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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Beneficial effect of surfactant in adsorption/desorption of lignocellulose-degrading enzymes on/from lignin with different structure

Nonionic surfactant Tween 80 is effective in alleviating the adsorption of lignocellulose-degrading enzymes onto lignin. However, the impacts of lignin structural characteristics on this mitigation effect of Tween 80 were still not clear. Herein, effects of Tween 80 on cellulase and xylanase adsorption on different enzymatic residual lignins (ERLs) and poplar samples were investigated. Besides, effects of Tween 80 on desorption of the two enzyme preparations from different ERLs and poplar samples were also evaluated. By adding Tween 80, the inhibition of ERLs to cellulase hydrolysis was offset and the positive role of Tween 80 in Avicel hydrolysis with presence of ERLs was more effective. Binding strength of cellulase with ERLs was alleviated from 236.0 – 410.9 to 43.9 – 116.6 mL/g after adding 0.5 mg/mL Tween 80. When ERLs was more hydrophobic and had more condensed phenolic OH, the alleviation effect of Tween 80 on cellulase adsorption on ERLs was intensified but its positive effect on enhancing cellulase desorption was weakened. Tween 80 was effective in increasing xylanase activity and preventing xylanase deactivation. Further, with the increase of lignin content and phenolic OH in pretreated poplar, the effect of Tween 80 in alleviating xylanase adsorption on poplar samples was intensified but the effect in enhancing xylanase desorption from poplar samples was weakened. The results provided distinct findings to understand the interaction between Tween 80 and cellulase/xylanase in enzymatic saccharification of lignocelluloses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Growth mechanisms of large, faceted crystals grown from solutions

Here, the paper describes optical techniques and methods used to study growth mechanisms and phenomena occurring on multiple faces of real bulk crystals grown from aqueous and organic solutions. Using examples of ionic KDP and molecular trans-stilbene crystals, it shows how in-situ and ex-situ surface observations can be applied to identify growth structures characteristic for the dislocation, two-dimensional (2D), and 3D cluster deposition mechanisms. Results are analyzed and applied to understanding of defects origins and methods for their elimination in practical growth of large, high optical quality crystals.

2D growth mechanism↗
DOE OSTI2025

Explaining drivers of housing prices with nonlinear hedonic regressions

Housing markets play a critical role in shaping the spatial and demographic evolution of urban areas. Simulating housing price dynamics can enhance projections of future urban development outcomes. However, traditional hedonic regressions for housing prices, which neglect nonlinear interactions among explanatory variables, often exhibit limited predictive performance. While machine learning (ML) methods can provide a more flexible representation of the relationships between predictors, they are often regarded as “black boxes” due to their complexity and lack of transparency. Interpretable ML techniques provide a promising route by combining the flexibility of ML methods with approaches to analyze the relationships between inputs and outputs. In this study, we employ interpretable ML to analyze the patterns driving the housing market in Baltimore, Maryland, USA. We train an Artificial Neural Network (ANN) to predict Baltimore housing prices based on structural characteristics (e.g., home size, number of stories) and locational attributes (e.g., distance to the city center). We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We find that the ML model achieves higher predictive accuracy and explains 16 % more of housing price variance than a traditional linear regression model. The interpretable ML model also reveals more nuanced and realistic nonlinear relationships between housing sales price and predictors as well as interactive effects underlying Baltimore home price dynamics. For instance, while the linear model indicates a steady housing price increase over time, our interpretable ML model detects a post-2008 decline, with smaller properties experiencing the sharpest drop.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The {10$\overline{1}$2} non-cozone twin-twin interactions in Mg: A stability and mobility study using 3-D atomistic simulations

Due to easy activation of tensile twinning in Mg, multiple {10$\overline{1}$2} twin variants can interact with each other and form twin-twin boundaries over the course of plastic deformation. Previous studies using 2-D settings provide only a partial understanding of these interactions, especially the non-cozone ones. Here, atomistic simulations are used to study the 3-D structural characteristic and evolution of the non-cozone {10$\overline{1}$2} twin-twin junctions. The study reveals the existence of new twin-twin boundaries (TTBs) such as TTB BP and TTB K2 , formed after the interaction between the basal prismatic and conjugate twin interfaces with the coherent twin boundary. Here, for both non-cozone twin-twin interactions, the {10$\overline{1}$2} TTB and its associated twin-twin junctions are found to play a major role in the {10$\overline{1}$2} twin's stability and mobility. Specifically, they promote the growth of the 3-D twin in both the normal and forward directions during the interaction and hinder the detwinning process upon unloading.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sulfurized Polyacrylonitrile for High-Performance Lithium–Sulfur Batteries: In-Depth Computational Approach Revealing Multiple Sulfur’s Reduction Pathways and Hidden Li + Storage Mechanisms for Extra Discharge Capacity

Like no other sulfur host material, polyacrylonitrile-derived sulfurized carbon (SPAN) promises improved electrochemical performance for lithium–sulfur batteries, based on its compatibility with carbonate solvents and ability to prevent self-discharge and shuttle effect. However, a complete understanding of the SPAN’s lithiation mechanism is still missing because its structural features vary widely with synthesis conditions, and its electrochemical performance deviates from elemental sulfur. This study continues our research on the elucidation of the SPAN’s structural characteristics and lithiation mechanisms via computational approaches. Here, our models reproduce most experimental data regarding carbon’s graphitization level and conjugated ordering, sulfur–carbon covalent bonding, sulfur loading, and elemental composition. Our simulations emulate the discharge voltage observed in experiments for the first discharge, which reveals that sulfur follows multiple reduction pathways based on its interaction with the carbon backbone. Sulfur reduction takes place above 1.0 V vs Li/Li + mostly in the SPAN-like material, with no long-chain lithium polysulfide formation. Below 1.0 V vs Li/Li + , the backbone’s electrochemical activity occurs via multiple C–Li and N–Li interactions, mostly with edge carbon atoms and pyridinic nitrogen. Moreover, we identify Li + binding sites throughout the graphitized backbone that might lead to prohibited energy costs for Li + deintercalation, which may explain the irreversible capacity loss between the first and second discharges. This work improves understanding of lithiation mechanisms in sulfurized carbon, which is useful for rationally designing SPAN synthesis pathways tailored to increase sulfur loading and enhanced electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗
DOE OSTI2020

Rational Design and Synthesis of Hierarchical Porous Mn–N–C Nanoparticles with Atomically Dispersed MnNx Moieties for Highly Efficient Oxygen Reduction Reaction

Developing transition-metal excluding iron and cobalt–nitrogen–carbon (M–N–C) electrocatalysts for the oxygen reduction reaction (ORR) is critical to substantially promote the development of precious-metal-free metal–air batteries and fuel cells. In the work, Mn–N–C nanoparticles with atomically dispersed MnNx moieties were synthesized by pyrolyzing Mn-ion–dual-pyridine coordinated complex, which was obtained via a simple condensation reaction between 2,6-diamino-pyridine and 2,6-diacetyl-pyridine with MnCl 2 as the Mn source. The precursor features with a characteristic structure of dual-pyridine ligand, which possesses a strong coordinating capability for Mn 2+ , facilitating the formation of highly dispersed nitrogen-coordinated Mn sites (MnN x ). Attributed to the highly active atomic MnN x sites, hierarchical pore structure, and high surface area of the Mn–N–C derived from the new precursor, it exhibits outstanding ORR performance in 0.1 M KOH with an almost direct four-electron reaction path and high selectivity of O 2 into H 2 O (low H2O2 production <3.5%). The half-wave potential of Mn–N–C is 0.88 V vs RHE, which is 20 mV higher than that of commercial Pt/C catalyst and reaches to the level of Fe–N–C catalyst obtained by the same method. Meanwhile, the feasibility of Mn–N–C for practical application is validated by its higher-performance power output in Zn–air battery with a maximum power density of 132 mW cm –2 compared to that of Pt/C (121 mW cm –2 ) using the same catalyst loading of 1.0 mg cm –2 . This work develops a convenient route to develop non-Fe or Co–N–C electrocatalyst for the ORR.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The System for Classification of Low-Pressure Systems (SyCLoPS): An All-In-One Objective Framework for Large-Scale Data Sets

We propose the first unified objective framework (SyCLoPS) for detecting and classifying all types of low-pressure systems (LPSs) in a given data set. We use the state-of-the-art automated feature tracking software TempestExtremes (TE) to detect and track LPS features globally in ERA5 and compute 16 parameters from commonly found atmospheric variables for classification. A Python classifier is implemented to classify all LPSs at once. The framework assigns 16 different labels (classes) to each LPS data point and designates four different types of high-impact LPS tracks, including tracks of tropical cyclone (TC), monsoonal system, subtropical storm and polar low. The classification process involves disentangling high-altitude and drier LPSs, differentiating tropical and non-tropical LPSs using novel criteria, and optimizing for the detection of the four types of high-impact LPS. A comparison of our labels with those in the International Best Track Archive for Climate Stewardship (IBTrACS) revealed an overall accuracy of 95% in distinguishing between tropical systems, extratropical cyclones, and disturbances. SyCLoPS produces a better TC detection skill compared to the previous algorithms, highlighted by an approximately 6% reduction in the false alarm rate compared to the previous TE algorithm. The vertical cross section composite of the four types of high-impact LPS we detect each shows distinct structural characteristics. Finally, we demonstrate that SyCLoPS is valuable for investigating various aspects of LPSs in climate data, such as the evolution of a single LPS track, patterns of LPS frequencies, and precipitation or wind influence associated with a particular LPS class.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Structural insights into functional properties of the oxidized form of cytochrome c oxidase

Abstract Cytochrome c oxidase (C c O) is an essential enzyme in mitochondrial and bacterial respiration. It catalyzes the four-electron reduction of molecular oxygen to water and harnesses the chemical energy to translocate four protons across biological membranes. The turnover of the C c O reaction involves an oxidative phase, in which the reduced enzyme (R) is oxidized to the metastable O H state, and a reductive phase, in which O H is reduced back to the R state. During each phase, two protons are translocated across the membrane. However, if O H is allowed to relax to the resting oxidized state (O), a redox equivalent to O H , its subsequent reduction to R is incapable of driving proton translocation. Here, with resonance Raman spectroscopy and serial femtosecond X-ray crystallography (SFX), we show that the heme a 3 iron and Cu B in the active site of the O state, like those in the O H state, are coordinated by a hydroxide ion and a water molecule, respectively. However, Y244, critical for the oxygen reduction chemistry, is in the neutral protonated form, which distinguishes O from O H , where Y244 is in the deprotonated tyrosinate form. These structural characteristics of O provide insights into the proton translocation mechanism of C c O.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mosaic lateral heterostructures in two-dimensional perovskite

Lateral heterostructures are important for exploring exotic physics, developing new devices and achieving device miniaturization. Endo-epitaxial growth occurring in patterned templates presents a promising strategy to realize extensive patterned areas in heterostructures, as recently demonstrated with two-dimensional (2D) covalent materials. However, the conventional lithography and etching processes used to prepare patterned templates are too aggressive for 2D lead halide perovskites, owing to their inherently soft and unstable ionic lattice. Here we create square holes of controllable size within 2D lead halide perovskites, enabling the fabrication of continuous lateral heterostructures over large areas. We demonstrate that the square holes form through spontaneous etching, a process initiated by internal strain and stabilized along the [100]/[010] crystallographic direction. Furthermore, the size of the square holes can be controlled by adjusting the etching time and temperature. Moreover, by incorporating a rapid solvent evaporation growth technique, the edges of the square holes act as templates for epitaxial growth of another type of perovskite, incorporating different halide or metal ions. Finally, we realized a series of mosaic lateral heterostructures that can emit various colours for light-emitting devices. As a result, this synthesis of diverse 2D perovskite mosaic lateral heterostructures provides valuable insights into the structural characteristics of perovskites and offers a versatile material platform for the development of complex integrated emitting devices.

Organic–inorganic nanostructures↗
DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗
DOE OSTI2020

Thermodynamics, dynamics, and structure of supercritical water at extreme conditions

Molecular dynamics (MD) simulations to understand the thermodynamic, dynamic, and structural changes in supercritical water across the Frenkel line and the melting line have been performed. The two-phase thermodynamic model [J. Phys. Chem. B(2010), 114(24), 8191-8198] and the velocity autocorrelation functions are used to locate the Frenkel line and to calculate the thermodynamic and dynamic properties. The Frenkel lines obtained from the two-phase thermodynamic model and the velocity autocorrelation criterion do not agree with each other. Structural characteristics and the translational diffusion dynamics of water suggest that this inconsistency could arise from the two oscillatory modes in water, which are associated with the bending of hydrogen bonds and intermolecular collisions inside the first coordination shell. Finally, the overall results lead us to conclude that the universality of the Frenkel line as a dynamic crossover line from rigid to nonrigid fluids is preserved in water.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

A biomass pretreatment using cellulose-derived solvent Cyrene

Despite only recently becoming available in the quantities required for solvent usage, the cellulose-derived solvent, named Cyrene, has gained significant attention in green chemistry in recent years. To fulfill the sustainability criteria of future biorefineries, a novel renewable biomass pretreatment using Cyrene and water was developed for the first time. Results showed that Cyrene has high potential as a green pretreatment solvent in terms of lignin fractionation/recovery and sugar release in the follow-up enzymatic hydrolysis. The mechanism of this pretreatment was revealed by investigating the structural characteristics of pretreated biomass, and the recovered lignin was also fully characterized to assess its valorization potential. Results indicated that Cyrene pretreatment could be performed at a mild condition (120 °C) to reduce the lignin condensation and the cleavage of β-O-4 linkages without compromising lignin removal and the following sugar platform. The successful utilization of this cellulose-derived solvent in pretreatment will further contribute to the realization of a “closed-loop” biorefinery process.

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

Natural deep eutectic solvent mediated extrusion for continuous high-solid pretreatment of lignocellulosic biomass

Several deep eutectic solvents (DESs) have been demonstrated to be highly effective for lignocellulosic biomass pretreatment, combining the advantages of simple synthesis, relatively low chemical cost and better biocompatibility. However, low biomass loading that is usually involved with DES pretreatment hinders its practical use. Here, a twin-screw extruder was used for pretreating biomass sorghum bagasse at solid loadings up to 50%, mediated by a neutral-pH DES, choline chloride : glycerol (ChCl : Gly). This continuous extrusion process led to high glucose and xylose yields of >85% from enzymatic saccharification of the pretreated sorghum. A combination of microscopic, spectroscopic, and X-ray diffraction analyses demonstrate a high degree of defibration and disruption of the biomass cell wall structures; however, little or no change in chemical compositions. Further results from gel permeation chromatographic (GPC) and nuclear magnetic resonance (NMR) spectroscopic analyses indicate that ChCl : Gly-mediated extrusion preserved the basic lignin structural characteristics with no significant differences between extruded biomass at a solid loading of 30% and 50%. This study demonstrates the potential of DES-mediated extrusion as a highly effective continuous high-solid biomass pretreatment technology for industrially relevant applications.

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

High-speed x-ray phase contrast imaging and digital image correlation analysis of microscale shock response of an additively manufactured energetic material simulant

The performance of energetic materials subjected to dynamic loading significantly depends on their micro- and meso-scale structural morphology. The geometric versatility offered by additive manufacturing opens new pathways to tailor the performance of these materials. Additively manufactured energetic materials (AMEMs) have a wide range of structural characteristics with a hierarchy of length scales and process-inherent heterogeneities, which are hitherto difficult to precisely control. It is important to understand how these features affect AMEMs’ response under dynamic/shock loading. Therefore, temporally and spatially resolved measurements of both macroscopic behavior and micro- and meso-level processes influencing macroscopic behavior are required. In this paper, we analyze the shock compression response of an AMEM simulant loaded under several impact conditions and orientations. Furthermore, x-ray phase contrast imaging (PCI) is used to track features across the observed shock front and determine the linear shock velocity vs particle velocity equation of state, as well as to quantify the interior deformation fields via digital image correlation (DIC) analyses. Photon Doppler velocimetry is simultaneously used to measure the particle velocities of the specimens, which are consistent with those obtained from x-ray PCI. The DIC analyses provide an assessment of the average strain fields inside the material, showing that the average axial strain depends on the loading intensity and reaches as high as 0.23 for impact velocities up to 1.5 km/s. The overall results demonstrate the utility of x-ray PCI for probing “in-material” equation of state and interior strains associated with dynamic shock compression behavior of the AMEM simulant.

3D printing↗
DOE OSTI2021

Atomic scale investigation of aluminum incorporation, defects, and phase stability in β -(Al x Ga 1-x ) 2 O 3 films

The development of novel ultra-wide bandgap (UWBG) materials requires precise understanding of the atomic level structural origins that give rise to their important properties. We study the aluminum atom incorporation, defect formation, and their relationships with phase stability in β-(Al x Ga 1-x ) 2 O 3 films, a promising candidate for UWBG applications, to explain atomic scale structural characteristics and properties using a combination of quantitative scanning transmission electron microscopy (STEM) and density functional theory (DFT). Our STEM analysis indicates that ~54% of the incorporated Al substitutes on the octahedrally coordinated Ga 2 site in a series of films grown with different techniques and alloy concentrations. DFT calculations show that, while Al energetically prefers the octahedral site, surface reconstructions and kinetic limitations during the epitaxial growth are responsible for Al occupying both octahedral and tetrahedral sites in (Al x Ga 1-x ) 2 O 3 , ultimately limiting the stability of the β-phase at x < ~50%. Local heterogeneity of composition results in the formation of a planar defect, affecting the stability of the β-phase. The similarity of such inclusions to the metastable γ-phase is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The relaxation behavior of supercooled and glassy imidacloprid

Employing dielectric spectroscopy, oscillatory shear rheology, and calorimetry, the present work explores the molecular dynamics of the widely used insecticide imidacloprid above and below its glass transition temperature. In its supercooled liquid regime, the applied techniques yield good agreement regarding the characteristic structural (alpha) relaxation times of this material. In addition, the generalized Gemant–DiMarzio–Bishop model provides a good conversion between the frequency-dependent dielectric and shear mechanical responses in its viscous state, allowing for an assessment of imidacloprid’s molecular hydrodynamic radius. In order to characterize the molecular dynamics in its glassy regime, we employ several approaches. These include the application of frequency–temperature superposition (FTS) to its isostructural dielectric and rheological responses as well as use of dielectric and calorimetric physical aging and the Adam–Gibbs–Vogel model. While the latter approach and dielectric FTS provide relaxation times that are close to each other, the other methods predict notably longer times that are closer to those reflecting a complete recovery of ergodicity. In conclusion, this seemingly conflicting dissimilarity demonstrates that the molecular dynamics of glassy imidacloprid strongly depends on its thermal history, with high relevance for the use of this insecticide as an active ingredient in technological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electronic reconstruction at the polar (111)-oriented oxide interface

Atomically flat (111) interfaces between insulating perovskite oxides provide a landscape for new electronic phenomena. For example, the graphene-like coordination between interfacial metallic ion layer pairs can lead to topologically protected states [Xiao et al., Nat. Commun. 2, 596 (2011) and A. Rüegg and G. A. Fiete, Phys. Rev. B 84, 201103 (2011)]. The metallic ion/metal oxide bilayers that comprise the unit cell of the perovskite (111) heterostructures require the interface to be polar, generating an intrinsic polar discontinuity [Chakhalian et al., Nat. Mater. 11, 92 (2012)]. Here, we investigate epitaxial heterostructures of (111)-oriented LaAlO 3 /SrTiO 3 (LAO/STO). We find that during heterostructure growth, the LAO overlayer eliminates the structural reconstruction of the STO (111) surface with an electronic reconstruction, which determines the properties of the resulting two-dimensional conducting gas. This is confirmed by transport measurements, direct determination of the structure and atomic charge from coherent Bragg rod analysis, and theoretical calculations of electronic and structural characteristics. Interfacial behaviors of the kind discussed here may lead to new growth control parameters useful for electronic devices.

36 MATERIALS SCIENCE↗