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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Gradient synthesis of carbon quantum dots and activated carbon from pulp black liquor for photocatalytic hydrogen evolution and supercapacitor

Black liquor (BL) is a by-product of the chemical pulping industry and is mainly used as a low-value fuel; however, its potential to produce high-value products has not been fully exploited. In this study, a green and simple strategy is reported for the gradient production of Na + -functionalized carbon quantum dots (Na + -CQDs) for the first time, N and S co-doped CQDs (N/S-CQDs), and N and S co-doped KOH-activated carbon (N/S-KAC) from BL by dialysis, hydrothermal carbonization and activation-carbonization, respectively. Due to the good electron trapping ability, photoluminescence and promising up-conversion luminescence of CQDs, the hydrogen evolution efficiency of Na + -CQDs/TiO 2 and N/S-CQDs/TiO 2 photocatalysts was improved by 2.45 and 1.46 times, respectively, compared with pure TiO 2 . N/S-KAC with a high specific surface area of 2294 m 2 g -1 provides an excellent specific capacitance of 253 F g -1 at 0.5 A g -1 and a promising energy density of 26.92 Wh kg -1 under a power density of 566 W kg -1 for the fabricated symmetrical supercapacitor. Moreover, the electrode material has good cycling stability with a capacitance retention of ~ 93.91% after 5000 cycles. In conclusion, this pathway provides a versatile and scalable approach for the construction and co-production of nanostructured materials, photocatalysts and energy storage devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A high order Cartesian grid, finite volume method for elliptic interface problems

We present a higher-order finite volume method for solving elliptic PDEs with jump conditions on interfaces embedded in a 2D Cartesian grid. Second, fourth, and sixth order accuracy is demonstrated on a variety of tests including problems with high-contrast and spatially varying coefficients, large discontinuities in the source term, and complex interface geometries. We include a generalized truncation error analysis based on cell-centered Taylor series expansions, which then define stencils in terms of local discrete solution data and geometric information. In the process, we develop a simple method based on Green's theorem for computing exact geometric moments directly from an implicit function definition of the embedded interface. This approach produces stencils with a simple bilinear representation, where spatially-varying coefficients and jump conditions can be easily included and finite volume conservation can be enforced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-throughput identification of novel heat tolerance genes via genome-wide pooled mutant screens in the model green alga Chlamydomonas reinhardtii

Different high temperatures adversely affect crop and algal yields with various responses in photosynthetic cells. The list of genes required for thermotolerance remains elusive. Additionally, it is unclear how carbon source availability affects heat responses in plants and algae. Here, we utilized the insertional, indexed, genome-saturating mutant library of the unicellular, eukaryotic green alga Chlamydomonas reinhardtii to perform genome-wide, quantitative, pooled screens under moderate (35°C) or acute (40°C) high temperatures with or without organic carbon sources. We identified heat-sensitive mutants based on quantitative growth rates and identified putative heat tolerance genes (HTGs). By triangulating HTGs with heat-induced transcripts or proteins in wildtype cultures and MapMan functional annotations, we presented a high/medium-confidence list of 933 Chlamydomonas genes with putative roles in heat tolerance. Triangulated HTGs include those with known thermotolerance roles and novel genes with little or no functional annotation. About 50% of these high-confidence HTGs in Chlamydomonas have orthologs in green lineage organisms, including crop species. Arabidopsis thaliana mutants deficient in the ortholog of a high-confidence Chlamydomonas HTG were also heat sensitive. This work expands our knowledge of heat responses in photosynthetic cells and provides engineering targets to improve thermotolerance in algae and crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Phosphonate functionalized magnetic mesoporous silica for rare earth element recovery from citrate assisted solid waste extracts

The growing high demand of rare earth elements (REEs) has prompted extensive research on REE recovery from waste streams. This study reports the synthesis and evaluation of phosphonate-functionalized magnetic mesoporous silica (MMS-PP) for REE recovery from the acidic extracts of solid wastes. MMS-PP was synthesized using surfactant template and post-synthesis methods, and tested using simulated and real extraction solutions from citrate-assisted REE extracts from municipal solid waste incineration (MSWI) ash. The organic-inorganic hybrid MMS-PP was evaluated for La recovery from 50 mM simulated citrate extract, with the adsorption capacity of 13.5 mg/g compared to ∼2.5 mg/g for non-functionalized MMS. The MMS-PP material exhibited fast adsorption within 10 min, good La selectivity against competing Na + and Ca 2+ , moderate selectivity against Al 3+ and Fe 3+ , high recyclability over multiple adsorption-desorption cycles, and equivalent efficiency for La, Ce, Nd, and Y recovery. Furthermore, the MMS-PP material also demonstrated 70–95% REE recovery from real citrate extracts of MSWI ash, and the spent MMS-PP material can be regenerated and reused for multiple cycles. Functionalized mesoporous materials in combination with organic-ligand assisted extraction can potentially provide a green, effective, and tunable solid-liquid separation platform for REE recovery from complex solid waste streams.

REE recovery↗
DOE OSTI2022

Spin relaxation rate for heavy quarks in weakly coupled QCD plasma

We compute the relaxation rate of the spin density of heavy quarks in a perturbative QCD plasma to leading-log order in the coupling constant g. The spin relaxation rate Γ s in spin hydrodynamics is shown to be Γ s ~ g 4 log(1/g)T(T/M) 2 in the heavy-quark limit T/M $\ll$ 1, which is smaller than the relaxation rate of other non- hydrodynamic modes by additional powers of T/M. We demonstrate three different methods to evaluate the spin relaxation rate: 1) the Green-Kubo formula in the spin hydrodynamic regime, 2) the spin density correlation function in the strict hydrodynamic limit, and 3) quantum kinetic theory of the spin distribution function in momentum space. We highlight the interesting differences between these methods, while they are ultimately connected to each other by the underlying Ward-Takahashi identity for the non-conserved spin density.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A New Approach to Monitoring Solvent Extraction Processes for the Nuclear Industry

As part of an initiative to steward research, development, and innovation into the nuclear fuel cycle, Idaho National Laboratory is building the Beartooth testbed. Beartooth will include a cascade of centrifugal contactors, glove box lines, solidification, and dissolution equipment to aid in the progression of novel separation techniques and provide hands-on opportunities to early-career separation scientists. Beartooth will incorporate novel monitoring techniques using sensors and machine learning algorithms to inform a process operator of separation conditions. This research is examining monitoring technologies not typically used in nuclear separation processes such as acoustic microphones, accelerometers, infrared cameras, red-green-blue color sensors, among others. These sensors are being examined for their functionality within a separation process and their ability to detect applicable signals. Machine learning methods are being developed to determine their utility in detecting faults and alerting operators of expected and unexpected events. These methods have the potential to impact Safeguards by Design efforts and real-time decision making. This overview will detail preliminary results from acoustic, vibration, and color sensors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Function and Evolution of the Plant MES Family of Methylesterases

Land plant evolution has been marked by numerous genetic innovations, including novel catalytic reactions. Plants produce various carboxyl methyl esters using carboxylic acids as substrates, both of which are involved in diverse biological processes. The biosynthesis of methyl esters is catalyzed by SABATH methyltransferases, and understanding of this family has broadened in recent years. Meanwhile, the enzymes catalyzing demethylation—known as methylesterases (MESs)—have received less attention. Here, we present a comprehensive review of the plant MES family, focusing on known biochemical and biological functions, and evolution in the plant kingdom. Thirty-two MES genes have been biochemically characterized, with substrates including methyl esters of plant hormones and several other specialized metabolites. One characterized member demonstrates non-esterase activity, indicating functional diversity in this family. MES genes regulate biological processes, including biotic and abiotic defense, as well as germination and root development. While MES genes are absent in green algae, they are ubiquitous among the land plants analyzed. Extant MES genes belong to three groups of deep origin, implying ancient gene duplication and functional divergence. Two of these groups have yet to have any characterized members. Much remains to be uncovered about the enzymatic functions, biological roles, and evolution of the MES family.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Deep Green Unannotated Protein Structures

The Deep Green list is based on the identification and curation of conserved unannotated proteins in three green lineage (Viridiplantae) model organisms; Arabidopsis thaliana, Chlamydomonas reinhardtii, and Setaria viridis. Preliminary characterization of Deep Green proteins and genes was done using various informatics tools and published data sets and is presented in Knoshaug, Sun, et al., 2023, submitted. The structures of these unannotated proteins were also predicted using AlphaFold (Jumper et al., 2021). The data deposited here are the AlphaFold structural predictions having the highest pLDDT score and thus identified as the best folded structure (ranked_0). These data enable others to do in-depth structural characterizations to aid in functional characterization leading to deeper understanding of plant biology. References: Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S. A. A., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., Back, T., Petersen, S., Reiman, D., Clancy, E., Zielinski, M., Steinegger, M., Pacholska, M., Berghammer, T., Bodenstein, S., Silver, D., Vinyals, O., Senior, A. W., Kavukcuoglu, K., Kohli, P. and Hassabis, D. (2021) Highly accurate protein structure prediction with AlphaFold. Nature, 596:583-589. Knoshaug, E. P., Sun, P., Nag, A., Nguyen, H., Mattoon, E. M., Zhang, N., Liu, J., Chen, C., Cheng, J., Zhang, R., St. John, P., and Umen, J. (submitted) Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii, Arabidopsis thaliana, and Setaria viridis.

09 BIOMASS FUELS↗
DOE OSTI2023

Direct selection of functional fluorescent-protein antibody fusions by yeast display

Antibodies are important reagents for research, diagnostics, and therapeutics. Many examples of chimeric proteins combining the specific target recognition of antibodies with complementing functionalities such as fluorescence, toxicity or enzymatic activity have been described. However, antibodies selected solely on the basis of their binding specificities are not necessarily ideal candidates for the construction of chimeras. Here, we describe a high throughput method based on yeast display to directly select antibodies most suitable for conversion to fluorescent chimera. A library of scFv binders was converted to a fluorescent chimeric form, by cloning thermal green protein into the linker between VH and VL, and directly selecting for both binding and fluorescent functionality. This allowed us to directly identify antibodies functional in the single chain TGP format, that manifest higher protein expression, easier protein purification, and one-step binding assays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spectroscopic Characterization of Mn 1+ Low Oxidation State in Prussian Blue-Based Battery Anodes

Stabilization of ions in exotic oxidation states is beneficial for the development of new materials for green energy technologies. Exotic Mn 1+ was proposed to play a role in the function of sodium-based Prussian blue analogues (PBA) batteries, a highly sought-out technology for industrial energy storage. Here, we report the detailed electronic structure characterization of uncharged and charged sodium-based manganese hexacyanomanganate anodes via Mn K-edge X-ray absorption spectroscopy (XAS), Kβ nonresonant X-ray emission (XES), and resonant inelastic X-ray scattering (RIXS). The latter allowed us to obtain site-selective XANES information about two distinct Mn centers. The obtained spectroscopic data represent the first electronic structure characterization of low-spin Mn 1+ using hard X-ray RIXS and XES and allowed us to confirm its role in anode reduction. In conclusion, our experimental approach can be expanded to analysis of analogues with other 3d transition metals broadening the application of exotic ionic states in materials engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Observed Temperature and Moisture Advection Characteristics in the Southern Great Plains

Until recently, advection profiles in the planetary boundary layer have been difficult to quantify from observations. As a result, not much is known about its basic characteristics, like magnitude and diurnal cycles, or how these differ as a function of large-scale environments. Here, to provide insight into advective characteristics, a Green’s Theorem–based method for calculating profiles of advection in the lowest 3 km from an array of ground-based thermodynamic and kinematic profiling instruments has been applied to 2 years of observations from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observing site. Since advection largely depends on synoptic-scale forcing, a self-organizing map (SOM) was used to classify days based on mean sea level pressure analyses; from that, the diurnal evolution of vertical profiles of advection for different synoptic environments was quantified. The overall mean magnitude of the potential temperature advection is approximately ±3 K h −1 , while the moisture advection is approximately ±1.5 g kg −1 h −1 , with substantial variability in the sign and magnitude of the advective tendencies at different heights and throughout the diurnal cycle. Advection magnitude is strongly connected to the strength of synoptic-scale forcing, which varies depending on the time of year. Variability in advection is larger for potential temperature than it is for moisture, and strongly forced environments, like midlatitude cyclones, feature greater variability in the advection magnitude than weakly forced or quiescent environments.

advection↗
DOE OSTI2022

3D printing of void-free glass monoliths: rheological and geometric considerations

Direct ink writing (DIW) is a versatile additive manufacturing technique capable of printing 3D architectures from a broad range of materials. The key advantage of DIW is the ability to spatially control both the architecture and the composition of the printed part, which enables the production of components with previously unachievable combinations of functionalities. One emergent application space for DIW has been in additively manufactured glass optics, where a “green body” is patterned layer-by-layer by extruding a silica-based slurry through a microfluidic nozzle and then thermally consolidated to transparent glass. A critical aspect of the process is ensuring that the printed part is completely free of voids that can occur in the interstitial spaces between the extruded filaments. This outcome is governed by the interplay between ink rheology and strains imposed by the printing process and geometric packing of the filaments. Here, we explore the strain- and rate-dependent deformation events in the DIW process to determine conditions that enable the printing of void-free monoliths without sacrificing shape fidelity. We focus on yield stress fluids consisting of fumed silica nanoparticles dispersed in organic solvents at varied volume fractions to control the rheological properties. We investigate the printability of these ink materials as a function of print process variables and devise the appropriate dimensionless parameters that capture the geometry-dependent and rate-dependent effects on the deformation of the extruded ink. Lastly, we use these scaling arguments to construct a phase diagram for void-free monolith printability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Catalytic conversion of high S-lignin to a sustainable tri-epoxide polymer precursor

More than 40 million tons of thermosetting plastics are produced annually and 70% of those are epoxy polymers. The synthesis of bio-based epoxide provides a pathway for making renewable thermoset plastics. We describe in this study the use of a genetically modified high-S poplar lignin to produce 4-propyl-2,6-dimethoxyphenol (DMPP), which is converted to the tri-functional compound propylpyrogallol (DMPPO) by a reaction catalysed by N 2 O 5 in the green solvent water. The resulting DMPPO can be converted to a novel tri-epoxide by reaction with epichlorohydrin. Native high-S lignin as well as several organosolv lignins extracted from this poplar biomass were investigated as feedstocks. Notably, direct reductive catalytic fractionation (RCF) of the high-S poplar wood over Pd–Zn/C catalyst with Pd : Zn ratio 1 : 10 at 225 °C under 35 bar H 2 in methanol gave the highest yield of biophenol monomers from the lignin present, the major product being DMPP. Under optimized conditions, conversion of DMPP to DMPPO over the Nb 2 O 5 was nearly quantitative (96% yield), and this conversion could be made without extensive prior purification of the DMPP. The Nb 2 O 5 catalyst could be recycled several times before significant deactivation. This sequence of two catalytic reactions demonstrates that the production of epoxides from lignin-derived DMPPO is a realistic strategy for making renewable polymer building blocks from biomass.

09 BIOMASS FUELS↗
DOE OSTI2025

Steric Modulation of Protein‐Mediated Nanoparticle Assembly: Controlling Cluster Size, Polydispersity, and FRET Responses by Rebalancing Short‐ and Long‐Range Interactions

Understanding and manipulating protein-nanoparticle interactions is of broad interest to fields ranging from nanomedicine to the biological fabrication of functional hierarchical materials. This study investigates how steric forces introduced by a pegylated derivative of superfolder green fluorescent protein (sfGFP) that is monofunctional for silica binding modulate the delicate interplay of long-range (electrostatic and van der Waals) and short-range (protein-mediated) interactions in pH-responsive silica nanoparticle (SiNP) assembly by bifunctional silica-binding sfGFP. Increasing the length of the PEG segment and pre-incubating SiNPs with increasing concentrations of pegylated proteins enables precise control over cluster size within the 800–1450 nm range with a sixfold decrease in polydispersity index to a remarkable 0.1 endpoint. Weakening short-range attractive interactions via mutagenesis extends this control to clusters in the 50–250 nm range and reveals that the Förster resonance energy transfer (FRET) efficiency of clusters scales linearly with cluster diameter below 230 nm but increases only by 15% as clusters grow to 1450 nm. Furthermore, these findings enable the development of a system that provides an optical readout to dynamic changes in solution conditions enacted by a combination of pH adjustment and ion charge screening.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Shape- and Orientation-Dependent Scattering of Isolated Gold Nanostructures Using Polarized Dark-Field Microscopy

In this work, we demonstrate a simple and robust method for measuring the shape- and orientation-dependent optical scattering of various plasmonic nanostructures adsorbed onto a solid surface using polarized dark-field microscopy. By analyzing the dark-field scattering images of gold nanostructures using grazing incidence polarized light with a bench-top microscope, we are able to correlate optical scattering from the individual nanostructures with their shape and orientation. Depending on the size, shape, and orientation of the plasmonic nanostructures, they exhibit characteristic angle- and polarization-dependent scattering signals. Extracting the red, green, and blue channels of the scattering signals from a color-imaging detector as a function of azimuthal angle provides a polar plot of color intensity values that is characteristic of the underlying nanostructure. Examples are presented for various nanostructures, including spherical nanoparticles, nanotriangles, and nanorods. Experimental results are complemented by numerical calculations of the scattering spectra of representative model nanostructures. We demonstrate that the polarization- and orientation-dependent scattering behavior is a consequence of various localized surface plasmon modes existing in the nanostructures and can be used to verify the shape of individual objects as well as quickly identify the orientation of numerous objects on a densely populated substrate. We anticipate that this method will provide a rapid and efficient complement to the typical structural analysis of nanoparticles that is achieved by electron microscopy as well as providing a simple method for generating detailed information of the optical scattering of various types of individual plasmonic nanostructures.

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

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Role of defects in ultra-high gain in fast planar tin gallium oxide UV-C photodetector by MBE

Here we report ultra-high responsivity of epitaxial (Sn x Ga 1–x ) 2 O 3 (TGO) Schottky UV-C photodetectors and experimentally identified the source of gain as deep-level defects, supported by first principles calculations. Epitaxial TGO films were grown by plasma-assisted molecular beam epitaxy on (–201) oriented n-type β-Ga 2 O 3 substrates. Fabricated vertical Schottky devices exhibited peak responsivities as high as 3.5 ×10 4 A/W at –5 V applied bias under 250 nm illumination with sharp cutoff shorter than 280 nm and fast rise/fall time in milliseconds order. Hyperspectral imaging cathodoluminescence (CL) spectra were examined to find the mid-bandgap defects, the source of this high gain. Irrespective of different tin mole fractions, the TGO epilayer exhibited extra CL peaks at the green band (~2.20 eV) not seen in β-Ga 2 O 3 along with enhancement of the blue emission-band (~2.64 eV) and suppression of the UV emission-band. Based on hybrid functional calculations of the optical emission expected for defects involving Sn in β-Ga 2 O 3 , V Ga –Sn complexes are proposed as potential defect origins of the observed green and blue emission-bands. Such complexes behave as acceptors that can efficiently trap photogenerated holes and are predicted to be predominantly responsible for the ultra-high photoconductive gain in the Sn-alloyed Ga 2 O 3 devices by means of thermionic emission and electron tunneling. Regenerating the V Ga –Sn defect complexes by optimizing the growth techniques, we have demonstrated a planar Schottky UV-C photodetector of the highest peak responsivity.

36 MATERIALS SCIENCE↗