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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 73 records · Page 4

Fluoropolymer Aging Phenomena

This project aims to investigate structural and morphological changes in fluoropolymers induced by both processing and aging phenomena such as heat, time, and irradiation. Fluoropolymers are an important class of thermoplastics that are broadly used in industry as o-rings and seals when chemical resistance and thermal performance are important. They are also often used in thin film geometries as binders in batteries, insulation layers, water barriers, and anti-fouling coatings. For all of these applications, mechanical integrity and aging are important aspects of their use. Changes in the crystalline morphology are known to impact the mechanical properties of the polymer and can lead to failure. The broad goals of this project are to correlate compositional changes, morphological changes, and mechanical changes. report focuses on the morphological changes that are correlated with nuclear magnetic resonance (NMR), calorimetry and mechanical testing. We plan to compare structure and morphology measurements across complementary bulk and surface techniques. We use in situ atomic force microscopy (AFM) to measure domain shape and crystallization kinetics; in situ NMR to measure crystalline composition; and differential scanning calorimetry (DSC) to measure melting temperatures.

36 MATERIALS SCIENCE↗

A review of low-rank methods for time-dependent kinetic simulations

Time-dependent kinetic models are ubiquitous in computational science and engineering. The underlying integro-differential equations in these models are high-dimensional, comprised of a six–dimensional phase space, making simulations of such phenomena extremely expensive. In this article we demonstrate that in many situations, the solution to kinetics problems lives on a low dimensional manifold that can be described by a low-rank matrix or tensor approximation. We then review the recent development of so-called low-rank methods that evolve the solution on this manifold. The two classes of methods we review are the dynamical low-rank (DLR) method, which derives differential equations for the low-rank factors, and a Step-and-Truncate (SAT) approach, which projects the solution onto the low-rank representation after each time step. Thorough discussions of time integrators, tensor decompositions, and method properties such as structure preservation and computational efficiency are included. We further show examples of low-rank methods as applied to particle transport and plasma dynamics.

97 MATHEMATICS AND COMPUTING↗

Kinetic Model of HoxEFU reduction by NADH [SWR-26-087]

This repository is used to release code generated for manuscripts on the Photosynthetic Energy Transduction core program. This code simulates the reduction of HoxEFU by NADH. The electro transfer rate constants for the simulation are specified in the .csv files. The two .csv files correspond tot he two models described in Dawson et al. Cell. Rep. Phys. Sci. 2026. The code utilizes a chemical master equation, a set of differential equations, defining the time evolution of the oxidation and reduction kinetics of NAD+, NADH, a FMN flavin, and a set of iron sulfur clusters. The kinetics of HoxEFU reduction by NADH are evaluated by numerical integration of the chemical master equation using a variable-time-step Runge-Kutta algorithm.

Dahl, Peter [National Laboratory of the Rockies (N↗

Site-Differentiated Iron–Sulfur Cluster Ligation Affects Flavin-Based Electron Bifurcation Activity

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP+ oxidoreductase (NfnSL), which couples the thermodynamically favorable reduction of NAD+ to drive the unfavorable reduction of ferredoxin from NADPH. The interaction of NfnSL with its substrates is constrained to strict stoichiometric conditions, which ensures minimal energy losses from non-productive intramolecular electron transfer reactions. However, the determinants for this are not well understood. One curious feature of NfnSL is that both initial acceptors of bifurcated electrons are unique iron–sulfur (FeS) clusters containing one non-cysteinyl ligand each. The biochemical impact and mechanistic roles of site-differentiated FeS ligands are enigmatic, despite their incidence in many redox active enzymes. Herein, we describe the biochemical study of wild-type NfnSL and a variant in which one of the site-differentiated ligands has been replaced with a cysteine. Results of dye-based steady-state kinetics experiments, substrate-binding measurements, biochemical activity assays, and assessments of electron distribution across the enzyme indicate that this site-differentiated ligand in NfnSL plays a role in maintaining fidelity of the coordinated reactions performed by the two electron transfer pathways. Given the commonality of these cofactors, our findings have broad implications beyond electron bifurcation and mechanistic biochemistry and may inform on means of modulating the redox balance of the cell for targeted metabolic engineering approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Transient-Response methodology based on experiments and modeling for Cu-Redox Half-Cycle kinetic analysis on a Cu-SSZ-13 SCR catalyst

In this report the Standard SCR reaction catalyzed by Cu-SSZ-13 is a redox process consisting of a reduction half cycle (RHC) and an oxidation half cycle (OHC) that cycle the active Cu sites between the Cu(II) and Cu(I) states. In the current work, a transient-response methodology consisting of experimental transient response Cu-redox (TRCR) measurements and kinetic modeling was developed for detailed study of individual SCR Cu-redox half cycles. The TRCR protocol allows quantification of the reducible Cu density, Cu(II)-Cu(I) partitioning, relative native RHC and OHC rates, and limiting half cycle during SCR. The half-cycle kinetics are studied over a wide (170–450 °C) temperature, and in differential segments along the catalyst length using spatially resolved capillary inlet mass-spectrometry (SpaciMS). The protocol alone provides two independent measures indicating that OHC increases faster than RHC with temperature, and that at all but the lowest temperature SCR is RHC limited. Introducing the transient kinetic models allows half-cycle reaction pathways, orders and activation energies to be studied and determined; e.g., RHC involves surface and gas-phase NH 3 routes, and OHC with O 2 involves dimer formation. Application of the full methodology provides further confirmation and quantification of the protocol conclusions, and specifically the first measurements of RHC and OHC activation energies; specifically for parallel RHC surface and gas-phase routes, and experimentally obtained OHC activation energy vs. first-principle calculations in the literature. Beyond insights related to the degreened catalyst studied here, the methodology provides a broadly available approach for quantifying how aging processes selectively impact RHC and OHC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Silicon alloying enhances fast heating rate combustion of aluminum particles

Alloys and composites of aluminum (Al) have shown promise in regulating and enhancing particle combustion for energy generation applications. Recent work on aluminum-silicon (Al-Si) spherical alloy particles has shown improved combustion at low heating rates through enhanced diffusion accompanying a lower melting temperature. This study extends reactivity analysis to higher heating rates, comparing oxidation of Al-Si with Al. Flame speeds of Al-Si powder mixed with molybdenum trioxide (MoO 3 ) powder (Al-Si+MoO 3 ) exhibited a faster transition to steady propagation relative to Al+MoO 3 . Bomb calorimetry experiments revealed up to 5.8% greater early temperature rise for Al-Si powder. Rapid steady propagation for Al-Si mixture and faster temperature rise for Al-Si particles were attributed to accelerated kinetics evidenced in thermal equilibrium analysis of the mixtures using a differential scanning calorimeter (DSC). Larger DSC exotherms in the early stages of oxidation (i.e., 480–720 °C) correlated with early heat release and promoted steady flame propagation for Al-Si+MoO 3 compared with Al+MoO 3 . Furthermore, in multiple heating rate DSC studies, Al-Si+MoO 3 ignited at a lower heating rate (i.e., 15 ⁰C/min) than Al+MoO 3 (i.e., 20 ⁰C/min). Both mixtures ignited at temperatures less than 625 °C which is above the melting temperature of Al-Si (574 °C) and below Al (659 °C). Thus, alloy particle fuels with enhanced diffusion-controlled kinetics promote steady flame propagation and show promise for energy generation applications. This is especially promising for technologies driven by enhanced condensed phase combustion such as some propellant additives or applications dependent on reliable burn rates such as pyrotechnic time delay formulations and primers.

36 MATERIALS SCIENCE↗

Statistical distributions for transient transport

Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.

TAP reactor↗

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗

First inclusive triple-differential measurement of the muon-antineutrino charged-current cross section using the NOvA Near Detector

We present the first measurement of the triple-differential muon antineutrino charged-current inclusive cross section, using the NOvA Near Detector and $12.5 \times 10^{20}$ protons on target in the NuMI beam. This sample of muon antineutrino interactions is the largest ever published, with approximately 1 million selected muon antineutrino events. The triple-differential cross section is measured in the final-state kinetic energy, the scattering angle, and the available energy of the interaction. The measurement enables phase-space regions populated by differing neutrino reaction processes to be isolated and the transition regions between them to be defined. The results are compared with the predictions of the main event generators used in the neutrino community and we observe energy- and angle-dependent discrepancies across a broad range of energies and interaction types

Abubakar, S. [Erciyes U.]↗

Spectrometer-free quantitative vapor sensing and classification via spatiotemporal imaging of porous silicon metasurfaces

Metasurfaces offer a compact platform for optical vapor sensing, but their practical deployment has been limited by weak evanescent light–matter interactions and reliance on spectrally resolved instrumentation. Here, we report porous silicon (pSi) metasurfaces for spectrometer-free quantitative detection of volatile organic compounds (VOCs) with strongly enhanced light–matter interaction. The engineered porosity increases sensitivity by >100× relative to non-porous dielectric metasurfaces, enabling limits of detection of 1.65 ppm for methanol and 9.1 ppm for ethanol across a broad dynamic range (<10 ppm to >103 ppm). Imaging-based readout provides a lightweight, spectrometer-free pathway for real-time quantitative sensing. Beyond quantitative detection, the mesoporous architecture introduces adsorption–desorption kinetics as an additional information channel. Analysis of the resulting spatiotemporal signatures enables kinetic fingerprinting without reliance on infrared spectral features or surface functionalization, and a lightweight machine-learning classifier differentiates acetone, methanol, ethanol, and isopropanol with 91.6% accuracy. These results establish porous metasurfaces as spatiotemporal sensing elements that couple quantitative vapor detection with kinetic fingerprinting through real-time dynamical responses, enabling low-cost, high-performance optical sensors.

Dash, Tomoshree [Clemson University]↗

Stability analysis of a one-dimensional multiphysics model of a molten salt fast reactor

Reactor designs with a fast neutron spectrum have recently moved into the research focus for possible Generation IV reactor concepts - a representative of which is the molten salt fast reactor (MSFR). In order to assess the safety and reliability of this reactor concept, it is necessary to obtain knowledge of the system behaviour. An important part of this research concerns the dynamical stability of the MSFR. Research regarding the MSFR stability so far has either been using linearized models for stability criteria or only been examining certain transients at fixed parameter values. This work delivers a comprehensive stability analysis for a non-linearized MSFR model, and a wide range of values for all relevant parameters. For this purpose, a one-dimensional MSFR model was set up, taking neutron kinetics and thermal hydraulics in the form of a system of differential equations into account. The stability of this model was investigated by means of the numerical tool MATCONT, which was used to monitor the evolution of a so-called fixed-point solution, here referring to the steady state at operating conditions of the system, while system parameters got varied. The MATCONT analyses showed no loss of stability for any of the considered parameter variations and no solutions that might co-exist in parallel with the steady-state fixed-point solution. Therefore these results indicate a stable fixed point to which all solution transients converge, making the considered MSFR model insusceptible to deviations from the equilibrium. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Measurement of the muon neutrino charged-current mesonless cross section in the NOvA near detector

NOvA is a long-baseline accelerator neutrino experiment at Fermilab. Its physics goals include precision neutrino oscillation measurements, neutrino interaction cross-section measurements and beyond Standard Model explorations. We present a measurement of muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is performed as a function of the kinematics of the final state muon. Our chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and it provides handles for constraining the cross section systematic uncertainties in oscillation analyses in present and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA Near detector. This allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. We study strategies for constraining the remaining charged-pion background via Michel electron information in a template fitting approach. The main experimental result is a two-dimensional differential cross section as a function of final-state muon kinetic energy and polar angle. The parameters of this measurement, including binning and unfolding, were optimized to reduce the expected systematic uncertainty in the total cross section. The final result shows good agreement with the main GENIE-based simulation framework that was independently fine-tuned in NOvA. We finally propose improvements and subsequent steps that build on this analysis and further dissect the final states of neutrino interactions. This work has been supported by US DOE grant DE-SC0015684.

Sánchez Falero, Sebastián Jesús [Iowa State U.]↗

Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control

The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.

catalysts↗

Investigations on the Thermal Stability and Kinetics of Biolubricants Synthesized from Different Types of Vegetable Oils

Petroleum-based lubricants raise environmental concerns due to their non-biodegradability and toxicity, whereas biobased lubricants underperform owing to low thermal stability. This study examined and compared three vegetable oils, along with their chemically modified versions, to better understand their suitability as biolubricants. High oleic soybean oil (HOSOY), regular soybean oil (RSOY), and waste cooking oil (WCO) were subjected to chemical modification, where isopropyl groups were attached to the fatty acid chains of the oils to produce branched oils, i.e., b-HOSOY, b-RSOY, and b-WCO. The detailed kinetic study of each regular and modified sample was investigated using thermogravimetric analysis. The kinetic parameters, such as the activation energies, reaction rate, and pre-exponential factor, were generated via Friedman methods. The differential thermal gravimetric (DTG) analysis showed low volatilization at the onset temperature in each modified oil as compared with the unmodified samples under an oxidative environment. Furthermore, the comparative kinetic studies demonstrated the enhanced thermoxidative stability of the modified products relative to their unaltered counterparts. Among the tested oils, the b-RSOY showed an average activation energy of 325 kJ/mol, followed by the b-WCO: 300 kJ/mol and the b-HOSOY: 251 kJ/mol, indicating the most stable modified product under an oxidative environment. For all the samples, the pre-exponential factors were in good agreement with the activation energies, which validates that finding the pre-exponential components is crucial to the kinetic analysis.

Sarker, Majher I. (ORCID:0000000299509274)↗

Thermal Decomposition Kinetics of 4,6‐Diamino‐5,7‐dinitro‐benzo‐furazan

This experimental study investigated the thermal decomposition kinetics of 4,6-diamino-5,7-dinitro-benzo-furazan (referred to as F1 hereafter)—an important decomposition product of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB—a prototypical insensitive high explosive). Simultaneous differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and mass spectrometry (MS) measurements were employed to determine the decomposition kinetics of F1 and to track the evolution of product gases. The DSC profiles were measured at 10 different heating rates between 0.025°C/min and 10°C/min. The measured exotherms were influenced by F1 melting at heating rates above 0.25°C/min, and corresponding changes in decomposition enthalpy and TGA mass-loss-rate profiles indicated a transition from solid-to-gas decomposition to an increasing contribution from liquid-to-gas decomposition. Analysis of low-heating-rate DSC data between 0.025°C/min and 0.17°C/min with the extended Prout–Tompkins model yielded an activation energy of 305 kJ/mol for solid-to-gas F1 decomposition, higher than previous values inferred from TATB decomposition models involving F1. This study provides the first direct experimental determination of the energy barrier for F1 decomposition. MS measurements showed that the major gaseous products matched species previously reported for TATB decomposition (e.g., CO 2 , HCN, C 2 N 2 , etc.), with water identified as the dominant product. Furthermore, these results provide important experimental constraints for improving chemical kinetics models of TATB decomposition and for predicting the reactivity, stability, and safety of TATB-based high explosives under long-term aging conditions and abnormal thermal environments.

4,6-Diamino-5,7-dinitro-benzo-furazan↗

Dissipation measures in weakly collisional plasmas

ABSTRACT The physical foundations of the dissipation of energy and the associated heating in weakly collisional plasmas are poorly understood. Here, we compare and contrast several measures that have been used to characterize energy dissipation and kinetic-scale conversion in plasmas by means of a suite of kinetic numerical simulations describing both magnetic reconnection and decaying plasma turbulence. We adopt three different numerical codes that can also include interparticle collisions: the fully kinetic particle-in-cell vpic, the fully kinetic continuum Gkeyll, and the Eulerian Hybrid Vlasov–Maxwell (HVM) code. We differentiate between (i) four energy-based parameters, whose definition is related to energy transfer in a fluid description of a plasma, and (ii) four distribution function-based parameters, requiring knowledge of the particle velocity distribution function. There is an overall agreement between the dissipation measures obtained in the PIC and continuum reconnection simulations, with slight differences due to the presence/absence of secondary islands in the two simulations. There are also many qualitative similarities between the signatures in the reconnection simulations and the self-consistent current sheets that form in turbulence, although the latter exhibits significant variations compared to the reconnection results. All the parameters confirm that dissipation occurs close to regions of intense magnetic stresses, thus exhibiting local correlation. The distribution function-based measures show a broader width compared to energy-based proxies, suggesting that energy transfer is co-localized at coherent structures, but can affect the particle distribution function in wider regions. The effect of interparticle collisions on these parameters is finally discussed.

79 ASTRONOMY AND ASTROPHYSICS↗

First Simultaneous Measurement of Differential Muon-Neutrino Charged-Current Cross Sections on Argon for Final States with and without Protons Using MicroBooNE Data

We report the first double-differential neutrino-argon cross section measurement made simultaneously for final states with and without protons for the inclusive muon neutrino charged-current interaction channel. The proton kinematics of this channel are further explored with a differential cross section measurement as a function of the leading proton’s kinetic energy that extends across the detection threshold. These measurements use data collected with the MicroBooNE detector from 6.4 × 10 20 protons on target from the Fermilab booster neutrino beam with a mean neutrino energy of ∼ 0.8 GeV . Extensive data-driven model validation utilizing the conditional constraint formalism is employed. This motivates enlarging the uncertainties with an empirical reweighting approach to minimize the possibility of extracting biased cross section results. The extracted nominal flux-averaged cross sections are compared to widely used event generator predictions revealing severe mismodeling of final states without protons for muon neutrino charged-current interactions, possibly from insufficient treatment of final state interactions. These measurements provide a wealth of new information useful for improving event generators which will enhance the sensitivity of precision measurements in neutrino experiments. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries and electrocatalysts. Experimental characterizations of such materials by operando microscopy produce rich image datasets, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗