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At least 73 records · Page 4

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗

Targeted synthesis, characterization, and electrochemical analysis of transition-metal-oxide catalysts for the oxygen evolution reaction

Hydrogen fuel can be produced through the electrochemical splitting of water, an energy-intensive process that requires the use of electrocatalysts to be more efficient. Whereas current precious-metal-based electrocatalysts might be costly on a larger scale, transition-metal-oxide catalysts are more earth abundant and have shown promising activity. Here, the development and improvement of highly active transition-metal-oxide electrocatalysts is thus an important area of study where different catalyst enhancement strategies are used to drive the field forward. Additionally, transition-metal-oxide catalysts come in various different structures with their own advantages; thus, this review is focused on investigating the continuing field of transition-metal-oxide electrocatalysts of different structures and innovative methods of improving activity. By the end, new and promising paths forward in this field will be highlighted, particularly in the development of rock-salt oxides for the water-splitting system.

08 HYDROGEN↗

S -factor and scattering-parameter extractions from ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}{ \rightarrow }^{7}\mathrm{Be}+\gamma $

Previous studies of the reaction ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}\to {}^{7}\mathrm{Be}+\gamma $ have mainly focused on providing the best central value and error bar for the S factor at solar energies. Experimental measurements of this capture reaction at higher energies, the ${}^{3}\mathrm{He}$–${}^{4}\mathrm{He}$ scattering phase shifts, as well as properties of ${}^{7}\mathrm{Be}$ and its excited state, have been used to constrain the theoretical models employed for this purpose. Here we show that much more information than was previously appreciated can be extracted from angle-integrated capture data alone. We use the next-to-leading-order (NLO) amplitude in an effective field theory (EFT) for ${}^{3}\mathrm{He}+{}^{4}\mathrm{He}\to {}^{7}\mathrm{Be}+\gamma $ to perform the extrapolation. At this order the EFT describes the capture process using an s-wave scattering length and effective range, the asymptotic properties of ${}^{7}\mathrm{Be}$ and its excited state, and short-distance contributions to the E1 capture amplitude. We extract the multi-dimensional posterior of all these parameters via a Bayesian analysis that uses capture data below 2 MeV. We find that properties of the ${}^{7}\mathrm{Be}$ ground and excited states are well constrained. The total S factor $S(0)\,={0.577}_{-0.016}^{+0.015}$ keV b, while the branching ratio for excited- to ground-state capture at zero energy, ${Br}(0)={0.406}_{-0.011}^{+0.013}$, both at 68% degree of belief. This S(0) is broadly consistent with other recent evaluations, and agrees with the previously recommended value $S(0)=0.56\pm 0.03\,\,\mathrm{keV}$ b, but has a smaller error bar. We also find significant constraints on ${}^{3}\mathrm{He}$–${}^{4}\mathrm{He}$ scattering parameters, and we obtain constraints on the angular distribution of capture gamma rays, which is important for interpreting experiments. The path forward for this reaction seems to lie with better measurements of the scattering phase shifts and S(E)'s angular dependence away from zero energy, together with better understanding of the asymptotic normalization coefficients of the ${}^{7}$Be bound states' wave functions. Lastly, data on these could further reduce the uncertainty on S(0).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High-fidelity Pebble Bed Reactor Depletion Based on Pebble Tracking Transport in Griffin

The pebble tracking transport (PTT) method is a high-fidelity, heterogeneous deterministic transport technique for pebble bed reactor analysis. It discretizes the broad-group neutron transport equation in space and angle with the discontinuous finite element and the discrete ordinates method, and utilizes various solving techniques, including mesh sweeping and diffusion acceleration, to provide pebble- wise reaction rates. This work presents the extension of the PTT method to enable fuel depletion capability in the Griffin code. We discuss the implementation details of the PTT-based high-fidelity depletion where isotope inventory of all individual pebbles is tracked through pre-determined pebble flow paths in the core. The implementation is verified with a generic pebble bed reactor model. Some preliminary equilibrium core results are included. Future works are also discussed.

97 - MATHEMATICS AND COMPUTING↗

ATcT — Active Thermochemical Tables Python Interface

SF-25-140 atct is a lightweight, Python client for the ATcT v1 API that enables programmatic access to high-accuracy thermochemical data and turnkey reaction-enthalpy analysis. The package implements full v1 endpoint coverage (species lookup by ATcT ID, name, formula, SMILES, InChI, CAS RN; covariance queries; health checks) with robust error handling, retries, and environment-based configuration for local/production endpoints. Beyond data retrieval, atct provides rigorously implemented reaction calculators that propagate uncertainties via either (i) a conventional independent-errors method (0 K or 298.15 K) or (ii) covariance-aware propagation using provided covariances at 298.15 K. Typed data classes ensure transparent, reproducible data structures and carry ATcT Thermochemical Network (TN) version identifiers for provenance. Dual import paths and comprehensive examples facilitate integration into research pipelines, enabling reproducible thermochemical calculations, automated validation, and downstream method development.

Bross, DavidHamilton [Argonne National Laboratory ↗

Charting C–C coupling pathways in electrochemical CO 2 reduction on Cu(111) using embedded correlated wavefunction theory

The electrochemical CO 2 reduction reaction (CO 2 RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C 2+ ) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO 2 RR electrocatalysts is mechanistic analysis of the best metal catalyst thus far identified, namely, copper (Cu), via quantum mechanical computations to complement experiments. Here, we apply embedded correlated wavefunction (ECW) theory, which regionally corrects the electron exchange-correlation error in density functional theory (DFT) approximations, to examine multiple C–C coupling steps involving adsorbed CO (*CO) and its hydrogenated derivatives on the most ubiquitous facet, Cu(111). We predict that two adsorbed hydrogenated CO species, either *COH or *CHO, are necessary precursors for C–C bond formation. The three kinetically feasible pathways involving these species yield all three possible products: *COH–CHO, *COH–*COH, and *OCH–*OCH. The most kinetically favorable path forms *COH–CHO. In contrast, standard DFT approximations arrive at qualitatively different conclusions, namely, that only *CO and *COH will prevail on the surface and their C–C coupling paths produce only *COH–*COH and *CO–*CO, with a preference for the first product. This work demonstrates the importance of applying qualitatively and quantitatively accurate quantum mechanical method to simulate electrochemistry in order ultimately to shed light on ways to enhance selectivity toward C 2+ product formation via CO 2 RR electrocatalysts.

30 DIRECT ENERGY CONVERSION↗

Role of Pr-Vacancies and O-Interstitials on the Activity and Stability of (Pr 1−x Ln x ) 2 NiO 4 (Ln = La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) towards Oxygen Reduction Reactions: A DFT Study

Praseodymium nickelate, Pr 2 NiO 4 (PNO), is a promising electrode to promote oxygen reduction reaction (ORR) in a solid oxide fuel cell, but it exhibits phase transformation during electrochemical operation. The origin of the simultaneous phase transformation and high electrochemical performance remains obscure. We carried out a systematic density functional theory study to elucidate the mechanism for this conjugated phenomenon. Charge, electronic structure, and normal-mode analysis suggest the presence of peroxide. Our study shows that the formation of peroxide (O 2 2– ) is attributed to both oxygen interstitials and Pr vacancies. The peroxide species limits the oxygen ion migration due to the additional energy required to break its O–O bond, which leads to a decrease in ORR activity. Subsequently, we investigate the diffusion paths of Pr-ions while comparing them with those of other Ln 3+ ions (La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO. The formation energies for various Ln 3+ cation occupancies are calculated, as well as segregation energies in CeO 2 (111) surfaces. Lastly, criteria for effective Ln 3+ dopants are developed. La, Nd, and Pm are proposed as potential substituents in PNO to obtain a stable structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling, Performance Assessment, and Nodal Data Analysis of TRISO-Fueled Systems with Shift

This technical report documents several enhancements to the Shift Monte Carlo (MC) code under the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in fiscal year (FY) 2022. Performance enhancements were added to Shift specifically for tristructural isotropic (TRISO)–fueled reactor systems and guided based on performance analysis in FY 2021. For the pebble performance model developed in previous studies, the runtime improved by ~ 91× compared to the original model and ~ 2× compared to the user-optimized model. Compared to Serpent, Shift is ~ 3× slower if Serpent delta-tracking is enabled but ~ 2× faster when delta-tracking is disabled. The multigroup cross section generation was improved through simplifying tally input definitions, porting several post-processing tally operations from Python scripts into the Shift code base, and accounting for production reactions in the scattering multiplicity. Progress was also made on two emerging capabilities: (1) the development of Titan (a Shift reactor physics user interface) and (2) initial investigation into path-length tallies for computing multigroup scattering matrices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Carbon Dioxide Utilization for Plasma Nanosynthesis of Carbon

This DOE Phase I SBIR project has developed a glow discharge-based plasma process to convert carbon dioxide to sold carbon and water. By adding natural gas, the additional enthalpy can be used to reform the output carbon dioxide to value added carbon and EPA-compliance-grade water, thus creating a process that has no gaseous products at all, such as: CO 2 + CH 4 → 2C + 2H 2 O, which is simply the exothermic reverse of the syngas reaction. During the Phase I work, several milestones were accomplished successfully. a. First, a synthesis reactor was designed, assembled, and successfully operated using the combined simultaneous operation of glow discharge and microwaves. DC discharge and microwaves can also be operated individually, allowing multiple configurations to be used This is one of the first reactors of its kind, and perhaps the first ever. b. Second, the research team successfully produced carbon nanomaterials using carbon dioxide as the source of carbon via CO 2 + 2H 2 → C + 2H 2 O. This is certainly one of the first processes to use plasma to convert carbon dioxide to nanocarbon, and perhaps the first ever demonstration. c. Third, it was also shown that carbon monoxide and carbon dioxide can be used with methane to reduce the synthesis temperature of ASI graphene decorated carbon nanotubes (GDCNT). Hitherto GDCNT were only fabricated above 1200 °C. GDCNT was synthesized at 780 °C. CO 2 + C → 2CO; 2 CO + CH 4 → 3 C + 2H 2 O, and also, CH 4 + CO 2 → 2 C + 2H 2 O. d. Fourth, closed cycle synthesis of nanomaterial was demonstrated with over 80% conversion of carbon dioxide to carbon and water was achieved, on the basis of pressure drop during glow discharge. e. Fifth, plasma operation was achieved via glow discharge and microwaves at 500 Torr, demonstrating a path forward to atmospheric pressure operation f. Sixth, using carbon monoxide and carbon dioxide in an electrothermal furnace, we produced 350 grams per hour of high-quality nanotubes in a single furnace, compared to 200 grams per hour for the commercial process. Controlling the enthalpy prevents self-extinguishing hot gas pyrolysis. Thus, carbon dioxide enhances the properties and reduces the production cost. This is a near term advance that can go into trial production in the near term. g. Seventh, economic analysis suggests an economic plan forward, producing carbon nanotubes for less than $50 per pound. The use of hydrogen and carbon dioxide as the feedstocks is acceptable from a cost basis, and in fact hydrogen is less expensive than carbon monoxide. Niche applications are available in the near term, though quantities relevant to sequestration remain a far-term goal. h. Eighth, though it was not the research team’s intention to create a new process for producing carbon monoxide, it was realized that almost by accident we demonstrated plasma reforming of carbon dioxide via a plasma version of the reverse Boudouard reaction. Accordingly, we have contacted a major gas manufacturer (Matheson Gas) to determine whether there is interest in creating an industrial version of the process. i. Ninth, a long-range strategy is identified in which a progressively more carbon-conscious world will seek to create solid carbon as a means of sequestering carbon dioxide, impeding its return to the atmosphere. In the long term the price must drop by orders of magnitude with larger production, and assuming success, solid carbon could be the preferred form for sequestration rather than underground storage. If carbon can be made as cheaply as dirt, or nearly so, then it can serve a useful purpose as structural material for housing, soil amendments in agriculture and fillers to modify low areas.

03 NATURAL GAS↗

Rhenium-Sulfido and -Dithiolato Corroles: Reflections on Chalcophilicity

The high-temperature (~180 °C) reaction between free-base meso-triarylcorroles and Re 2 (CO) 10 , followed by exposure to PCl 3 and thiols (or elemental sulfur), affords rhenium-sulfido (ReS) corroles in 67-76% yields. The use of shorter reaction times, lower temperatures (~130 °C), and a dithiol (e.g., ethane-1,2-dithiol) also allows the isolation of rhenium-dithiolato corroles, presumptive intermediates on the path to ReS corroles. The ReS corroles exhibit high thermal stability and two reversible oxidations and reductions in their cyclic voltammograms, with redox potentials nearly identical to those observed for analogous ReO corroles. The electrochemical HOMO-LUMO gaps of the complexes, at 2.2 eV, are consistent with ligand-centered oxidation and reduction. The UV-vis spectra of ReS corroles, on the other hand, differ significantly from those of their ReO counterparts. Scalar-relativistic DFT calculations suggest that this difference reflects low-energy LUMO+2 and LUMO+3 levels, consisting of Re-S π-antibonding interactions; the ReO corroles, in contrast, exhibit a larger LUMO+1/LUMO+2 gap, as expected for a relatively classical Gouterman-type metalloporphyrin analogue. The high stability of ReS corroles is consistent with geochemists' view of rhenium as a moderately chalcophilic element (i.e., one that partitions into sulfide melts) as well as with a recent quantitative analysis of thiophilicity, which indicates that rhenium's oxophilicity and thiophilicity are essentially evenly balanced.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

General framework for quantifying dissipation pathways in open quantum systems. III. Off-diagonal subsystem–bath couplings

This paper extends the previously reported theory of dissipation pathways [C. W. Kim and I. Franco, J. Chem. Phys. 160, 214111 (2024)] to incorporate off-diagonal subsystem–bath coupling, which is often required to model molecular systems where the environment directly influences transitions and couplings between subsystem states. We systematically derive master equations for both population transfer and dissipation into individual bath components, for which we also rigorously prove energy conservation and detailed balance. The approach is based on second-order perturbation theory with respect to the subsystem–bath couplings, whose form is not limited to any specific model. The accuracy of the developed method is tested by applying it to diverse model Hamiltonians involving linearly coupled harmonic oscillator baths and comparing the outcomes against the hierarchical equations of motion (HEOM) method. Overall, our method accurately quantifies the contributions of specific bath components to the overall dissipation while significantly reducing the computational cost compared to numerically exact methods such as HEOM, thus offering a path to examine how vibronic interactions steer non-adiabatic processes in realistic chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalytic reforming of methane with H 2 S via dynamically stabilized sulfur on transition metal oxides and sulfides

Reforming of methane with H 2 S is a promising path to directly utilize sour natural gas reserves, although some aspects of the mechanism and structure–function relations remain elusive. In this report we show that metal oxides of group 4–6 elements, which are inert for steam and dry methane reforming reactions, are active and stable (pre)catalysts for the H 2 S reforming of methane. The key active sites are sulfur species (S*) that are dynamically bound to metal cations during catalysis. Similar H/D isotope exchange patterns and universal rate inhibition by H 2 on representative catalysts indicate that H 2 S decomposition and recombination of surface hydrogen atoms are quasi-equilibrated, whereas CH 4 dissociation steps are reversible, yet not quasi-equilibrated. An in-depth analysis of the kinetic data and isotopic substitution effects identifies S*-mediated C–H bond cleavage as the most plausible rate-limiting step common for all catalysts, with subtle yet essential differences between 3d and 4d/5d catalysts in the thermodynamic stability of S*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Influence of Nominal Composition on the Microstructure, Tensile Properties, and Weldability of Cast Monel Alloys

Cast Monel alloys are used in many industrial applications that require a combination of good mechanical properties and excellent resistance to corrosion. Despite relative widespread use, there has been limited prior research investigating the fundamental composition–structure–property relationships. Here in this work, microstructural characterization, thermal analysis, electron probe microanalysis, tensile testing, and Varestraint testing were used to assess the effects of variations in nominal composition on the solidification path, microstructure, mechanical properties, and solidification cracking susceptibility of cast Monel alloys. It was found that Si segregation caused the formation of silicides at the end of solidification in grades containing at least 3 wt pct Si. While increases to Si content led to significant improvements in strengthening due to the precipitation of β 1 -Ni 3 Si, the silicide eutectics acted as crack nucleation sites during tensile loading which severely reduced ductility. The solidification cracking susceptibility of low-Si Monel alloys was found to be relatively low. However, increases to Si concentration and the onset of associated eutectic reactions increased the solidification temperature range and drastically reduced cracking resistance. Increases in the Cu and Mn concentrations were found to reduce the solubility limit of Si in austenite which promoted additional eutectic formation and exacerbated the reductions in ductility and/or weldability.

36 MATERIALS SCIENCE↗

Variational deep learning of equilibrium transition path ensembles

Here, we present a time-dependent variational method to learn the mechanisms of equilibrium reactive processes and efficiently evaluate their rates within a transition path ensemble. This approach builds off of the variational path sampling methodology by approximating the time-dependent commitment probability within a neural network ansatz. The reaction mechanisms inferred through this approach are elucidated by a novel decomposition of the rate in terms of the components of a stochastic path action conditioned on a transition. This decomposition affords an ability to resolve the typical contribution of each reactive mode and their couplings to the rare event. The associated rate evaluation is variational and systematically improvable through the development of a cumulant expansion. We demonstrate this method in both over- and under-damped stochastic equations of motion, in low-dimensional model systems, and in the isomerization of a solvated alanine dipeptide. In all examples, we find that we can obtain quantitatively accurate estimates of the rates of the reactive events with minimal trajectory statistics and gain unique insights into transitions through the analysis of their commitment probability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Open‐Air Combustion Synthesis with Rapid Plasma Processing of Large‐Area Transparent Conducting Oxides

A vacuum-free, high-throughput synthesis of indium tin oxide (ITO) via Combustion Oxidation with Rapid Plasma Processing (CORP) utilizes a solution-based exothermic combustion reaction to generate the oxide with tunable control of either amorphous or crystalline phases. A subsequent open-air, forming gas plasma treatment is used to introduce oxygen vacancies and promote crystallization. Here, the evolution of the oxide structure is elucidated by extended X-ray absorption spectroscopy fine structure analysis. Using CORP, fabrication of 300 cm 2 of ITO possessing a champion sheet resistance of 38 Ω sq. −1 , visible transmission of 89%, conductivity stability for over 250 days, roughness < 2nm, and Haacke figure of merit (%T 550nm 10 /R s ) of 0.012 Ω −1 is achieved. Cost modeling of CORP demonstrates up to a 67% reduction in price for TCOs using fully continuous, in-line unit operations compared with vacuum sputtering. The work shows a path toward a low-cost, vacuum-free manufacturing method for TCOs at commercial scales.

42 ENGINEERING↗

Understanding parton evolution in matter from renormalization group analysis

We perform a renormalization group (RG) analysis of collinear hadron production in deep inelastic scattering on nuclei. We consider the limit where the parent parton energy E is large, while the medium opacity remains small. We identify the fixed order and leading enhanced medium contributions to the semi-inclusive cross sections and derive RG equations that resum multiple emissions near the endpoints of the splitting functions at first order in opacity. These evolution equations treat the same type of radiation enhancement in matter as the modified Dokshitzer-Gribov-Lipatov-Altarelli-Parisi approach, but differ in the way one regulates the collinear divergences. They provide a unique analytic insight into the problem of resummation and a faster and more efficient path to phenomenology. The new RG evolution framework is applied to study fragmentation in eA reactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Computing with a Chemical Reservoir

Contemporary computation is expensive, with large language models and artificial intelligence becoming more common in daily life. However, high-performance computing is reaching the limits in speed and energy expenditure, and domain science requires ever-increasing computational capacity, with simulations and data analysis pipelines ever-growing in complexity. As we progress towards post-exascale computation, with the associated high energy costs, new methods of energy-conscious computation are required. Novel analog and hybrid digital-analog systems can overcome these challenges, and chemical reactions offer a promising avenue. Computers based on chemistry can provide compact desktop devices with immense computational power. These devices are readily scalable by considering greater reaction systems or vessels, meeting the high-performance requirements for scientific workflows. In this article, we present ChemComp, a compilation pipeline for the conversion of ordinary differential equations into implementable chemical reactions. We then demonstrate the solving capabilities of ChemComp by emulating a potential chemical reservoir device. We leverage the multi-layer intermediate representation (MLIR) compiler framework to implement an expressive chemical reaction abstraction and propose a path for chemical reaction networks (CRNs) to represent mathematical problems effectively. Combined, we demonstrate a potential workflow that can harness chemistry’s computing power to create energy-efficient, high-performance computation systems for contemporary computing needs.

artificial intelligence↗

Field-driven ion pairing dynamics in concentrated electrolytes

Here, we investigate ion pairing dynamics in electrolytes driven far from equilibrium using molecular simulations and nonequilibrium rate theory. Focusing on 0.5M LiPF 6 in water and acetonitrile under uniform electric fields, we compute transition path theory observables, including reactive fluxes and mean first-passage times of ion pairing. Moreover, we introduce a dynamical proxy of free-ion population, where its field-induced change is strongly correlated with the nonlinear enhancement of conductivity, yielding an increase of 40% at 50 mV/Å in acetonitrile, compared to that of less than 10% in aqueous electrolytes. Further kinetic analysis elucidates that Onsager’s classical theory substantially overestimates field-induced enhancement of ion pair dissociation in molecular electrolytes. This discrepancy arises from solvent-mediated dynamical pathways and field-induced dielectric decrement that suppress ion pair dissociation within explicit solvents, highlighting that a faithful description of molecular details is essential. Our results provide a molecular interpretation of nonlinear electrolyte transport beyond continuum theories and establish a general framework for quantifying nonequilibrium reaction kinetics in condensed phase systems.

Moon, Seokjin [University of California, Berkeley,↗