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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Water vapor transport through bioenergy grass residues and its effects on soil water evaporation

Miscanthus is a productive perennial grass that is suitable as a bioenergy crop in “marginal” lands (e.g., eroded soils) with low water holding capacity. However, little is known about the impact of miscanthus residues on vapor transport and soil water budgets. Laboratory experiments were conducted to measure the vapor conductance through miscanthus residues and its effect on soil water evaporation. The ranges for the length, width, and thickness of residue elements were 0.5–9.0, 0.1–0.5, and 0.1–0.5 cm, respectively. Average residue areal, bulk, and skeletal densities were 0.88 kg m –2 , 24 kg m –3 , and 1006 kg m –3 , respectively, giving a porosity of 0.98 m 3 m –3 . A power function described the decrease in conductance with increasing residue load. The corresponding conductance for a residue load of 0.88 kg m –2 was 1.6 mm s –1 . During the first days of a 60-day drying experiment, cumulative evaporation showed logarithmic decay with increasing residue load. Conversely, cumulative evaporation during the last days of the study showed little difference between treatments. Measurements indicated that there is a “critical” residue load (~1.0 kg m –2 ) beyond which evaporation no longer decreases appreciably when the soil is under the stage 1 evaporation regime. Results suggest that soil water conservation in marginal lands may be accomplished by maintaining moderate amounts of bioenergy grass residue covering the soil. Determining “critical” loads for different residue types is a knowledge gap that merits further research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An unexpected hydratase synthesizes the green light-absorbing pigment fucoxanthin

Abstract The ketocarotenoid fucoxanthin and its derivatives can absorb blue–green light enriched in marine environments. Fucoxanthin is widely adopted by phytoplankton species as a main light-harvesting pigment, in contrast to land plants that primarily employ chlorophylls. Despite its supreme abundance in the oceans, the last steps of fucoxanthin biosynthesis have remained elusive. Here, we identified the carotenoid isomerase-like protein CRTISO5 as the diatom fucoxanthin synthase that is related to the carotenoid cis–trans isomerase CRTISO from land plants but harbors unexpected enzymatic activity. A crtiso5 knockout mutant in the model diatom Phaeodactylum tricornutum completely lacked fucoxanthin and accumulated the acetylenic carotenoid phaneroxanthin. Recombinant CRTISO5 converted phaneroxanthin into fucoxanthin in vitro by hydrating its carbon–carbon triple bond, instead of functioning as an isomerase. Molecular docking and mutational analyses revealed residues essential for this activity. Furthermore, a photophysiological characterization of the crtiso5 mutant revealed a major structural and functional role of fucoxanthin in photosynthetic pigment–protein complexes of diatoms. As CRTISO5 hydrates an internal alkyne physiologically, the enzyme has unique potential for biocatalytic applications. The discovery of CRTISO5 illustrates how neofunctionalization leads to major diversification events in evolution of photosynthetic mechanisms and the prominent brown coloration of most marine photosynthetic eukaryotes.

Biochemistry & Molecular Biology↗
DOE OSTI2021

An investigation of high entropy alloy conductivity using first-principles calculations

The Kubo–Greenwood equation, in combination with the first-principles Korringa–Kohn–Rostoker coherent potential approximation (KKR-CPA) can be used to calculate the DC residual resistivity of random alloys at T = 0 K. We implemented this method in a multiple scattering theory based ab initio package, MuST, and applied it to the ab initio study of the residual resistivity of the high entropy alloy Al x CoCrFeNi as a function of x. The calculated resistivities are compared with experimental data. We also predict the residual resistivity of refractory high entropy alloy MoNbTaV x W. Furthermore, the calculated resistivity trends are also explained using theoretical arguments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These important enzymes are often bimodular, including a catalytic domain and carbohydrate binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relationships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able discriminate GH7 CBHs and EGs with up to 99% accuracy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our ML results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

nf-core/proteinfamilies: a scalable pipeline for the generation of protein families

The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity, and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterized sequences with the few experimentally characterized ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline (nf-core/proteinfamilies) that generates nascent protein families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage scales approximately linearly with input size, and the biological benchmarks showed that the generated protein families closely resemble manually curated families in widely used databases.

Nextflow↗
DOE OSTI2021

Heat transport in liquid water from first-principles and deep neural network simulations

In this work, we compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way that a DNN model, trained on meta-GGA (SCAN) data, reduces the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accelerating self-consistent field iterations in Kohn-Sham density functional theory using a low-rank approximation of the dielectric matrix

We present an efficient preconditioning technique for accelerating the fixed-point iteration in real-space Kohn-Sham density functional theory (DFT) calculations. The preconditioner uses a low-rank approximation of the dielectric matrix (LRDM) based on Gâteaux derivatives of the residual of fixed-point iteration along appropriately chosen direction functions. We develop a computationally efficient method to evaluate these Gâteaux derivatives in conjunction with the Chebyshev filtered subspace iteration procedure, an approach widely used in large-scale Kohn-Sham DFT calculations. Further, we propose a variant of LRDM preconditioner based on adaptive accumulation of low-rank approximations from previous self-consistent field iterations, and also extend the LRDM preconditioner to spin-polarized Kohn-Sham DFT calculations. We demonstrate the robustness and efficiency of the LRDM preconditioner against other widely used preconditioners on a range of benchmark systems with sizes ranging from ~100 to 1100 atoms (~500–20,000 electrons). The benchmark systems include various combinations of metal-insulating-semiconducting heterogeneous material systems, nanoparticles with localized d orbitals near the Fermi energy, nanofilm with metal dopants, and magnetic systems. In all benchmark systems, the LRDM preconditioner converges robustly within 20–30 iterations. In contrast, other widely used preconditioners show slow convergence in many cases, as well as divergence of the fixed-point iteration in some cases. Lastly, we demonstrate the computational efficiency afforded by the LRDM method, with up to 3.4-fold reduction in computational cost for the total ground-state calculation compared to other preconditioners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Hierarchical Self-Assembly of Carbon Dots into High-Aspect-Ratio Nanowires

Here, we report a spontaneous and hierarchical self-assembly mechanism of carbon dots prepared from citric acid and urea into nanowire structures with large aspect ratios (>50). Scattering-type scanning near-field optical microscopy (s-SNOM) with broadly tunable mid-IR excitation was used to interrogate details of the self-assembly process by generating nanoscopic chemical maps of local wire morphology and composition. s-SNOM images capture the evolution of wire formation and the complex interplay between different chemical constituents directing assembly over the nano- to microscopic length scales. We propose that residual citrate promotes tautomerization of melamine surface functionalities to produce supramolecular shape synthons comprised of melamine-cyanurate adducts capable of forming long-range and highly directional hydrogen-bonding networks. This intrinsic, heterogeneity-driven self-assembly mechanism reflects synergistic combinations of high chemical specificity and long-range cooperativity that may be harnessed to reproducibly fabricate functional structures on arbitrary surfaces.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Advances in ionic liquid recycling for lignocellulosic biomass pretreatment

Ionic liquids (ILs) are promising solvents for the pretreatment of lignocellulosic biomass due to their ability to disrupt cellulose, hemicellulose, and lignin structures. However, large-scale implementation requires the development of efficient recovery and recycling methods. This review provides a comprehensive analysis of the recyclability potential of ILs used in biomass pretreatment, emphasizing their mechanisms, recent innovations, and ongoing challenges. We begin by discussing the structural diversity and tunability of ILs, which underlie their effectiveness in biomass deconstruction. The distinct roles of IL anions and cations in dissolving specific biomass components are systematically presented and compared. Advances in IL recycling techniques, including antisolvent precipitation methods, membrane separation, and distillation, are critically examined, with attention to how mechanistic insights can inform the design of more efficient and selective recovery strategies. Despite progress, significant challenges remain to scaling up IL-based biomass processing, including high cost, environmental concerns, and impact of biomass-derived impurities (e.g., lignin residues, sugars, proteins) on IL purity and functionality after reuse. We also review the applicability of different ILs based on life cycle assessments and techno-economic analyses. Lastly, we identify critical research gaps and propose future directions, including the design and development of next-generation ILs with improved recyclability, reduced toxicity, and enhanced economic viability for industrial-scale applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum simulation of bosons with the contracted quantum eigensolver

Abstract Quantum computers are promising tools for simulating many-body quantum systems due to their potential scaling advantage over classical computers. While significant effort has been expended on many-fermion systems, here we simulate a model entangled many-boson system with the contracted quantum eigensolver (CQE). We generalize the CQE to many-boson systems by encoding the bosonic wavefunction on qubits. The CQE provides a compact ansatz for the bosonic wave function whose gradient is proportional to the residual of a contracted Schrödinger equation. We apply the CQE to a bosonic system, where N quantum harmonic oscillators are coupled through a pairwise quadratic repulsion. The model is relevant to the study of coupled vibrations in molecular systems on quantum devices. Results demonstrate the potential efficiency of the CQE in simulating bosonic processes such as molecular vibrations with good accuracy and convergence even in the presence of noise.

Physics↗
DOE OSTI2024

Structural and biochemical characterization of the mitomycin C repair exonuclease MrfB

Mitomycin C (MMC) repair factor A (mrfA) and factor B (mrfB), encode a conserved helicase and exonuclease that repair DNA damage in the soil-dwelling bacterium Bacillus subtilis. Here we have focused on the characterization of MrfB, a DEDDh exonuclease in the DnaQ superfamily. We solved the structure of the exonuclease core of MrfB to a resolution of 2.1 Å, in what appears to be an inactive state. In this conformation, a predicted α-helix containing the catalytic DEDDh residue Asp172 adopts a random coil, which moves Asp172 away from the active site and results in the occupancy of only one of the two catalytic Mg 2+ ions. We propose that MrfB resides in this inactive state until it interacts with DNA to become activated. By comparing our structure to an AlphaFold prediction as well as other DnaQ-family structures, we located residues hypothesized to be important for exonuclease function. Using exonuclease assays we show that MrfB is a Mg 2+ -dependent 3'–5' DNA exonuclease. We show that Leu113 aids in coordinating the 3' end of the DNA substrate, and that a basic loop is important for substrate binding. This work provides insight into the function of a recently discovered bacterial exonuclease important for the repair of MMC-induced DNA adducts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Early Signal of Emerging Nuclear Collectivity in Neutron-Rich 129Sb

Radioactive 129Sb, which can be treated as a proton plus semimagic 128Sn core within the particle-core coupling scheme, was studied by Coulomb excitation. Reduced electric quadrupole transition probabilities, B(E2), for the 2+Ⓧπg7/2 multiplet members and candidate πd5/2 state were measured. The results indicate that the total electric quadrupole strength of 129Sb is a factor of 1.39(11) larger than the 128Sn core, which is in stark contrast to the expectations of the empirically successful particle-core coupling scheme. Shell-model calculations performed with two different sets of nucleon-nucleon interactions suggest that this enhanced collectivity is due to constructive quadrupole coherence in the wave functions stemming from the proton-neutron residual interactions, where adding one nucleon to a core near a double-shell closure can have a pronounced effect. The enhanced electric quadrupole strength is an early signal of the emerging nuclear collectivity that becomes dominant away from the shell closure.

Gray, Tim↗
DOE OSTI2025

Transcription of hepatitis B surface antigen shifts from cccDNA to integrated HBV DNA during treatment

The cornerstone of functional cure for chronic hepatitis B (CHB) is hepatitis B surface antigen (HBsAg) loss from blood. HBsAg is encoded by covalently closed circular DNA (cccDNA) and HBV DNA integrated into the host genome (iDNA). Nucleos(t)ide analogs (NUCs), the mainstay of CHB treatment, rarely lead to HBsAg loss, which we hypothesized was due to continued iDNA transcription despite decreased cccDNA transcription. To test this, we applied a multiplex droplet digital PCR that identifies the dominant source of HBsAg mRNAs to 3,436 single cells from paired liver biopsies obtained from 10 people with CHB and HIV receiving NUCs. With increased NUC duration, cells producing HBsAg mRNAs shifted their transcription from chiefly cccDNA to chiefly iDNA. This shift was due to both a reduction in the number of cccDNA-containing cells and diminished cccDNA-derived transcription per cell; furthermore, it correlated with reduced detection of proteins deriving from cccDNA but not iDNA. Despite this shift in the primary source of HBsAg, rare cells remained with detectable cccDNA-derived transcription, suggesting a source for maintaining the replication cycle. Functional cure must address both iDNA and residual cccDNA transcription. Further research is required to understand the significance of HBsAg when chiefly derived from iDNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Scalable Process for Upcycling Carbon Dioxide (CO 2 ) and Coal Combustion Residues into Construction Products

Anthropogenic sources of carbon dioxide are generated from a number of sources, but the key among these are ordinary Portland cement (OPC) production and combustion of fossil fuels. Cement production is the largest global CO 2 source from the mineral decomposition of carbonates. Combination of the limestone decomposition and thermal requirements of the clinkering process causes cement production to contribute 8-9% of annual global CO 2 emissions. Combustion of fossil fuels (coal, oil and gas) was shown to contribute a much larger portion of global CO 2 emissions. As of 2018, combustion of fossil fuels accounted for 65% of global CO 2 , where 41% was derived from stationary sources for electricity and heat generation and the other 24% was related to transport. To reduce these contributions, key steps forward in CO 2 utilization technologies are required. The purpose of this project is to demonstrate the feasibility of the Reversa process evolving from a TRL-3 technology at the bench-scale up to TRL-6 technology at the pilot-scale. The reliability of the Reversa technology was tested to prove the effective production of concrete masonry units (CMUs) at bench scale, where the units exceeded the required 13.8 MPa compressive strength requirements. The overall goal of this project was to accelerate the development of a CO 2 mineralization process that synergistically utilizes CO 2 in flue gas and coal combustion residues (CCRs) to synthesize carbonated concrete, a functional replacement for traditional concrete. The culmination of this work resulted in 12 successful production runs at the Integrated Test Center (ITC), Gillette, WY using coal flue gas as a CO 2 source. This was followed by 6 production runs which were completed at the National Carbon Capture Center (NCCC), Wilsonville, AL, using coal-fired and natural gas (NG) flue gas as the CO 2 source. Over the course of the production runs at NCCC and ITC, the CO 2 utilization as a function of time, 24-h CO 2 uptake, electricity usage, and 28-d net area compressive strength recorded for each run. The ITC and NCCC demonstrations achieved an average of 0.19 and 0.1 g CO 2 /g reactant, respectively. Both demonstrations exceeded the project’s target goals of uptake > 0.05 g CO 2 /g reactant. Average compressive strength of the ITC blocks was 18.24 MPa at 28-days. This exceeded the target strength of 13.8 MPa specified by ASTM C90. ITC and NCCC produced an average CO 2 utilization efficiency of 74.9 and 57.9%, respectively. Both demonstration averages were within the target range of 50 to 90% utilization efficiency. For some production runs the NCCC demo did exceeded the a CO 2 utilization efficiency of 75%. An LCA of the Reversa process compared to an industry standard product revealed a net CO 2 reduction of 39% to 42%. This exceeded the target requirement of >25% net CO 2 reduction. Collection of this data was used to determine that the project was successful as the demonstration goals were achieved: (1) achieving in excess of 75% CO 2 utilization efficiency, (2) utilizing greater than 250 kg of CO 2 per production batch/run, and (3) ensuring compliance of carbonated blocks with industry standard specifications (ASTM C90).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Proton Dynamics Scenarios in the Integrable Optics Test Accelerator (IOTA) at Fermilab

The Integrable Optics Test Accelerator (IOTA) at Fermilab provides a versatile platform for studying the interplay of space-charge, impedance, and non-linear optics in high-intensity hadron beams within synchrotrons and storage rings. This report examines the parameters and dynamics of 2.5~MeV proton beam operations in two configurations of the bare IOTA lattice: one for demonstrating Non-linear Integrable Optics with the Danilov-Nagaitsev magnet, and the other for use with electron cooling. We offer order-of-magnitude estimates of the transverse emittance growth rate as a function of beam intensity, highlighting contributions from residual gas scattering, intra-beam scattering, and space-charge effects. Under nominal conditions, the beam lifetime is projected to be less than 7~minutes at low intensity with the current vacuum quality, and fewer than 100,000~turns at high intensity due to strong space-charge effects. The calculations presented here will guide strategies to mitigate emittance growth and inform future IOTA experiments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Unexpected “Spontaneous” Evolution of Catalytic, MOF-Supported Single Cu(II) Cations to Catalytic, MOF-Supported Cu(0) Nanoparticles

A desirable feature of metal–organic frameworks (MOFs) is their well-defined structural periodicity and the presence of well-defined catalyst grafting sites (e.g., reactive –OH and –OH 2 groups) that can support single-site heterogeneous catalysts. However, one should not overlook the potential role of residual organic moieties, specifically formate ions that can occupy the catalyst anchoring sites during MOF synthesis. Here we show how these residual formate species in a Zr-based MOF, NU-1000, critically alter the structure, redox capability, and catalytic activity of postsynthetically incorporated Cu(II) ions. Single-crystal X-ray diffraction measurements established that there are two structurally distinct types of Cu(II) ions in NU-1000: one type with residual formate and one without. In NU-1000 with formate, Cu(II) solely binds to the node via the formate-unoccupied, bridging μ 3 –OH, whereas in the formate-free case, it displaces protons from two node hydroxo ligands and resides close to the terminal –OH 2 . Under an inert atmosphere, node-bound formate facilitates the unanticipated reduction of isolated Cu(II) to nanoparticulate Cu(0)—a behavior which is essentially absent in the formate-free analogue because no other sacrificial reductant is present. When the two MOFs were tested as benzyl alcohol oxidation catalysts, we observed that residual formate boosts the catalytic turnover frequency. Density functional calculations showed that node-bound formate acts as a sacrificial two-electron donor and assists in reducing Cu(II) to Cu(0) by a nonradical pathway. The negative Gibbs free energy of reaction (ΔG) and enthalpy of reaction (ΔH) indicate that the reduction is thermodynamically favorable. Here, the work presented here highlights how the often-neglected residual formate prevalent in nearly all zirconium-based MOFs can significantly modulate the properties of supported catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural insights reveal interplay between LAG-3 homodimerization, ligand binding, and function

Lymphocyte activation gene-3 (LAG-3) is an inhibitory receptor expressed on activated T cells and an emerging immunotherapy target. Domain 1 (D1) of LAG-3, which has been purported to directly interact with major histocompatibility complex class II (MHCII) and fibrinogen-like protein 1 (FGL1), has been the major focus for the development of therapeutic antibodies that inhibit LAG-3 receptor-ligand interactions and restore T cell function. Here, we present a high-resolution structure of glycosylated mouse LAG-3 ectodomain, identifying that cis-homodimerization, mediated through a network of hydrophobic residues within domain 2 (D2), is critically required for LAG-3 function. Additionally, we found a previously unidentified key protein-glycan interaction in the dimer interface that affects the spatial orientation of the neighboring D1 domain. Mutation of LAG-3 D2 residues reduced dimer formation, dramatically abolished LAG-3 binding to both MHCII and FGL1 ligands, and consequentially inhibited the role of LAG-3 in suppressing T cell responses. Intriguingly, we showed that antibodies directed against D1, D2, and D3 domains are all capable of blocking LAG-3 dimer formation and MHCII and FGL-1 ligand binding, suggesting a potential allosteric model of LAG-3 function tightly regulated by dimerization. Furthermore, our work reveals unique epitopes, in addition to D1, that can be targeted for immunotherapy of cancer and other human diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning

Residual-based adaptive strategies are widely used in scientific machine learning yet remain largely heuristic. We introduce a variational framework that formalizes these methods through convex transformations of the residual, where different transformations correspond to distinct objective functionals. For instance, exponential weights target uniform error minimization, while linear weights recover quadratic error minimization. This perspective reveals adaptive weighting as a means of selecting sampling distributions that optimize a primal objective, directly linking discretization choices to error metrics. This principled approach yields three key benefits: it enables systematic design of adaptive schemes, reduces discretization error by lowering estimator variance, and enhances learning dynamics by improving gradient signal-to-noise ratio. Extending the framework to operator learning, we demonstrate substantial performance gains across diverse optimizers and architectures. Our results provide a theoretical perspective for residual-based adaptivity and establish a foundation for principled discretization and training.

97 MATHEMATICS AND COMPUTING↗