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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adsorption Thermodynamics for Process Simulation

Adsorption has rapidly evolved in recent decades and is an established separation technology extensively practiced in gas separation industries and others. However, rigorous thermodynamic modeling of multicomponent adsorption equilibrium remains elusive, and industrial practitioners rely heavily on expensive and time-consuming trial-and-error pilot studies to develop adsorption units. Here, this article highlights the need for rigorous adsorption thermodynamic models and the limitations and deficiencies of existing models such as the extended Langmuir isotherm, dual-process Langmuir isotherm, and adsorbed solution theory. It further presents a series of recent advances in the generalization of the classical Langmuir isotherm of single-component adsorption by deriving an activity coefficient model to account for the adsorbed phase adsorbate–adsorbent interactions, substituting adsorbed phase adsorbate and vacant site concentrations with activities, and extending to multicomponent competitive adsorption equilibrium, both monolayer and multilayer. Requiring a minimum set of physically meaningful model parameters, the generalized Langmuir isotherm for monolayer adsorption and the generalized Brunauer–Emmett–Teller isotherm for multilayer adsorption address various thermodynamic modeling challenges including adsorbent surface heterogeneity, isosteric enthalpies of adsorption, BET surface areas, adsorbed phase nonideality, adsorption azeotrope formation, and multilayer adsorption. Also discussed is the importance of quality adsorption data that cover sufficient temperature, pressure, and composition ranges for reliable determination of the model parameters to support adsorption process simulation, design, and optimization.

09 BIOMASS FUELS↗
DOE OSTI2019

Role of Defects in Ion Transport in Block Copolymer Electrolytes

Ion conducting block copolymers can overcome traditional limitations of homopolymer electrolytes by phase separating into nanoarchitectures that can be simultaneously optimized for two or more orthogonal material properties such as high ionic conductivity and mechanical stability. A key challenge in understanding the ion transport properties of these materials is the difficulty of extracting structure-function relationships without having complete knowledge of all nanoscale transport pathways in bulk samples. In this paper, we demonstrate a method for deriving structure-transport relationships for ion conducting block copolymers using thin films and interdigitated electrodes. Well-defined and directly imaged structure in films of poly(styrene)-block-poly(2-vinylpyridine) is controlled using techniques of directed self-assembly then the poly(2-vinylpyridine) is selectively converted into an ion conductor. The ion conductivity is found to be directly proportional to the total number of connected paths between electrodes and the path length. A single defect such as a dislocation anywhere in the path of an ion conducting route disconnects and precludes that pathway from contributing to the conductivity and results in an increase in the dielectric parameter of the film. When all the ion conduction pathways are blocked between electrodes, the conductivity is negligible, 4 orders of magnitude lower compared to a completely connected morphology and the dielectric parameter increases by a factor of 50. Lastly, these results have profound implications for the interpretation, design, and processing of block copolymer electrolytes for applications as ion conducting membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Li-Ion Diffusion Correlations in LiAlGeO 4 : Quasielastic Neutron Scattering and Ab Initio Simulation

Here, we investigated the impact of Li stoichiometry and host flexibility on Li + diffusion processes in LiAlGeO 4 at the microscopic level using quasielastic neutron scattering (QENS) and ab initio molecular dynamics (AIMD) simulations. Using sufficiently long AIMD trajectories, we could simulate the observed QENS signal and identify the localized dynamics of Li in crystalline LiAlGeO 4 . Such information is vital to identify the bottleneck of diffusion processes and design materials for battery application. Our AIMD simulations in LiAlGeO 4 reveal that the Li + conductivity can be significantly improved by manipulating the Li stoichiometry and/or host flexibility via amorphization. We determined that excess Li stoichiometry enhances the Coulomb repulsion of neighboring Li sites and softens the host structure to enable faster Li + diffusion along the hexagonal c-axis. In the amorphous structure, random orientations of AlO 4 and GeO 4 polyhedral units create a wide distribution of intersite distances and significantly soften the host structure, greatly enhancing the Li + diffusion. The simulations are used to understand the nature of diffusion, especially the role of the host structure, the possible hopping pathways, and the diffusion behavior in various structures of LiAlGeO 4 .

localized dynamics↗
DOE OSTI2020

Cadmium Selective Etching in CdTe Solar Cells Produces Detrimental Narrow-Gap Te in Grain Boundaries

Recent advances in design and processing technology have made possible commercialization of polycrystalline (px)-CdTe as a photovoltaic absorber. Grain boundaries (GBs) are the most prominent structural defects in these devices and undergo significant changes during device fabrication. However, the effects of device fabrication processes on these GBs are not entirely understood. Prevailing models of GBs in thin-film photovoltaics consider individual GBs to have homogeneous properties in their area. Here, using an aberration-corrected scanning transmission electron microscope (STEM)-based low-loss and core-loss electron energy-loss spectroscopy (EELS), we show that back-surface etching of CdTe leads to inhomogeneity within individual grain boundaries. We observe that etching the back surface leads to the conversion of a region of GBs from CdTe to an elemental Te, which has an only 0.33 eV band gap, as deep as 1 μm from the back surface. The presence of elemental Te in GBs this deep into the absorber layer will increase recombination in the absorber layer and limit the extractable open-circuit voltage, thus reducing device efficiency. However, additive methods for back contact formation such as deposition of Te, ZnTe, or other materials preserve the CdTe stoichiometry of the GBs. Thus, especially for the next generations of CdTe-based cells having longer minority carrier diffusion length and/or thinner absorber layers, additive back contacting methods are superior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pyrazine-Fused Porous Graphitic Framework-Based Mixed Matrix Membranes for Enhanced Gas Separations

Membrane-based separations can mitigate the capital- and energy-intensive challenges associated with traditional thermally driven processes. To further push the boundary of gas separations, mixed matrix membranes (MMMs) have been extensively exploited; however, identifying an optimal nanofiller to boost the separation performance of MMMs beyond Robeson permeability-selectivity upper bounds remains an ongoing challenge. In this study, a new class of MMMs based on pyrazine-fused crystalline porous graphitic frameworks (PGFs) is reported. At a loading of 6 wt % PGFs, the MMMs surpass the current H 2 /CH 4 Robeson upper bound, ideally suited for applications such as H 2 regeneration. In addition, the fabricated MMMs exhibit appealing CO 2 separation performance, closely approaching the current Robeson upper bounds for CO 2 separation. Compared with the pristine polymeric membranes, the PGF-based MMMs display a record-high enhancement of gas permeability over 120% while maintaining intrinsic gas selectivities. Highlighting the crucial role of the crystallinity of nanofillers, this study demonstrates a facile and effective approach in formulating high-performance MMMs, complementing state-of-the-art membrane formation processes. The design principles open the door to energy-efficient separations of gas mixtures with enhanced productivity compatible with the current membrane manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Variable-Temperature Scattering and Spectroscopy Characterizations for Temperature-Dependent Solution Assembly of PffBT4T-Based Conjugated Polymers

The solution structure of conjugated polymers (CPs) from which the films are cast is critical for tailoring the thin-film morphology thus device performance. Here, we used multimodal variable-temperature scattering and spectroscopy tools to fully quantify the solution assembly of poly[(5,6-difluoro-2,1,3-benzothiadiazol-4,7-diyl)-alt-(3,3'''-dialkyl-2,2';5',2'';5'',2'''-quaterthiophen-5,5'''-diyl)] (PffBT4T) polymers with varying side-chain lengths at different assembly temperatures. The conformational and aggregation behaviors for PffBT4T-based CPs were found to be very sensitive to both temperature and side chain length using ultraviolet–visible (UV–vis) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, dynamic light scattering (DLS), and small-angle neutron scattering (SANS). We found that with slightly increasing side chain length from 2-octyldodecyl (C8C12) to 2-nonyltridecyl (C9C13), PffBT4T-based CPs show a significant decrease in aggregation-to-dissolved chain transition temperature (10 °C), degree of aggregation, enthalpy change of aggregation, and size of the aggregates in solution. At room temperature, PffBT4T polymer strongly aggregated to form fabric structure with the film thickness of a few nanometers in thickness and hundreds of nanometers in length, as probed by atomic force microscopy (AFM), transmission electronic microscopy (TEM), and dynamic light scattering (DLS). At the elevated temperature above the aggregation-to-dissolved chain transition temperature, PffBT4T is fully dissolved and adopts a semiflexible coil conformation with the persistence length of 3.1 nm for PffBT4T-C8C12 and a slightly increased persistence length of 3.4 nm for PffBT4T-C9C13, according to temperature-dependent SANS measurements. Longer side chains of PffBT4T-C9C13 also lead to less aggregation enthalpy gain compared with PffBT4T-C8C12. This work provides a solution structure manipulating strategy of CPs and thus will inspire the molecular design and processing protocols of CPs toward higher performance electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Highly Selective Oxygen Reduction to Hydrogen Peroxide on a Carbon-Supported Single-Atom Pd Electrocatalyst

Selective electrochemical two-electron oxygen reduction is a promising route for renewable and on-site H 2 O 2 generation as an alternative to the anthraquinone process. In this study, we report a high-performance nitrogen-coordinated single-atom Pd electrocatalyst, which is derived from Pd-doped zeolitic imidazolate frameworks (ZIFs) through one-step thermolysis. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) combined with X-ray absorption spectroscopy verifies atomically dispersed Pd atoms on nitrogen-doped carbon (Pd-NC). The single-atom Pd-NC catalyst exhibits excellent electrocatalytic performance for two-electron oxygen reduction to H 2 O 2 , which shows ~95% selectivity toward H 2 O 2 and an unprecedented onset potential of ~0.8 V versus revisable hydrogen electrode (RHE) in 0.1 M KOH. Density functional theory (DFT) calculations demonstrate that the Pd-N 4 catalytic sites thermodynamically prefer *–O bond breaking to O–O bond breaking, corresponding to a high selectivity for H 2 O 2 production. This work provides a deep insight into the understanding of the catalytic process and design of high-performance 2e– ORR catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2024

Techno-Economic Analysis and Life Cycle Assessment of the Production of Biodegradable Polyaliphatic–Polyaromatic Polyesters

Poly(butylene-adipate terephthalate) (PBAT) is a polyaliphatic–polyaromatic polyester that is biodegradable and has found application in several markets, making it a widely produced biodegradable polymer worldwide. However, the production of PBAT is carbon-intensive, as it relies on the use of petroleum-based monomers. There is, thus, significant interest in identifying polyesters that are biodegradable and less carbon-intensive (e.g., use of biomass- derived monomers). In this work, we develop a detailed process model (and an associated database) for the production of polyaliphatic–polyaromatic polyesters including petroleum-based PBAT and biomass-derived alternatives including poly(pentylene- adipate terephthalate) and poly(pentylene-adipate furandicarboxy- late). Techno-economic analysis (TEA) reveals that the production costs of these polyesters strongly depend on monomer costs (accounting for over 90% of the total production cost) and identifies market conditions under which biomass-based polyesters can be cost-competitive to petroleum-based PBAT. Life cycle assessment (LCA) shows that biomass-derived polyesters can reduce the global warming impact of PBAT by half. Altogether, the proposed TEA/LCA model aims to provide guidance into polyesters that are most promising and help assess their overall economic and environmental performance.

42 ENGINEERING↗
DOE OSTI2020

Characterizing Variability in Lignocellulosic Biomass: A Review

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Recently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We further examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

09 BIOMASS FUELS↗
DOE OSTI2013

Conjugates of Magnetic Nanoparticle -- Actinide Specific Chelator for Radioactive Waste Separation

A novel nanotechnology for the separation of radioactive waste that uses magnetic nanoparticles (MNPs) conjugated with actinide specific chelators (MNP-Che) is reviewed with a focus on design and process development. The MNP-Che separation process is an effective way of separating heat generating minor actinides (Np, Am, Cm) from spent nuclear fuel solution to reduce the radiological hazard. It utilizes coated MNPs to selectively adsorb the contaminants onto their surfaces, after which the loaded particles are collected using a magnetic field. The MNP-Che conjugates can be recycled by stripping contaminates into a separate, smaller volume of solution, and then become the final waste form for disposal after reusing number of times. Due to the highly selective chelators, this remediation method could be both simple and versatile while allowing the valuable actinides to be recovered and recycled. Key issues standing in the way of large-scale application are stability of the conjugates and their dispersion in solution to maintain their unique properties, especially large surface area, of MNPs. With substantial research progress made on MNPs and their surface functionalization, as well as development of environmentally benign chelators, this method could become very flexible and cost-effective for recycling used fuel. Finally, the development of this nanotechnology is summarized and its future direction is discussed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Direct observation of dual-step twinning nucleation in hexagonal close-packed crystals

Design and processing of advanced lightweight structural alloys based on magnesium and titanium rely critically on a control over twinning which, however, remains elusive to date and is dependent on an explicit understanding on the twinning nucleation mechanism in hexagonal close-packed (HCP) crystals. Here, by using in-situ high resolution transmission electron microscopy, we directly reveal a “dual-step” twinning nucleation mechanism in HCP rhenium nanocrystals. It is found that nucleation of the predominant {10 -12} twinning is initiated by disconnections on the Prismatic¦Basal interfaces which establish the lattice correspondence of the twin with a minor deviation from the ideal orientation. Subsequently, the minor deviation is corrected by the formation of coherent twin boundaries through rearrangement of the disconnections on the Prismatic¦Basal interface; thereafter, the coherent twin boundaries propagate by twinning disconnections. The findings provide much-needed high-resolution evidences to the twinning nucleation mechanism in HCP crystals, with crucial implications for engineering advanced structural alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Non-averaged single-molecule tertiary structures reveal RNA self-folding through individual-particle cryo-electron tomography

Large-scale and continuous conformational changes in the RNA self-folding process present significant challenges for structural studies, often requiring trade-offs between resolution and observational scope. Here, we utilize individual-particle cryo-electron tomography (IPET) to examine the post-transcriptional self-folding process of designed RNA origami 6-helix bundle with a clasp helix (6HBC). By avoiding selection, classification, averaging, or chemical fixation and optimizing cryo-ET data acquisition parameters, we reconstruct 120 three-dimensional (3D) density maps from 120 individual particles at an electron dose of no more than 168 e - Å -2 , achieving averaged resolutions ranging from 23 to 35 Å, as estimated by Fourier shell correlation (FSC) at 0.5. Each map allows us to identify distinct RNA helices and determine a unique tertiary structure. Statistical analysis of these 120 structures confirms two reported conformations and reveals a range of kinetically trapped, intermediate, and highly compacted states, demonstrating a maturation folding landscape likely driven by helix-helix compaction interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Predicting surface deformation during mechanical attrition of metallic alloys

Extensive efforts have been devoted in both the engineering and scientific domains to seek new designs and processing techniques capable of making stronger and tougher materials. One such method for enhancing such damage-tolerance in metallic alloys is a surface nano-crystallization technology that involves the use of hundreds of small hard balls which are vibrated using high-power ultrasound so that they impact onto the surface of a material at high speed (termed Surface Mechanical Attrition Treatment or SMAT). However, few studies have been devoted to the precise underlying mechanical mechanisms associated with this technology and the effect of processing parameters. As SMAT is dynamic plastic deformation process, here we use random impact deformation as a means to investigate the relationship between impact deformation and the parameters involved in the processing, specifically ball size, impact velocity, ball density and kinetic energy. Using analytical and numerical solutions, we examine the size of the indents and the depths of the associated plastic zones induced by random impacts, with results verified by experiment in austenitic stainless steels. In addition, global random impact and local impact frequency models are developed to analyze the statistical characteristics of random impact coverage, together with a description of the effect of random multiple impacts, which are more reflective of SMAT. We believe that these models will serve as a necessary foundation for further, and more energy-efficient, development of such surface nano-crystalline processing technologies for the strengthening of metallic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Abstract Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Experimental investigation on plasma parameter profiles on a wafer level with reactor gap lengths in an inductively coupled plasma

The gap length effect on plasma parameters is investigated in a planar type inductively coupled plasma at various conditions. The spatial profiles of ion densities and the electron temperatures on the wafer level are measured with a 2D probe array based on the floating harmonic method. At low pressures, the spatial profiles of the plasma parameters rarely changed by various gap lengths, which indicates that nonlocal kinetics are dominant at low pressures. However, at relatively high pressures, the spatial profiles of the plasma parameter changed dramatically. These plasma distribution profile characteristics should be considered for plasma reactor design and processing setup, and can be explained by the diffusion of charged particles and the local kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Improving the counting efficiency in time-correlated single photon counting experiments by dead-time optimization

Time-Correlated Single Photon Counting (TCSPC) has been long recognized as the most sensitive method for fluorescence lifetime measurements, but often requiring “long” data acquisition times. This drawback is related to the limited counting capability of the TCSPC technique, due to pile-up and counting loss effects. In recent years, multi-module TCSPC systems have been introduced to overcome this issue. Splitting the light into several detectors connected to independent TCSPC modules proportionally increases the counting capability. Of course, multi-module operation also increases the system cost and can cause space and power supply problems. In this paper, we propose an alternative approach based on a new detector and processing electronics designed to reduce the overall system dead time, thus enabling efficient photon collection at high excitation rate. We present a fast active quenching circuit for single-photon avalanche diodes which features a minimum dead time of 12.4 ns. We also introduce a new Time-to-Amplitude Converter (TAC) able to attain extra-short dead time thanks to the combination of a scalable array of monolithically integrated TACs and a sequential router. The fast TAC (F-TAC) makes it possible to operate the system towards the upper limit of detector count rate capability (∼80 Mcps) with reduced pile-up losses, addressing one of the historic criticisms of TCSPC. Preliminary measurements on the F-TAC are presented and discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗