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DOE OSTI2020

Simulating policy interventions in the interfirm diffusion of low-carbon technologies: An agent-based evolutionary game model

Policy interventions are frequently used by authorities around the world to mitigate carbon emissions. However, economic systems are essentially complex adaptive systems, which often exhibit unexpected responses to exogenous interventions and leave intervenors in a dilemma, even if the interventions are elaborately designed. To explore the behaviors of the diffusion system regarding low-carbon technologies, this study builds an agent-based model (ABM) to simulate enterprises' reactions to multiple policy interventions aimed at spurring low-carbon technology diffusion. The simulated enterprises are in a complex network where they play evolutionary games with their neighbors, which enables the model to possess two critical features of economic systems: adaptiveness and equilibrium. The model reveals a dilemma of policy interventions: intuitively, carbon taxes, asymmetric penalties (only imposed on un-low-carbon enterprises) and subsidies can improve the diffusion, which is consistent with previous research; counter-intuitively, all these policies turn out to be inefficient or even harmful to low-carbon enterprises because of the diffusion system's high adaptiveness. Specifically, when carbon taxes and penalties increase, both the low-carbon and un-low-carbon enterprises end up with the equilibrium of equivalent but lower profits. In contrast, all the enterprises earn equivalent but more profits even though subsidies are only given to the low-carbon enterprises, which implies that the un-low-carbon enterprises (indirectly) grab a portion of the subsidies and accordingly weaken the incentive effect of subsidies. These system behaviors are summarized as "equalizing effect" because the system tends to equalize the impact of both positive and negative interventions among all enterprises even though the policy interventions are asymmetrically imposed on one type of the enterprises. The findings also indicate that policies implemented to enlarge green market sizes can help policymakers bypass the dilemma.

Agent-based modeling↗

DOE OSTI2019

CO 2 -Induced displacement and diffusive transport of shale geofluids in silica nanopores of varying sizes

The need to recover our energy resources in a sustainable manner necessitates the development of technological approaches to reduce water use and enhance the use and storage of alternative processing fluids such as CO 2 . These societal and technological needs require a fundamental understanding of the pore-scale organization and transport behaviors of confined fluids. Therefore, the aim of this study is to establish a molecular-scale basis for evaluating CO 2 -induced selective adsorption and diffusive transport behavior of hydrocarbon fluids such as propane and toluene in silica nanopores with sizes in the range of 2–10 nm. The studied fluids are composed of CO 2 -propane, CO 2 -propane-toluene, and CO 2 -toluene. CO 2 was found to adsorb preferentially to the silica surfaces by forming hydrogen bonds with the surface hydroxyl (–OH) groups. The selective adsorption of CO 2 over propane was significantly higher compared to toluene at the pore sizes in the range of 2–10 nm. Increasing pore size reduces the extent of CO 2 , propane and toluene adsorbed on the silica surfaces while the corresponding diffusivities increased. Anisotropic diffusivities of the confined molecules were noted. More polar and higher molecular weight constituents of the oil such as toluene diffuse more slowly in confinement. These studies provide detailed scientific insights into the role of CO 2 in enhancing hydrocarbon recovery from unconventional and complex porous environments. These molecular-scale investigations suggest that CO 2 has a higher tendency to displace lighter aliphatic hydrocarbon molecules such as propane away from the surface as opposed to heavier hydrocarbon molecules such as toluene.

42 ENGINEERING↗

DOE OSTI2025

A dynamic likelihood approach to filtering transport processes: advection-diffusion dynamics

A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems –waves–, and in this paper, it is extended via a split step formulation, to handle advection-diffusion problems. In the dynamic likelihood approach, observations and their statistics are used to propagate probabilities along characteristics, evolving the likelihood in time. The estimate posterior thus inherits phase information. For advection-diffusion the advective part of the time evolution is handled on the basis of observations alone, while the diffusive part is informed through the model as well as observations. We expect, and indeed show here, that in advection-dominated problems, the DLF approach produces better estimates than other assimilation approaches, particularly when the observations are sparse and have low uncertainty. The added computational expense of the method is cubic in the total number of observations over time, which is on the same order of magnitude as a standard Kalman filter and can be mitigated by bounding the number of forward propagated observations, discarding the least informative data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Preferential adsorption of noble gases in zeolitic tuff with variable saturation: A modeling study of counter-intuitive diffusive-adsorptive behavior

Noble gas transport through geologic media has important applications in the prediction and characterization of measured gas signatures related to underground nuclear explosions (UNEs). Retarding processes such as adsorption can cause significant species fractionation of radionuclide gases, which has implications for measured and predicted signatures used to distinguish radioxenon originating from civilian nuclear facilities or from UNEs. Accounting for the effects of variable water saturation in geologic media on tracer transport is one of the most challenging aspects of modeling gas transport because there is no unifying relationship for the associated tortuosity changes between different rock types, and reactive transport processes such as adsorption that are affected by the presence of water likewise behave differently between gas species. In this study, we perform numerical diffusive-adsorptive transport simulations to estimate gas transport parameters associated with bench-scale laboratory diffusion cell experiments measuring breakthrough in zeolitic and non-zeolitic rocks for a gaseous mixture of xenon, krypton, and SF 6 at varying degrees of water saturation (S w ). Counter-intuitive transport behavior was observed in the zeolitic rock experiments whereby breakthrough concentrations were significantly higher when the core was partially saturated (S w = 17 %) than under dry (S w = 0 %) conditions. Breakthrough of xenon was especially retarded in the dry core – likely due to comparatively high affinity of xenon for zeolitic adsorption sites – and estimated effective diffusion coefficients for all gases were approximately an order of magnitude lower than what is predicted by porosity-tortuosity models. We propose the counter-intuitive behavior observed is because water infiltration of zeolite nanopores reduces both the adsorptive capacity of the rock and the tortuosity of connected flow paths. We developed a two-site competitive kinetic Langmuir adsorption reaction for the porous media transport simulator in order to constrain transport parameters within zeolitic tuff, where differential adsorption to zeolite and non-zeolite pores was observed. We determined that liquid saturation-dependent diffusive-adsorptive transport is affected by subtle and at times competing processes that are specific to different gases, which have a significant overall influence on effective transport parameters.

58 GEOSCIENCES↗

DOE OSTI2023

A diffusion–deformation model with damage for polymer undergoing rapid decompression failure

Green hydrogen is emerging as one of the most promising alternatives to replace fossil fuels. While hydrogen gas has a good energy density by weight, its poor energy density by volume requires it to be stored under high pressure for commercial use. The hydrogen infrastructure developed to handle this high pressure hydrogen contains multiple components made of polymers as sealing agents. Although polymers do not react chemically with hydrogen gas, they undergo a mechanical failure when high pressure hydrogen gas is suddenly depressurized. This phenomenon known as 'rapid decompression failure' occurs due to the diffusion of hydrogen through polymer and getting trapped inside pre-existing cavities or voids. Here, in this paper, a continuum mechanics-based coupled diffusion-deformation-damage model was developed to predict the hydrogen distribution, stress distribution, and damage propagation inside the polymer while it undergoes rapid decompression failure. The polymer was modeled as a hyperelastic material because it represents the nonlinear material response observed in uniaxial tensile tests perfectly. The effects of hydrogen diffusivity, pre-existing cavity size, cavity location, applied hydrogen pressure, and depressurization rate on damage initiation were studied. It was found that the coefficient of diffusion plays an important role in damage initiation and damage was mostly concentrated in the inside areas rather than near the surface. Experiments were conducted with EPDM polymer which agreed well with the predicted trends using the given model. The effect of adding carbon black and silica filler particles and plasticizer to the pure EPDM polymer was also studied. It was found that damage during RDF decreases with the addition of fillers, but increases with the addition of the plasticizer. Finally, the damage evolution in the presence of two cavities was also studied, and was found that the interaction of stress fields around the cavities alters the damage occurring during RDF.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Micro-tensile testing of neutron-irradiated Al/Zr and Zr/U-Mo diffusion bonds

This study focuses on micro-tensile testing of neutron-irradiated Al/Zr and Zr/U-Mo diffusion bonds, which are integral to the structure and performance of nuclear fuel plates used in the fuel being developed for U.S. high-power research reactors. During fabrication, two distinct diffusion bonds occur—one at the Zr/U-10Mo interface via roll bonding, and the Zr/Al interface via hot isostatic pressing at 833 K. This work utilizes micro-tensile testing specimens approximately 7 × 7 × 18 μm 3 , which are sufficiently large to encompass the identified diffusion zones to evaluate the failure strength and identify the failure location. For the Zr/Al interface, all failures occurred in the bulk aluminum. The average yield strength, ultimate strength, and strain at failure for the two parent samples were: 125 ± 10 MPa, 139 ± 24 MPa, 156 ± 21 MPa, 185 ± 14 MPa, 37.9 ± 5.6 %, and 29.7 ± 3.4 %, respectively. For specimens across the Zr/U-Mo interface, failures occurred either in the bulk Zr or U-Mo, with no failures observed in the diffusion region. For specimens that failed in the bulk Zr the failure strength and strain for the two parent samples were 570 MPa, 710 ± 131 MPa, and 43.3 %, 27.3 ± 6.6 % respectively. The specimens that failed in the bulk U-Mo had failure strengths and strains of 596 ± 32 MPa, 548 ± 124 MPa, and 2.2 ± 1.3 %, 1.5 ± 0.6 % respectively. In conclusion, these findings support the development of accurate thermo-mechanical models for irradiated fuel performance by identifying the mechanical limits and failure locations within the bonded regions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

A Robust Numerical Treatment of Solid-Phase Diffusion in Pseudo Two-Dimensional Lithium-Ion Battery Models

Solid-phase diffusion in active materials of lithium-ion batteries significantly affects charging and safety-related behavior of lithium-ion batteries. Therefore, it is essential to develop an efficient and robust numerical algorithm for solving solid-phase diffusion equations in physics-based battery models. In this work, we discuss the origins of numerical instabilities that can occur when solving the solid-phase diffusion equations using iterative methods. Then, in order to resolve such issues, we propose a simple numerical treatment to the surface flux term of discretized solid-phase diffusion equations. To demonstrate its numerical robustness, the proposed method is implemented into a pseudo two-dimensional (P2D) physics-based battery model and simulations are conducted at wide ranges of operating conditions. Even with extremely poor initial guesses for the Li+ concentrations of the active materials, computations using the proposed method do not diverge and the their computational speeds are comparable to those with conventional initial guesses. Comprehensive tests of the proposed method are also performed with a dynamic current profile based on US06 driving profile and a multi-stage charging profile with very high initial C-rate (12C).

battery modeling↗

DOE OSTI2025

Effect of high scandium doping in barium zirconate on nickel diffusion and performance of proton-conducting solid oxide electrolyzer cells

Proton-conducting solid oxide electrolyzer cells (p-SOECs) are emerging but promising technologies for hydrogen production. However, due to the lack of a robust electrolyte, p-SOECs struggle simultaneously to display high performance, Faradaic efficiency, and durability. Motivated by its high proton concentrations and stability as a barium zirconate, we have investigated BaZr 0.6 Sc 0.4 O 3-δ (BZSc40) as a potential next-generation p-SOEC electrolyte. Here, we found elevated levels of NiO diffusion through BZSc40 electrolytes during high-temperature sintering, attributed to the large oxygen vacancy concentrations present in BZSc40, as revealed by first-principle computational results. Controlling NiO diffusion is critical, as it can facilitate densification and grain size growth, but it may also detrimentally impact performance by causing electronic leakage. By optimizing sintering temperature when fabricating BZSc40 cells, we successfully controlled NiO diffusion, achieving sufficient electrolyte densification along with high performance and Faradaic efficiency. BZSc40 cells reached −0.99 A/cm 2 at 1.3 V and 600 °C and exhibited enhanced durability with a 3.37 mV/kh degradation rate at −0.8 A/cm 2 over a 200-h testing period. BZSc40 electrolytes demonstrated superior performance over BaZr 0.8 Y 0.2 O 3-δ (BZY20). In addition to elevated current densities and grain sizes, BZSc40 cells achieved Faradaic efficiencies of 76 % compared to 54 % for BZY20 at −0.2 A/cm 2 and 600 °C. This work lays the foundation for BZSc40 as a potential electrolyte due to its advantages over BZY20 while demonstrating the significance of controlling NiO diffusion when fabricating p-SOECs.

Electrolyzer↗

DOE OSTI2024

Electric field enhanced diffusion welding of alloy 617: Microstructural characteristics and mechanical properties

This study investigated the microstructural characteristics and mechanical behavior of diffusion welded nickel-based Alloy 617 obtained by electric field-assisted sintering (EFAS) using various parameters. The interfacial microstructure exhibited different characteristics including good grain boundary (GB) migration across the interface in the samples diffusion-welded at 1100 °C and a flat interface in the samples joined at 1000 °C and 1050 °C. The interface consisted of fine Al 2 O 3 oxides, while precipitation of interfacial M 23 C 6 carbides was not observed. Grain boundaries migrated across the Al 2 O 3 oxides, leaving these oxides within the grains. Graded grain size was observed, with grain coarsening being more significant near the sample surface due to the temperature gradient induced by EFAS. Tensile testing revealed that the specimens fractured in the matrix away from the interface, indicting strong diffusion-welded joints. Further, the peak tensile strength of 807 MPa was obtained in the samples welded at 1000 °C due to minimal grain growth. The materials obtained at 1100 °C exhibited reduced tensile strength but improved ductility. Strain maps revealed by digital image correlation showed alternating high and low strain segments in the samples produced at 1000 °C and 1050 °C, indicating that the flat interfaces with no GB migration were less ductile compared to the matrix. A greater strain uniformity was observed along the bond interfaces with improved GB migration. The hardness reduced near the sample surfaces due to enlarged grains induced by temperature gradient. This study demonstrates that GB migration and enhanced mechanical strength can be achieved in diffusion-welded Alloy 617.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Electroluminescence pulse shape and electron diffusion in liquid argon measured in a dual-phase TPC

Here, we report the measurement of the longitudinal diffusion constant in liquid argon with the DarkSide-50 dual-phase time projection chamber. The measurement is performed at drift electric fields of 100 V/cm, 150 V/cm, and 200 V/cm using high statistics $^{39}$Ar decays from atmospheric argon. We derive an expression to describe the pulse shape of the electroluminescence signal (S2) in dual-phase TPCs. The derived S2 pulse shape is fit to events from the uppermost portion of the TPC in order to characterize the radial dependence of the signal. The results are provided as inputs to the measurement of the longitudinal diffusion constant DL, which we find to be (4.12 $\pm$ 0.04) cm$^2$/s for a selection of 140keV electron recoil events in 200V/cm drift field and 2.8kV/cm extraction field. To study the systematics of our measurement we examine datasets of varying event energy, field strength, and detector volume yielding a weighted average value for the diffusion constant of (4.09 $\pm$ 0.09) cm$^2$ /s. The measured longitudinal diffusion constant is observed to have an energy dependence, and within the studied energy range the result is systematically lower than other results in the literature.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Conditions for translation and scaling invariance of the neutron diffusion equation

Lie group methods are applied to the time-dependent, monoenergetic neutron diffusion equation in materials with spatial and time dependence. To accomplish this objective, the underlying 2nd order partial differential equation (PDE) is recast as an exterior differential system so as to leverage the isovector symmetry analysis approach. Some of the advantages of this method as compared to traditional symmetry analysis approaches are revealed through its use in the context of a 2nd order PDE. In this context, various material properties appearing in the mathematical model (e.g., a diffusion coefficient and macroscopic cross section data) are left as arbitrary functions of space and time. The symmetry analysis that follows is restricted to a search for translation and scaling symmetries; consequently the Lie derivative yields specific material conditions that must be satisfied in order to maintain the presence of these important similarity transformations. The principal outcome of this work is thus the determination of analytic material property functions that enable the presence of various translation and scaling symmetries within the time-dependent, monoenergetic neutron diffusion equation. The results of this exercise encapsulate and generalize many existing results already appearing in the literature. While the results contained in this work are primarily useful as phenomenological guides pertaining to the symmetry behavior of the neutron diffusion equation under certain assumptions, they may eventually be useful in the construction of exact solutions to the underlying mathematical model. Furthermore, the results of this work are also useful as a starting point or framework for future symmetry analysis studies pertaining to the neutron transport equation and its many surrogates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Solute diffusion behavior during heat treatment and its impact in Sc-microalloyed Al-Cu system

Scandium (Sc) is a promising microalloying element that enhances the strength and thermal stability of aluminum (Al) alloys. However, these benefits are not fully realized in aluminum-copper (Al-Cu) systems, and corrosion resistance often declines due to the complex phase evolution and diffusion behavior of Cu and Sc. Here, to clarify this, solute diffusion behavior and Cu-Sc interaction during heat treatment (HT) were investigated using in situ synchrotron-based transmission x-ray microscopy (TXM), wide-angle x-ray scattering (WAXS), and x-ray absorption near-edge structure (XANES) spectroscopy. The results, supported by electron microscopy, reveal strong Cu-Sc bonding that significantly impedes solute diffusion, leading to inhomogeneous solute distribution and non-uniform precipitation. Moreover, the Al-Cu-Sc eutectic phase exhibits high thermal stability, resisting dissolution even near the matrix liquidus. These findings quantitatively elucidate the sluggish diffusion kinetics of Cu and Sc, which can help redesign HT schedules to improve both mechanical properties and corrosion resistance in Sc-microalloyed Al-Cu alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Temperature-dependent diffuse reflectance measurements of ceramic powders in the near- and mid-infrared spectra

Radiative properties are critical to quantify radiative energy fluxes between surfaces and in participating media. However, there is limited experimental data on temperature-dependent radiative properties of materials. Herein, this work focuses on experimentally measuring temperature-dependent diffuse reflectance in the near- and mid-infrared spectra (1–20 μm) for ceramic particles with applications as heat-transfer and thermal-storage media in concentrated solar power (CSP) plants. Specifically, a commercially available sintered bauxite proppant, ACCUCAST ID80, and its primary chemical constituents—alumina (Al 2 O 3 ) and silica (SiO 2 )—are measured in powder form using a Fourier transform infrared spectrometer (FTIR) coupled with a specialized diffuse reflectance accessory and a heated stage. Room-temperature diffuse reflectance measurements show increased absorption in tests with greater mass fractions of the ceramic samples. There is a strong correlation in the measured reflectance spectra of ACCUCAST with alumina and silica in the spectral range 2000–500 cm –1 (5–20 μm). Whereas, for shorter wavelengths (< 5 μm), the absorptance for ACCUCAST is greater than the absorptance for alumina and silica, indicating contributions from other chemical species present in the composite material. For the first time, temperature-dependent diffuse reflectance measurements are reported for ACCUCAST up to 1000 °C. These results are compared against those of alumina and silica through the calculation of a thermal emittance. All three materials exhibit a calculated emittance of ~0.9 at room temperature. However, this value decreases to ~0.6 for ACCUCAST and drops to less than 0.4 for alumina and silica at 1000 °C. Thermal cycling in air at 1000 °C resulted in a visible color change from dark grey to light orange for ACCUCAST and a subsequent larger increase in reflectance for wavelengths less than 5 μm as compared to ACCUCAST thermally cycled at 1000 °C in vacuum. Alumina and silica spectra proved to be largely unaffected by thermal cycling under atmospheric conditions. Overall, this study establishes a powerful technique for the characterization of radiative properties of particulate materials as a function of temperature and presents a detailed case study of ACCUCAST, a candidate for next-generation particle-based CSP.

14 SOLAR ENERGY↗

DOE OSTI2024

Role of Short-Range Order on Diffusion Coefficients in the Li–Mg Alloy

Li–Mg alloys are important because of their beneficial role in fostering uniform plating and stripping of lithium in all-solid-state batteries. The alloy Li x Mg 1–x forms a solid solution on the BCC crystal structure when the lithium content is greater than x ≈ 0.3. The activation barriers of lithium and magnesium exchanges with a vacancy, crucial for substitutional diffusion, are predicted to be exceptionally low and almost identical, with negligible dependence on the alloy composition. The equilibrium vacancy concentration at room temperature is predicted to be very low, and it also remains almost constant with no dependence on Mg content in the alloy (for x Li ≥ 0.5). Nevertheless, both experiments and kinetic Monte Carlo simulations indicate that the tracer diffusion coefficients decrease by almost an order of magnitude with the addition of Mg to the alloy. In this contribution, the crucial role that chemical short-range order plays in affecting the diffusion coefficients is studied. Chemical short-range order is found to increase the effective activation barrier for lithium and magnesium diffusion by making successive atomic hops with vacancies correlated.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Particle-Phase Diffusion Modulates Partitioning of Semivolatile Organic Compounds to Aged Secondary Organic Aerosol

The diffusivity of semivolatile organic compounds (SVOCs) in the bulk particle phase of a viscous atmospheric secondary organic aerosol (SOA) can have a profound impact on aerosol growth and size distribution dynamics. Here, we investigate the bulk diffusivity of SVOCs formed from photo-oxidation of isoprene as they partition to a bimodal aerosol consisting of an Aitken (potassium sulfate) and accumulation mode (aged α-pinene SOA) particles as a function of relative humidity (RH). The model analysis of the observed size distribution evolution shows that liquid-like diffusion coefficient values of D b > 10 –10 cm 2 s –1 fail to explain the growth of the Aitken mode. Instead, much lower values of Db between 2.5 × 10 –15 cm 2 s –1 at 32% RH and 8 × 10 –15 cm 2 s –1 at 82% RH were needed to successfully reproduce the growth of both modes. The diffusivity within the aged α-pinene SOA remains appreciably slow even at 80% RH, resulting in hindered partitioning of SVOCs to large viscous particles and allowing smaller and relatively less viscous particles to effectively absorb the available SVOCs and grow much faster than would be possible otherwise. Our results have important implications for modeling SOA formation and growth in the ambient atmosphere.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Temperature-Dependent Constrained Diffusion of Micro-Confined Alkylimidazolium Chloride Ionic Liquids

Alkylimidazolium chloride ionic liquids (ILs) have many uses in a variety of separation systems, including micro-confined separation systems. To understand the separation mechanism in these systems, the diffusion properties of analytes in ILs under relevant operating conditions, including micro-confinement dimension and temperature, should be known. For example, separation efficiencies for various IL-based microextraction techniques are dependent on the sample volume and temperature. Temperature-dependent (20–100 °C) fluorescence recovery after photobleaching (FRAP) was utilized to determine the diffusion properties of a zwitterionic, hydrophilic dye, ATTO 647, in alkylimidazolium chloride ILs in micro-confined geometries. These micro-confined geometries were generated by sandwiching the IL between glass substrates that were separated by ~1 to 100 μm. From the measured temperature-dependent FRAP data, we note alkyl chain length-, thickness-, and temperature-dependent diffusion coefficients, with values ranging from 0.021 to 46 μm 2 /s. Deviations from Brownian diffusion are observed at lower temperatures and increasingly less so at elevated temperatures; the differences are attributed to alterations in intermolecular interactions that reduce temperature-dependent nanoscale structural heterogeneities. Furthermore, the temperature- and thickness-dependent data provide a useful foundation for efficient design of micro-confined IL separation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Proton Diffusion in Liquid 1,2,3-Triazole Studied by Incoherent Quasi-Elastic Neutron Scattering

Improving the proton transport in polymer electrolytes impacts the performance of next-generation solid-state batteries. However, little is known about proton conductivity in nonaqueous systems due to the lack of an appropriate level of fundamental understanding. Here, we studied the proton transport in small molecules with dynamic hydrogen bonding, 1,2,3-triazole, as a model system of proton hopping in a nonaqueous environment using incoherent quasi-elastic neutron scattering. By using the jump-diffusion model, we identified the elementary jump-diffusion motion of protons at a much shorter length scale than those by nuclear magnetic resonance and impedance spectroscopy for the estimated long-range diffusion. In addition, a spatially restricted diffusive motion was observed, indicating that proton motion in 1,2,3-triazole is complex with various local correlated dynamics. In conclusion, these correlated dynamics will be important in elucidating the nature of the proton dynamics in nonaqueous systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗