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At least 253 records · Page 14

Emergence of asymmetric skew-scattering dominated anomalous Nernst effect in the spin gapless semiconductors Co 1+x Fe 1-x CrGa

Heusler alloy-based spin gapless semiconductors (SGSs) with very high Curie temperatures ( T C ) have recently gained enormous attention because of their unconventional electronic structures. They exhibit a nonzero band gap in one of the spin channels and a zero band gap in the other spin channel, making them an important class of materials for tunable spin transport. Here, we report the experimental observation of anomalous Nernst effect (ANE) in Co 1 + x Fe 1 - x CrGa ( x = 0 , 0.2, 0.4, and 0.5), which are the emerging quaternary Heusler alloy-based SGSs. While the electron-electron elastic scattering and the disorder-mediated weak localization effect play the major roles in electrical transport for all the samples at low temperatures, the magnon-drag effect was found to dominate the longitudinal thermoelectric transport. The ANE coefficient at room temperature increases from ≈ 0.018 μ V K - 1 for x = 0 to ≈ 0.063 μ V K - 1 for x = 0.5 , which is higher than that for Ni 81 Fe 19 and compressively strained SrRu O 3 films. Our analysis indicates that the observed ANE in these samples originates from asymmetric skew scattering of charge carriers.

36 MATERIALS SCIENCE↗

Transient behavior of drift and ionization in atmospheric pressure nitrogen discharge

The fluid models are frequently used to describe a non-thermal plasma such as a streamer discharge. The required electron transport data and rate coefficients for the fluid model are parametrized using the local field approximation (LFA) in first order models and the local-mean-energy approximation (LMEA) in second order models. We performed Monte Carlo simulations in Nitrogen gas with step changes in the E/N (reduced electric field) to study the behavior of the transport properties in the transient phase. During the transient phase of the simulation, we extract the instantaneous electron mean energy, which is different from the steady state mean electron energy, and the corresponding transport parameters and rate coefficients. Our results indicate that the mean electron energy is not a suitable parameter for mobility/drift of electrons due to big difference in momentum relaxation and energy relaxation. Furthermore, the high energy threshold rates such as ionization show a strong correlation to mean electron energy. In second order models where the energy-balance equation is solved, we suggest that it would rather be appropriate to use the local electric field to find electron drift velocity in gases such as Nitrogen and the local mean electron energy to determine the ionization and excitation rates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mean force kinetic theory applied to self-diffusion in supercritical Lennard-Jones fluids

A new kinetic-theory-based calculation of the self-diffusion coefficient for dense supercritical Lennard-Jones fluids is presented. The mean force kinetic theory, which was recently developed for transport in dense plasmas, is applied for the calculation of diffusion in dense neutral fluids. The calculation only requires the pair distribution function, a quantity that is readily calculable from equilibrium statistical mechanics for many systems, including the Lennard-Jones fluid. The self-diffusion coefficients are compared with calculations from molecular dynamics simulations, and good agreement at high density is demonstrated, even in the vicinity of the solid–fluid coexistence line. A comparison of different kinetic models with molecular dynamics simulations demonstrates that the transport coefficients have important contributions due to particle interaction via a potential of mean force and local correlations, which increase the collision rate. The new calculations compare well to those from free-volume theory and overcome a limitation of this theory that prevents its use in systems that interact via long range monotonic potentials. It is expected that this approach will also apply to other systems, including neutral-plasma and neutral-electrolyte mixtures.

79 ASTRONOMY AND ASTROPHYSICS↗

Sensitivity Calculations for Systems with Polyethylene Reflector Materials Using CLUTCH

The SCALE 6.2.4 code package contains four sequences for calculating $k_{eff}$ sensitivity coefficients. Two of these sequences use deterministic transport solvers: a one-dimensional (1D) capability based on XSDRN, and a two-dimensional (2D) capability based on NEWT. These sequences are restricted to the multigroup (MG) treatment of neutron energy. The three-dimensional (3D) sequences use the KENO V.a or KENO-VI Monte Carlo transport codes and can be used to calculate sensitivity coefficients with either MG or continuous-energy (CE) transport. The 3D sensitivities are ultimately reported in an MG structure, regardless of the method used in the transport calculations. If desired, the sensitivity coefficients can be reported with very fine energy resolution from a CE calculation, but they are calculated only in the MG library structure in the MG mode. CE TSUNAMI methods are available in SCALE starting in SCALE version 6.2. Sensitivity coefficients were generated using the 3D sequences as part of the generation of the SCALE 6.2.2 Validation Report; difficulties encountered when using the CLUTCH method for thick, fissionable-material reflectors were discussed and investigated as documented in a previous paper. This paper discusses the difficulties encountered in generating accurate sensitivity coefficients using the CLUTCH technique for polyethylene reflectors for two fast spectrum benchmarks. Direct perturbation (DP) calculations were performed to confirm the accuracy of the total sensitivity coefficient for important isotopes with large sensitivities in the system. Discrepancies were detected for CLUTCH-calculated sensitivity coefficients in the reflector of a critical experiment with a radial polyethylene reflector. A simple polyethylene-reflected plutonium sphere was then used to further investigate the discrepancy. Calculations performed using the iterated fission probability (IFP) method generated accurate sensitivity coefficients in both cases. The results of this study emphasize the need to confirm CLUTCH sensitivity results with DP calculations. IFP calculations are generally less efficient but more reliable than CLUTCH calculations. Improvements to the CLUTCH methodology that retain the greater efficiency but address identified difficulties are therefore potentially useful to analysts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Statistical distributions for transient transport

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

TAP reactor↗

On the minimum transport required to passively suppress runaway electrons in SPARC disruptions

In Izzo et al (2022 Nucl. Fusion 62 096029), state-of-the-art modeling of thermal and current quench (CQ) magnetohydrodynamics (MHD) coupled with a self-consistent evolution of runaway electron (RE) generation and transport showed that a non-axisymmetric (n = 1) in-vessel coil could passively prevent RE beam formation during disruptions in SPARC, a compact high-field tokamak projected to achieve a fusion gain Q > 2 in DT plasmas. However, such suppression requires finite transport of REs within magnetic islands and re-healed flux surfaces; conservatively assuming zero transport in these regions leads to an upper bound of RE current ~1MA compared to ~8.7MA of pre-disruption plasma current. Further investigation finds that core-localized electrons, within r/a < 0.4 and with kinetic energies ~0.2–15 MeV, contribute most to the RE plateau formation. Yet only a relatively small amount of transport, i.e. a diffusion coefficient ~18 m 2 s -1 , is needed in the core to fully mitigate these REs. Properly accounting for (a) the CQ electric field's effect on RE transport in islands and (b) the contribution of significant RE currents to disruption MHD may help achieve this.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SAS4A/SASSYS-1 Modeling Improvements for the Transition to Natural Circulation

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. In recent years, SAS has undergone a number of improvements to enable improved safety analyses that meet end users’ modernized needs while complying with the current regulatory environment. Improvements made in versions 5.6 and 5.7 released within the last year include the development of anisotropic Reynolds number dependent loss coefficients throughout the core and heat transport systems, the ability to distinguish the transition friction factor from the fully developed laminar and turbulent friction factors, and timedependent direct coolant and wall heating for pipe-like elements in the heat transport systems. While it was possible to capture loss coefficients, friction factors, and heat transfer from an element to a heat sink within SAS in previous versions of the code, users were required to end the simulation and restart it to adjust the input to account for any significant changes to the values during the transient. With these improvements, users can better capture flow reversal, pump heating, and the transition from forced to natural circulation without being limited to constant orifice coefficients, constant heat sinks, or the need to restart the simulation and modify input. In order to demonstrate the application of these improvements, a loss of flow transient is simulated for the Advanced Burner Test Reactor (ABTR).

SAS4A/SASSYS-1↗

Diffusion and migration in polymer electrolytes

Mixtures of neutral polymers and lithium salts have the potential to serve as electrolytes in next-generation rechargeable Li-ion batteries. The purpose of this review is to expose the delicate interplay between polymer-salt interactions at the segmental level and macroscopic ion transport at the battery level. Since complete characterization of this interplay has only been completed in one system: mixtures of poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO/LiTFSI), we focus on data obtained from this system. We begin with a discussion of the activity coefficient, followed by a discussion of six different diffusion coefficients: the Rouse motion of polymer segments is quantified by D seg , the self-diffusion of cations and anions is quantified by D self,+ and D self,- , and the build-up of concentration gradients in electrolytes under an applied potential is quantified by Stefan-Maxwell diffusion coefficients, D 0+ , D 0- , and D +- . The Stefan-Maxwell diffusion coefficients can be used to predict the velocities of the ions at very early times after an electric field is applied across the electrolyte. The surprising result is that D 0- is negative in certain concentration windows. A consequence of this finding is that at these concentrations, both cations and anions are predicted to migrate toward the positive electrode at early times. We describe the controversies that surround this result. Knowledge of the Stefan-Maxwell diffusion coefficients enable prediction of the limiting current. We argue that the limiting current is the most important characteristic of an electrolyte. Excellent agreement between theoretical and experimental limiting current is seen in PEO/LiTFSI mixtures. What sequence of monomers that, when polymerized, will lead to the highest limiting current remains an important unanswered question. It is our hope that the approach presented in this review will guide the development of such polymers.

25 ENERGY STORAGE↗

Double brane holographic model dual to 2d ICFTs

A minimal single brane holographic model can be used as a dual to 2d conformal interfaces (ICFTs) to calculate the transmission coefficient T of energy transported across the defect as well as boundary entropy log g, the additional entanglement entropy for some sub-region that encloses the defect. Both T and log g are uniquely determined by the tension characterizing the brane. In contrast, in field theory defects typically the transmission coefficient can be dialed from 0 to 1 independently for each allowed value of log g. To address this discrepancy, we look at a double brane (3-region bulk) holographic model. Merger of two single brane interfaces creates genuinely new interfaces which indeed allow a range of accessible transmission coefficients for a fixed value of log g. In particular, the T = 0 limit of two completely decoupled BCFTs can be achieved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Low-Temperature Characterization of a Nonaqueous Liquid Electrolyte for Lithium Batteries

Rechargeable batteries exhibit poor performance at low temperatures due to sluggish ion transport through the electrolytic phase. Ion transport is governed by three transport parameters—conductivity, diffusion coefficient, and the cation transference number with respect to the solvent velocity—and the thermodynamic factor. Understanding how these parameters change with temperature is necessary for designing improved electrolytes. In this work, we combine electrochemical techniques with electrophoretic NMR to determine the temperature dependence of these parameters for a liquid electrolyte, LiTFSI salt dissolved in tetraglyme between −20 and 45 °C. At colder temperatures, all species in the electrolyte tend to move more slowly due to increasing viscosity, which translates to a monotonic decrease in conductivity and diffusion coefficient with decreasing temperature. Surprisingly, we find that the field-induced velocity of solvent molecules at a particular salt concentration is a nonmonotonic function of temperature. The cation transference number with respect to the solvent velocity thus exhibits a complex dependence on temperature and salt concentration. The measured thermodynamic and transport properties are used to predict concentration gradients that will form in a lithium-lithium symmetric cell under a constant applied potential as a function of temperature using concentrated solution theory. The calculated steady current at −20 °C is lower than that at 45 °C by roughly two orders of magnitude.

25 ENERGY STORAGE↗

All-Inorganic Halide Perovskites as Potential Thermoelectric Materials: Dynamic Cation off-Centering Induces Ultralow Thermal Conductivity

Halide perovskites are anticipated to impact next generation high performance solar cells because of their extraordinary charge transport and optoelectronic properties. However, their thermal transport behavior has received limited attention. In this work, we studied the thermal transport and thermoelectric properties of the CsSnBr 3–x I x perovskites. We find a strong correlation between lattice dynamics and an ultralow thermal conductivity for series CsSnBr 3–x I x reaching 0.32 Wm –1 K –1 at 550 K. The CsSnBr 3–x I x also possess a decent Seebeck coefficient and controllable electrical transport properties. The crystallography data and theoretical calculations suggest the Cs atom deviates from its ideal cuboctahedral geometry imposed by the perovskite cage and behaves as a heavy atom rattling oscillator. This off-center tendency of Cs, together with the distortion of SnX 6 (X = Br or I) octahedra, produces a highly dynamic and disordered structure in CsSnBr 3–x I x , which gives rise to a very low Debye temperature and phonon velocity. Moreover, the low temperature heat capacity data suggests strong coupling between the low frequency optical phonons and heat carrying acoustical phonons. In conclusion, this induces strong phonon resonance scattering that induces the ultralow lattice thermal conductivity of CsSnBr 3–x I x .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complete characterization of a lithium battery electrolyte using a combination of electrophoretic NMR and electrochemical methods

Improving transport properties of electrolytes is important for developing lithium-ion batteries for future energy storage applications. In Newman's concentrated solution theory, electrolytes are characterized by three transport parameters, conductivity, diffusion coefficient, and transference number, in addition to the thermodynamic factor. In this work, these parameters are all determined for an exemplar liquid electrolyte, lithium bis(trifluoromethanesulfonyl)imide mixed in tetraethylene glycol dimethyl ether, using electrochemical methods. The intrinsic coupling between parameters obtained by electrochemical methods results in large error bars in the transference number that obscure the transport behavior of the electrolyte. Here, we use electrophoretic NMR (eNMR) to measure the electric-field-induced ion and solvent velocities to obtain the transference number directly, which enables determination of the thermodynamic factor with greater certainty. In conclusion, our work indicates that the combination of eNMR and electrochemical methods provides a robust approach for complete characterization of battery electrolytes.

25 ENERGY STORAGE↗

Demonstrate Improved Ag Diffusion and Describe the Basis for Pd Penetration Modeling in SiC

In past work, an effective diffusivity coefficient was determined for Ag transport through the silicon carbide layer of a tristructural isotropic fuel particle. The effective diffusivity coefficient accounts for the microstructure of the silicon carbide and includes both bulk diffusion and grain boundary diffusion of Ag. In this report, the model has been improved by accounting for the enhanced concentration of vacancies in the bulk due to irradiation, which substantially influence bulk diffusivity at low temperatures. To improve the BISON model and make it fission rate dependent, effective diffusivity calculations have been performed that incorporate the radiation modified bulk diffusivity. The microstructure and irradiation-dependent effective diffusivity has also been implemented into BISON, and its predictions for Ag release from tristructural isotropic fuel have been successfully compared to AGR-1 post irradiation measurements. Moreover, a new feature has been developed in the Multiphysics Object-Oriented Simulation Environment (MOOSE) to account for different grain boundary types. The Ag diffusivity in 5 (210)/[001] grain boundaries has been computed and was found to be greater than in random high-angle grain boundaries. The presence of the fission product Pd can also have an important effect on the properties of the silicon carbide layer in tristructural isotropic particles. The penetration of Pd into the silicon carbide layer causes a corrosion reaction that can lead to the failure of the silicon carbide layer; however, this corrosion reaction is not well understood. To enable an improved understanding of the mechanism, ab-initio molecular dynamics simulations of Pd interaction with bulk silicon carbide have been performed. The improved understanding of the reaction will form a basis for future improvements to the BISON’s Pd penetration failure model

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Influence of Aqueous Dispersivity on Transport of Radiological Material at LANL MDA G - 20450

Aqueous dispersivity is a phenomenon by which a solute moving in groundwater mixes with water that does not contain the solute and becomes diluted. Solutes take paths of varying lengths through pore networks or experience slower velocities due to interactions with pore walls. Aqueous dispersivity leads to breakthrough curves with earlier arrival than expected in purely advective systems and persistent 'tails,' or late-arriving, dilute concentrations of the solute. Dispersivity can be longitudinal (in the direction of flow) or transverse (orthogonal to flow). LANL has disposed of radioactive material at Material Disposal Area (MDA) G since the late 1950's. Most of the disposed materials at MDA G are low-level waste (LLW), but other types of radioactive wastes are disposed or stored at the site. For example, there is a collection of remote-handled transuranic waste (RH-TRU) waste in 33 shafts, which were intended to be stored retrievably. Aqueous-phase radionuclides included in models of contaminant transport at MDA G are subject to dispersive processes in porous media of the vadose zone and saturated zone. To model dispersivity at MDA G probabilistically, we created site-specific distributions of aqueous dispersivity. First, we performed a comprehensive review of peer-reviewed publications, reports from other performance assessments of MDA G, and documentation from sites that were considered similar based on expert opinion, such as Yucca Mountain. Data were included from a wide range of sources, so that distributions developed based on the data reflect the current state of knowledge in properties of the subsurface environment. Data were grouped based on value type (e.g., determined via experiment or used in a different model), rock type, zone type (saturated or unsaturated), and site, and were weighted in the distributions according to their relevance to the site and zone type. We combined Monte Carlo simulation and bootstrapping techniques to produce approximate distributions of mean aqueous dispersivity. Distributions of dispersivity for saturated and unsaturated zone transport are differentiated by data weight and the length scales over which transport occurs. We find that underestimating or disregarding transverse dispersivity may lead to overstating simulated well capture in the saturated zone at MDA G. Neglecting transverse dispersivity is a common assumption due in part to use of one-dimensional transport models that do not consider solute spreading orthogonal to flow. Also, we find that variability in longitudinal dispersivity is associated with substantial travel time alterations in the MDA G unsaturated zone and in simulated contaminant breakthrough times at a downstream observation plane in the MDA G saturated zone. Finally, at large scales (>1000 m), a linear trend between the dispersivity coefficient and length over which transport occurs may overestimate the dispersivity coefficient. Future modeling work with application to solute spreading could include interacting advective and diffusive zones in the highly fractured basalt below MDA G. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Correlating conductivity and Seebeck coefficient to doping within crystalline and amorphous domains in poly(3-(methoxyethoxyethoxy)thiophene)

Molecular doping of conjugated polymers (CPs) plays a vital role in optimizing organic electronic and energy applications. For the case of organic thermoelectrics, it is commonly believed that doping CPs with a strong dopant could result in higher conductivity (σ) and thus better power factor (PF). Herein, by investigating thermoelectric performance of a polar side-chain bearing CP, poly(3- (methoxyethoxyethoxy)thiophene) (P3MEET), vapor doped with fluorinatedderivative of tetracyanoquinodimethane FnTCNQ (n = 1, 2, 4), we show that using strong dopants can in fact have detrimental effects on the thermoelectric performance of CPs. Despite possessing higher electron affinity, doping P3MEET with F4TCNQ only results in a σ (27.0 S/cm) comparable to samples doped with other two weaker dopants F2TCNQ and F1TCNQ (26.4 and 20.1 S/cm). Interestingly, F4TCNQ-doped samples display a marked reduction in the Seebeck coefficient (α) compared to F1TCNQ- and F2TCNQ-doped samples from 42 to 13 μV/ K, leading to an undesirable suppression of the PF. Additionally, structural characterizations coupled with Kang-Snyder modeling of the α–σ relation show that the reduction of α in F4TCNQ-doped P3MEET samples originates from the generation of low mobility carrier within P3MEET's amorphous domain. Our results demonstrate that factors such as dopant distribution and doping efficiency within the crystalline and amorphous domains of CPs should play a crucial role in advancing rational design for organic thermoelectrics.

36 MATERIALS SCIENCE↗

A Fast Butterfly-Compressed Hadamard–Babich Integrator for High-Frequency Helmholtz Equations in Inhomogeneous Media with Arbitrary Sources

Here we present a butterfly-compressed representation of the Hadamard-Babich (HB) ansatz for the Green's function of the high-frequency Helmholtz equation in smooth inhomogeneous media. For a computational domain discretized with Nv discretization cells, the proposed algorithm first solves and tabulates the phase and HB coefficients via eikonal and transport equations with observation points and point sources located at the Chebyshev nodes using a set of much coarser computation grids, and then butterfly compresses the resulting HB interactions from all Nv cell centers to each other. The overall CPU time and memory requirement scale as O(Nv log2 Nv) for any bounded two-dimensional (2D) domains with arbitrary excitation sources. A direct extension of this scheme to bounded 3D domains yields an O(Nv4/3) CPU complexity, which can be further reduced to quasi-linear complexities with proposed remedies. The scheme can also efficiently handle scattering problems involving inclusions in inhomogeneous media. Although the current construction of our HB integrator does not accommodate caustics, the resulting HB integrator itself can be applied to certain sources, such as concave-shaped sources, to produce caustic effects. Compared to finite-difference frequency domain methods, the proposed HB integrator is free of numerical dispersion and requires fewer discretization points per wavelength. As a result, it can solve wave propagation problems well beyond the capability of existing solvers. Remarkably, the proposed scheme can accurately model wave propagation in 2D domains with 640 wavelengths per direction and in 3D domains with 54 wavelengths per direction on a state-of-the-art supercomputer at Lawrence Berkeley National Laboratory.

Hadamard--Babich ansatz↗

Ion diffusion coefficients in poly(3-alkylthiophenes) for energy conversion and biosensing: role of side-chain length and microstructure

Conductive polymers are promising materials as active elements for energy storage and conversion devices due to mixed ion–electron conduction. The ion diffusion coefficient is a relative measure of the efficacy of ion transport, allowing for comparison between materials and electrochemical conditions. In this work, diffusion coefficients of hexafluorophosphate (PF6–) counterions in poly(3-alkylthiophene) (P3AT) materials are measured as a function of both side-chain length and microstructure using electrochemical impedance spectroscopy (EIS). For semi-crystalline films, the diffusion coefficient is found to be anomalous and nearly independent of applied electrochemical potential. Here, the anomalous behavior of diffusion indicates that spin casting yields compact films with an enthalpic barrier to ion transport, attributed to ionic trapping. Diffusion coefficient values ~10 –11 cm 2 s –1 were measured for all films, indicating interchain spacing, in the absence of strong intermolecular interactions with the electrolyte, is not a viable design strategy to control ion transport. For the prototypical system of poly(3-hexylthiophene), we observe almost no potential dependence in ion transport for regioregular and regiorandom films of comparable molecular weight, with both exhibiting anomalous diffusion. Alternatively, changing the microstructure of poly(3-hexylthiophene) to a mostly amorphous, ion-imprinted structure yields ~500× increase in the diffusion coefficient to ~2 × 10 –8 cm 2 s –1 at 0.8 V vs. Ag/Ag + with behavior closer to ordinary diffusion. Collectively, these results indicate new insight into ion transport in conductive polymers, where ionic trapping effects can be mitigated through electrodeposition protocols over post-synthesis processing (i.e. spin coating).

14 SOLAR ENERGY↗

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable geometric deep learning (GDL) model for chemical mixtures, DiffMix, which is applied in guiding robotic experimentation and optimization towards fast charging battery electrolytes. In particular, we extend mixture thermodynamic and transport laws by creating GDL-learnable physical coefficients. We evaluate our model with mixture thermodynamics and ion transport properties, where we show improved prediction accuracy and model robustness of Diff-Mix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electrolytes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients. By combining GDL, mixture physics laws, and robotic experimentation, DiffMix expands the predictive modeling methods for chemical mixtures and enables efficient optimization in large chemical spaces.

25 - ENERGY STORAGE↗