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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 127 records · Page 7

Mass spectrometry and spectroscopic characterization of a tetrameric photosystem I supercomplex from Leptolyngbya ohadii , a desiccation-tolerant cyanobacterium

Cyanobacteria inhabiting desert biological soil crusts face the harsh conditions of the desert. They evolved a suite of strategies toward desiccation-hydration cycles mixed with high light irradiations, etc. In this study we purified and characterized the structure and function of Photosystem I (PSI) from Leptolyngbya ohadii, a desiccation-tolerant desert cyanobacterium. We discovered that PSI forms tetrameric (PSI-Tet) aggregate. We investigated it by using sucrose density gradient centrifugation, clear native PAGE, high performance liquid chromatography, mass spectrometry (MS), time-resolved fluorescence (TRF) and time-resolved transient absorption (TA) spectroscopy. MS analysis identified the presence of two PsaB and two PsaL proteins in PSI-Tet and uniquely revealed that PsaLs are N-terminally acetylated in contrast to non-modified PsaL in the trimeric PSI from Synechocystis sp. PCC 6803. Chlorophyll (Chl) a fluorescence decay profiles of the PSI-Tet performed at 77 K revealed two emission bands at ∼690 nm and 725 nm with the former appearing only at early delay time. The main fluorescence emission peak, associated with emission from the low energy Chls a, decays within a few nanoseconds. TA studies demonstrated that the 725 nm emission band is associated with low energy Chls a with absorption band clearly resolved at ∼710 nm at 77 K. As a result, our work suggests that the heterogenous composition of PsaBs and PsaL in PSI-Tet is related with the adaptation mechanisms needed to cope with stressful conditions under which this bacterium naturally grows.

59 BASIC BIOLOGICAL SCIENCES↗

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗

Techno-Economic Analysis of a Microgrid System for Rural Communities in the United States

Access to running water has been a pressing issue in many developing countries across the globe, and also continues to be a problem in some rural areas in the United States. Today, more than two million Americans living in rural areas lack access to basic water supply and infrastructure. Rural communities tend to be located in environmentally fragile areas with poor economic conditions, making access to appropriate, low-cost technology for clean water supply and sanitation more challenging. In addition, many of the water resources located in these areas are being jeopardized by climate change in recent years. This research proposes a photovoltaic (PV)-battery microgrid system for powering water pumps in off-grid areas in an effort to identify economically and technologically feasible solution to the problems. Utilizing the HOMER Pro software, developed by the U.S. National Renewable Energy Laboratory (NREL), the case of the Navajo Nation is examined by analyzing the effects of this region's air temperature on the life and performance of battery storage and the economics of the proposed microgrid system.

battery↗

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗

A gated graph transformer for protein complex structure quality assessment and its performance in CASP15

Abstract Motivation Proteins interact to form complexes to carry out essential biological functions. Computational methods such as AlphaFold-multimer have been developed to predict the quaternary structures of protein complexes. An important yet largely unsolved challenge in protein complex structure prediction is to accurately estimate the quality of predicted protein complex structures without any knowledge of the corresponding native structures. Such estimations can then be used to select high-quality predicted complex structures to facilitate biomedical research such as protein function analysis and drug discovery. Results In this work, we introduce a new gated neighborhood-modulating graph transformer to predict the quality of 3D protein complex structures. It incorporates node and edge gates within a graph transformer framework to control information flow during graph message passing. We trained, evaluated and tested the method (called DProQA) on newly-curated protein complex datasets before the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) and then blindly tested it in the 2022 CASP15 experiment. The method was ranked 3rd among the single-model quality assessment methods in CASP15 in terms of the ranking loss of TM-score on 36 complex targets. The rigorous internal and external experiments demonstrate that DProQA is effective in ranking protein complex structures. Availability and implementation The source code, data, and pre-trained models are available at https://github.com/jianlin-cheng/DProQA.

59 BASIC BIOLOGICAL SCIENCES↗

X-composer: enabling cross-environments in-situ workflows between HPC and cloud

As large-scale scientific simulations and big data analyses become more popular, it is increasingly more expensive to store huge amounts of raw simulation results to perform post-analysis. To minimize the expensive data I/O, "in-situ" analysis is a promising approach, where data analysis applications analyze the simulation generated data on the fly without storing it first. However, it is challenging to organize, transform, and transport data at scales between two semantically different ecosystems due to the distinct software and hardware difference. To tackle these challenges, we design and implement the X-Composer framework. X-Composer connects cross-ecosystem applications to form an "in-situ" scientific workflow, and provides a unified approach and recipe for supporting such hybrid in-situ workflows on distributed heterogeneous resources. X-Composer reorganizes simulation data as continuous data streams and feeds them seamlessly into the Cloud-based stream processing services to minimize I/O overheads. For evaluation, we use X-Composer to set up and execute a cross-ecosystem workflow, which consists of a parallel Computational Fluid Dynamics simulation running on HPC, and a distributed Dynamic Mode Decomposition analysis application running on Cloud. Our experimental results show that X-Composer can seamlessly couple HPC and Big Data jobs in their own native environments, achieve good scalability, and provide high-fidelity analytics for ongoing simulations in real-time.

Wang, Dali↗

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis

Integrating renewable resources within the transmission grid at a wide scale poses significant challenges for economic dispatch as it requires analysis with more optimization parameters, constraints, and sources of uncertainty. This motivates the investigation of more efficient computational methods, especially those for solving the underlying linear systems, which typically take more than half of the overall computation time. In this paper, we present our work on sparse linear solvers that take advantage of hardware accelerators, such as graphical processing units (GPUs), and improve the overall performance when used within economic dispatch computations. We treat the problems as sparse, which allows for faster execution but also makes the implementation of numerical methods more challenging. We present the first GPU-native sparse direct solver that can execute on both AMD and NVIDIA GPUs. We demonstrate significant performance improvements when using high-performance linear solvers within alternating current optimal power flow (ACOPF) analysis. Furthermore, we demonstrate the feasibility of getting significant performance improvements by executing the entire computation on GPU-based hardware. Finally, we identify outstanding research issues and opportunities for even better utilization of heterogeneous systems, including those equipped with GPUs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cytochrome P450–catalyzed biosynthesis of furanoditerpenoids in the bioenergy crop switchgrass ( Panicum virgatum L.)

Specialized diterpenoid metabolites are important mediators of plant-environment interactions in monocot crops. To understand metabolite functions in plant environmental adaptation that ultimately can enable crop improvement strategies, a deeper knowledge of the underlying species-specific biosynthetic pathways is required. Furthermore, we report the genomics-enabled discovery of five cytochrome P450 monooxygenases (CYP71Z25-CYP71Z29) that form previously unknown furanoditerpenoids in the monocot bioenergy crop Panicum virgatum (switchgrass). Combinatorial pathway reconstruction showed that CYP71Z25-CYP71Z29 catalyze furan ring addition directly to primary diterpene alcohol intermediates derived from distinct class II diterpene synthase products. Transcriptional co-expression patterns and the presence of select diterpenoids in switchgrass roots support the occurrence of P450-derived furanoditerpenoids in planta. Integrating molecular dynamics, structural analysis and targeted mutagenesis identified active site determinants that contribute to the distinct catalytic specificities underlying the broad substrate promiscuity of CYP71Z25-CYP71Z29 for native and non-native diterpenoids.

59 BASIC BIOLOGICAL SCIENCES↗

Comparison of methodologies used to determine aromatic lignin unit ratios in lignocellulosic biomass

Abstract Background Multiple analytical methods have been developed to determine the ratios of aromatic lignin units, particularly the syringyl/guaiacyl (S/G) ratio, of lignin biopolymers in plant cell walls. Chemical degradation methods such as thioacidolysis produce aromatic lignin units that are released from certain linkages and may induce chemical changes rendering it difficult to distinguish and determine the source of specific aromatic lignin units released, as is the case with nitrobenzene oxidation methodology. NMR methods provide powerful tools used to analyze cell walls for lignin composition and linkage information. Pyrolysis-mass spectrometry methods are also widely used, particularly as high-throughput methodologies. However, the different techniques used to analyze aromatic lignin unit ratios frequently yield different results within and across particular studies, making it difficult to interpret and compare results. This also makes it difficult to obtain meaningful insights relating these measurements to other characteristics of plant cell walls that may impact biomass sustainability and conversion metrics for the production of bio-derived fuels and chemicals. Results The authors compared the S/G lignin unit ratios obtained from thioacidolysis, pyrolysis-molecular beam mass spectrometry (py-MBMS), HSQC liquid-state NMR and solid-state (ss) NMR methodologies of pine, several genotypes of poplar, and corn stover biomass. An underutilized approach to deconvolute ssNMR spectra was implemented to derive S/G ratios. The S/G ratios obtained for the samples did not agree across the different methods, but trends were similar with the most agreement among the py-MBMS, HSQC NMR and deconvoluted ssNMR methods. The relationship between S/G, thioacidolysis yields, and linkage analysis determined by HSQC is also addressed. Conclusions This work demonstrates that different methods using chemical, thermal, and non-destructive NMR techniques to determine native lignin S/G ratios in plant cell walls may yield different results depending on species and linkage abundances. Spectral deconvolution can be applied to many hardwoods with lignin dominated by S and G units, but the results may not be reliable for some woody and grassy species of more diverse lignin composition. HSQC may be a better method for analyzing lignin in those species given the wealth of information provided on additional aromatic moieties and bond linkages. Additionally, trends or correlations in lignin characteristics such as S/G ratios and lignin linkages within the same species such as poplar may not necessarily exhibit the same trends or correlations made across different biomass types. Careful consideration is required when choosing a method to measure S/G ratios and the benefits and shortcomings of each method discussed here are summarized.

09 BIOMASS FUELS↗

Immunization of cows with HIV envelope trimers generates broadly neutralizing antibodies to the V2-apex from the ultralong CDRH3 repertoire

The generation of broadly neutralizing antibodies (bnAbs) to conserved epitopes on HIV Envelope (Env) is one of the cornerstones of HIV vaccine research. The animal models commonly used for HIV do not reliably produce a potent broadly neutralizing serum antibody response, with the exception of cows. Cows have previously produced a CD4 binding site response by homologous prime and boosting with a native-like Env trimer. In small animal models, other engineered immunogens were shown to focus antibody responses to the bnAb V2-apex region of Env. Here, we immunized two groups of cows (n = 4) with two regimens of V2-apex focusing Env immunogens to investigate whether antibody responses could be generated to the V2-apex on Env. Group 1 was immunized with chimpanzee simian immunodeficiency virus (SIV)-Env trimer that shares its V2-apex with HIV, followed by immunization with C108, a V2-apex focusing immunogen, and finally boosted with a cross-clade native-like trimer cocktail. Group 2 was immunized with HIV C108 Env trimer followed by the same HIV trimer cocktail as Group 1. Longitudinal serum analysis showed that one cow in each group developed serum neutralizing antibody responses to the V2-apex. Eight and 11 bnAbs were isolated from Group 1 and Group 2 cows, respectively, and showed moderate breadth and potency. Potent and broad responses in this study developed much later than previous cow immunizations that elicited CD4bs bnAbs responses and required several different immunogens. All isolated bnAbs were derived from the ultralong CDRH3 repertoire. The finding that cow antibodies can target more than one broadly neutralizing epitope on the HIV surface reveals the generality of elongated structures for the recognition of highly glycosylated proteins. The exclusive isolation of ultralong CDRH3 bnAbs, despite only comprising a small percent of the cow repertoire, suggests these antibodies outcompete the long and short CDRH3 antibodies during the bnAb response.

Microbiology↗

A FAIR-compliant parts catalogue for genome engineering and expression control in Saccharomyces cerevisiae

The synthetic biology toolkit for baker's yeast, Saccharomyces cerevisiae, includes extensive genome engineering toolkits and parts repositories. However, with the increasing complexity of engineering tasks and versatile applications of this model eukaryote, there is a continued interest to expand and diversify the rational engineering capabilities in this chassis by FAIR (findable, accessible, interoperable, and reproducible) compliance. In this study, we designed and characterised 41 synthetic guide RNA sequences to expand the CRISPR-based genome engineering capabilities for easy and efficient replacement of genomically encoded elements. Moreover, we characterize in high temporal resolution 20 native promoters and 18 terminators using fluorescein and LUDOX CL-X as references for GFP expression and OD600 measurements, respectively. Additionally, all data and reported analysis is provided in a publicly accessible jupyter notebook providing a tool for researchers with low-coding skills to further explore the generated data as well as a template for researchers to write their own scripts. We expect the data, parts, and databases associated with this study to support a FAIR-compliant resource for further advancing the engineering of yeasts.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Butterfly biodiversity increases with prairie strips and conservation management in row crop agriculture

Abstract Butterfly abundances are declining globally, with meta‐analysis showing a rate of −2% per year. Agriculture contributes to butterfly decline through habitat loss and degradation. Prairie strips—strips of farmland actively restored to native perennial vegetation—are a conservation practice with the potential to mitigate biodiversity loss, but their impact on butterfly biodiversity is not known. Working within a 30‐year‐old experiment that varied land use intensity, from natural areas to croplands (maize–soy–wheat rotation), we introduced prairie strips to less intensely managed crop treatments. Treatments included conservation land, biologically based (organic) row crops with prairie strips, reduced input row crops with prairie strips, no‐till row crops and conventional row crops. We measured butterfly abundance and richness: (1) within prairie strips and (2) across the gradient of land use intensity at the plot level. Butterfly abundance was higher within prairie strips than in all other treatments. Across the land use intensity gradient at the plot level, the conservation land treatment had the highest abundance, treatments with prairie strips had intermediate levels and no‐till and conventional treatments had the lowest abundances. Also across entire plots, butterfly richness increased as land use intensity decreased. Treatments with prairie strips, which also had reduced land use intensity, had distinct butterfly communities as they harboured several butterfly species that were not found in other row crop treatments. In addition to the known effects of prairie strips on ecosystem services including erosion control and increased water quality, prairie strips can increase biodiversity in multifunctional landscapes.

Kemmerling, Lindsey R.↗

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗

Vegetation Management Cost and Maintenance Implications of Different Ground Covers at Utility-Scale Solar Sites

Utility-scale solar photovoltaics (PV) is the largest and fastest-growing sector of the solar energy market, and plays an important role in ensuring that state and local jurisdictions can meet renewable energy targets. Potential adverse environmental impacts of utility-scale solar PV are well-documented, and the effects of diverse mitigation and dual land use strategies under the banner of ’low-impact solar’ are justly receiving more attention; this article seeks to contribute to improving understanding of this topic. Capital costs for different PV configurations are well-documented; however, operation and maintenance (O&M) costs for vegetation management at low-impact utility-scale solar PV sites are not as well-understood, particularly as they compare to costs for sites that use more conventional ground cover practices, such as turfgrass or gravel. After a literature review of different vegetation strategies and O&M cost considerations, we collected data from utility-scale solar PV O&M stakeholders, including site owners/operators, O&M service providers, vegetation maintenance companies, and solar graziers, on costs and activities associated with vegetation management at low-impact, agrivoltaic, and conventional PV sites. In this paper, we perform data analysis to detail the per-activity and total O&M costs for vegetation management at PV sites with different ground covers and management practices, providing the most comprehensive and detailed assessment of PV vegetation O&M costs to date. For the 54 sites included in our analysis, we found that while the per-acre and per-kilowattdc (kWdc) costs for individual activities, such as mowing, trimming, and herbicide application at native or pollinator friendly ground covers, were lower than at turfgrass sites, the total combined vegetation O&M costs were slightly higher; this is presumably because more individual activities are required for the first 3–5 years of vegetation establishment. Qualitative results include recommendations from data providers for site and system design, and ongoing vegetation management operations.

14 SOLAR ENERGY↗

Virtual Growth of SRF Materials: A Machine Learning Approach to Predict the Crystalline Structural Ordering in Nb Surface Oxides

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Unlisted, US, IL; Fermilab]↗

Elemental Analysis of Bio-Oils by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Laboratory Analytical Procedure (LAP), Issue Date: May 13, 2022

Concentrations of inorganic elements is a key quality metric for bio-oils as certain elements impact upgrading processes and product quality. Unless reduced or removed during production and processing, alkali and alkaline metals native to lignocellulosic biomass can carry over into bio-oils contributing to ash content and degraded catalyst performance during upgrading to hydrocarbon fuels or chemical products. Non-metallic elements such as sulfur and phosphorus can also negatively impact upgrading catalysts and product quality. Inductively coupled plasma optical emission spectroscopy (ICP-OES) can be used to measure inorganic elements of interest in bio-oils. This procedure covers the preparation and analysis of fast pyrolysis (FP) and catalytic fast pyrolysis (CFP) bio-oils. The concentrations of these elements can indicate potential bio-oil quality from the perspective of deoxygenation processes. The implications of elemental composition will depend on process parameters such as upgrading catalyst sensitivities. This Laboratory Analytical Procedure (LAP) covers two methods for quantification of inorganic elements by ICP-OES: Procedure A uses microwave assisted digestion with concentrated nitric acid, and Procedure B is an organic ICP-OES method utilizing a diglyme solvent.

09 BIOMASS FUELS↗

Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data

AI and simulation workloads consume and generate large amounts of data that need to be searched, transformed and merged with other data. With the goal of treating data as a first-class citizen inside a traditionally compute-centric HPC environment, we explore how the use of accelerators and high-speed interconnects can speed up tasks which otherwise constitute bottlenecks in computational discovery workflows. BlazingSQL is SQL engine that runs natively on NVIDIA GPUs and supports internode communication for fast analytics on terabyte-scale tabular data sets. We show how a fast interconnect improves query performance if leveraged through the Unified Communication X (UCX) middleware. We envision that future computing platforms will integrate accelerated database query capabilities for immediate and interactive analysis of large simulation data.

Glaser, Jens↗