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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing the Mechanism of Selective Phosphate Adsorption from Wastewater Using Aqueous and Synchrotron X-ray Characterization

Ion exchange shows promise for recovering phosphate from wastewater as value-added products, but requires high phosphate selectivity to compete with conventional treatment. Hybrid anion exchange (HAIX) resins, which contain non-selective basic functional groups and selective iron oxide nanoparticles (FeOnp), can effectively remove phosphate from wastewater. However, knowledge gaps remain regarding the mechanisms of phosphate selectivity and influence of competing ions, hindering needed efforts to model adsorption dynamics and design scalable adsorption processes for varying wastewaters. To address these gaps, we integrated aqueous-phase adsorption analysis with solid-phase, synchrotron-based X-ray characterization; this integration facilitated elucidation of the distribution and speciation of iron, phosphate, and competing anions on HAIX resins. We compared a quaternary ammonium-functionalized HAIX resin (SBA) to a tertiary amine version (WBA) to determine the role of functional groups. X-ray radiography revealed differences in FeOnp speciation (goethite vs. ferrihydrite) and distribution (peripheral vs. homogeneous) between the resins, resulting in varied phosphate affinity and intraparticle diffusion resistance. Using micro-X-ray fluorescence (μ-XRF) and micro-X-ray absorption near-edge structure (μ-XANES) spectroscopy, we identified differences in where and how phosphate binds across resin types and wastewaters. Across wastewater compositions, FeOnp sites in WBA contribute more to phosphate adsorption than in SBA, possibly due to variations in Fe distribution and speciation. Phosphate adsorption densities calculated from quantitative μ-XRF maps matched those from aqueous analysis, demonstrating the effectiveness of this integrated approach. Altogether, results demonstrate the use of synchrotron-based X-ray characterization for investigating adsorption mechanisms and advance HAIX as a phosphate recovery technology from complex wastewaters.

Nutrient recovery↗
DOE OSTI2019

The dependence of radius on relative humidity and solute mass at high relative humidities up to and including 100%

This manuscript presents a rigorous examination of the equilibrium radius ratio of hygroscopic aerosol particles that are solution drops of ideal and actual inorganic solutes for a range of solute masses in the relative humidity range 99-100%. Analysis is presented first for ideal solutes over a range of solute masses for different hygroscopicities, providing a theoretical framework for the subsequent analysis of actual solutes. Dimensionless quantities are used to reduce the Kohler equation to one with no free parameters and an approximate solution is presented. Next analysis is presented for three common inorganic solutes of atmospheric importance: sodium chloride, ammonium sulfate, and sulfuric acid, with a range of solute masses considered for each substance. The extent to which non-ideality is important for these solutes over the ranges of relative humidities and solute masses considered is examined. A simple but accurate single-parameter expression is presented for the equilibrium radius ratio as a function of relative humidity that contains the dependenceso on solute mass and composition for these solutes. The accuracy of this expression is quantified and factors that limit this accuracy are discussed. The expression is accurate to within 5% over most of the range of mass-equivalent dry radii from 10 to 250 nm and relative humidities from below 99 up to 100%, over which the equilibrium radius ratio varies by more than a factor of five, and it remains finite at 100% relative humidity. Lastly, measurements of hygroscopic growth of aerosol particles in this relative humidity range are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Nanoscale membranes that chemically isolate and electronically wire up the abiotic/biotic interface

Abstract By electrochemically coupling microbial and abiotic catalysts, bioelectrochemical systems such as microbial electrolysis cells and microbial electrosynthesis systems synthesize energy-rich chemicals from energy-poor precursors with unmatched efficiency. However, to circumvent chemical incompatibilities between the microbial cells and inorganic materials that result in toxicity, corrosion, fouling, and efficiency-degrading cross-reactions between oxidation and reduction environments, bioelectrochemical systems physically separate the microbial and inorganic catalysts by macroscopic distances, thus introducing ohmic losses, rendering these systems impractical at scale. Here we electrochemically couple an inorganic catalyst, a SnO 2 anode, with a microbial catalyst, Shewanella oneidensis , via a 2-nm-thick silica membrane containing -CN and -NO 2 functionalized p -oligo(phenylene vinylene) molecular wires. This membrane enables electron flow at 0.51 μA cm −2 from microbial catalysts to the inorganic anode, while blocking small molecule transport. Thus the modular architecture avoids chemical incompatibilities without ohmic losses and introduces an immense design space for scale up of bioelectrochemical systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A flexible and scalable scheme for mixing computed formation energies from different levels of theory

Abstract Computational materials discovery efforts are enabled by large databases of properties derived from high-throughput density functional theory (DFT), which now contain millions of calculations at the generalized gradient approximation (GGA) level of theory. It is now feasible to carry out high-throughput calculations using more accurate methods, such as meta-GGA DFT; however recomputing an entire database with a higher-fidelity method would not effectively leverage the enormous investment of computational resources embodied in existing (GGA) calculations. Instead, we propose here a general procedure by which higher-fidelity, low-coverage calculations (e.g., meta-GGA calculations for selected chemical systems) can be combined with lower-fidelity, high-coverage calculations (e.g., an existing database of GGA calculations) in a robust and scalable manner. We then use legacy PBE(+ U ) GGA calculations and new r 2 SCAN meta-GGA calculations from the Materials Project database to demonstrate that our scheme improves solid and aqueous phase stability predictions, and discuss practical considerations for its implementation.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Insight into different environmental niches adaptation and allergenicity from the Cladosporium sphaerospermum genome, a common human allergy-eliciting Dothideomycetes

Cladosporium sphaerospermum, a dematiaceous saprophytic fungus commonly found in diverse environments, has been reported to cause allergy and other occasional diseases in humans. However, its basic biology and genetic information are largely unexplored. A clinical isolate C. sphaerospermum genome, UM 843, was re-sequenced and combined with previously generated sequences to form a model 26.89 Mb genome containing 9,652 predicted genes. Functional annotation on predicted genes suggests the ability of this fungus to degrade carbohydrate and protein complexes. Several putative peptidases responsible for lung tissue hydrolysis were identified. These genes shared high similarity with the Aspergillus peptidases. The UM 843 genome encodes a wide array of proteins involved in the biosynthesis of melanin, siderophores, cladosins and survival in high salinity environment. In addition, a total of 28 genes were predicted to be associated with allergy. Orthologous gene analysis together with 22 other Dothideomycetes showed genes uniquely present in UM 843 that encode four class 1 hydrophobins which may be allergens specific to Cladosporium. The mRNA of these hydrophobins were detected by RT-PCR. The genomic analysis of UM 843 contributes to the understanding of the biology and allergenicity of this widely-prevalent species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Identification of the Criegee intermediate reaction network in ethylene ozonolysis: Impact on energy conversion strategies and atmospheric chemistry

The reaction network of the simplest Criegee Intermediate (CI) CH2OO has been studied experimentally during the ozonolysis of ethylene. The results provide valuable information about plasma- and ozone-assisted combustion processes and atmospheric aerosol formation. A network of CI reactions was identified, which can be described best by the sequential addition of CI with ethylene, water, formic acid, and other molecules containing hydroxy, aldehyde, and hydroperoxy functional groups. Species resulting from as many as four sequential CI addition reactions were observed, and these species are highly oxygenated oligomers that are known components of secondary organic aerosols in the atmosphere. Insights into these reaction pathways were obtained from a near-atmsopheric pressure jet-stirred reactor coupled to a high-resolution molecular-beam mass spectrometer. The mass spectrometer employs single-photon ionization with synchrotron-generated, tunable vacuum-ultraviolet radiation to minimize fragmentation via near-threshold ionization and to observe mass-selected photoionization efficiency (PIE) curves. Species identification is supported by comparisons of the mass-selected, experimentally observed photo-ionization thresholds with theoretical calculations for the ionization energies. A variety of multi-functional peroxide species are identified, including hydroxymethyl hydroperoxide (HOCH2OOH), hydroperoxymethyl formate (HOOCH2OCHO), methoxymethyl hydroperoxide (CH3OCH2OOH), ethoxymethyl hydroperoxide (C2H5OCH2OOH), 2-hydroxyethyl hydroperoxide (HOC2H4OOH), dihydroperoxy methane (HOOCH2OOH), and 1-hydroperoxypropan-2-one [CH3C(=O)CH2OOH]. A semi-quantitative analysis of the signal intensities as function of successive CI additions and temperature provides mechanistic insights and valuable information for future modeling work of the associated energy conversion processes and atmospheric chemistry. Furthermore this work provides further evidence that the CI is a key intermediate in the formation of oligomeric species via the formation of hydroperoxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A posteriori snapshot location for POD in optimal control of linear parabolic equations

In this paper we study the approximation of an optimal control problem for linear parabolic PDEs with model order reduction based on Proper Orthogonal Decomposition (POD-MOR). POD-MOR is a Galerkin approach where the basis functions are obtained upon information contained in time snapshots of the parabolic PDE related to given input data. In the present work we show that for POD-MOR in optimal control of parabolic equations it is important to have knowledge about the controlled system at the right time instances. We propose to determine the time instances (snapshot locations) by an a posteriori error control concept. The proposed method is based on a reformulation of the optimality system of the underlying optimal control problem as a second order in time and fourth order in space elliptic system which is approximated by a space-time finite element method. Finally, we present numerical tests to illustrate our approach and show the effectiveness of the method in comparison to existing approaches.

Mathematics↗
DOE OSTI2014

Photoluminescence study of the substitution of Cd by Zn during the growth by atomic layer epitaxy of alternate CdSe and ZnSe monolayers

We present a study of the substitution of Cd atoms by Zn atoms during the growth of alternate ZnSe and CdSe compound monolayers (ML) by atomic layer epitaxy (ALE) as a function of substrate temperature. Samples contained two quantum wells (QWs), each one made of alternate CdSe and ZnSe monolayers with total thickness of 12 ML but different growth parameters. The QWs were studied by low temperature photoluminescence (PL) spectroscopy. We show that the Cd content of underlying CdSe layers is affected by the exposure of the quantum well film to the Zn flux during the growth of ZnSe monolayers. The amount of Cd of the quantum well film decreases with higher exposures to the Zn flux. A brief discussion about the difficulties to grow the Zn{sub 0.5}Cd{sub 0.5}Se ordered alloy (CuAu-I type) by ALE is presented.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Atomic orbital-based SOS-MP2 with tensor hypercontraction. I. GPU-based tensor construction and exploiting sparsity

We present a tensor hypercontracted (THC) scaled opposite spin second order Møller-Plesset perturbation theory (SOS-MP2) method. By using THC, we reduce the formal scaling of SOS-MP2 with respect to molecular size from quartic to cubic. We achieve further efficiency by exploiting sparsity in the atomic orbitals and using graphical processing units (GPUs) to accelerate integral construction and matrix multiplication. The practical scaling of GPU-accelerated atomic orbital-based THC-SOS-MP2 calculations is found to be N{sup 2.6} for reference data sets of water clusters and alanine polypeptides containing up to 1600 basis functions. The errors in correlation energy with respect to density-fitting-SOS-MP2 are less than 0.5 kcal/mol for all systems tested (up to 162 atoms).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Pressure-induced suppression of Jahn–Teller distortions and enhanced electronic properties in high-entropy oxide (Mg 0.2 Ni 0.2 Co 0.2 Zn 0.2 Cu 0.2 )O

Jahn–Teller distortions are often observed in Cu II -containing complex oxides resulting in remarkable changes of physical properties. Tuning the Jahn–Teller distortions with pressure has attracted considerable interest but is less studied in Cu II -containing high-entropy oxides (HEOs). We found that pressure can suppress the structural distortions originating from the Jahn–Teller effect of CuO 6 octahedra in the rock salt-type (Mg 0.2 Ni 0.2 Co 0.2 Zn 0.2 Cu 0.2 )O HEO and significantly modify its electronic properties. Synchrotron x-ray diffraction shows that the structural distortions arising from the Jahn–Teller effect of CuO 6 octahedra are progressively suppressed, and the distorted structure evolves into a nearly ideal form under compression. Alternating current impedance and ultraviolet-visible absorption measurements reveal a dramatic resistance drop by more than three orders of magnitude and an obvious bandgap decrease in ~0.1 eV, respectively, accompanied by the pressure-induced suppression of structural distortions. Our study presents a promising route for tuning the structural distortions and the electronic structures of Cu II -containing HEOs for optimizing materials functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scattered-light uniformity imager for diagnosing laser absorption asymmetries on OMEGA

Light scattered from a target is the most-direct measurement for diagnosing laser absorption in a direct-drive implosion. Observations from OMEGA implosions show much larger scattered-light asymmetries than predictions. A new instrument has been developed to absolutely measure the scattered-light intensity and nonuniformity for the purpose of diagnosing the asymmetry. The scattered-light uniformity imager (SLUI) diagnostic records the variation in scattered-light intensity over a transmission diffuser using a charge-coupled device (CCD)/lens assembly. At the standard operating position, an 11.3° (f/2.5) cone of light is collected. A stray light baffle, debris shield, and antireflection absorbing filter are also incorporated into the diagnostic payload inserted into the target chamber. The imaging parts of the diagnostic (light baffle, vacuum window, filters, lens, and CCD camera) are located outside the target chamber. Five SLUIs have been built and deployed in OMEGA’s ten-inch manipulator diagnostic ports, covering almost 5% of the emission surface, enabling an absolute scattered-light measurement should be within a few percent of the global average. Each SLUI system is calibrated offline, providing absolute scattered-light intensity measurements. Based on the measured point spread function, each diffuser plate image contains over 20 000 independent scattered-light absolute-intensity measurements of the variation over the collection cone. SLUI provides a platform to study scattered light and absorption asymmetries, and their possible sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Augmenting subspace optimization methods with linear bandits

In this work, we consider the framework of methods for unconstrained minimization that are, in each iteration, restricted to a model that is only a valid approximation to the objective function on some affine subspace containing an incumbent point. These methods are of practical interest in computational settings where derivative information is either expensive or impossible to obtain. Recent attention has been paid in the literature to employing randomized matrix sketching for generating the affine subspaces within this framework. We consider a relatively straightforward, deterministic augmentation of such a generic subspace optimization method. In particular, we consider a sequential optimization framework where actions consist of one-dimensional linear subspaces and rewards consist of (approximations to) the magnitudes of directional derivatives computed in the direction of the action subspace. Reward maximization in this context is consistent with maximizing lower bounds on descent guaranteed by first-order Taylor models. This sequential optimization problem can be analysed through the lens of dynamic regret. We modify an existing linear upper confidence bound (UCB) bandit method and prove sublinear dynamic regret in the subspace optimization setting. We demonstrate the efficacy of employing this linear UCB method in a setting where forward-mode algorithmic differentiation can provide directional derivatives in arbitrary directions and in a derivative-free setting. For the derivative-free setting, we propose SS-POUNDers, an extension of the derivative-free optimization method POUNDers that employs the linear UCB mechanism to identify promising subspaces. Our numerical experiments suggest a preference, in either computational setting, for employing a linear UCB mechanism within a subspace optimization method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Decoupling limits in multi-sector supergravities

Conventional approaches to cosmology in supergravity assume the existence of multiple sectors that only communicate gravitationally. In principle these sectors decouple in the limit M{sub pl}→∞. In practice such a limit is delicate: for generic supergravities, where sectors are combined by adding their Kähler functions, the separate superpotentials must contain non-vanishing vacuum expectation values supplementing the naïve global superpotential. We show that this requires non-canonical scaling in the naïve supergravity superpotential couplings to recover independent sectors of globally supersymmetric field theory in the decoupling limit M{sub pl} → ∞.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Abstract Motivation Multiple sequence alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Results Here, we implement a smooth and differentiable version of the Smith–Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold2 and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of optimizing predictions of protein sequences with methods that are not fully understood. Availability and implementation Our code and examples are available at: https://github.com/spetti/SMURF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A temperature-sensitive FERONIA mutant allele that alters root hair growth

Abstract In plants, root hairs undergo a highly polarized form of cell expansion called tip-growth, in which cell wall deposition is restricted to the root hair apex. In order to identify essential cellular components that might have been missed in earlier genetic screens, we identified conditional temperature-sensitive (ts) root hair mutants by ethyl methanesulfonate mutagenesis in Arabidopsis thaliana. Here, we describe one of these mutants, feronia-temperature sensitive (fer-ts). Mutant fer-ts seedlings were unaffected at normal temperatures (20°C), but failed to form root hairs at elevated temperatures (30°C). Map based-cloning and whole-genome sequencing revealed that fer-ts resulted from a G41S substitution in the extracellular domain of FERONIA (FER). A functional fluorescent fusion of FER containing the fer-ts mutation localized to plasma membranes, but was subject to enhanced protein turnover at elevated temperatures. While tip-growth was rapidly inhibited by addition of rapid alkalinization factor 1 (RALF1) peptides in both wild-type and fer-ts mutants at normal temperatures, root elongation of fer-ts seedlings was resistant to added RALF1 peptide at elevated temperatures. Additionally, at elevated temperatures fer-ts seedlings displayed altered reactive oxygen species (ROS) accumulation upon auxin treatment and phenocopied constitutive fer mutant responses to a variety of plant hormone treatments. Molecular modeling and sequence comparison with other Catharanthus roseus receptor-like kinase 1L (CrRLK1L) receptor family members revealed that the mutated glycine in fer-ts is highly conserved, but is not located within the recently characterized RALF23 and LORELI-LIKE-GLYCOPROTEIN 2 binding domains, perhaps suggesting that fer-ts phenotypes may not be directly due to loss of binding to RALF1 peptides.

Plant Sciences↗
DOE OSTI2014

Tensor network implementation of bulk entanglement spectrum

Many topologically nontrivial states of matter possess gapless degrees of freedom on the boundary, and when these boundary states delocalize into the bulk, a phase transition occurs, and the system becomes topologically trivial. We show that tensor networks provide a natural framework for analyzing such topological phase transitions in terms of the boundary degrees of freedom which mediate it. To do so, we make use of a correspondence between a topologically nontrivial ground state and its phase transition to a trivial phase established in T. Hsieh and L. Fu (arXiv:1305.1949). This involved computing the bulk entanglement spectrum (BES) of the ground state upon tracing out an extensive subsystem. Here, this work implements BES via tensor network representations of ground states. In this framework, the universality class of the quantum critical entanglement Hamiltonian in d spatial dimensions is either derived analytically or mapped to a classical statistical model in d +1 dimensions, which can be studied using Monte Carlo or tensor renormalization-group methods. As an example, we analytically derive the universality classes of topological phase transitions from the spin-1 chain Haldane phase and demonstrate that the Affleck-Kennedy-Lieb-Tasaki (AKLT) wave function (and its generalizations) remarkably contains critical six-vertex (and, in general, eight-vertex) models within it.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗