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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rational synthesis of high-performance Ni-rich layered oxide cathode enabled via probing solid-state lithiation evolution

Lithium (Li)-ion batteries using nickel (Ni)-rich layered oxide cathode have been pursued with interest due to high practical energy density. A fundamental understanding of the reaction pathways and structural evolution of the solid-phase synthesis of these materials is crucial for their rational design and process development for mass production. In this work, structural evolution during solid-state synthesis was traced via in situ technique, with a particular emphasis on the lithiation reaction and migration of transition metal (TM) ions. The sintering process is governed by the competitive relationship of decomposition and lithiation reactions, which can be regulated through temperature windows. Controlling the melting point of the Li sources, as well as their affinity to cathode precursors, is highly desired to maintain the layered ordering of TM ions throughout the whole synthesis process, which simplifies the manufacturing process and improves the quality of the manufactured cathode material.

25 ENERGY STORAGE↗
DOE OSTI2024

A simple model for short-range ordering kinetics in multi-principal element alloys

Short-range ordering (SRO) in multi-principal element alloys influences material properties such as strength and corrosion. While some degree of SRO is expected at equilibrium, predicting the kinetics of its formation is challenging. We present a simplified isothermal concentration-wave (CW) model to estimate an effective relaxation time of SRO formation. Estimates from the CW model agree to within a factor of five with relaxation times obtained from kinetic Monte Carlo (kMC) simulations when above the highest ordering instability temperature. Further, the advantage of the CW model is that it only requires mobility and thermodynamic parameters, which are readily obtained from alloy mobility databases and Metropolis Monte Carlo simulations, respectively. The simple parameterization of the CW model and its analytical nature makes it an attractive tool for the design of processing conditions to promote or suppress SRO in multicomponent alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Non-Covalent Interactions and Helical Packing in Thiophene-Phenylene Copolymers: Tuning Solid-State Ordering and Charge Transport for Organic Field-Effect Transistors

In this study, we introduce two thiophene-phenylene-thiophene (TPT) polymers designed to leverage noncovalent intramolecular interactions to regulate main-chain conformation and enhance solid-state ordering. By incorporating unsubstituted thiophene (T) or bithiophene (2T) units, we reveal striking divergence in the thermal, morphological, and optoelectronic properties of the resulting films, facilitated by these noncovalent interactions. Using a combination of computational and experimental approaches, we show that annealing yields remarkably different polymer conformations and, consequently, charge transport properties. TPT-T undergoes a significant structural transformation, adopting a more planar backbone conformation and a highly crystalline, edge-on molecular orientation. In contrast, the introduction of a single additional thiophene unit in TPT-2T leads to a more isotropic molecular orientation with a slight preference for face-on alignment, resulting in a heterogeneous film structure that hinders charge transport despite achieving tighter molecular packing. Remarkably, despite being composed of achiral components, TPT-2T develops chirality upon annealing, indicating the formation of a helical conformation. Organic field-effect transistor measurements reveal that the well-ordered alignment in annealed TPT-T films results in higher charge carrier mobility and a narrower distribution of mobility values than in TPT-2T. These findings provide critical insights into the structure−property relationships of conjugated polymers, offering guidance for optimizing molecular design and processing strategies for highperformance organic electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Theoretical Insights on the Fragmentation of Cellulosic Oligomers to Form Hydroxyacetone and Hydroxyacetaldehyde

The presence of heavy unknown oligomeric sugar products in bio-oil is evidenced in experimental results reported in the literature. In this paper, we study the fragmentation reactions yielding acetol and glycolaldehyde from oligomeric sugars following previous work on dehydration reactions to propose structures of these oligomers. Acetol and glycolaldehyde are primary products of cellulose fast pyrolysis but the fragmentation reaction mechanism of these compounds from oligomers merits further study. The density functional theory (DFT) approach was employed to study this reaction. Results revealed that acetol and glycolaldehyde fragments are favorably removed from the non-reducing end based on their thermodynamic stabilities. Theoretical FTIR and NMR spectra were calculated to aid in understanding the structures of the oligomeric sugars. Also, the thermodynamics and physical properties of these compounds were estimated using the Group Contribution Method (GCM). In conclusion, these properties are essential in the design of processing technologies and the upgrading of products.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Molecular Dynamics Investigation of Nanoscale Hydrophobicity of Polymer Surfaces: What Makes Water Wet?

The wettability of a polymer surface–related to its hydrophobicity or tendency to repel water–can be crucial for determining its utility, such as for a coating or a purification membrane. While wettability is commonly associated with the macroscopic measurement of a contact angle between surface, water, and air, the molecular physics that underlie these macroscopic observations are not fully known, and anticipating relative behavior of different polymers is challenging. To address this gap in molecular-level understanding, we use molecular dynamics simulations to investigate and contrast interactions of water with six chemically distinct polymers: polytetrafluoroethylene, polyethylene, polyvinyl chloride, poly(methyl methacrylate), Nylon 66, and polyvinyl alcohol. We show that several prospective quantitative metrics for hydrophobicity agree well with experimental contact angles. Moreover, the behavior of water in proximity to these polymer surfaces can be distinguished with analysis of interfacial water dynamics, extent of hydrogen bonding, and molecular orientation–even when macroscopic measures of hydrophobicity are similar. The predominant factor dictating wettability is found to be the extent of hydrogen bonding between polymer and water, but the precise manifestation of hydrogen bonding and its impact on surface-water structure varies. In the absence of hydrogen bonding, other molecular interactions and polymer mechanics control hydrophobic ordering. Furthermore, these results provide new insights into how polymer chemistry specifically impacts water-polymer interactions and translates to surface hydrophobicity. Such factors may facilitate the design or processing of polymer surfaces to achieve targeted wetting behavior, and presented analyses can be useful in studying the interfacial physics of other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 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 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 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 OSTI2026

Filament extension atomizers: A study of integration potential into spray dryers for high-viscosity and non-Newtonian fluids

Filament extension atomizers (FEAs) are an emerging class of spray nozzles designed to atomize high-viscosity and non-Newtonian fluids that are challenging for conventional pressure or two-fluid nozzles. In this study, we investigate the influence of roller geometry, surface velocity, roller material, and fluid rheology on the atomization performance of FEA systems using concentrated whey protein suspensions (50–70 wt. %). Extensional and shear rheology experiments, along with high-speed imaging and particle image velocimetry, reveal that filament breakup dynamics are governed by competition between inertial, capillary, and viscoelastic stresses. High roller rotational velocity leads to narrower spray cones, contradicting rheology experiments and suggests a significant inertial contribution to filament breakup. Smaller rollers operating at the same rotational velocity led to broader spray cones consistent with expectations. An FEA nozzle was integrated into a conventional dryer producing particles in the 100 μm range. Results suggest that FEA technology enables atomization of highly viscous fluids at industrially relevant spray cone angles similar to those generated by pressure nozzles, offering a pathway to improve energy efficiency in spray drying by enabling higher solids loading feedstocks. Furthermore, these insights provide critical guidance for optimizing FEA nozzle designs and process parameters across a range of applications.

Energy efficiency↗