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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 235 records · Page 13

The landscape of regulatory element evolution in a C4 perennial grass

Gene regulatory evolution is a well-known source of phenotypic diversity and adaptive evolution. Although cis-regulatory elements (CREs) play a vital role in gene expression evolution, the molecular evolution of CREs remains mostly unknown due to the difficulty in identifying and characterizing these functional elements. Comparative genomic analyses of noncoding DNA can be leveraged to identify conserved noncoding sequences (CNS), many of which may harbor functional CREs conserved by purifying selection. However, purely computational inference of CREs from putative CNS can be erroneous due to the complex genomic architecture in plants. One promising experimental approach to identify CREs is by profiling accessible chromatin regions (ACRs) that are often associated with the location of CREs. In this study, we use comparative genomics along with the profiling of ACRs to study the molecular evolution of putative functional noncoding regulatory regions in Panicoid grasses. We identified sets of CNS that varied in relationship to the degree of evolutionary divergence among the studied taxa, including identifying core-Panicoid-CNS. We augmented this analysis by profiling ACRs in Panicum hallii ecotypes using ATAC-seq. ACRs had low SNP density at the summit, harbored a high frequency of core-Panicoid-CNS, and were enriched with expression QTL. These data help to annotate the P. hallii genome for putative functional elements and suggest that a large proportion of these ACRs are evolving under purifying selection. Turnover in CNS and ACR between ecotypes of P. hallii identifies a small set of putatively divergent CREs that may underlie differences in gene regulation between genotypes from inland and coastal habitats. In summary, we profiled ACRs in Panicoid grasses and integrated this data with our putative CNS prediction framework, which provides unique insight into patterns of polymorphism and divergence in CREs in C4 perennial grasses.

59 BASIC BIOLOGICAL SCIENCES↗

RatXcan: A framework for cross-species integration of genome-wide association and gene expression data

Genome-wide association studies (GWAS) have implicated specific alleles and genes as risk factors for numerous complex traits. However, translating GWAS results into biologically and therapeutically meaningful discoveries remains extremely challenging. Most GWAS results identify noncoding regions of the genome, suggesting that differences in gene regulation are the major driver of trait variability. To better integrate GWAS results with gene regulatory polymorphisms, we previously developed PrediXcan (also known as “transcriptome-wide association studies” orTWAS), which maps SNPs to predicted gene expression using GWAS data. In this study, we developed RatXcan, a framework that extends this methodology to outbred heterogeneous stock (HS) rats. RatXcan accounts for the close familial relationships among HS rats by modeling the relatedness with a random effect that encodes the genetic relatedness. RatXcan also corrects for polygenic-driven inflation because of the equivalence between a relatedness random effect and the infinitesimal polygenic model. To develop RatXcan, we trained transcript predictors for 8,934 genes using reference genotype and expression data from five rat brain regions. We found that the cis genetic architecture of gene expression in both rats and humans was sparse and similar across brain tissues. We tested the association between predicted expression in rats and two example traits (body length and BMI) using phenotype and genotype data from 5,401 densely genotyped HS rats and identified a significant enrichment between the genes associated with rat and human body length and BMI. Thus, RatXcan represents a valuable tool for identifying the relationship between gene expression and phenotypes across species and paves the way to explore shared biological mechanisms of complex traits.

Genetics & Heredity↗

Raman spectroscopic investigation of ianthinite [U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O, a rare mixed-valence uranium oxide hydrate

Ianthinite ([[U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O) is an exotic mineral that possesses U in both tetravalent and hexavalent oxidation states and is structurally related to the U 3 O 8 polymorphs, which are commonly encountered technogenic materials in the nuclear fuel cycle. Despite the similarities between U 3 O 8 and ianthinite, and the importance of ianthinite in U paragenesis, no Raman spectra have been reported for this mineral. Here, to gain a more complete understanding of how structural attributes of ianthinite give rise to observable spectroscopic features and how these may relate to important materials in the nuclear fuel cycle, we provide, for the first time, Raman spectra of ianthinite. Ianthinite readily oxidizes at ambient conditions, complicating analysis of phase-pure material. Several analytical methods are employed herein to decouple the Raman features of ianthinite from its alteration product(s). First, a simple difference spectrum is presented, then results of Raman spectroscopic mapping are employed, and finally, we use a novel processing and analysis method. Each analysis method provides different insight into structural features that are unique to ianthinite, in particular, features that are attributable to U(IV) in distorted octahedral coordination in both ianthinite and U 3 O 8 phases.

Spano, Tyler L. [Oak Ridge National Laboratory (OR↗

Program Generators for Exascale and Beyond (Final Technical Report)

The major goals of this project were to devise programming models and supporting tools that simplify the construction of specialized high‐performance generators, leading to improvements over the state of the art along the various dimensions of portability, performance, and productivity. In particular, the project achieved these goals by focusing on domain‐specific languages (DSLs) as intermediate layers in a translation and optimization framework, on composability of program generators, on re‐targeting legacy code, and on fundamental methodologies such as stage polymorphism or "generic programming in time".

97 MATHEMATICS AND COMPUTING↗

Proteomics Analysis of Human Contaminant Proteins

Complete characterization of unknowns via proteomics remains challenging. There exist regions of mass spectrometry-based proteomics data where empirical measurements are not attributed to peptides, and/or sequenced peptides from mass spectra are not attributed to any source. These uncharacterized regions are known as the “dark” proteome. Many proteomics tools rely on some a priori knowledge of sample composition; few tools allow for investigation of unknowns without relying on composition assumptions. Further, the potential low abundance of minor traces in these uncharacterized regions can make elucidation of the “dark” proteome challenging. Herein, we describe the development and evaluation of approaches to study the “dark” proteome and move towards an untargeted approach for more complete characterization, namely by studying minor human protein traces in non-human samples and combining that approach with non-human source organism identification without relying on assumptions. Human protein markers, in the form of genetically variant peptides, have been extensively examined in a variety of human matrices, including blood, plasma, and hair, but have yet to be investigated in non-human samples, such as cell cultures, as human contaminant traces. Genetically variant peptides are those that are found in proteins carrying single nucleotide polymorphisms. In this work, we aimed to (1) investigate the feasibility of detecting human contaminant genetically variant peptides (GVPs) in a diverse set of non-human organisms using public proteomics data and a computational pipeline, as well as to (2) develop a combined capability for untargeted source organism characterization and GVP detection. To our knowledge, this is the first report of applying these approaches towards a more complete proteomic characterization of unknowns. We successfully demonstrate the feasibility of broad human contaminant GVP detection in proteomics data, develop a better understanding of GVP detectability, characterize the sample-to-sample variability in GVP detection, and identify a core set of GVPs that can potentially be used as markers indicative of the human contaminant traces portion of the “dark” proteome. Further, we developed and evaluated a combined pipeline, MARLOWE-GVP, that enables both untargeted source organism characterization and GVP detection. We show high accuracy of correct source organism characterization and high degree of similarity of human contaminant GVP detection compared to the conventional approach. Success on both these efforts have allowed us to advance our understanding and characterization of the “dark” proteome.

59 BASIC BIOLOGICAL SCIENCES↗

Accelerated Design of Cost-Effective Thermal/Environmental Barrier Coatings based on High-Entropy Rare Earth Disilicates: A First-Principles Study

This project aims to design cost-effective thermal/environmental barrier coatings (TEBC) based on high entropy rare earth disilicates to protect SiC-based ceramic matrix composites from chemical and thermal attack for better performance of components in the hot section of gas turbine engines. To accelerate the alloy design, we utilize first-principles density functional theory (DFT) together with combinatorial chemistry methodology to predict key properties including phase stability, apparent bulk coefficient of thermal expansion (ABCTE), intrinsic lattice thermal conductivity, and temperature-dependent elastic constants. Specifically, this project focuses on β-RE2Si2O7 (RE=Yb, Y, Er, Lu, La, Ce,) with β-Yb2Si2O7 and β-Y2Si2O7 as the benchmark. Our DFT calculations predict that Er1/4Lu1/4Y3/4Yb3/4Si2O7 and Er1/2Lu1/2Y1/2Yb1/2Si2O7 have ultralow lattice thermal conductivity < 0.23 W/m/K at 1500 K and a good match of average ABCTE (5.1 - 5.2×10-6 K-1) with SiC. Owing to the low cost and abundant supply of Ce and La, the A- and G-La2Si2O7/Ce2Si2O7 disilicates are also studied. Our study shows that G-phase Ce2Si2O7 has an ultralow thermal conductivity (0.26 W/m/K at 1500 K) and the apparent bulk ABCTE (≈6.9×10-6 K-1) slightly higher than SiC, demonstrating great potential as low-cost high-performance T/EBC. However, La2Si2O7 and Ce2Si2O7 undergo an A-phase to G-phase polymorphic transition at around 1470 K.

environmental barrier coatings↗

Remote Instrumentation and Data Acquisition

This poster outlines the development and implementation of a remote data acquisition system for waveform analysis using a Rohde & Schwarz oscilloscope. The project involved capturing waveform data, and transferring it to a local machine for visualization and analysis. The core logic was developed in C++ with a focus on object oriented programming and the use of polymorphism so the main application can interact with any instrument without knowing its exact type, simplifying the overall logic and making it easier to add or swap out components without changing the rest of the codebase.. The system issues Standard Commands for Programmable Instruments (SCPI) via a socket connection and parses the oscilloscope s ASCII waveform data. The C++ application was containerized using Docker for ease of portability, and reproducibility. Emphasis was placed on secure networking practices, error handling, and effective data capture. The report describes the technical steps taken, challenges encountered, and future work, providing insight into the practical integration of hardware interfacing with remote computational environments.

Parikh, Jaymil [Illinois U., Urbana]↗

High entropy oxides prediction and discovery by the Mixed Enthalpy-Entropy Descriptor

The vast, high-dimensional composition space of high-entropy oxides (HEOs) offers exceptional opportunities for functional materials discovery, yet it also poses a fundamental challenge: the rational and efficient prediction of stable, synthesizable compositions and the corresponding structure–property relationships. Despite growing interest, the field still lacks broadly applicable, physically grounded descriptors capable of navigating various large chemical spaces. Here, we introduce a Mixed Enthalpy–Entropy Descriptor (MEED) that enables rapid, first-principles–based prediction of HEOs synthesizability across diverse chemistries. Using MEED, we perform high-throughput screening of two distinct HEO families: rocksalt oxides and perovskite oxides. The predicted top candidates in each family were experimentally validated. MEED reveals unifying thermodynamic and structural principles governing stability across both chemical compositions and polymorphs, providing mechanistic insight into the formation of high-entropy phases. This work significantly broadens the accessible chemical design space for HEOs and establishes a data-efficient framework for accelerating the discovery of next-generation functional materials.

Yu, Liping [University of Central Florida]↗

The Structure-Properties Relationship of Alternative Bismaleimide Variants for Candidacy for Additive Manufacturing

Modernizing the manufacturing of high-performance polymer foams such as amino-poly(oxadiazole) bismaleimide (APO-BMI), a bismaleimide resin with superior thermal and compressive strength that incorporates additive manufacturing (AM) techniques, is crucial for its applications, but the parameters for AM can be challenging based on the physical properties of the associated monomer. For our applications, selective laser sintering (SLS) is typically used. SLS is a 3D printing technique that allows for complex shapes and geometries without structural supports while also providing high resolution material. However, printing thermosets like APO-BMI with SLS is challenging due to the complex melting and curing considerations required when selecting parameters. Additionally, the temperature difference between melting and curing of APO-BMI is over a hundred º C, which makes selecting a sintering window especially difficult. This work explores structural modifications of APO-BMI that may be more amenable for selective laser sintering. The effects of how different structural changes such as substitution pattern, heteroatom identity in the bridge, and bridge length affect the thermal properties of the material were also compared. All APO variants were found to have a smaller temperature window between the melting and curing peaks based on differential scanning calorimetry (DSC) which is advantageous for SLS. Small structural changes significantly altered the melting and curing properties of APO. Additionally, DSC revealed significant polymorphisms in APO-BMI and other APO variants which could be attributed to differences in thermal history and would need to be considered when adapting for SLS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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]↗

Viskores: Integrating Parallel Scientific Visualization Research into Applications

Viskores is a scientific visualization library that is the primary deployment of such algorithms to the parallel accelerated processors of modern DOE supercomputers. In this paper, we review the capabilities provided by Viskores and how these capabilities are leveraged by other software in the high-performance computing ecosystem. We discuss the Viskores data representation and pay particular attention to array management. Through this array management we describe how data is adapted between Viskores and other software along with strategies for converting dynamic, polymorphic objects to static representations better suited to GPU processing. We conclude with several examples of Viskores integrating with high-performance software that is used in production today.

Moreland, Ken [ORNL] (ORCID:0000000270513288)↗

RWRtoolkit Narrative

This narrative presents a demonstration of RWRtools methods to the important bioenergy feedstock Panicum virgatum (Switchgrass) by leveraging networks from the model plant Arabidopsis thaliana. We used a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with Switchgrass shoot biomass. We then assigned these SNPs to Switchgrass genes, and using Phytozome (Goodstein et al., 2012), assigned these 38 Switchgrass GWAS genes to 32 Arabidopsis orthologs. These 32 genes are the starting set of genes (i.e. the seed gene set) for this demo narrative.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive SNP Data for 1,323 GWAS Population in Populus trichocarpa and Combined Annotation Files for P. trichocarpa v3.0 and v3.1

The VCF dataset includes genetic variations found in 1,323 Populus trichocarpa genotypes, providing valuable information for scientists studying plant genetics. Researchers have generated this dataset using whole-genome DNA short-read sequencing on the Illumina Genome Analyzer, HiSeq 2000, and HiSeq 2500 platforms. This sequencing effort ensured a minimum expected sequencing depth of 15×. The dataset comprises more than 9.7 million single nucleotide polymorphisms (SNPs) and indel variants. The combined annotation files are derived from P. trichocarpa v3.0 and v3.1. We merged these files to create a comprehensive annotation file used for GWAS analysis. In total, 38,830 genes overlapped between the two versions. For overlapping genes, we defined the start as the smaller and the end as the larger among the two versions to increase the likelihood of locating candidate genetic loci. Additionally, we included 2,505 unique genes from v3.0 and 4,120 unique genes from v3.1, resulting in a total of 45,455 genes in the updated annotation file.

09 BIOMASS FUELS↗

Genomic Analysis of the Natural Variation of Fatty Acid Composition in Seed Oils of Camelina sativa

Camelina sativa is an oilseed crop that has shown strong promise as a biofuel feedstock. The profile of fatty acids greatly influences the oil quality; however, genetic mechanisms that determine the natural variation of fatty acid composition in camelina are not fully understood. A genome wide association study (GWAS) was performed to uncover genetic loci that may contribute to the contents of major fatty acids such as oleic and linolenic acids in camelina seed. Two approaches were taken to improve the GWAS efficiency. First, growing a diversity panel of 212 accessions in four locations and two nitrogen fertilization conditions revealed great variation in fatty acid contents in seeds. Second, using an improved reference genome, abundant markers, including 203,320 single nucleotide polymorphisms (SNPs) and 99,067 insertions/deletions (indels), were developed, which refined the population structure of the diversity panel. GWAS resulted in 118 genetic markers across 31 trait/treatment conditions. Closely linked markers were determined based on linkage decay and by comparing secondarily associated markers when highly associated ones were removed. Candidate genes were examined by comparing the pangenomes of 12 high-quality reference genomes. This study provides new resources to understand seed lipid metabolism and improve camelina oils through molecular breeding.

Life Sciences & Biomedicine - Other Topics↗

Pyridine Complexes of Iodobismuthate(III) Anions

We report a rare family of pyridine-coordinated iodobismuthate(III) salts supported by alkyltriphenylphosphonium and tetraphenylphosphonium cations. Reactions of BiI 3 with Ph 3 PR + I − (R = Me, Et, n Pr, n Bu, Ph) in neat pyridine, followed by crystallization, yield structurally tunable bismuth-halide-pyridine anions dictated by reagent stoichiometry. Combination of BiI 3 and Ph 3 PR + I − in 2:1 ratio produced [Ph 3 PR] 2 [BiI 5 Py], 1 (R = Me, Et, n Pr, Ph), while combination in 1:1 ratio resulted in three compounds: [Ph 3 PR][cis-BiI 4 Py 2 ], 2 (R = n Pr, Ph), [Ph 3 PR][trans-BiI 4 Py 2 ], 3 (R = Me, Et, Ph), and [Ph 3 PR] 2 [transoid-Bi 2 I 8 Py 2 ], 4 (R = Me, Et, n Pr, n Bu, Ph). In many cases, the compounds were isolated as Py or Et 2 O solvates, and in some cases, multiple degrees of solvation or polymorphism were encountered. Hirshfeld analysis of 1–4 showed the major anion–cation/anion/solvent interactions to be H⋯I, H⋯H, and C⋯H. Diffuse reflectance measurements of representative compounds, all of which were yellow-orange to red-orange, revealed bandgaps in the range of 1.9–2.2 eV, where density-of-states KS-DFT calculations attribute the absorption to metal-centered charge transfer within the anionic unit. NLMO and QTAIM analyses further indicate predominantly ionic Bi(III)–I/pyridine bonding with robust inner-sphere coordination that is insensitive to anion speciation.

Bismuth Compounds↗

Virulence and Genetic Diversity of Puccinia spp., Causal Agents of Rust on Switchgrass (Panicum virgatum L.) in the USA

Switchgrass (Panicum virgatum L.) is an important cellulosic biofuel grass native to North America. Rust, caused by Puccinia spp. is the most predominant disease of switchgrass and has the potential to impact biomass conversion. In this study, virulence patterns were determined on a set of 38 switchgrass genotypes for 14 single-spore rust isolates from 14 field samples collected in seven states. Single nucleotide polymorphism (SNP) variation was also assessed in 720 sequenced cloned amplicons representing 654 base pairs of the elongation factor 1-α gene from the field samples. Five major haplotypes were identified differing by 11 out of the 39 SNP positions identified. STRUCTURE, Principal Coordinate Analysis, and phylogenetic analyses divided the rust population into two genetic clusters. Virginia and Georgia had the highest and lowest rust genetic diversity, respectively. Only nine accessions showed a differential disease response between the 14 isolates, allowing the identification of eight races, differing by 1–3 virulence factors. Overall, the results suggested clonal reproduction of the pathogen and a North–South differentiation via local adaptation. However, similar haplotypes and races were also recovered from several states, suggesting migration events, and highlighting the need to further investigate the switchgrass rust population structure and evolution in the USA.

Bahri, Bochra A. (ORCID:0000000159055880)↗

The Molecular Structures of Liquid and Glassy Nifedipine and Felodipine and Their Incorporation into PVP

Background: Amorphous drug formulations are commonly used to improve the solubility and bioavailability of poorly soluble molecular pharmaceuticals, yet less is known about their molecular conformations and local bonding interactions than their crystalline phases. Methods: High-energy X-ray diffraction structure factor measurements have been made on liquid and glassy nifedipine (NIF), felodipine (FEL), NIF 1:3 polyvinylpyrrolidone (PVP), and FEL 1:3 PVP wt.% mixtures. The corresponding X-ray pair distribution functions have been interpreted using empirical potential structure refinement using different models and density functional theory conformer calculations. Results: In both NIF and FEL, the NH···O inter-molecular hydrogen bonds between the pyridyl nitrogen and ester carbonyls are found to be considerably weaker than those observed in the crystalline polymorphs. For nifedipine, it is proposed that either inter-molecular NH…ON nitro bonds are present and/or a fraction (<20%) of conformational changes, with the aryl ring flipped, occur in the liquid state. For felodipine, the models indicate significant disorder associated with the methyl and ethyl side chains in the liquid state, with the main peak intensity at 3.0 Å arising from intra-molecular Cl-Cl atom pairs. When nifedipine molecules are incorporated into PVP, our models show they possess stronger NH···O bonds to the PVP polymer than felodipine molecules, which have stronger affinity for bonding to the polymer than to other felodipine molecules. Conclusions: The amorphous forms of both NIF and FEL show much weaker hydrogen bonding than found in their crystalline phases. Liquid NIF also exhibits configurations which are not observed in the crystal phases.

Amorphous Solid Dispersion↗

ε-VOPO 4 cathode for lithium ion batteries

The epsilon polymorph of vanadyl phosphate, ε-VOPO 4 , made from the solvothermally synthesized H 2 VOPO 4 , is a high density cathode material for lithium-ion batteries optimized to reversibly intercalate two Li-ions to reach the full theoretical capacity at least 50 cycles with a coulombic efficiency of 98%. This material adopts a stable 3D tunnel structure and can extract two Li-ions per vanadium ion, giving a theoretical capacity of 305 mAh/g, with an upper charge/discharge plateau at around 4.0 V, and one lower at around 2.5 V.

Siu, Carrie↗