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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A record high average ZT over a wide temperature range in a Single-layer Sb 2 Si 2 Te 6

Conversion of waste heat into usable energy requires development of thermoelectric materials with high efficiency in a wide temperature range. Here, using first principles theory and Boltzmann transport theory, we show that the thermoelectric performance of the p-type single-layer Sb 2 Si 2 Te 6 has a high figure of merit ZT of 2.62 at 900 K and a record high average ZT of ~1.93 (corresponding the conversion efficiency of ~23.2%) in the temperature range of 300-900 K. These values are significantly higher than the recently measured average ZT of ~0.57 in the temperature range of 310–823 K [Luo et al., Joule 4, 159–175 (2020)] in layered bulk Sb 2 Si 2 Te 6 . We attribute the large enhancement of ZT in the single layer material to the increase in the thermoelectric power factor resulting from the complex Fermi surface. Our work reveals the great potential of a single-layer Sb 2 Si 2 Te 6 for wide-temperature-range thermoelectric applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗
DOE OSTI2025

A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System

The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.

09 - BIOMASS FUELS↗
DOE OSTI2026

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Photoluminescence and Raman spectroscopy of wide bandgap semiconductors damaged by deep-UV laser irradiation

The effects of a pulsed, focused, deep-UV (4.66 eV) laser on wide and ultra-wide bandgap semiconductors were investigated with photoluminescence (PL) and Raman spectroscopy. Three semiconductor single crystals were studied: silicon carbide (6H-SiC), gallium nitride (GaN), and gallium oxide (β-Ga 2 O 3 ). Atomic emission lines from neutral Ga or Si were observed during the laser-damage process. For all three semiconductors, PL mapping (3.49 eV laser excitation) of the damaged material revealed visible emission bands in the 2.6–2.8 eV range, attributed to point defects. Raman spectra (2.33 eV excitation) showed a reduction in the Raman peak intensities in the damaged region, along with weak PL bands around 1.9–2.1 eV.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Automated Process Planning for Embossing and Functionally Grading Materials via Site-Specific Control in Large-Format Metal-Based Additive Manufacturing

The potential for site-specific, process-parameter control is an attribute of additive manufacturing (AM) that makes it highly attractive as a manufacturing process. The research interest in the functionally grading material properties of numerous AM processes has been high for years. However, one of the issues that slows developmental progress in this area is process planning. It is not uncommon for manual programming methods and bespoke solutions to be utilized for site-specific control efforts. This article presents the development of slicing software that contains a fully automated process planning approach for enabling through-thickness, process-parameter control for a range of AM processes. The technique includes the use of parent and child geometries for controlling the locations of site-specific parameters, which are overlayed onto unmodified toolpaths, i.e., a vector-based planning approach is used in which additional information, such as melt pool size for large-scale metal AM processes, is assigned to the vectors. This technique has the potential for macro- and micro-structural modifications to printed objects. A proof-of-principle experiment is highlighted in which this technique was used to generate dynamic bead geometries that were deposited to induce a novel surface embossing effect, and additional software examples are presented that highlight software support for more complex objects.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Chemical Profiles of the Oxides on Tantalum in State of the Art Superconducting Circuits

Abstract Over the past decades, superconducting qubits have emerged as one of the leading hardware platforms for realizing a quantum processor. Consequently, researchers have made significant effort to understand the loss channels that limit the coherence times of superconducting qubits. A major source of loss has been attributed to two level systems that are present at the material interfaces. It is recently shown that replacing the metal in the capacitor of a transmon with tantalum yields record relaxation and coherence times for superconducting qubits, motivating a detailed study of the tantalum surface. In this work, the chemical profile of the surface of tantalum films grown on c‐plane sapphire using variable energy X‐ray photoelectron spectroscopy (VEXPS) is studied. The different oxidation states of tantalum that are present in the native oxide resulting from exposure to air are identified, and their distribution through the depth of the film is measured. Furthermore, it is shown how the volume and depth distribution of these tantalum oxidation states can be altered by various chemical treatments. Correlating these measurements with detailed measurements of quantum devices may elucidate the underlying microscopic sources of loss.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strain–Chemical Gradient and Polarization in Metal Halide Perovskites

Metal halide perovskites (MHPs) have attracted broad research interest due to their outstanding optoelectronic performance. This performance has been attributed in part to the presence of polarization in these materials. However, the precise effects of chemical environment and strain condition on the polar states in MHPs have largely been missing. Herein it is revealed for the first time that chemical gradient is directly coupled with strain gradient in CH 3 NH 3 PbI 3 . This strain–chemical gradient induces an electric polarization that can potentially affect charge carrier dynamics. Furthermore, it is unveiled that this electric polarization—unlike ferroelectricity that only exists in noncentrosymmetric materials—can be present in both tetragonal and cubic phases of CH 3 NH 3 PbI 3 . This suggests that the strain–chemical gradient induced polarization is a more convincing explanation of the outstanding photovoltaic properties of MHPs than the hotly debated ferroelectric polarization. Finally, a mechanism of how this polarization impacts photovoltaic action is proposed, which offers insightful advances in the development of MHPs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Anomalous Magnetoelectric Coupling in the Paramagnetic State of a Chiral and Polar Magnet

Abstract Chiral magnets are excellent platforms for studying intertwined spin, charge, orbit, and lattice degrees of freedom in solid‐state materials. In this work, the anomalous magnetoelectric behavior in a chiral magnet K 2 Co 2 (SO 4 ) 3 is demonstrated using comprehensive experimental probes. This material adopts a P 2 1 3 chiral cubic structure at room temperature. Based on the results of high‐resolution synchrotron X‐ray diffraction, this study shows that the low‐temperature (<130 K) crystal structure is a P 2 1 monoclinic phase, both polar and chiral. Magnetic and thermodynamic measurements reveal highly frustrated magnetic interactions and possible non‐collinear antiferromagnetic ordering at an extremely low temperature ≈0.6 K. Critically, anomalous magnetoelectric correlations are experimentally detected in its paramagnetic temperature regime, which can arise from the synergetic interplay between magnetoelastic and piezoelectric effects. These findings thus indicate that K 2 Co 2 (SO 4 ) 3 is a unique material, displaying multiple emergent structural and magnetic phenomena. This is attributed to both its overall crystallographic symmetry and the fact that its magnetic ions are located at low‐symmetry sites.

Xu, Xianghan↗
DOE OSTI2023

A High Energy–Density, Cobalt–Free, Low–Nickel LiNi 0.7 Mn 0.25 Al 0.05 O 2 Cathode with a High–Voltage Electrolyte for Lithium–Metal Batteries

Cobalt-free cathode materials have garnered increased attention for applications in next-generation batteries for electric vehicles, as cobalt is considered to have at a high supply chain risk. Here, the use of a localized saturated electrolyte (LSE) to enable stable cycling of a cobalt-free, low-nickel layered-oxide cathode LiNi 0.7 Mn 0.25 Al 0.05 O 2 (NMA-70) to higher voltages (4.6 V) in a lithium-metal battery is demonstrated. Compared to the baseline LP57 electrolyte, the LSE extends the cycle life from ≈100 cycles to ≈400 cycles before reaching 80% capacity retention. Visual indicators of cell degradation, such as product deposition, are observed on electrodes cycled in LP57. It is shown that cycling NMA-70 in LSE reduces the overall active material loss and overpotential growth during extended cycling. This is attributed to the formation of a beneficial fluorinated interphase layer, a lower degree of rock-salt phase formation, and a reduction in the gas evolution from the cathode surface. The decrease in gas evolution from the cathode cycled in LSE reflects a lower degree of electrolyte reactivity and an overall improvement in the safety characteristics of the cell. Furthermore, this study highlights the importance of a stable electrolyte to enable the high-voltage cycling of alternative, lower nickel, and cobalt-free cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

An objective inter-comparison of trash mark constellations generated by manual and automated detection methods

Trash marks are unintentional markings observed on printed, scanned, or photocopied documents that result from permanent defects or transient material in office machines and can be used for source attribution of questioned documents. Trash mark examinations have been in use in forensic laboratories for decades, yet the method remains relatively untested and relies on training, experience, and anecdotal information to support its validity. Herein this study generated and harnessed objective data to empirically test one of the foundational theories for assessing the origin of photocopied documents: provided trash marks are present in sufficient quantity and/or quality, no two machines will exhibit a constellation of trash marks that is indistinguishable from another. In this project, objective trash mark location and size data was generated for 50 known photocopiers using both a traditional and a novel, automated method. Inter-machine comparisons were conducted using a novel variant of the Hausdorff distance algorithm to generate a quantitative assessment of how similar or different the 2450 pairs of trash mark constellations were from one another. This study found that each of the machines bearing one or more trash marks exhibited objective differences in their trash mark constellations, ultimately providing support for the tested hypothesis

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Structural, Electronic, and Thermal Properties of CdSnAs 2

Structural, electrical, and thermal properties of CdSnAs 2 , with analyses from temperature-dependent transport properties over a large temperature range, are reported. Phase-pure microcrystalline powders were synthesized that were subsequently densified to a high-density homogeneous polycrystalline specimen for this study. Temperature-dependent transport indicates n-type semiconducting behavior with a very high and nearly temperature independent mobility over the entire measured temperature range, attributed to the very small electron effective mass of this material. The Debye model was successfully applied to model the thermal conductivity and specific heat. Furthermore, this work contributes to the fundamental understanding of this material, providing further insight and allowing for investigations into altering this and related physical properties of these materials for technological applications.

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

Rapid Atomic Ordering Transformation toward Intermetallic Nanoparticles

Chemically ordered intermetallic nanoparticles are promising candidates for energy-related applications such as electrocatalysis. However, the synthesis of intermetallics generally requires long annealing (several hours) to achieve the ordered structure, which causes nanoparticles agglomeration and diminished performance, particularly for catalysis. Herein, we demonstrate a new rapid Joule heating approach that can synthesize highly ordered and well-dispersed intermetallic nanoparticles. As a proof-of-concept, we synthesized fully ordered Pd 3 Pb intermetallic nanoparticles that feature small size distribution (~6 nm). Computational analysis of the L1 2 Pd 3 Pb material suggests that this rapid atomic ordering transformation can be attributed to a vacancy-mediated diffusion mechanism. Moreover, the nanoparticles demonstrate excellent electrocatalytic activity and exceptional stability for the oxygen reduction reaction (ORR), retaining >95% of the current density over 10 h of chronoamperometry test with negligible structural and compositional changes. Furthermore, this study demonstrates a new strategy of providing a new direction for intermetallic synthesis and catalyst discovery.

25 ENERGY STORAGE↗
DOE OSTI2023

Intrinsic Formamidinium Tin Iodide Nanocrystals by Suppressing the Sn(IV) Impurities

The long search for non-toxic alternatives to lead halide perovskites (LHPs) has shown that some compelling properties of LHPs, such as low effective masses of carriers, can only be attained in their closest Sn(II) and Ge(II) analogs, despite their tendency to oxidation. Judicious choice of chemistry allowed formamidinium tin iodide (FASnI 3 ) to reach a power conversion efficiency of 14.81% in photovoltaic devices. This progress motivated us to develop a synthesis of colloidal FASnI 3 NCs with a concentration of Sn(IV) reduced to an insignificant level and probe their intrinsic structural and optical properties. Intrinsic FASnI 3 NCs exhibit unusually low absorption coefficients of 4 x 10 3 cm -1 at the first excitonic transition, a 190 meV increase of the bandgap as compared to the bulk material, and a lack of excitonic resonances. These features are attributed to a highly disordered lattice, distinct from the bulk FASnI 3 as supported by structural characterizations and first-principles calculations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

A Review of Computational Models for the Flow of Milled Biomass Part I: Discrete-Particle Models

Biomass is a renewable and sustainable energy resource. Current design of biomass handling and feeding equipment leverage both experiments and numerical modeling. This paper reviews the state-of-the-art discrete element methods (DEM) for the flow of milled biomass (Part I), accompanied by a comprehensive review on continuum-based computational models (Part II). The present review on DEM is primarily focused on the features and suitability of various particle shape models for different types of milled biomass because particle shape is the predominant attribute controlling the flow behavior of complex-shaped granular material. The general strengths and weaknesses in the applicability of those models for the milled biomass modeling are summarized. In particular, comments are provided to balance the numerical model capabilities and the computational cost for the development of DEM models. To our best knowledge, this is the first-of-its-kind review on DEM specifically for biomass. Our study indicates that the current DEM models require further development, calibration, and validation based on a deep understanding of biomass particle contact mechanics and experimental data support before they can be reliably used for predictive simulations in handling and feeding systems.

42 ENGINEERING↗
DOE OSTI2023

DNA metabarcoding reveals consumption of diverse community of amphibians by invasive wild pigs (Sus scrofa) in the southeastern United States

Abstract Invasive wild pigs ( Sus scrofa ) are one of the most widespread, destructive vertebrate species globally. Their success can largely be attributed to their generalist diets, which are dominated by plant material but also include diverse animal taxa. Wild pigs are demonstrated nest predators of ground-nesting birds and reptiles, and likely pose a threat to amphibians given their extensive overlap in wetland use. DNA metabarcoding of fecal samples from 222 adult wild pigs culled monthly from 2017 to 2018 revealed a diverse diet dominated by plant material, with 166 plant genera from 56 families and 18 vertebrate species identified. Diet composition varied seasonally with availability for plants and was consistent between sexes. Amphibians were the most frequent vertebrate group consumed and represented the majority of vertebrate species detected, suggesting amphibians are potentially vulnerable to predation by wild pigs in our study region. Mammal, reptile, and bird species were also detected in pig diets, but infrequently. Our results highlight the need for research on the impacts of wild pigs on amphibians to better inform management and conservation of imperiled species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The sol–gel autocombustion as a route towards highly CO 2 -selective, active and long-term stable Cu/ZrO 2 methanol steam reforming catalysts

The adaption of the sol-gel autocombustion method to the Cu/ZrO 2 system opens new pathways for the specific optimisation of the activity, long-term stability and CO 2 selectivity of methanol steam reforming (MSR) catalysts. Calcination of the same post-combustion precursor at 400 °C, 600 °C or 800 °C allows accessing Cu/ZrO 2 interfaces of metallic Cu with either amorphous, tetragonal or monoclinic ZrO 2 , influencing the CO 2 selectivity and the MSR activity distinctly different. While the CO 2 selectivity is less affected, the impact of the post-combustion calcination temperature on the Cu and ZrO 2 catalyst morphology is more pronounced. A porous and largely amorphous ZrO 2 structure in the sample, characteristic for sol-gel autocombustion processes, is obtained at 400 °C. This directly translates into superior activity and long-term stability in MSR compared to Cu/tetragonal ZrO 2 and Cu/monoclinic ZrO 2 obtained by calcination at 600 °C and 800 °C. The morphology of the latter Cu/ZrO 2 catalysts consists of much larger, agglomerated and non-porous crystalline particles. Based on aberration-corrected electron microscopy, we attribute the beneficial catalytic properties of the Cu/amorphous ZrO 2 material partially to the enhanced sintering resistance of copper particles provided by the porous support morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Sensor Reduction for Diversion Detection in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors are designed as a smaller, cheaper, and safer alternative to traditional nuclear power plants. Their non-traditional characteristics and prospect of mass production and deployment will likely require new approaches to nuclear safeguards. The primary proliferation concern with microreactors is the diversion of fuel material. Such diversion may produce measurable defects in key physical attributes like neutron flux, which may in turn be detectable using machine learning models. Preliminary work has demonstrated this ability for modeled nominal and diversion scenarios using large quantities of energy integrated neutron flux data. In practice, the number of available sensors for such measurements will be limited and energy integrated flux information will not be available. This work explores the ability of tree-based gradient boosted ensemble models to classify a given microreactor core is nominal or diversion, and determine the number of fuel pins diverted in the case of diversion with reduced numbers of sensors and more realistic detector responses. Classification accuracy of greater than 98% and regression errors as low as 5% of the total number of fuel pins were achieved with as few as 15 sensors, compared to 99% and 4.1% with a maximum of 240 sensors.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗