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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Integrated Neutronics Modeling for Inertial Fusion Energy Systems: Development and Application to LD-FIRST

Lawrence Livermore National Laboratory (LLNL) is proposing a new Laser Driven Fusion Integration Research and Science Test Facility (LD-FIRST) with the goal of providing an experimental testbed for future Inertial Fusion Energy (IFE) systems. However, IFE systems require detailed and accurate multiphysics modeling to quantify material damage, thermal loading, and tritium breeding within complex chamber environments. This article presents the first step in an integrated multiphysics framework that couples meshed CAD-based geometry within Monte Carlo neutronic simulations to enable high-fidelity analysis of IFE chamber concepts, with future coupling to external codes. The neutronics workflow utilizes OpenMC and its third-party capability to use CAD-based geometries through DAGMC and tally on unstructured meshes with Libmesh to evaluate neutron transport behavior, geometric fidelity, and material performance under reactor-relevant conditions. The use of tailored tallies on unstructured meshes in this framework allows direct transfer without interpolating to CFD simulation tools. Two IFE chambers were evaluated, both conceived by LLNL: HYLIFE-II and Laser IFE (LIFE). This work produced high-fidelity conformal surface and volumetric meshes of the HYLIFE-II and LIFE chambers with mapped spatial insight into material damage, thermal loading, and tritium breeding. The HYLIFE-II model was built utilizing available resources and used as a test case to verify that the neutronics framework can handle complex geometries. The LIFE chamber CAD was provided by LLNL and was the main focus of this work. This work analyzes multiple ternary alloy breeding materials for the LIFE chamber, across different 6 Li enrichments to produce data relevant to the LD-FIRST project. This work also investigates the level of model fidelity for the LIFE chamber, and results show that inclusion of detailed first wall and coolant structures increased the predicted tritium breeding ratio (TBR) by ~30%, highlighting the sensitivity of tritium breeding and the need for a high-fidelity simulation framework for IFE chambers. These developments provide a scalable toolset for the design and optimization of next-generation IFE chambers, forming a solid foundation for future coupled multiphysics analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

The Interplay of Pauli Repulsion, Electrostatics, and Field Inhomogeneity for Blueshifting and Redshifting Vibrational Probe Molecules

Many molecules' vibrational frequencies are sensitive to intermolecular electric fields, enabling them to probe the field in complex molecular environments. However, it is often unclear whether the probe is responding to the local electric field or other types of intermolecular interactions, inhibiting interpretation of the frequency and effectiveness as probes. This is especially true for molecules whose vibrational frequencies blueshift instead of the more typical redshift in hydrogen bonding configurations. In this work, we computationally investigate the causes of redshifting versus blueshifting over a range of vibrational reporters. First, we apply adiabatic energy decomposition analysis to a paradigmatic set of probes, finding that redshifting only occurs when electrostatic interactions are strong enough to overcome the dominant and large blueshifting contribution of Pauli repulsion. Furthermore, we demonstrate that field inhomogeneity can further shift the frequency of many probes substantially to either reinforce or counteract the shift expected from a homogeneous field. We find that redshifting is reinforced by electric field inhomogeneity, otherwise field inhomogeneity further weakens the electrostatic contribution relative to Pauli repulsion, leading to blueshifting. Further calculations indicate that the probe's response to field inhomogeneity can be understood by considering the mass of the atoms involved in the stretching mode and sign of the electric field. In explaining the interplay of different intermolecular interactions and field inhomogeneity for many probes, our results should enable the use and interpretation of spectroscopic probes and their connection to electric fields in more complex systems.

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

Experimental and Theoretical Confirmation of Covalent Bonding in α‐Pu

Plutonium's radioactivity provides functionality for nuclear batteries, nuclear reactors, etc., but its complex electronic properties harbor strongly correlated behavior giving rise to a host of interesting phenomena including the presence of a ca. 25% volume collapse between δ-Pu and α-Pu. The complex bonding environments of the ground state allotrope, α-Pu, serve as a unique testing ground for new computational and experimental approaches within the Pu science community. For the first time, a combination of novel ansatzes is used in all-electron density functional theory (DFT) and pair distribution functions (PDF) obtained from high-Q X-ray diffraction to study the bonding behavior in α-Pu. This first experimental and theoretical co-informed description of local bonding behavior for α-Pu reveals covalent bonds, which is a topic that remains of interest in this allotrope. The covalent bonding present at the atomistic level accounts for several of α-Pu's macropscopic properties (e.g., Poisson's ratio) that in turn explains its physical functionalities relative to other allotropic phases like δ-Pu.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Trace-Level, Multi-Gas Detection for Food Quality Assessment Based on Decorated Silicon Transistor Arrays

Multiplexed gas detection at room temperature is critical for practical applications, such as for tracking the complex chemical environments associated with food decomposition and spoilage. Here, an integrated array of multiple silicon-based, chemical-sensitive field effect transistors (CSFETs) is presented to realize selective, sensitive, and simultaneous measurement of gases typically associated with food spoilage. CSFETs decorated with sensing materials based on ruthenium, silver, and silicon oxide are used to obtain stable room-temperature responses to ammonia (NH 3 ), hydrogen sulfide (H 2 S), and humidity, respectively. For example, one multi-CSFET sensor signal changes from its baseline by 13.34 in response to 1 ppm of NH 3 , 724.45 under 1 ppm H 2 S, and 23.46 under 80% relative humidity, with sensitive detection down to 10 ppb of NH 3 and H 2 S. To demonstrate this sensor for practical applications, the CSFET sensor array is combined with a custom-printed circuit board into a compact, fully integrated, and portable system to conduct real-time monitoring of gases generated by decomposing food. By using existing silicon-based manufacturing methodologies, this room-temperature gas sensing array can be fabricated reproducibly and at low cost, making it an attractive platform for ambient gas measurement needed in food safety applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Self‐assembling Peptides with Internal Ionizable Unnatural Amino Acids: A General Approach to pH‐responsive Peptide Materials

Self‐assembled peptides are an emerging family of biomaterials that show great promise for a range of biomedical and biotechnological applications. Introducing and tuning the pH‐responsiveness of the assembly is highly desirable for improving their biological activities. Inspired by proteins with internal ionizable residues, we report a simple but effective approach to constructing pH‐responsive peptide assembly containing unnatural ionic amino acids with an aliphatic tertiary amine side chain. Through a combined experimental and computational investigation, we demonstrate that these residues can be accommodated and stabilized within the internal hydrophobic compartment of the peptide assembly. The hydrophobic microenvironment shifts their pK a significantly from a basic pH typically found for free amines to a more biologically relevant pH in the weakly acidic range. The pH‐induced ionization and ionization‐dependent self‐assembly and disassembly are thoroughly investigated and correlated with the biological activity of the assembly. This new approach has unique advantages in tuning the pH‐responsiveness of self‐assembled peptides across a large pH range in a complex biological environment. We anticipate the ionizable amino acids developed here can be widely applicable to the synthesis and self‐assembly of many amphiphilic peptides with endowed pH‐responsive properties to enhance their biological activities toward applications ranging from targeted therapeutic delivery to proton transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Molecular beam scattering from flat jets of liquid dodecane and water

Abstract Molecular beam experiments in which gas molecules are scattered from liquids provide detailed, microscopic perspectives on the gas–liquid interface. Extending these methods to volatile liquids while maintaining the ability to measure product energy and angular distributions presents a significant challenge. The incorporation of flat liquid jets into molecular beam scattering experiments in our laboratory has allowed us to demonstrate their utility in uncovering dynamics in this complex chemical environment. Here, we summarize recent work on the evaporation and scattering of Ne, CD 4 , ND 3 , and D 2 O from a dodecane flat liquid jet and present first results on the evaporation and scattering of Ar from a cold salty water jet. In the evaporation experiments, Maxwell–Boltzmann flux distributions with a cos θ angular distribution are observed. Scattering experiments reveal both impulsive scattering (IS) and trapping followed by thermal desorption (TD). Super‐specular scattering is observed for all four species scattered from dodecane and is attributed to anisotropic momentum transfer to the liquid surface. In the IS channel, rotational excitation of the polyatomic scatterers is a significant energy sink, and these species accommodate more readily on the dodecane surface compared to Ne. Our preliminary results on cold salty water jets suggest that Ar atoms undergo some vapor‐phase collisions when evaporating from the liquid surface. Initial scattering experiments characterize the mechanisms of Ar interacting with an aqueous jet, allowing for comparison to dodecane systems. Key Points Molecular beam scattering from flat liquid jets is a powerful technique to elucidate mechanistic detail at the gas–liquid interface. Previous dodecane scattering experiments have uncovered angularly‐resolved thermal desorption fractions and energy transfer at the interface for several small molecule scatterers. Preliminary results on scattering from cold salty water reveal mechanisms of interaction between argon and an aqueous jet.

Yang, Walt↗
DOE OSTI2023

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗
DOE OSTI2023

Invertible neural networks for real-time control of extrusion additive manufacturing

Material extrusion additive manufacturing (AM) has enabled an elegant fabrication pathway for a vast material library. Nonetheless, each material requires optimization of printing parameters generally determined through significant trial-and-error testing. To eliminate arduous, iteration-based optimization approaches, many researchers have used machine learning (ML) algorithms which provide opportunities for automated process optimization. Here, in this work, we demonstrate the use of an ML-driven approach for real-time material extrusion print-parameter optimization through in-situ monitoring of printed line geometry. To do this, we use deep invertible neural networks (INNs) which can solve both forward and inverse, or optimization, problems using a single network. By combining in-situ computer vision and deep INNs, the printing parameters can be autonomously optimized to print a target line width in 1.2 s. Furthermore, defects that occur during printing can be rapidly identified and corrected autonomously. The methods developed and presented in this work eliminate user-intensive, time-consuming, and iterative parameter discovery approaches that currently limit accelerated implementation of extrusion-based AM processes. Furthermore, the presented approach can be generalized to provide real-time monitoring and optimization pathways for increasingly complex AM environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A surrogate-model-based approach for estimating the first and second-order moments of offshore wind power

Power curve, the functional relationship that governs the process of converting a set of weather variables experienced by a wind turbine into electric power, is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input, thus ignoring the secondary, yet possibly significant effects of other environmental factors, (ii) they largely overlook the complex marine environment in which offshore turbines operate, potentially compromising their value in offshore wind energy applications, and (ii) they solely focus on the first-order properties of wind power, with little (or null) information about the variation around the mean behavior, which is important for ensuring reliable grid integration, asset health monitoring, and energy storage, among others. In light of that, this study investigates the impact of several wind-and wave-related factors on offshore wind power variability, with the ultimate goal of accurately predicting its first two moments. Further, our approach couples OpenFAST—a multi-physics wind turbine simulator—with Gaussian Process (GP) regression to reveal the underlying relationships governing offshore weather-to-power conversion. We first find that a multi-input power curve which captures the combined impact of wind speed, direction, and air density, can provide double-digit improvements, in terms of prediction accuracy, relative to univariate methods which rely on wind speed as the sole explanatory variable (e.g. the standard method of bins). Wave-related variables are found not important for predicting the average power output, but interestingly, appear to be extremely relevant in describing the fluctuation of the offshore power around its mean. Tested on real-world data collected at the New York/New Jersey bight, our proposed multi-input models demonstrate a high explanatory power in predicting the first two moments of offshore wind generation, testifying their potential value to the offshore wind industry.

17 WIND ENERGY↗
DOE OSTI2020

An automated cluster surface scanning method for exploring reaction paths on metal-cluster surfaces

Metal-cluster surfaces present a wide variety of unique coordination environments. This complexity makes it difficult to manually probe the surface reactivity of such clusters. Here, we present a simple and automated method to systematically discover reaction pathways on cluster surfaces, based on the automated cluster surface scanning (ACSS) technique for mapping out potential energy surfaces. We showcase our method on 55-atom icosahedral Cu and Ag clusters, where we determine the activation energies of four elementary steps common in heterogeneous catalysis – hydrogen recombination (H* + H* → H 2 * + *), oxygen recombination (O* + O* → O 2 * + *), water formation (OH* + H* → H 2 O* + *), and CO oxidation (CO* + O* → CO 2 * + *) – with density functional theory calculations (DFT-PBE + D3). We show that the ACSS method requires significantly less human effort than the established manually performed climbing-image nudged elastic band (MP + CI-NEB) technique and locates transition states with comparable accuracy (root-mean-squared error of 0.10 eV) and similar computational cost. Rigorous sampling of the potential energy surface with the ACSS method allows one to locate all lowest-energy reaction pathways obtained via the MP+CI-NEB approach, as well as alternative pathways that one may have missed with the MP+CI-NEB approach due to the many possible pathways available on these clusters. The accuracy and efficiency afforded by the ACSS method could enable high-throughput exploration of the diverse reactivity of metal clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale Concurrent Atomistic-Continuum (CAC) modeling of multicomponent alloys

We report strengthening in complex multicomponent systems such as solid solution alloys is controlled primarily by the dynamic interactions between dislocation lines and heterogeneously distributed solute species. Modeling of extended defect length scales in such multicomponent systems becomes prohibitively expensive, motivating the development of reduced order approaches. This work explores the application of the Concurrent Atomistic-Continuum (CAC) method to model dislocation mobility in random alloys at extended length scales. By employing recently developed average-atom interatomic potentials, the average “bulk” material response in coarse-grained regions interacts with true random solute species in the atomistic-scale domain. We demonstrate that spurious stresses in domain resolution transition regions are eliminated entirely due to the CAC formulation. Simultaneously, the key details of local stress fluctuation due to randomness in the dislocation core region are captured, and fluctuating stress smoothly decays to the long-range dislocation stress field response. Dislocation mobility calculations, for line lengths over 400 nm, are computed as a function of alloy composition in the model FeNiCr system and compared to full molecular dynamics (MD). The results capture the composition-dependent trends, while reducing degrees of freedom by nearly 40%. This approach can be readily extended to any system described by an EAM potential and facilitates the study of large-scale defect dynamics in complex solute environments to support computational alloy design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Temperature-dependent solid electrolyte interphase reactions drive performance in lithium-mediated nitrogen reduction to ammonia

The solid electrolyte interphase (SEI) is a vital component to control mass transport and selectivity in the lithium-mediated reduction of N 2 to NH 3 (Li-N 2 R). Finding strategies that generate the optimal SEI, a complex network of organic and inorganic species, can potentially improve Li-N 2 R performance. Here, we unravel structure-property relationships of the SEI by correlating its composition with the NH 3 faradaic efficiency (FENH3). By modifying the reaction temperature, we alter electrolyte decomposition reactions and observe changes in the SEI that explain FE NH3 trends between electrolyte solvents. We quantify a complex reaction environment at elevated temperatures where SEI formation is counteracted by etching reactions. This tradeoff leads to temporal fluctuations of FE NH3 , but the maximal FE NH3 can reach up to 40%, the highest value reported for batch cells at ambient pressure, thus far. In conclusion, our work underscores the potential of novel electrolytes that steer SEI selectivity and, ultimately, improve Li-N 2 R performance.

electrocatalytic nitrogen reduction↗
DOE OSTI2024

Underlying mechanism of structural transformation between GaSb and GaAs response to intense electronic excitation

Ion irradiation of semiconductors has emerged as a promising approach for fabricating self-organized nanosystems with high atomic precision, despite often being accompanied by undesirable phenomena. Exploring the mechanisms underlying structural transformations is crucial for assessing nanostructure array types under complex irradiation environments. By quantitatively calculating the thermodynamically driven processes and analyzing the impact of intrinsic structural parameters, distinct structural transformations in response to intense electronic excitation are systematically investigated in gallium antimonide (GaSb) and gallium arsenide (GaAs) systems. In high-energy regimes, the nanofibers layer of GaSb exhibits intriguing structural discrepancy, characterized by partial nanofibers with coherent boundaries, interspersed nanopores accompanied by antisite defects and Ga precipitates, distinguishing to a series of discontinuous latent tracks that emerged within cylindrical trajectories in GaAs. Furthermore, significant diffusion behaviors of the nanohillocks are discovered in GaAs, with higher average roughness than GaSb, driven by the gradient stress distribution influenced by the free-surface effects. The deposition energy for melting phase formation, Gibbs free energy, and Ga diffusion coefficients contribute to the distinctive structural features, evidencing relatively stable morphological configurations and higher irradiation resistance in GaAs. Consequently, special optoelectronic properties associated with structural discrepancies facilitate the design and optimization of material functionalities by irradiation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of shrub willow buffers strategically integrated in an Illinois corn-soybean field on soil health and microbial community composition

We report soil serves many important ecological functions and is an integral part of our existence as a society. However, concerns for soil health are growing globally, in part due to the negative impacts of agricultural management on soil resources. The production of perennial bioenergy crops on marginal land in row-crop production systems is one solution that could improve land-use efficiency and address the sustainability of cropland management. Because the relationship between crop management and the environment is complex, more research is needed to evaluate the potential benefits perennial bioenergy crop production has on soil health, as well as other ecosystem services. In this study, shrub willow buffers were strategically integrated into a corn-soybean cropping system with the main objective of reducing nitrate-N leaching from grain crop production while producing biomass for bioenergy. Two buffer systems (defined by landscape positions) were included for comparison, one on marginal land with exposure to nitrate-N leaching from upslope grain (southern plots) and one on fertile soils with less nitrate-N leaching potential (northern plots). Evaluation of soil (chemistry, bulk density, microbial community) and shrub willow vegetation properties ( fine roots, leaf litter decomposition, and nutrient uptake dynamics), showed that landscape position plays an important role in (1) the dynamics of soil chemical properties, (2) shrub willow's influence and productivity, and (3) the provision of additional ecosystem services such as reductions in nitrous oxide emissions and nitrate-N leaching. In addition, the combination of crop type and landscape position (N-grain, N-willow, S-grain, and S-willow) influenced the species composition of the soil microbial community, resulting in unique and identifiable communities. These results highlight the potential application of shrub willow buffers for ecosystem service provision and support of ecosystem processes; however, understanding the relationship between the microbial community, crop type, and landscape is important for understanding the sustainability of the design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Real-Time Detection of Hydrogen and Ammonia Isotopologues for Impurity Removal and Recovery of Tritium

To accommodate gas measurements for impurity removal and recovery of tritium, a silver-coated optical or waveguide is employed for collecting Raman scattered signals to determine relative hydrogen and ammonia isotopologue populations in real time. The data and results presented here demonstrate an analytical methodology for the analysis of four ammonia and three hydrogen isotopologues in a hydrogen–deuterium exchange reaction by gas phase Raman spectroscopy. Standard chemometric modeling techniques effectively unravel the signatures of the isotopologues involved observed here; however, a sophisticated quantum chemical approach supports the spectral assignments. An interpretation of the data presented here can emphasize the practicality and reliability of the gaseous monitoring system in complex chemical environments for the hydrogen fuel economy as well as the more distant energy source from a facility that handles tritium. There are still considerable concerns about the measurement of tritium in isotope separation and radiological impurities from gas processing. A common impurity in gas processing is ammonia, which can form readily in the presence of nitrogen and tritium. Substituted ammonia (NQ 3 ), where Q = H, D, or T, is traditionally removed through getters or diffusers along with other non-hydrogen contaminants. A preferable analytical approach is noninvasive and can be deployed for real-time process evaluation in radiological environments.

Ammonia↗
DOE OSTI2025

NiAl–MoO 2 S 2 Nanoparticles: Structural Evolution and Mechanistic Insights into High-Performance Selenium Oxyanion Removal across Diverse pH Conditions

Advancing sorbent materials for the selective removal of toxic oxyanions from water requires synthetic control, tunable chemistry, and an atomic-level understanding of structure–function relationships. Here, we report the synthesis and detailed characterization of NiAl–MoO 2 S 2 , a novel layered double hydroxide (LDH) nanomaterial designed for the efficient sequestration of selenium oxoanions (SeO 3 2– and SeO 4 2– ) from complex aqueous environments. The material is synthesized through a room-temperature ion-exchange process, wherein interlayer NO 3 – anions in NiAl–LDH are replaced with MoO 2 S 2 2– clusters, forming high-surface-area, flower-like nanoparticles. Comprehensive structural analysis using the synchrotron X-ray pair distribution function, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy reveals a distinct chemical transformation of intercalated [MoO 2 S 2 ] 2– into [Mo 2 O 2 S 6 ] 2– -like clusters, generating redox-active interlayers that drive selenium capture. This tailored interfacial chemistry underpins the material’s exceptional sorption performance, achieving distribution coefficients (K d ) ≥ 10 6 mL/g and maximum capacities of 343 mg/g for SeO 4 2– and 514 mg/g for SeO 3 2– , outperforming state-of-the-art inorganic sorbents. Importantly, NiAl–MoO 2 S 2 maintains high selectivity and capacity across acidic, neutral, and alkaline pH, efficiently removing selenium from ppm to sub-10 ppb trace levels, even in the presence of competing ions typical of natural and industrial waters. The selenium uptake proceeds via reductive precipitation coupled with the oxidation of molybdenum and sulfide within the LDH framework. This study highlights the power of strategic synthetic modification and interlayer functionalization in LDHs to unlock new structural motifs and redox chemistries, offering a scalable route to advanced materials for environmental remediation.

Adsorption↗
DOE OSTI2021

Polarization Effects in Water-Mediated Selective Cation Transport across a Narrow Transmembrane Channel

We report despite the progress in modeling complex molecular systems of ever-increasing complexity, a quantitatively accurate computational treatment of ion permeation through narrow membrane channels remains challenging. An important factor to reach this goal is induced electronic polarization, which is likely to impact the permeation rate of small ions through narrow molecular pores. In this work, we extended the recently developed polarizable force field based on the classical Drude oscillators to assess the role of induced polarization effects on the energetics of sodium and potassium ion transport across the gramicidin A (gA) ion channel. The inclusion of induced polarization lowers barriers present in 1D potential of mean force (PMF) for cation permeation by ~50% compared to those obtained with the additive force field. Conductance properties calculated with 1D PMFs from Drude simulations are in better agreement with experimental results. Polarization of single-file water molecules and protein atoms forming the narrow pore has a direct impact on the free-energy barriers and cation-specific solid-state NMR chemical shifts. Sensitivity analysis indicates that small changes to water–channel interactions can alter the free energy barrier for ion permeation. These results, illustrating polarization effects present in the complex electrostatic environment of the gA channel, have broad implications for revising proposed mechanisms of ion permeation and selectivity in a variety of ion channels.

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

Field-Driven Simulations to Probe the Impact of Ionic Correlations on Solution Transport Coefficients in Binary, Ternary, and Reciprocal Quaternary Aqueous Electrolytes

Ionic correlations play a critical role in governing transport properties of mixed-salt aqueous electrolyte solutions, yet their quantitative characterization remains challenging, particularly for multicomponent aqueous systems. Here, we develop a general nonequilibrium molecular dynamics framework to efficiently compute Onsager transport coefficients and ionic correlations in mixed-salt aqueous solutions. Using field-driven simulations, we obtain accurate Onsager matrices for LiCl/ KCl, KCl/KBr, and LiBr/KCl electrolyte solutions with significantly reduced computational cost relative to equilibrium Green−Kubo methods. The framework enables direct assessment of how attractive cation−anion and repulsive like-ion interactions contribute to conductivity and salt diffusivity across compositions. While static ion pairing exhibits strong composition dependence, dynamic ion correlations remain nearly invariant, leading to constant deviations from Nernst−Einstein predictions. These results highlight the disconnect between static ion association and dynamic transport correlations, and they establish a transferable approach for analyzing ion transport in complex electrolyte environments relevant to separation processes and electrochemical systems.

36 MATERIALS SCIENCE↗