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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 847 records · Page 47

Rethinking the soil core microbiome

The concept of a core microbiome emerged from host-associated research to describe microbial members or functions conserved across clearly defined spatial, temporal, and biological boundaries. In soil- and plant-associated microbiome research, however, the term has increasingly shifted toward analytically defined subsets selected using study-specific thresholds or criteria. Synthesizing recent literature and cross-site analyses of bioenergy crop field soils, we show that the original biological meaning of the core microbiome has been blurred by dataset-specific analytical criteria. Taxa designated as ‘core’ were highly sensitive to methodological choices and often reflected explanatory value rather than conserved biological membership. Moreover, many studies that identify taxonomic ‘core’ members interpret their significance in functional terms, suggesting that functional conservation may be the biological interest. Taxonomic conservation may not be the most biologically meaningful target in highly heterogeneous soil and rhizosphere systems, where functional conservation may persist despite taxonomic turnover. Accordingly, ‘core microbiome’ should be reserved for microbial components explicitly demonstrated to be conserved across defined spatial, temporal, and environmental dimensions and linked to conserved ecological functions, while taxa selected for explanatory value are better described as ‘explanatory subsets of taxa’. Greater terminological precision will improve cross-study comparability and strengthen ecological inference in plant–soil microbiome research.

bioenergy crops↗

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗

Ultrafast nonlinear absorption of Haldane model quantum dots

We study theoretically the nonlinear absorbance of Haldane model quantum dots (QDs) placed in the field of an ultrashort and strong optical pulse. The absorbance strongly depends on the frequency of the pulse. When the frequency of the pulse is much less than the QD bandgap, the absorbance shows strong dependence on the pulse amplitude and, as a function of an internal phase of the Haldane model, the absorbance has maxima at intermediate values of the phase. When the frequency of the pulse becomes closer to, but still less than, the bandgap, the absorbance has a weak dependence on the pulse amplitude and, as a function of the internal phase, it has a maximum at the phase of 900 when the QD bandgap also has the smallest value. Furthermore, nonlinear electron dynamics in such QD systems changes from almost reversible one at small pulse frequencies to highly irreversible dynamics at large frequencies of the pulse.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Accurate Electron Affinities and Orbital Energies of Anions from a Nonempirically Tuned Range-Separated Density Functional Theory Approach

The treatment of atomic anions with Kohn–Sham density functional theory (DFT) has long been controversial because the highest occupied molecular orbital (HOMO) energy, E HOMO , is often calculated to be positive with most approximate density functionals. We assess the accuracy of orbital energies and electron affinities for all three rows of elements in the periodic table (H–Ar) using a variety of theoretical approaches and customized basis sets. Among all of the theoretical methods studied here, we find that a nonempirically tuned range-separated approach (constructed to satisfy DFT-Koopmans’ theorem for the anionic electron system) provides the best accuracy for a variety of basis sets, even for small basis sets where most functionals typically fail. Previous approaches to solve this conundrum of positive E HOMO values have utilized non-self-consistent methods; however, electronic properties, such as electronic couplings/gradients (which require a self-consistent potential and energy), become ill-defined with these approaches. In contrast, the nonempirically tuned range-separated procedure used here yields well-defined electronic couplings/gradients and correct E HOMO values because both the potential and resulting electronic energy are computed self-consistently. Orbital energies and electron affinities are further analyzed in the context of the electronic energy as a function of electronic number (including fractional numbers of electrons) to provide a stringent assessment of self-interaction errors for these complex anion systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of End-Functionalized Poly(norbornenes) and Poly(ethylidene norbornenes) Using a Pd(II) Catalyst in Combination with Chain Transfer Agents

Synthesis of end-functionalized poly(norbornene)s (PNBs) and poly(ethylidenenorbornene)s (PENBs) were prepared using the palladium catalyst t Bu 3 PPdMeCl/NaBAr f in combination with chain transfer agents (CTAs) 4-penten-1-ol and 10-undecenal. These CTAs produce polymers end-capped with -OH and -CHO groups, respectively, in high yields with M n values in the range of 6K to 17K, depending on the molar ratio of the CTA: monomer. End-functionalized PNBs and PENBs with precisely controlled Mn values and very narrow molecular weight distributions were accessed by using 4-penten-1-ol and 10-undecenal as chain-terminating agents following living polymerizations in which monomer is completely consumed. The utility of the aldehyde-functionalized polymers is illustrated via coupling to a dye molecule and by synthesis of ambiphilic diblock copolymers, PNB-b-PEG and PENB-b-PEG.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing Uncertainty through Functional Data Analysis in Gas Breakthrough Data

Detecting subsurface explosions from radionuclide gas migration through rock fractures is an effective way to identify nuclear activity. Los Alamos National Laboratory (LANL) has developed simulation methods, based on data from the 1962 Hardhat underground nuclear test, to predict gas breakthrough times at the surface. However, these methods rely on an imperfect understanding of the relationship between rock damage and fracture permeability. Our clinic project studies methods for predicting breakthrough curves that characterize total mass produced as a function of time, as well as quantifying the uncertainty associated with these predictions. The model that is currently employed to relate damage to permeability uses an empirically motivated power-law expression, with a range of parameter values that are compatible with the experimental Hardhat data. We develop emulators, built from functional data analysis techniques and trained on simulation data, that rapidly predict the gas breakthrough curve given a damage field and given the parameter values of the power-law equation. Using Bayesian regression, we address the problem of uncertainty quantification in our emulators. Finally, in order to test the robustness of the model, we further validate it on a damage field representing different physical conditions.

58 GEOSCIENCES↗

Functional Properties of Porous Ti-48.0 at.% Ni Shape Memory Alloy Produced by Self-Propagating High-Temperature Synthesis

The functional behavior of the porous shape memory alloy produced by self-propagating high-temperature synthesis from the Ti-48.0 at.% Ni powder mixture was studied. It was found that a large unelastic strain recovered on unloading and it was not attributed to the pseudoelasticity effect. A decrease in deformation temperatures did not influence the value of strain that recovered on unloading, while the effective modulus decreased from 1.9 to 1.44 GPa. It was found that the porous Ti-48.0 at.% Ni alloy revealed the one-way shape memory effect, where the maximum recoverable strain was 5%. The porous Ti-48.0 at.% Ni alloy demonstrated the transformation plasticity and the shape memory effects on cooling and heating under a stress. An increase in stress did not influence the shape memory effect value, which was equal to 1%. It was shown that the functional properties of the porous alloy were determined by the TiNi phase consisted of the two volumes Ti{sub 49.3}Ni{sub 50.7} and Ti{sub 50}Ni{sub 50} where the martensitic transformation occurred at different temperatures. The results of the study showed that the existence of the Ti{sub 49.3}Ni{sub 50.7} volumes in the porous Ti-48.0 at.% Ni alloy improved the functional properties of the alloy.

36 MATERIALS SCIENCE↗

Biomarker Mapping on Skin Tape Strips Using MALDI Mass Spectrometry Imaging

Keratinocyte organization and biochemistry are important in forming the skin’s protective barrier. Intrinsic and extrinsic factors can affect skin barrier function at the cellular and molecular levels. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometric imaging, a technique which combines both molecular aspects and histological details, has proven to be a valuable method in various disciplines including pharmacology, dermatology and cosmetology. It typically requires ex vivo samples, prepared following frozen tissue sectioning. This paper demonstrates the feasibility of performing MALDI analysis on tape strips collected non-invasively on skin. The aim is to obtain molecular imaging of corneocytes on tapes towards novel biological insights. Tapes were collected from two skin sites (volar forearm and cheek) of human volunteers. Ten molecules relating to skin barrier function were detected with a single mode of acquisition at high spatial resolution with a 7 T MALDI-Fourier transform ion cyclotron resonance (FTICR) instrument. The method sensitivity was adequate to create molecular maps which could be overlaid on transmission microscopy images of the same area of the tape. Analysis of the molecular distributions from tapes at the two skin sites was consistent with the known skin properties of the two sites, confirming the validity of the observations. Hierarchical clustering analysis was used to differentiate corneocyte populations based on their molecular profiles. Furthermore, morphological analysis provided a new way of considering statistical populations of corneocytes on the same tape, rather than measuring a single averaged value, providing additional useful information relating to their structure-function relationship. .

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Exploring the strong-coupling region of SU( N ) Seiberg-Witten theory

We consider the Seiberg-Witten solution of pure N = 2 gauge theory in four dimensions, with gauge group SU(N). A simple exact series expansion for the dependence of the 2(N – 1) Seiberg-Witten periods a I (u), a DI (u) on the N – 1 Coulomb-branch moduli un is obtained around the Z 2N -symmetric point of the Coulomb branch, where all u n vanish. This generalizes earlier results for N = 2 in terms of hypergeometric functions, and for N = 3 in terms of Appell functions. Using these and other analytical results, combined with numerical computations, we explore the global structure of the Kähler potential K = 1/2Σ I Im(a¯ I a DI ), which is single valued on the Coulomb branch. Evidence is presented that K is a convex function, with a unique minimum at the Z 2N -symmetric point. Finally, we explore candidate walls of marginal stability in the vicinity of this point, and their relation to the surface of vanishing Kähler potential.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Melting down a tetraquark: D*D(*) interactions and T c c ( 3875 ) + in a hot environment

We discuss the modification of the properties of the tetraquark-like and its heavy quark spin partner, immersed in a hot bath of pions. We consider these exotic states as purely isoscalar DD* and D*D* S-wave bound states, respectively. Finite temperature effects are incorporated through the D and D* state-of-the-art thermal spectral functions calculated in [G. Montana et al., Phys. Rev. D, 102 (2020) 096020], using the imaginary-time formalism. We find important modifications of the DD* and D*D* scattering amplitudes already for MeV, and show that the hot-bath lineshapes of these tetraquark-like states strongly depend on their Weinberg molecular content. We find that the thermal and spectral functions change more rapidly with temperature for high molecular probabilities P0. For large values of P0, the widths significantly increase with temperature, leading to the melting of these exotic states for temperatures larger than 80 MeV. For small molecular components, the changes in the spectral functions of these states due to temperature become significantly less important. All these results show that any future experimental determination of the D(*)D* scattering amplitudes at finite temperature will provide valuable insights into the molecular content of the and exotics.

Montesinos, V. (ORCID:0000000261862777)↗

Learning energy-based representations of quantum many-body states

Efficient representation of quantum many-body states on classical computers is a problem of practical importance. An ideal representation of a quantum state combines a succinct characterization informed by the structure and symmetries of the system along with the ability to predict the physical observables of interest. Several machine-learning approaches have been recently used to construct such classical representations, which enable predictions of observables and account for physical symmetries. However, the structure of a quantum state typically gets lost unless a specialized is employed based on prior knowledge of the system. Moreover, most such approaches give no information about what states are easier to learn in comparison with others. Here, we propose a generative energy-based representation of quantum many-body states derived from Gibbs distributions used for modeling the thermal states of classical spin systems. Based on the prior information on a family of quantum states, the energy function can be specified by a small number of parameters using an explicit low-degree polynomial or a generic parametric family such as neural nets and can naturally include the known symmetries of the system. Our results show that such a representation can be efficiently learned from data using exact algorithms in a form that enables the prediction of expectation values of physical observables. Importantly, the structure of the learned energy function provides a natural explanation for the difficulty of learning an energy-based representation of a given class of quantum states when measured in a certain basis. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IRDFF-II: A New Neutron Metrology Library

High quality nuclear data is the most fundamental underpinning for all neutron metrology applications. This paper describes the release of version II of the International Reactor Dosimetry and Fusion File (IRDFF-II) that contains a consistent set of nuclear data for fission and fusion neutron metrology applications up to 60 MeV neutron energy. The library is intended to support: a) applications in research reactors; b) safety and regulatory applications in the nuclear power generation in commercial fission reactors; and c) material damage studies in support of the research and development of advanced fusion concepts. The paper describes the contents of the library, documents the thorough verification process used in its preparation, and provides an extensive set of validation data gathered from a wide range of neutron benchmark fields. The new IRDFF-II library includes 119 metrology reactions, four cover material reactions to support self-shielding corrections, five metrology metrics used by the dosimetry community, and cumulative fission products yields for seven fission products in three different neutron energy regions. In support of characterizing the measurement of the residual nuclei from the dosimetry reactions and the fission product decay modes, the present document lists the recommended decay data, particle emission energies and probabilities for 68 activation products. It also includes neutron spectral characterization data for 29 neutron benchmark fields for the validation of the library contents. Additional six reference fields were assessed (four from plutonium critical assemblies, two measured fields for thermal-neutron induced fission on 233U and 239Pu targets) but not used for validation due to systematic discrepancies in C/E reaction rate values or lack of reaction-rate experimental data. Another ten analytical functions are included that can be useful for calculating average cross sections, average energy, thermal spectrum average cross sections and resonance integrals. The IRDFF-II library and comprehensive documentation is available online at www-nds.iaea.org/IRDFF/. Evaluated cross sections can be compared with experimental data and other evaluations at www-nds.iaea.org/exfor/endf.htm. The new library is expected to become the international reference in neutron metrology for multiple applications.

IAEA IRDFF↗

Comparative operando XPS studies of quasi-Fermi level splitting and open-circuit voltage in CZTSe/CdS and CIGS/CdS junctions and device structures

This contribution describes operando x-ray photoelectron spectroscopy (opXPS) studies of Cu(In,Ga)Se 2 (CIGS) and Cu 2 ZnSnSe 4 (CZTSe) absorber layers and device structures. X-ray-excited valence-band and core-level spectra were acquired on bare absorber surfaces and after CdS and ZnO:Al depositions in standard absorber/CdS/ZnO/ZnO:Al device stacks. OpXPS data sets were acquired at various x-ray fluxes, with and without white-light illumination. From these measurements, quasi-Fermi level splitting (ΔE F ) values in the absorber/CdS junctions were measured directly as a function of excitation conditions. For both CIGS and CZTSe, results show that ..delta..EF proportional to the full open-circuit voltage (V OC ) of the completed devices is present after the deposition of the CdS layer - i.e., E F = qV OC - demonstrating that the so-called V OC deficit in CZTSe solar cells is also present at this stage of processing. The authors find that photoexcitation due to x-rays or stray visible light during XPS or similar measurements can produce measurable photovoltages in materials, absorber/CdS junctions, and finished devices. In situ current density versus voltage measurements on a typical CIGS device reveal that x-ray-induced photoexcitation associated with typical XPS measurement conditions is equivalent to ~3 x 10 -3 suns, which in this study produced V OC = 440 mV. These findings demonstrate that accounting for photoexcitation conditions during XPS or similar measurements can improve band-offset determinations and produce more reliable values for the junction built-in voltage. The implications of the study findings on the CZTSe V OC deficit and device performance are discussed.

36 MATERIALS SCIENCE↗

First-principles investigation of the thermophysical properties of NaCl, PuCl 3 , and NaCl-PuCl 3 Molten salts

Molten salts have a variety of applications that span the nuclear and solar industries, and which involve thermal storage and heat transfer. There is a present knowledge gap in the thermophysical properties of molten salts, which limits the readiness level of molten salt applications. This is especially pertinent for molten salt reactors where the fissile material is dissolved within the molten salt. Ab initio molecular dynamics is a common method employed to investigate the structural and thermophysical properties at elevated temperatures. NaCl-PuCl 3 is a candidate fuel salt in molten salt reactors. The scope of this study is to investigate the seven unique compositions and a range of temperatures of NaCl-PuCl 3 and calculate the density, heat capacity, compressibility, enthalpy of mixing, and coefficient of thermal expansion. Within this work, the van der Waals (vdW) interactions are primarily handled with the vdW-DF2 functional but spot-checked with both the dDsC and DFT-D3 methods. The calculated densities are in good agreement with the NaCl and the eutectic compositions, and no experimental values exist for PuCl 3 at these temperatures. The densities are fit to a first-order Redlich-Kister expansion as a function of both composition and temperature. The heat capacity in the literature is scattered but the calculated values agree well with one of the experimental results. Here, the heat capacity increases as a linear function with respect to concentration at a rate of about 7.5 J/mol-K per 10 mol% PuCl 3 .

36 MATERIALS SCIENCE↗

Multirate Exponential Rosenbrock Methods

In this paper we propose a novel class of methods for high-order accurate integration of multirate systems of ordinary differential equation initial-value problems. The proposed methods construct multirate schemes by approximating the action of matrix φ functions within explicit exponential Rosenbrock (ExpRB) methods, thereby called multirate ExpRB (MERB) methods. They consist of the solution to a sequence of modified “fast” initial-value problems, which may themselves be approximated through subcycling any desired initial-value problem solver. In addition to proving how to construct MERB methods from certain classes of ExpRB methods, we provide rigorous convergence analysis of these methods and derive efficient MERB schemes of orders 2 through 6 (the highest-order infinitesimal multirate methods to date). Lastly, we then present numerical simulations to confirm these theoretical convergence rates and to compare the efficiency of MERB methods against other recently introduced high-order multirate methods.

97 MATHEMATICS AND COMPUTING↗

The developments in modifying functionality of lignin and its application in biocomposites

With the advancement of sustainable material innovations, renewable natural biopolymers are gradually replacing traditional metal and petroleum-based synthetic materials due to their environmental friendliness, biodegradability, and economic advantages. Lignin, the second most abundant natural aromatic polymer in the plant kingdom, has emerged as a key candidate raw material for the development of green polymer systems because of its unique phenylpropane unit network structure, high carbon content, and rich functional group characteristics. However, challenges such as the inherent structural complexity, chemical inertness, and uneven molecular weight distribution of lignin limit its direct application. By employing modification strategies such as chemical functionalization and physical regulation, researchers can precisely control its reactivity, thermal stability, and interfacial compatibility, enabling the preparation of high-performance lignin-based functional composites. Here, this paper systematically reviews the principles and methodological advancements in lignin's multi-dimensional modification technology. It analyzes the mechanisms by which various chemical and physical modification techniques enhance the mechanical properties, functional responsiveness, and environmental adaptability of materials, and discusses innovative applications in fields such as intelligent packaging, biomedical materials, and energy storage devices. Furthermore, this review addresses the key challenges encountered in the high-value transformation of lignin, with the aim of offering a theoretical framework and technical pathway for the transformative development of lignin from agricultural and forestry by-products to functional material platforms.

Functional composites↗

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

59 BASIC BIOLOGICAL SCIENCES↗

Self-interaction-corrected Kohn–Sham effective potentials using the density-consistent effective potential method

Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn–Sham eigenvalues are not electron removal energies except for the highest occupied orbital. The eigenvalues of the highest occupied molecular orbitals often underestimate the electron removal or ionization energies due to the self-interaction (SI) errors in approximate density functionals. Here, we adapt and implement the density-consistent effective potential method of Kohut, Ryabinkin, and Staroverov (2014) to obtain SI-corrected local effective potentials from the SI-corrected Fermi–Löwdin orbitals and density in the Fermi–Löwdin orbital self-interaction correction scheme. The implementation is used to obtain the density of states (photoelectron spectra) and HOMO–LUMO gaps for a set of molecules and polyacenes. Good agreement with experimental values is obtained compared to a range of SI uncorrected density functional approximations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗