent with expected neutral population structure. However, allelic variation at major effect loci associated with adult migration timing (chromosome 28: GREB1L / ROCK1 ) and age at maturity (chromosome 25: SIX6 ) reflected how selection has acted on phenotypic variation in contrast with neutral structure. Variation at major effect loci was influenced by evolutionary processes with differing signals between the strongly divergent Coastal and Inland lineages, while allele frequencies within and among populations within the Inland lineage have been driven by local natural selection as well as recent anthropogenic influences. Recent anthropogenic effects appeared to have influenced the frequency of major effect alleles including artificial selection for specific traits in hatchery stocks with subsequent gene flow into natural populations. Selection from environmental factors at various scales has also likely influenced variation for major effect alleles. These results reveal evolutionary mechanisms that influence allele frequencies at major effect loci that are critical for conservation of phenotypic traits and life history variation of this protected species.

Willis, Stuart↗