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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 163 records · Page 9

In-Operando Evaluation of Solid Oxide Fuel Cell (SOFC) Cathodes for Enhanced Oxygen Reduction Reaction (ORR) Activity and Durability

Through this project we developed a new in-operando 18 O-isotope exchange technique, and determined the oxygen reduction reaction (ORR) kinetics and mechanisms in various solid oxide fuel cell (SOFC) cathodes under real operating conditions of applied voltage. We were able to measure and determine oxygen surface exchange coefficients of labeled oxygen with La 0.8 Sr 0.2 MnO 3 (LSM), La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3 (LSCF) and other cathode material samples with varying compositions. We related the cell polarization conditions to the surface exchange process and surface exchange coefficient, and suggested a model to describe this relation. Our findings imply that LSCF keeps its higher exchange rate performance over LSM under real operating conditions. Changing the A-site cation ratio in LSM can enhance its performance, especially under cathodic polarizations larger than -400mV. Cathode powder composites of LSM and LSCF with YSZ and GDC show lower exchange coefficient values under applied polarization compared to the single constituent powder samples, probably due to limited contact between the powder particles. Using our model and basic electrochemical properties of the cathode materials we are able to successfully predict the exchange kinetic properties of SOFC cathode material under real operating conditions of applied voltage / current from surface exchange coefficients obtained in the absence of an applied bias.

36 MATERIALS SCIENCE↗

Structural Evolution and Transition Dynamics in Lithium Ion Battery under Fast Charging: An Operando Neutron Diffraction Investigation

Abstract Fast charging (<15 min) of lithium‐ion batteries (LIBs) for electrical vehicles (EVs) is widely seen as the key factor that will greatly stimulate the EV markets, and its realization is mainly hindered by the sluggish diffusion of Li + . To have a mechanistic understanding of Li + diffusion within LIBs, in this study, structural evolutions of electrodes for a Ni‐rich LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) || graphite cylindrical cell with high areal loading (2.78 mAh cm −2 ) are developed for operando neutron powder diffraction study at different charging rates. Via sequential Rietveld refinements, changes in structures of NMC622 and Li x C 6 are obtained during moderate and fast charging (from 0.27 C to 4.4 C). NMC622 exhibits the same structural evolution regardless of C‐rates. For phase transitions of Li x C 6 , the stage I (LiC 6 ) phase emerges earlier during the stepwise intercalation at a lower state of charge when charging rate is increased. It is also found that the stage II (LiC 12 ) → stage I (LiC 6 ) transition is the rate‐limiting step during fast charging. The LiC 12 → LiC 6 transition mechanism is further analyzed using the Johnson–Mehl–Avrami–Kolmogorov model. It is concluded as a diffusion‐controlled, 1D phase transition with decreasing nucleation kinetics under increasing chargingrates.

25 ENERGY STORAGE↗

Predicting metal–metal interactions. II. Accelerating generalized schemes through physical insights

Operando-computational frameworks that integrate descriptors for catalyst stability within catalyst screening paradigms enable predictions of rates and selectivity on chemically faithful representations of nanoparticles under reaction conditions. These catalyst stability descriptors can be efficiently predicted by density functional theory (DFT)-based models. The alloy stability model, for example, predicts the stability of metal atoms in nanoparticles with site-by-site resolution. In this work, we use physical insights to present accelerated approaches of parameterizing this recently introduced alloy-stability model. These accelerated approaches meld quadratic functions for the energy of metal atoms in terms of the coordination number with linear correlations between model parameters and the cohesive energies of bulk metals. By interpolating across both the coordination number and chemical space, these accelerated approaches shrink the training set size for 12 fcc p- and d-block metals from 204 to as few as 24 DFT calculated total energies without sacrificing the accuracy of our model. We validate the accelerated approaches by predicting adsorption energies of metal atoms on extended surfaces and 147 atom cuboctahedral nanoparticles with mean absolute errors of 0.10 eV and 0.24 eV, respectively. This efficiency boost will enable a rapid and exhaustive exploration of the vast material space of transition metal alloys for catalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nondestructive Analysis of Commercial Batteries

Electrochemical batteries play a crucial role for powering portable electronics, electric vehicles, large-scale electric grids, and future electric aircraft. However, key performance metrics such as energy density, charging speed, lifespan, and safety raise significant consumer concerns. Enhancing battery performance hinges on a deep understanding of their operational and degradation mechanisms, from material composition and electrode structure to large-scale pack integration, necessitating advanced characterization methods. These methods not only enable improved battery performance but also facilitate early detection of substandard or potentially hazardous batteries before they cause serious incidents. Here, this review comprehensively examines the operational principles, applications, challenges, and prospects of cutting-edge characterization techniques for commercial batteries, with a specific focus on in situ and operando methodologies. Furthermore, it explores how these powerful tools have elucidated the operational and degradation mechanisms of commercial batteries. By bridging the gap between advanced characterization techniques and commercial battery technologies, this review aims to guide the design of more sophisticated experiments and models for studying battery degradation and enhancement.

36 MATERIALS SCIENCE↗

Quantifying Reaction and Rate Heterogeneity in Battery Electrodes in 3D through Operando X-ray Diffraction Computed Tomography

In composite battery electrode architectures, local limitations in ionic and electronic transport can result in nonuniform energy storage reactions. Understanding such reaction heterogeneity is important to optimizing battery performance, including rate capability and mitigating degradation and failure. Here, we use spatially resolved X-ray diffraction computed tomography to map the reaction in a composite electrode based on the LiFePO 4 active material as it undergoes charge and discharge. Accelerated reactions at the electrode faces in contact with either the separator or the current collector demonstrate that both ionic and electronic transport limit the reaction progress. The data quantify how nonuniformity of the electrode reaction leads to variability in the charge/discharge rate, both as a function of time and position within the electrode architecture. Importantly, this local variation in the reaction rate means that the maximum rate that individual cathode particles experience can be substantially higher than the average, control charge/discharge rate, by a factor of at least 2-5 times. As a result, this rate heterogeneity may accelerate rate-dependent degradation pathways in regions of the composite electrode experiencing faster-than-average reaction and has important implications for understanding and optimizing rate-dependent battery performance. Benchmarking multiscale continuum model parameters against the observed reaction heterogeneity permits extension of these models to other electrode geometries.

25 ENERGY STORAGE↗

Forty years of temporal analysis of products

Detailed understanding of mechanisms and reaction kinetics are required in order to develop and optimize catalysts and catalytic processes. While steady state investigations are known to give a global view of the catalytic system, transient studies are invaluable since they can provide more detailed insight into elementary steps. For almost thirty years temporal analysis of products (TAP) has been successfully utilized for transient studies of gas phase heterogeneous catalysis, and there have been a number of advances in instrumentation and numerical modeling methods in that time. In the current work, the range of available TAP apparatus will be discussed while detailed explanations of the types of TAP experiment, the information that can be determined from these experiments and the analysis methods are also included. TAP is a complex methodology and is often viewed as a niche specialty. Here, part of the intention of this work is to highlight the significant contributions TAP can make to catalytic research, while also discussing the issues which will make TAP more relevant and approachable to a wider segment of the catalytic research community. With this in mind, an outlook is also disclosed for the technique in terms of what is needed to revitalize the field and make it more applicable to the recent advances in catalyst characterization (e.g. operando modes ).

36 MATERIALS SCIENCE↗

Unraveling the Dynamic Network in the Reactions of an Alkyl Aryl Ether Catalyzed by Ni/γ-Al 2 O 3 in 2-Propanol

The reductive cleavage of aryl ether linkages is a key step in the disassembly of lignin to its monolignol components, where selectivity is determined by the kinetics of multiple parallel and consecutive liquid-phase reactions. Triphasic hydrogenolysis of 13 C-labeled benzyl phenyl ether (BPE, a model compound with the same C-O bond energy as the major β-O-4 linkage in lignin), catalyzed by Ni/γ-Al 2 O 3 , was observed directly at elevated temperatures (150 - 175 °C) and pressures (79-89 bar) using operando magic-angle spinning NMR spectroscopy. Liquid-vapor partitioning in the NMR rotor was quantified using the 13 C NMR resonances for the 2-propanol solvent, whose chemical shifts report on the internal reactor temperature. At 170 °C, BPE is converted to toluene and phenol with k 1 = 0.17 s -1 g cat -1 and an apparent activation barrier of (80 ± 8) kJ mol -1 . Subsequent phenol hydrogenation occurs much more slowly (k 2 = 0.0052 s -1 g cat -1 at 170-175 °C), such that cyclohexanol formation is significant only at higher temperatures. Toluene is stable under these reaction conditions, but its methyl group undergoes facile H/D exchange (k 3 = 0.046 s -1 g cat -1 at 175 °C). While the source of the reducing equivalents for both hydrogenolysis and hydrogenation is exclusively H 2 /D 2(g) rather than the alcohol solvent at these temperatures, the initial isotopic composition of adsorbed H/D on the catalyst surface is principally determined by the solvent isotopic composition (2-PrOH/D). All reactions are preceded by a pronounced induction period associated with catalyst activation. In air, Ni nanoparticles are passivated by a surface oxide monolayer, whose removal under H 2 proceeds with an apparent activation barrier of (72 ± 13) kJ mol -1 . Finally ,the operando NMR spectra provide molecularly-specific, time-resolved information about the multiple simultaneous and sequential processes as they occur at the solid-liquid interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗

Active species in chloroaluminate ionic liquids catalyzing low-temperature polyolefin deconstruction

Abstract Chloroaluminate ionic liquids selectively transform (waste) polyolefins into gasoline-range alkanes through tandem cracking-alkylation at temperatures below 100 °C. Further improvement of this process necessitates a deep understanding of the nature of the catalytically active species and the correlated performance in the catalyzing critical reactions for the tandem polyolefin deconstruction with isoalkanes at low temperatures. Here, we address this requirement by determining the nuclearity of the chloroaluminate ions and their interactions with reaction intermediates, combining in situ 27 Al magic-angle spinning nuclear magnetic resonance spectroscopy, in situ Raman spectroscopy, Al K-edge X-ray absorption near edge structure spectroscopy, and catalytic activity measurement. Cracking and alkylation are facilitated by carbenium ions initiated by AlCl 3 - tert -butyl chloride (TBC) adducts, which are formed by the dissociation of Al 2 Cl 7 − in the presence of TBC. The carbenium ions activate the alkane polymer strands and advance the alkylation cycle through multiple hydride transfer reactions. In situ 1 H NMR and operando infrared spectroscopy demonstrate that the cracking and alkylation processes occur synchronously; alkenes formed during cracking are rapidly incorporated into the carbenium ion-mediated alkylation cycle. The conclusions are further supported by ab initio molecular dynamics simulations coupled with an enhanced sampling method, and model experiments using n-hexadecane as a feed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learning

Understanding the origins of enhanced reactivity of supported, subnanometer in size, metal oxide clusters is challenging due to the scarcity of methods capable to extract atomic-level information from the experimental data. Due to both the sensitivity of X-ray absorption near edge structure (XANES) spectroscopy to the local geometry around metal ions and reliability of theoretical spectroscopy codes for modeling XANES spectra, supervised machine learning approach has become a powerful tool for extracting structural information from the experimental spectra. Here, we present the application of this method to grazing incidence XANES spectra of size-selective Cu oxide clusters on flat support, measured in operando conditions of the methanation reaction. We demonstrate that the convolution neural network can be trained on theoretical spectra and utilized to “invert” experimental XANES data to obtain structural descriptors—the Cu–Cu coordination numbers. As a result, we were able to distinguish between different structural motifs (Cu 2 O-like and CuO-like) of Cu oxide clusters, transforming in reaction conditions, and reliably evaluate average cluster sizes, with important implications for the understanding of structure, composition, and function relationships in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Operando Depth-Resolved Measurement of Solvation Entropy, Interfacial Transport, and Charge-Transfer Kinetics in Lithium-Ion Batteries

Understanding and improving the performance and longevity of lithium-ion batteries critically depends on insight into the dynamic processes occurring at buried electrode-electrolyte interfaces. However, direct, depth-resolved, and operando diagnosis of these interfaces remains a longstanding challenge due to their inaccessibility beneath bulk materials, the limitations of conventional surface- and bulk-sensitive characterization tools, and the difficulty of maintaining realistic cell environments during measurement. These challenges have made it nearly impossible to uniquely resolve important interfacial properties such as charge transfer resistance, SEI (solid electrolyte interphase) resistance, and solvation entropy at the individual electrode interfaces within a working cell, information that is essential for mechanistic insight and accelerated battery design. Here, in this study, we report the development of multiharmonic electro-thermal spectroscopy (METS), an operando technique that enables depth-resolved measurement of solvation entropy, interfacial transport resistance, charge-transfer resistance, and SEI resistance at individual electrode-electrolyte interfaces within practical lithium-ion batteries. By leveraging frequency-dependent, thermal-wave sensing and interface-specific modeling, METS uniquely attributes interfacial properties to specific electrodes, as validated by comparison with traditional electrochemical impedance spectroscopy (EIS). The ability to spatially and temporally resolve interfacial processes in real time provides new diagnostic capabilities that are crucial for mechanistic studies of battery degradation and for the rapid development of next-generation energy storage systems.

Chalise, Divya [University of California, Berkeley↗

Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts

Abstract Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO 2 (111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An all optical approach for comprehensive in-operando analysis of radiative and nonradiative recombination processes in GaAs double heterostructures

We demonstrate an all optical approach that can surprisingly offer the possibility of yielding much more information than one would expect, pertinent to the carrier recombination dynamics via both radiative and nonradiative processes when only one dominant deep defect level is present in a semiconductor material. By applying a band-defect state coupling model that explicitly treats the inter-band radiative recombination and Shockley–Read–Hall (SRH) recombination via the deep defect states on an equal footing for any defect center occupation fraction, and analyzing photoluminescence (PL) as a function of excitation density over a wide range of the excitation density (e.g., 5–6 orders in magnitude), in conjunction with Raman measurements of the LO-phonon plasmon (LOPP) coupled mode, nearly all of the key parameters relevant to the recombination processes can be obtained. They include internal quantum efficiency (IQE), minority and majority carrier density, inter-band radiative recombination rate (W r ), minority carrier nonradiative recombination rate (W nr ), defect center occupation fraction (f), defect center density (N t ), and minority and majority carrier capture cross-sections (σ t and σ tM ). While some of this information is thought to be obtainable optically, such as IQE and the W r /W nr ratio, most of the other parameters are generally considered to be attainable only through electrical techniques, such as current-voltage (I-V) characteristics and deep level transient spectroscopy (DLTS). Following a procedure developed herein, this approach has been successfully applied to three GaAs double-heterostructures that exhibit two distinctly different nonradiative recombination characteristics. The method greatly enhances the usefulness of the simple PL technique to an unprecedented level, facilitating comprehensive material and device characterization without the need for any device processing.

14 SOLAR ENERGY↗

Chemical and Structural Insights into Solid Electrolyte Interphase Evolution for Sodium Metal Electrodes

The solid electrolyte interphase (SEI) critically governs the reversibility of sodium metal batteries, through dynamically mediating ion transport and interfacial reactions. However, its kinetic evolution under operating conditions, and how it influences interfacial stability, remains poorly understood. Here, in this study, we reveal that the SEI undergoes coupled chemical and mechanical changes during sodium plating and stripping, leading to spatial and temporal heterogeneity that drives interfacial degradation. Synchrotron operando grazing-incidence wide-angle X-ray scattering and soft X-ray absorption spectroscopy capture the sequential formation and dissolution of inorganic SEI phases (NaF, NaH, NaOH, Na 2 PO 3 F), accompanied by depth-dependent alterations in organic SEI components. Mesoscale modeling connects this evolving SEI heterogeneity to localized current density fluctuations and stress accumulation at the Na interface, identifying pathways to electrically isolated sodium formation. These findings show that SEI instability fundamentally limits reversibility in sodium metal batteries, and that controlling SEI chemistry–mechanics coupling is essential to achieving its durability.

36 MATERIALS SCIENCE↗

Low-Temperature Non-Oxidative Coupling of Methane on Atomically Dispersed Titanium–Aluminum–Boron Nanopowder

Nonoxidative coupling of methane represents a long-standing challenge in heterogeneous catalysis, as it requires activation of the carbon–hydrogen (C–H) bond, controlled carbon–carbon (C–C) bond formation, and effective hydrogen management without relying on oxidants. Here, we report a low-temperature C–H activation and nonoxidative C–C coupling of methane over atomically dispersed titanium–aluminum–boron nanopowder (Ti–Al–B NP) utilizing a catalytic microreactor coupled to synchrotron single-photon photoionization reflectron time-of-flight mass spectrometry. The soft-ionization, in situ probing method detects the nascent reaction products and radical intermediates under operando conditions, including methyl radical, C2 hydrocarbons, and molecular hydrogen. Methane activation is initiated at 800 K, approximately 700 K below the gas-phase decomposition threshold, leading predominantly to ethylene formation with selectivity reaching up to 78% among the C–C coupled products. Electronic structure calculations on model Ti–Al–B clusters elucidate a cooperative catalytic mechanism in which titanium enables methane adsorption and C–H activation, boron acts as a reversible hydrogen reservoir, and aluminum stabilizes methylene intermediates, thereby facilitating selective C–C coupling and dehydrogenation. These findings establish a distinct catalyst architecture for nonoxidative methane coupling based on earth abundant elements alternative to expensive platinum and other noble metal-containing conventional catalysts and provide molecular-level design principles for controlling dehydrogenation and subsequent C–C bond formation in challenging light alkane conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatially Resolved Potential and Li-Ion Distributions Reveal Performance-Limiting Regions in Solid-State Batteries

The performance of solid-state electrochemical systems is intimately tied to the potential and lithium distributions across electrolyte–electrode junctions that give rise to interface impedance. Here, we combine two operando methods, Kelvin probe force microscopy (KPFM) and neutron depth profiling (NDP), to identify the rate-limiting interface in operating Si-LiPON-LiCoO 2 solid-state batteries by mapping the contact potential difference (CPD) and the corresponding Li distributions. The contributions from ions, electrons, and interfaces are deconvolved by correlating the CPD profiles with Li-concentration profiles and by comparisons with first-principles-informed modeling. Furthermore, we find that the largest potential drop and variation in the Li concentration occur at the anode–electrolyte interface, with a smaller drop at the cathode–electrolyte interface and a shallow gradient within the bulk electrolyte. Correlating these results with electrochemical impedance spectroscopy following battery cycling at low and high rates confirms a long-standing conjecture linking large potential drops with a rate-limiting interfacial process.

25 ENERGY STORAGE↗

X‐Ray Scattering Reveals Ion‐Induced Microstructural Changes During Electrochemical Gating of Poly(3‐Hexylthiophene)

Abstract The heterogeneous microstructure of semicrystalline polymers complicates the relationship between their electrical conductivity and carrier concentration. Charge transport models typically describe conductivity with an assumption of uniform doping throughout the material. Here, the evolution in morphology and optoelectronic properties of poly(3‐hexylthiophene) (P3HT) is reported as a function of carrier concentration in an organic electrochemical transistor using a polymeric ionic liquid (PIL) as the gate insulator. Operando grazing incidence X‐ray scattering reveals that negatively charged ions from the dielectric first infiltrate the amorphous regions of the semiconductor, and then penetrate the crystalline regions at a critical carrier density of 4 × 10 20 cm −3 . Upon infiltration, the crystallites expand by 12% in the alkyl stacking direction and compress by 4% in the π–π stacking direction. The change in crystal structure of P3HT correlates with a sharply increasing effective carrier mobility. UV–visible spectroscopy reveals that holes induced in P3HT first reside in the crystalline regions of the polymer, which verifies that a charge carrier need not be in the same physical domain as its associated counterion. The dopant‐induced morphological changes of P3HT rationalize the dependence of mobility on carrier concentration, suggesting a phase transition of crystalline regions at high carrier concentration.

Thomas, Elayne M.↗

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗