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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Kinetically versus thermodynamically controlled factors governing elementary pathways of GaP(111) surface oxidation

GaP and related III-V semiconductors have attracted interest as high-efficiency photoelectrochemical electrodes for solar water splitting. However, their efficacy is linked to the presence, identity, and integrity of native surface oxides, which are structurally and chemically complex and evolve during operation. Using ambient pressure X-ray photoelectron spectroscopy (APXPS) coupled with ab initio simulations, we track key chemical motifs expressed during evolution of GaP(111) surface oxides, their associated reaction kinetics, and their correlations with electronic properties. We identify two distinct thermal regimes corresponding to kinetically and thermodynamically controlled oxidation. Below 600 K, exposure to O2 generates kinetically facile Ga-O-Ga configurations, whereas higher temperatures cause activated oxygen to insert into Ga–P bonds as part of a thermodynamically driven transformation into a complex, heterogeneous 3D network of surface POx (1≤x ≤ 4) groups and Ga2O3 species, the latter of which eventually dominates upon depletion of surface phosphorus. Here our study highlights the critical competition between kinetic and thermodynamic factors during GaP oxidation, yielding insights for fabricating stable III-P-based photoelectrodes with precisely engineered surface properties.

08 HYDROGEN↗
DOE OSTI2020

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism allows the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In current research using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13 C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chapter 14: Dynamic Flux Analysis: An Experimental Approach of Fluxomics

Metabolic flux analysis represents an essential perspective to understand cellular physiology and offers quantitative information to guide pathway engineering. A valuable approach for experimental elucidation of metabolic flux is dynamic flux analysis, which estimates the relative or absolute flow rates through a series of metabolic intermediates in a given pathway. It is based on kinetic isotope labeling experiments, liquid chromatography-mass spectrometry (LC-MS), and computational analysis that relate kinetic isotope trajectories of metabolites to pathway activity. Herein, we illustrate the mathematic principles underlying the dynamic flux analysis and mainly focus on describing the experimental procedures for data generation. This protocol is exemplified using cyanobacterial metabolism as an example, for which reliable labeling data for central carbon metabolites can be acquired quantitatively. This protocol is applicable to other microbial systems as well and can be readily adapted to address different metabolic processes.

BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Characterizing and Engineering Trehalose Biosynthesis Pathways to Improve Acetate Tolerance in Pseudomonas putida KT2440

Alkaline pretreatment can depolymerize lignin into a diverse mixture of monomers and smaller compounds, enabling bioconversion of these compounds to value-added chemicals in engineered bacterial hosts such as Pseudomonas putida KT2440. Acetate and salts comprise approximately 8% and 32% of the lignin stream, respectively. High concentrations of these components can cause cell death in P. putida, so lignin-derived streams must be fed in lower amounts to decrease stress. Investigation of the mechanisms of bacterial tolerance to chemicals in lignin-rich substrates is therefore required to overcome this obstacle in lignin bioconversion. Previous work has shown that trehalose, an endogenously produced disaccharide, is involved in tolerance to heat, cold, and osmotic stress, as well as implicated in acid stress in other bacteria. As such, trehalose biosynthesis presents a useful target to increase acetate and osmotic tolerance in P. putida. This work investigates the native TreSA, TreSB, and TreY/TreZ trehalose biosynthesis pathways in this bacterial strain as well as the OtsAB pathway of Sphingobium sp. SYK-6. Overexpression of the OtsAB pathway in P. putida increased tolerance to acetate relative to wild-type. Additionally, functional knockouts of treSA, treSB, treY, and treZ in P. putida showed that interruption of any trehalose biosynthesis pathway, and, in the case of TreY/TreZ, interruption of the pathway at any point, significantly hindered growth in acetate as well as on glucose and LB broth. Each trehalose biosynthesis pathway was then engineered for overexpression in P. putida to determine whether overexpression of these genes conferred additional tolerance to acetate. The TreSA, TreSB, OtsA, and OtsB enzymes were also expressed and purified to determine the reaction rates and kinetics of these pathways. The hypothetical glycoside hydrolase family 15 protein, encoded in the gene located in between otsB and otsA in the Sphingobium operon, was purified as well to investigate its potential involvement in the OtsAB pathway. The findings of this work illuminated the mechanisms of trehalose biosynthesis in P. putida and identified genetic targets to improve strain tolerance to common components of alkaline-pretreated lignin streams. These findings could ultimately improve yields of desired products from lignin in engineered strains of P. putida.

alkaline pretreatment↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Comparisons of bpy and phen Ligand Backbones in Cr-Mediated (Co-)Electrocatalytic CO 2 Reduction

Due to the rise in atmospheric carbon dioxide (CO 2 ) concentrations, there is a need for the development of new strategies to enhance the selectivity and activity of the electrocatalytic conversion of CO 2 to value-added products. The incorporation of redox mediators (RMs) as co-catalysts to enhance the transfer of redox equivalents during catalysis has been gaining more attention in recent years across a variety of small molecule transformations. We have shown that using Cr-centered complexes with sulfone-based RMs leads to an enhancement of CO 2 reduction electrocatalysis under protic conditions via an inner-sphere mechanism. In these co-catalytic systems, an oxygen atom of the reduced RM binds to the Cr center to form a key intermediate stabilized by pancake bonding between the reduced aromatic components of the catalyst ligand backbone and the RM. This interaction facilitates the transfer of an electron and accesses a more kinetically favorable reaction pathway. Here, we show that expanding the aromatic character of the ligand backbone of the catalyst as well as the RM can cause a greater enhancement of co-electrocatalytic activity. These results suggest that further activity improvements can be achieved by focusing on the kinetic and thermodynamic parameters which control association between the catalyst and RM.

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

Electrochemically-Induced Phase Transformations in Battery Storage Compounds (Final Technical Report)

Compounds of interest for ion storage in advanced batteries frequently exhibit phase transformations as the working ion concentration varies. Under large electrochemical driving forces inherent to practical use, systems are often driven far from equilibrium. This program combines experiments and theory to understand the phase transition behavior of ion insertion compounds when electrochemically driven far from equilibrium. As model systems, we focus on alkaline metal phosphates AMPO4 (A = alkali; M = first row transition metal) of olivine structure, which are both technologically interesting and ideally suited for fundamental study due to the ability to systematically tune transformation strain, and along with it, the phase transformation pathway. Behavior in compositions having large transformation strains (~15 vol%) requiring plasticity for strain accommodation is emphasized. Experimental techniques include operando characterization of structure while simultaneously varying electrokinetic parameters, and high resolution microscopy of nanoscale and interfacial phenomena. Phase-field modeling is used to model the thermodynamics and kinetics of competing transformation pathways, extended to include the effects of plasticity, and integrated with porous electrode kinetic theory to treat multi-particle effects. Success in this project will lead to an ability to design ion storage compounds with predictable transformation pathways, electrochemical kinetics, capacity utilization, and durability. New technologically important compounds may also be discovered.

36 MATERIALS SCIENCE↗
DOE OSTI2025

dynamics of organic-mineral interactions at the metal oxide-solution interface as studied via binding energetics (Final report)

This project focused on addressing longstanding fundamental and experimental uncertainties on how dissolved organic substances (DOS) interact with metal oxide surface under environmentally relevant conditions. By leveraging a custom-built real-time, in-tandem flow adsorption microcalorimetry-UV-Vis/fluorescence spectroscopy platform, we characterized the binding energetics, kinetics and mechanistic pathways driving DOS-metal oxide interactions at temporal resolution on the order of 1-5 seconds. We studied a diverse suite of model organic compounds/substances – including monocarboxylates (e.g. acetate and benzoate), di-carboxylates (oxalate and succinate), amino acids, amino-based nanparticles and natural organic matter – interacting at the mineral-water interface of structurally- and/or chemically distinct metal oxides (including SiO2, boehmite, ferrihydrite, and γ-Al2O3). Our results indicated that DOS-metal oxide interactions are governed by multi-step reaction pathways, often switching between distinct, resolvable enthalpy- and entropy-driven non-electrostatic or electrostatic configurations. To quantify these interactions, we developed and implemented an analytical workflow that integrates peak deconvolution and Monte-Carlo based error propagation to determine site-specific thermodynamic and kinetic parameters for individual binding/debinding events. In addition to resolving apparent first-order rate constants of each event, we were able to quantify associated apparent equilibrium constants as well as free energy, enthalpy and entropy contribution to the activation and subsequent progression of the binding/debinding process across compounds, compound class and metal oxide surfaces. The kinetic-thermodynamic data produced in this study captured how the interplay between oxide surface reactivity and DOS molecular structure jointly drives binding-debinding dynamics. Notably, that at pH below PZC of the oxide surface, neutral species were heavily involved in monocarboxylate binding, while anionic species drove dicarboxylate binding. Also, that among amino acids 1) positional isomers show distinctive binding characteristics to each other while enantiomers show no significant differences in binding characteristics, 2) molecules that bind via outer-sphere complexation show a larger entropic shift between binding and debinding with no impact on oxide surface while 3) inner-sphere interactions increased anion exchange capacity of the oxide surface. The new insights and data from this work has great potential for improving predictive modeling of carbon dynamics and specifically organic-mineral interactions in environmental and industrial systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Effect of Strength of Soluble and Solid Acid Catalysts on Selectivity in Aldol Reactions

Aldol reactions can follow the classical condensation path and produce an α,β-unsaturated carbonyl compound and water, however in some cases, aldol chemistry may be steered towards a fission that gives an olefin and a carboxylic acid. This investigation examines how the strength of Brønsted acid sites—both in homogeneous and heterogeneous catalysis—controls these two pathways and their kinetics. The cross-aldol reaction between benzaldehyde and 3-pentanone served as test case. Batch reactions, conducted in toluene as solvent at a temperature of 140 °C under autogenous pressure, were analyzed by GC and in situ ATR-FTIR spectroscopy to determine product distributions and rate constants for condensation and fission pathways. A series of soluble acids including a family of sulfonic acids mostly favored the condensation pathway, with formic acid as the weakest in the series by its pKa being inactive for aldol chemistry. Significant amounts of fission products were rare except for the known selectivity of phosphoric acid, and the circumstances were difficult to delineate. For the sulfonic acid family, the logarithm of the first-order condensation rate constants scaled only roughly with pKa (water) values, whereas a good correlation was obtained with calculated deprotonation Gibbs energies in toluene. A series of H-forms of isomorphously substituted beta zeolites, HESiBEA with E = Al, Ga, Fe, or B, favored the fission pathway. Site density and site strength were characterized by calorimetric measurements of the heats of adsorption of isopropylamine, which decreased in the order Al > Ga, Fe > B. The logarithm of the site-normalized first-order fission rate constants scaled roughly with the heats of adsorption and correlated excellently with reported deprotonation energies. In conclusion, acid strength mainly affects activity and can be seen as a pre-requisite for either aldol condensation or fission chemistry, whereas additional, yet to be full clarified catalyst properties and reaction conditions are required to steer aldol chemistry towards fission selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Experimental and computational investigations of ethane and ethylene kinetics with copper oxide particles for Chemical Looping Combustion

In this work, reaction pathways for the oxidation of methane, ethane, and ethylene with CuO was obtained by ReaxFF Molecular Dynamics (MD) simulations between temperatures of 1000 K and 2000 K. Experiments in a fixed-bed flow reactor were preformed with methane, ethane, and ethylene at temperatures ranging from 500 K to 1000 K with time-dependent species measurements from an Electron-Ionization Molecular Beam Mass Spectrometer (MBMS), and species validation with Gas Chromatography (GC) for detection of complete and intermediate combustion products. The MBMS and GC allow for the detection of oxygenated species and larger species produced from radical reformation. The simulation and experiment agree on the production of such species as CH 3 CHO, CH 2 O, CO, and H 2 O, which allow for the creation of simple C1 and C2 reaction pathways, which can be used in kinetic models of C2 species and larger fuels such as biofuels, which inherently depend on C1 and C2 kinetics and reaction pathway. The simulation and experiment disagree on the formation of C 2 H 2 , CH 3 OH, and CO 2 with large amounts of C 2 H 2 being measured in the ethylene oxidation simulations and CH 3 OH being formed in methane oxidation simulations, while neither species were experimentally found. In the case of CO 2 large amounts of CO 2 are rapidly produced in experiments with C2 fuels at 800 K, while little-to-no CO 2 was observed in simulations. This is believed to be resulting from the extremely short timescale of the simulations, preventing total oxidation of the fuel. Here, the differences in products produced between simulation and experiment allow for the potential to modify the ReaxFF potential functions to more accurately model the experimental products of Cu–H–O–C reaction kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Aldehyde cool-flame chemistry explains a missing source of organic acids

Combustion emission is a significant source of organic acids, impacting atmospheric chemistry and climate. Their formation mechanisms, however, remain poorly understood, leading to underestimation in kinetic models. We investigate the cool-flame oxidation of key combustion intermediates—C 1 –C 4 aldehydes and benzaldehyde. Using in-situ synchrotron vacuum ultraviolet photoionization mass spectrometry, we observe the direct conversion of aldehydes to organic acids, a process enhanced by HO 2 radicals. Quantum chemistry calculations reveal that the reaction of RC(O)O 2 with HO 2 on the singlet potential energy surface contributes to organic acids. Incorporating this pathway into a kinetic model significantly improves organic acid prediction. Despite the high-temperature nature of engine combustion, significant spatial and temporal inhomogeneities (e.g., near-wall regions and crevice volumes) lead to localized cool-flame conditions, facilitating organic acid formation and emission. Elucidating the acid formation under cool-flame conditions provides a critical mechanism for accurately modelling anthropogenic organic acid emissions and developing mitigation strategies.

SVUV-PIMS↗
DOE OSTI2024

Elucidating the formation mechanisms of zeolites using data-driven modelling and in-situ characterization

Zeolites are the main solid catalysts used by the chemical industry. The use of zeolites in separations and as shape selective catalysts requires control of the width and connectivity of their pores. 235 distinct zeolite frameworks have been synthesized to date, of over 2 million that have been proposed. Recent work indicates that the limitation is in large part kinetic: new synthetic pathways are required to access new zeolites. Organic cations are used to direct the synthesis towards specific zeolites. However, the molecular mechanisms by which cations direct the nucleation towards specific zeolites is not known. Elucidating these mechanisms is key to realize new zeolites for catalysis and separations, and is the focus of this project. This project developed and implemented a synergistic, data-driven computational and experimental approach to resolve the molecular pathways of nucleation, growth, and polymorph selection of zeolites and the role of organic cations in directing their formation. The project developed computationally efficient and accurate models for the study of the nucleation and growth of pure silica zeolites in molecular simulations, using machine learning with data from experiments. Simulations with these models were integrated with scanning tunneling electron microscopy, computer vision, and deep learning to unveil the molecular pathways of formation of a zeolite. Of particular interest in this project was to elucidate the role of amorphous precursors in the nucleation of the zeolite. Previous experiments indicate that zeolites are born within non-crystalline aggregates in which the silicates and organic cations have local and medium range order similar to that of the zeolite. The organic cations that direct the formation of zeolites and those that direct the formation of ordered mesoporous silicas are similar. We hypothesized that the frustrated attraction that for large organic cations leads to the formation of stable mesophases that direct the synthesis of mesoporous silicas, could promote the formation of metastable mesophases that can assist in the nucleation and polymorph selection of zeolites. The simulations resolved how structure directing agents build crystalline order and showed that mesoscopic pre-ordering occurs is not required to facilitate the nucleation of zeolites, because the synthesis occurs at high driving forces, where the barriers for nucleation are negligible. This project unveiled that polymorph selection in zeolite synthesis occurs after nucleation, opening a distinct area of control through the kinetics of growth and not through nucleation barriers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Observing and Modeling the Sequential Pairwise Reactions that Drive Solid‐State Ceramic Synthesis

Abstract Solid‐state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing reaction conditions and precursors for ceramic synthesis can be a laborious, trial‐and‐error process, as heterogeneous mixtures of precursors often evolve through a complicated series of reaction intermediates. Here, ab initio thermodynamics is used to model which pair of precursors has the most reactive interface, enabling the understanding and anticipation of which non‐equilibrium intermediates form in the early stages of a solid‐state reaction. In situ X‐ray diffraction and in situ electron microscopy are then used to observe how these initial intermediates influence phase evolution in the synthesis of the classic high‐temperature superconductor YBa 2 Cu 3 O 6+ x (YBCO). The model developed herein rationalizes how the replacement of the traditional BaCO 3 precursor with BaO 2 redirects phase evolution through a low‐temperature eutectic melt, facilitating the formation of YBCO in 30 min instead of 12+ h. Precursor selection plays an important role in tuning the thermodynamics of interfacial reactions and emerges as an important design parameter in planning kinetically favorable synthesis pathways to complex ceramic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A reversible four-electron Sn metal aqueous battery

Sn is a promising metal anode for aqueous batteries, with up to four-electron redox available per atom (903 mAh g −1 Sn ). However, practically harnessing the four-electron Sn(OH) 6 2− /Sn reversibility remains challenging due to limited mechanistic understanding. Here, in this study, we reveal a kinetically asymmetric redox pathway involving a successive four-electron plating and a stepwise 2 + 2 electron stripping through a Sn(OH) 3 − intermediate. The crossover of Sn(OH) 3 − induces a reversible self-discharge that reduces Coulombic efficiency but does not impact cyclability, demonstrated by four-electron Sn-Ni full cells that sustain >800 h of stable cycling. By tuning the ion selectivity of the separator to suppress Sn(OH) 3 − crossover while allowing OH − transport, we further demonstrate high Sn utilization (67%) and high energy density (143.1 Wh L −1 cell). The results provide key understandings of the tradeoffs in engineering reversible multi-electron metal anodes and define a new benchmark for practical energy density that exceeds any Sn-based aqueous batteries to date.

SN anode↗
DOE OSTI2020

Formation and energetics of amorphous rare earth (RE) carbonates in the RE 2 O 3 –CO 2 –H 2 O system

Amorphous materials are of interest in the genesis of crystalline solids. They are often the first to precipitate from supersaturated solutions and are in the nanometer size range, transforming into a nanocrystalline metastable phase, and then to thermodynamically stable phases. One must seek knowledge of the composition, structure, thermodynamics, kinetics, and reaction pathways that relate the amorphous and crystalline phases. The subject of this study is the amorphous phases in the system RE 2 O 3 -CO 2 –H 2 O (RE- La, Nd, Dy,Yb). They were synthesized via direct precipitation and urea hydrolysis, and characterized by powder XRD, DTA with mass spectrometric analysis of the evolved gases. Phases have the non-stoichiometric composition RE 2 O 3 ·xCO 2 ·yH 2 O (1 < x < 3, 3 < y <7), which is different from that of crystalline simple carbonates and hydroxycarbonates. Thus we consider them to be amorphous precursors, rather than amorphous carbonates. High temperature oxide melt solution calorimetry in molten sodium molybdate solvent was used to derive their enthalpies of formation from oxides and elements. Increase of energetic stability per mole of RE 2 O 3 compounds occurs in the order: RE 2 O 3 → 2RE(OH)3→ 2REO(OH) → RE 2 O 2 CO 3 → Amorphous precursor → 2(REOHCO 3 ) → RE 2 (CO 3 ) 3 ·yH 2 O. We calculated the enthalpies of possible transformations of amorphous precursors to crystalline phases and conclude that thermodynamics determines the dependence of the crystallizing products on the temperature and partial pressure of CO 2 and H 2 O. Amorphous precursors are clearly intermediate in the synthesis, and ternary phases containing both H 2 O and CO 2 compete with each other in terms of thermodynamic stability. The energy landscape obtained here will allow one to directly synthesize specific products and control their functionality.

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

Spatiotemporal and Statistical Mapping of Transition Metal Equilibria in Alkaline Media

Transition metal dissolution and redeposition (D/R) kinetics in alkaline media play a critical role in various chemical and electrochemical processes. Competitive reaction kinetics between different transition metals can modulate individual metal behavior in these processes. To date, these phenomena have remained largely unmeasured, and even when captured, they are difficult to statistically characterize due to their dynamic nature, simultaneous occurrence, and spatially heterogeneous nature. Here, in this study, we develop a statistical analysis framework based on in situ and operando X-ray fluorescence microscopy (XFM) to investigate the relative D/R kinetics of multiple transition metals in alkaline media. By employing statistical analysis, we quantify the spatial distribution of D/R species and assess the rate at which the system reaches equilibrium under varying reaction conditions. We show that pH does not simply change the rate of dissolution and redeposition, but reorganizes the cross-element kinetic correlations among Ni, Fe, and Mn and accelerates the spatial equilibration of D/R events, as quantified through correlation analysis, reaction-rate estimation, probability function distributions, and texture-based monitoring statistics. Additionally, we demonstrate how modifying the solvent environment can influence D/R kinetics, providing a pathway for tuning materials synthesis and process optimization. Our study offers valuable insights into the complex interplay between different transition metals and provides a reliable statistical framework for spatial analysis of diverse imaging data sets, enabling deeper extraction of latent information across multiple modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In Situ Visualization of the Pinning Effect of Planar Defects on Li Ion Insertion

Longevity of Li ion batteries strongly depends on the interaction of transporting Li ions in electrode crystals with defects. However, detailed interactions between the Li ion flux and structural defects in the host crystal remain obscure due to the transient nature of such interactions. Here, by in situ transmission electron microscopy and density function theory calculations, we reveal how the diffusion pathways and transport kinetics of a Li ion can be affected by planar defects in a tungsten trioxide lattice. We uncover that changes in charge distribution and lattice spacing along the planar defects disrupt the continuity of ion conduction channels and dramatically increase the energy barrier of Li diffusion, thus, arresting Li ions at the defect sites and twisting the lithiation front. In conclusion, the atomic-scale understanding holds critical implications for rational interface design in solid-state batteries and solid oxide fuel cells.

25 ENERGY STORAGE↗