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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 109 records · Page 6

Group additivity values for entropy and heat capacities of C 2 –C 8 alkanes, alkyl hydroperoxides, and their radicals

Group additivity values for the thermodynamic properties of oxygenated radicals are poorly determined due to the absence of high quality reference data. Here, a set of 58 group additive values (GAV) for the standard entropy and heat capacity of relevance to alkane oxidation is derived from fits to an extensive and accurate database of standard entropies (298.15 K) and heat capacities (300–3000 K) recently calculated with the “STAR-1D” formalism. The 192 species in this database represent the alkanes (RH), alkyl radicals ($\dot{R}$), alkyl hydroperoxides (RO 2 H), alkyl-peroxy (R$\dot{O}$ 2 ) and hydroperoxy-alkyl ($\dot{Q}$OOH) radicals for all of the isomers of C 2 –C 5 alkane fuels and a select number of isomers of C 6 –C 9 species. The STAR-1D thermochemical data for this set of species was previously obtained from a coupling of scaled B2PLYPD3/cc-pVTZ vibrational analyses with scaled ωB97X-D/cc-pVTZ one-dimensional hindered rotor corrections. The 2σ uncertainties in the GAV results relative to the STAR-1D data set are 2.4 cal K –1 mol –1 for the entropies and at most 2.0 cal K –1 mol –1 for the heat capacities in the temperature range 500–800 K. The 2σ fitting uncertainties in the heat capacity gradually reduce at higher temperatures reaching a value of 0.8 cal K –1 mol –1 at 2000 K decreasing to only 0.5 cal K –1 mol –1 at 3000 K. The high degree of accuracy for the GAV representations is obtained through the introduction of various new group terms, together with the re-optimization of existing group terms. Among the full set of 58 GAV terms, 25 include non-next-nearest neighbor interactions (NNI) and β-corrections. The updated GAVs can be applied in the prediction of entropies and heat capacities for a wide range of hydrocarbons and hydroperoxide species and their radicals, which is important to the accurate prediction of fuel reactivity at low-temperatures in the range 600–1000 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of E6 chiral gauge theories

We present exact nonperturbative vacuum solutions to chiral gauge theories based on the gauge group and several matter fermions in the fundamental -dimensional representation. They are obtained when supersymmetric versions are perturbed by small supersymmetry breaking by anomaly mediation. The universality classes obtained are very different from what can be conjectured by the tumbling hypothesis. In particular, the case with three may have an unbroken SU(3) symmetry with massless composite fermions in of SU(3). For this case, we employed numerical techniques to obtain the exact ground state.

Goh, Andrew↗

Synthesis and Thermal Oxidation Resistance of Boron-Rich Boron–Carbide Material

A boron-rich boron–carbide material (B4+δC) was synthesized by spark plasma sintering of a ball-milled mixture of high-purity boron powder and graphitic carbon at a pressure of 7 MPa and a temperature of 1930 °C. This high-pressure, high-temperature synthesized material was recovered and characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, Vickers hardness measurements, and thermal oxidation studies. The X-ray diffraction studies revealed a single-phase rhombohedral structure (space group R-3m) with lattice parameters in hexagonal representation as a = 5.609 ± 0.007 Å and c = 12.082 ± 0.02 Å. The experimental lattice parameters result in a value of δ = 0.55, or the composition of the synthesized compound as B4.55C. The high-resolution scans of boron binding energy reveal the existence of a B-C bond at 188.5 eV. Raman spectroscopy reveals the existence of a 386 cm−1 vibrational mode representative of C-B-B linear chain formation due to excess boron in the lattice. The measured Vickers microhardness at a load of 200 gf shows a high hardness value of 33.8 ± 2.3 GPa. Thermal gravimetric studies on B4.55C were conducted at a temperature of 1300 °C in a compressed dry air environment, and its behavior is compared to other high-temperature ceramic materials such as high-entropy transition metal boride. The high neutron absorption cross section, high melting point, high mechanical strength, and thermal oxidation resistance make this material ideal for applications in extreme environments.

36 MATERIALS SCIENCE↗

Edge counts for the auxiliary pair graph within the graphical unitary group approach

Closed-form expressions are presented for the numbers of edges in the auxiliary pair graphs (APGs) associated with non spin-orbit and spin-orbit Shavitt graphs for full configuration interaction expansions. A Shavitt graph is a visual representation of a configuration state function expansion space constructed via the graphical unitary group approach (GUGA). An APG is an organisational aid and a programmatic tool generated from a Shavitt graph. The number of edges in an APG determines bounds on the computational scaling as a function of the total numbers of electrons, orbitals, and spin multiplicities. The edge counts extend a suite of Shavitt graph statistics based on these functional parameters. The derivation and the presentation of the formulas for the edge counts has been assisted by the bra-ket interchange symmetry and the particle-hole interchange symmetry in the GUGA formalism. Furthermore, these symmetry operators produce one-to-one correspondences between various sets of edges, and this yields identities among some edge count formulas. There are 208 possible edge types. Of these, some do not contribute to two-electron operators, some are related by bra-ket interchange symmetry, and some are related by particle-hole interchange symmetry. For the remaining unique edge types, explicit expressions are derived for the numbers of edges.

74 ATOMIC AND MOLECULAR PHYSICS↗

The Unified Phenotype Ontology : a framework for cross-species integrative phenomics

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.

59 BASIC BIOLOGICAL SCIENCES↗

Automated classification of big X-ray diffraction data using deep learning models

Abstract In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of insights. Automated techniques require human intervention, and lack the performance and adaptability required for material exploration. Given the critical need for high-throughput automated XRD pattern analysis, we present a generalized deep learning model to classify a diverse set of materials’ crystal systems and space groups. In our approach, we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal properties. We also employ an expedited learning technique to refine our model’s expertise to experimental conditions. In addition, we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s decision-making. We evaluate our models using experimental data, materials unseen in training, and altered cubic crystals, where we observe state-of-the-art performance and even greater advances in space group classification.

Chemistry↗

Distinctive signals of frustrated dark matter

We study a renormalizable model of Dirac fermion dark matter (DM) that communicates with the Standard Model (SM) through a pair of mediators — one scalar, one fermion — in the representation (6, 1, $\frac{4}{3}$) of the SM gauge group SU(3) c x SU(2) L x U(1) Y . While such assignments preclude direct coupling of the dark matter to the Standard Model at tree level, we examine the many effective operators generated at one-loop order when the mediators are heavy, and find that they are often phenomenologically relevant. We reinterpret dijet and pair-produced resonance and jets + E$^{miss}_{T}$ searches at the Large Hadron Collider (LHC) in order to constrain the mediator sector, and we examine an array of DM constraints ranging from the observed relic density Ω χ h$^{2}_{Planck}$ to indirect and direct searches for dark matter. Tree-level annihilation, available for DM masses starting at the TeV scale, is required in order to produce Ω χ h$^{2}_{Planck}$ through freeze-out, but loops — led by the dimension-five DM magnetic dipole moment — are nonetheless able to produce signals large enough to be constrained, particularly by the XENON1T experiment. In some benchmarks, we find a fair amount of parameter space left open by experiment and compatible with freeze-out. In other scenarios, however, the open space is quite small, suggesting a need for further model-building and/or non-standard cosmologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Strain engineering a persistent spin helix with infinite spin lifetime

Persistent spin textures (PSTs) in solid-state materials arise from a unidirectional spin-orbit field in momentum space and offer a route to deliver long carrier spin lifetimes sought for future quantum microelectronic devices. Nonetheless, few three-dimensional materials are known to host PSTs owing to crystal symmetry and chemical requirements. There are even fewer examples demonstrated experimentally. Here we report that high-quality persistent spin textures can be obtained in the polar point groups containing an odd number of mirror operations. We use representation theory analysis and electronic structure calculations to formulate general discovery principles to identify PSTs hidden in known complex ternary layered and perovskite structures with large electric polarizations. We then show some of these materials exhibit PSTs without requiring any special crystalline symmetries. This finding removes the limitation imposed by mirror-symmetry protected PSTs that has limited compound discovery. Our general design approach enables the pursuit of persistent spin helices in materials exhibiting the C 3 v crystal class adopted by many quantum materials exhibiting large Rashba coefficients.

36 MATERIALS SCIENCE↗

Heliostat Consortium: Update on Resource, Training, and Education Development and Women+ in Concentrating Solar

One of the major barriers to Concentrating Solar Power (CSP) industry growth in the U.S. is the lack of accessibility of expert knowledge, a lack of a stable workforce pipeline, and little public awareness of the technology area. Improved Resource, Training, and Education (RTE) is needed to address these gaps, to draw workers into the field from diverse technology areas and backgrounds, and to reduce the learning curves of newcomers into the industry. As part of the RTE topic under the NREL-led Heliostat Consortium (HelioCon), a public online resource database has been created to support information sharing across the heliostat and CSP community. Here, information will be presented on the existing and planned database resources, including introductory information about CSP and heliostats, a reference library of texts and publications, educational videos, a CSP power tower plant database and case studies, a contact list of component suppliers and developers, and a list of available software/metrology tools. Women+ in Concentrating Solar is a newly created organization to promote the education, professional development, and advancement of underrepresented genders in the Concentrating Solar Power (CSP) community in a way that includes diverse backgrounds, attitudes, and perspectives. The main objectives of the groups are to provide the following opportunities for underrepresented genders: 1) organize events to provide networking opportunities and community building, 2) boost partnerships and scientific collaboration, 3) create resources to facilitate knowledge and experience sharing, 4) provide mentorship programs to support those new to the industry, 5) bring visibility to underrepresented genders and attract more to the field, and 6) promote Diversity, Equity, and Inclusion (DEI) and engage minorities and underrepresented groups. Initial activities being pursued by the group include creating an expert database to support event organizers in recruiting speakers with representation of all gender identities, hosting online networking and webinar events, organizing conference events including seminars and networking/social events, and establishing a mentorship program to connect members in the CSP community across the globe. The group is open to all genders and has grown to over 60 members in its first few months.

concentrating solar↗

Representation of Modes of Variability in Six U.S. Climate Models

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

54 ENVIRONMENTAL SCIENCES↗

Phylogenetic diversity of 200+ isolates of the ectomycorrhizal fungus Cenococcum geophilum associated with Populus trichocarpa soils in the Pacific Northwest, USA and comparison to globally distributed representatives

The ectomycorrhizal fungal symbiont Cenococcum geophilum is of high interest as it is globally distributed, associates with many plant species, and has resistance to multiple environmental stressors. C . geophilum is only known from asexual states but is often considered a cryptic species complex, since extreme phylogenetic divergence is often observed within nearly morphologically identical strains. Alternatively, C . geophilum may represent a highly diverse single species, which would suggest cryptic but frequent recombination. Here we describe a new isolate collection of 229 C . geophilum isolates from soils under Populus trichocarpa at 123 collection sites spanning a ~283 mile north-south transect in Western Washington and Oregon, USA (PNW). To further understanding of the phylogenetic relationships within C . geophilum , we performed maximum likelihood and Bayesian phylogenetic analyses to assess divergence within the PNW isolate collection, as well as a global phylogenetic analysis of 789 isolates with publicly available data from the United States, Japan, and European countries. Phylogenetic analyses of the PNW isolates revealed three distinct phylogenetic groups, with 15 clades that strongly resolved at >80% bootstrap support based on a GAPDH phylogeny and one clade segregating strongly in two principle component analyses. The abundance and representation of PNW isolate clades varied greatly across the North-South range, including a monophyletic group of isolates that spanned nearly the entire gradient at ~250 miles. A direct comparison between the GAPDH and ITS rRNA gene region phylogenies, combined with additional analyses revealed stark incongruence between the ITS and GAPDH gene regions, consistent with intra-species recombination between PNW isolates. In the global isolate collection phylogeny, 34 clades were strongly resolved using Maximum Likelihood and Bayesian approaches (at >80% MLBS and >0.90 BPP respectively), with some clades having intra- and intercontinental distributions. Together these data are highly suggestive of divergence within multiple cryptic species, however additional analyses such as higher resolution genotype-by-sequencing approaches are needed to distinguish potential species boundaries and the mode and tempo of recombination patterns.

59 BASIC BIOLOGICAL SCIENCES↗

Lowest-dimensional portals to SU( N ) exotics

New matter fields charged under the strong nuclear force would have dramatic phenomenological implications. In this work, we systematically explore how these new states, which we postulate belong to some representation of SU(3) of quantum chromo-dynamics, could interact with standard model fields: We analyze all lowest-dimensional “portal” operators for any SU(3) representation, and motivated by grand unification, we extend our results to SU( N ) for N > 3. We provide a publicly available python code, “tessellation,” that automatically constructs said lowest-dimensional portal operators for any new exotic matter field charged under SU( N ) for any N .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On triality defects in 2d CFT

We consider the triality fusion category discovered in the c = 1 Kosterlitz-Thouless theory. We analyze this fusion category using the tools from the group theoretical fusion category and compute the simple lines, fusion rules and F-symbols. We then studied the physical implication of this fusion category including deriving the spin selection rule, computing the asymptotic density of states of irreducible representations of the fusion category symmetries, and analyzing its anomaly and constraints under the renormalization group flow. There is another set of F-symbols for the fusion categories with the same fusion rule known in the literature. We find these two solutions are different as they lead to different spin selection rules. This gives a complete list of the fusion categories with the same fusion rule by the classification result in.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Euclidean formulation of relativistic quantum mechanics of N particles

A Euclidean formulation of relativistic quantum mechanics for systems of a finite number of degrees of freedom is discussed. Relativistic treatments of quantum theory are needed to study hadronic systems at subhadronic distance scales. While direct interaction approaches to relativistic quantum mechanics have proved to be useful, they have two disadvantages. One is that cluster properties are difficult to realize for systems of more than two particles. The second is that the relation to quantum field theories is indirect. Euclidean formulations of relativistic quantum mechanics provide an alternative representation that does not have these difficulties. More surprising, the theory can be formulated entirely in the Euclidean representation without the need for analytic continuation. In this work a Euclidean representation of a relativistic N-particle system is discussed. Kernels for systems of N free particles of any spin are given and shown to be reflection positive. Explicit formulas for generators of the Poincaré group for any spin are constructed and shown to be self-adjoint on the Euclidean representation of the Hilbert space. The structure of correlations that preserve both the Euclidean covariance and reflection positivity is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗

Space-energy separated representations for multigroup neutron diffusion using proper generalized decompositions

Proper generalized decomposition (PGD) can be described as a numerical extension of separation of variables and thus be employed as a solution technique for multi-dimensional problems, where dimensions should be understood in the phase-space context of the governing law at hand. This paper presents a PGD approach on efficiently solving problems involving multigroup neutron diffusion. Two PGD approaches are described: space-only and space-energy decompositions. Numerical results include 2-D and 3-D examples with two-, seven-, and 145-group structures. The PGD solutions are compared against traditional multi-dimensional finite element discretization. For few-group problems, both PGD approaches prove effective for mildly heterogeneous geometries, but showed reduced performance with increasing heterogeneity. The space-energy representation was found to be slower than the space-only approach for two-group problems, but proved more effective for seven-group problems. For even larger numbers of groups, the space-energy PGD decomposition was very effective at reducing the computational time.

42 ENGINEERING↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗