arXiv subjects

Martin Z. Bazant

Publications and source records attributed to Martin Z. Bazant.

At least 55 records · Page 3Linked to original sources

arXiv2021

Salt-in-Ionic-Liquid Electrolytes: Ion Network Formation and Negative Effective Charges of Alkali Metal Cations

Salt-in-ionic liquid electrolytes have attracted significant attention as potential electrolytes for next generation batteries largely due to their safety enhancements over typical organic electrolytes. However, recent experimental and computational studies have shown that under certain conditions alkali cations can migrate in electric fields as if they carried a net negative effective charge. In particular, alkali cations were observed to have negative transference numbers at small mole fractions of alkali metal salt that revert to the expected net positive transference numbers at large mole fractions. Simulations have provided some insights into these observations, where the formation of asymmetric ionic clusters, as well as a percolating ion network could largely explain the anomalous transport of alkali cations. However, a thermodynamic theory that captures such phenomena has not been developed, as ionic associations were typically treated via the formation of ion pairs. The theory presented herein, based on the classical polymer theories, describes thermoreversible associations between alkali cations and anions, where the formation of large, asymmetric ionic clusters and a percolating ionic network are a natural result of the theory. Furthermore, we present several general methods to calculate the effective charge of alkali cations in ionic liquids. We note that the negative effective charge is a robust prediction with respect to the parameters of the theory, and that the formation of a percolating ionic network leads to the restoration of net positive charges of the cations at large mole fractions of alkali metal salt. Overall, we find excellent qualitative agreement between our theory and molecular simulations in terms of ionic cluster statistics and the effective charges of the alkali cations.

cond-mat.stat-mech↗

arXiv2021

Dip-coating of bidisperse particulate suspensions

Dip-coating consists in withdrawing a substrate from a bath to coat it with a thin liquid layer. This process is well-understood for homogeneous fluids, but heterogeneities such as particles dispersed in the liquid lead to more complex situations. Indeed, particles introduce a new length scale, their size, in addition to the thickness of the coating film. Recent studies have shown that at first order, the thickness of the coating film for monodisperse particles can be captured by an effective capillary number based on the viscosity of the suspension, providing that the film is thicker than the particle diameter. However, suspensions involved in most practical applications are polydisperse, characterized by a wide range of particle sizes, introducing additional length scales. In this study, we investigate the dip coating of suspensions having a bimodal size distribution of particles. We show that the effective viscosity approach is still valid in the regime where the coating film is thicker than the diameter of the largest particles, although bidisperse suspensions are less viscous than monodisperse suspensions of the same solid fraction. We also characterize the intermediate regime that consists of a heterogeneous coating layer and where the composition of the film is different from the composition of the bath. A model to predict the probability of entraining the particles in the liquid film depending on their sizes is proposed and captures our measurements. In this regime, corresponding to a specific range of withdrawal velocities, capillarity filters the large particles out of the film.

cond-mat.soft↗

arXiv2021

Correlative image learning of chemo-mechanics in phase-transforming solids

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (e.g., due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. In this work, we developed a generalizable, physically-constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on Li$_X$FePO$_4$, a technologically-relevant battery positive electrode material. We uncovered the functional form of composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 $\leq$ X $\leq$ 1), including inside the thermodynamically-unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

cond-mat.mtrl-sci↗

arXiv2021

Blistering Failure of Elastic Coatings with Applications to Corrosion Resistance

A variety of polymeric surfaces, such as anti-corrosion coatings and polymer-modified asphalts, are prone to blistering when exposed to moisture and air. As water and oxygen diffuse through the material, dissolved species are produced, which generate osmotic pressure that deforms and debonds the coating.These mechanisms are experimentally well-supported; however, comprehensive macroscopic models capable of predicting the formation osmotic blisters, without extensive data-fitting, is scant. Here, we develop a general mathematical theory of blistering and apply it to the failure of anti-corrosion coatings on carbon steel. The model is able to predict the irreversible, nonlinear blister growth dynamics, which eventually reaches a stable state, ruptures, or undergoes runaway delamination, depending on the mechanical and adhesion properties of the coating. For runaway delamination, the theory predicts a critical delamination length, beyond which unstable corrosion-driven growth occurs. The model is able to fit multiple sets of blister growth data with no fitting parameters. Corrosion experiments are also performed to observe undercoat rusting on carbon steel, which yielded trends comparable with model predictions. The theory is used to define three dimensionless numbers which can be used for engineering design of elastic coatings capable of resisting visible deformation, rupture, and delamination.

cond-mat.soft↗

arXiv2021

Deionization Shocks in Crossflow

Shock electrodialysis is a recently developed electrochemical water treatment method which shows promise for water deionization and ionic separations. Although simple models and scaling laws have been proposed, a predictive theory has not yet emerged to fit experimental data and enable system design. Here, we extend and analyze existing "leaky membrane" models for the canonical case of a steady shock in cross flow, as in recent experimental prototypes. Two-dimensional numerical solutions are compared with analytical boundary-layer approximations and experimental data. The boundary-layer theory accurately reproduces the simulation results for desalination, and both models predict the data collapse of the desalination factor with dimensionless current, scaled to the incoming convective flux of cations. The numerical simulation also predicts the water recovery increase with current. Nevertheless, both approaches cannot quantitatively fit the transition from normal to over-limiting current, which suggests gaps in our understanding of extreme electrokinetic phenomena in porous media.

physics.flu-dyn↗

arXiv2021

Image Inversion and Uncertainty Quantification for Constitutive Laws of Pattern Formation

The forward problems of pattern formation have been greatly empowered by extensive theoretical studies and simulations, however, the inverse problem is less well understood. It remains unclear how accurately one can use images of pattern formation to learn the functional forms of the nonlinear and nonlocal constitutive relations in the governing equation. We use PDE-constrained optimization to infer the governing dynamics and constitutive relations and use Bayesian inference and linearization to quantify their uncertainties in different systems, operating conditions, and imaging conditions. We discuss the conditions to reduce the uncertainty of the inferred functions and the correlation between them, such as state-dependent free energy and reaction kinetics (or diffusivity). We present the inversion algorithm and illustrate its robustness and uncertainties under limited spatiotemporal resolution, unknown boundary conditions, blurry initial conditions, and other non-ideal situations. Under certain situations, prior physical knowledge can be included to constrain the result. Phase-field, reaction-diffusion, and phase-field-crystal models are used as model systems. The approach developed here can find applications in inferring unknown physical properties of complex pattern-forming systems and in guiding their experimental design.

physics.comp-ph↗

arXiv2021

Ion Clusters and Networks in "Water-in-Salt Electrolytes"

Water-in-salt electrolytes (WiSEs) are a class of super-concentrated electrolytes that have shown much promise in replacing organic electrolytes in lithium-ion batteries. At the extremely high salt concentrations of WiSEs, ionic association is more complicated than the simple ion pair description. In fact, large branched clusters can be present in WiSEs, and past a critical salt concentration, an infinite percolating ionic network can form spontaneously. In this work, we simplify our recently developed thermodynamic model of reversible ionic aggregation and gelation, tailoring it specifically for WiSEs. Our simplified theory only has a handful of parameters, all of which can be readily determined from simulations. Our model is able to quantitatively reproduce the populations of ionic clusters of different sizes as a function of salt concentration, the critical salt concentration for ionic gelation, and the fraction of ions incorporated into the ionic gel, as observed from molecular simulations of three different lithium-based WiSEs. The extent of ionic association and gelation greatly affects the effective ionic strength of solution, the coordination environment of active cations that is known to govern the chemistry of the solid-electrolyte interface, and the thermodynamic activity of all species in the electrolyte.

physics.chem-ph↗

arXiv2021

A Physics-Guided Neural Network Framework for Elastic Plates: Comparison of Governing Equations-Based and Energy-Based Approaches

One of the obstacles hindering the scaling-up of the initial successes of machine learning in practical engineering applications is the dependence of the accuracy on the size of the database that "drives" the algorithms. Incorporating the already-known physical laws into the training process can significantly reduce the size of the required database. In this study, we establish a neural network-based computational framework to characterize the finite deformation of elastic plates, which in classic theories is described by the Föppl--von Kármán (FvK) equations with a set of boundary conditions (BCs). A neural network is constructed by taking the spatial coordinates as the input and the displacement field as the output to approximate the exact solution of the FvK equations. The physical information (PDEs, BCs, and potential energies) is then incorporated into the loss function, and a pseudo dataset is sampled without knowing the exact solution to finally train the neural network. The prediction accuracy of the modeling framework is carefully examined by applying it to four different loading cases: in-plane tension with non-uniformly distributed stretching forces, in-plane central-hole tension, out-of-plane deflection, and buckling under compression. \hl{Three ways of formulating the loss function are compared: 1) purely data-driven, 2) PDE-based, and 3) energy-based. Through the comparison with the finite element simulations, it is found that all the three approaches can characterize the elastic deformation of plates with a satisfactory accuracy if trained properly. Compared with incorporating the PDEs and BCs in the loss, using the total potential energy shows certain advantage in terms of the simplicity of hyperparameter tuning and the computational efficiency.

cs.CE↗

arXiv2021

Growth morphology and symmetry selection of interfacial instabilities in anisotropic environments

The displacement of a fluid by another less viscous one in a quasi-two dimensional geometry typically leads to complex fingering patterns. In an isotropic system, dense-branching growth arises, which is characterized by repeated tip-splitting of evolving fingers. When anisotropy is present in the interfacial dynamics, the growth morphology changes to dendritic growth characterized by regular structures. We introduce anisotropy by engraving a six-fold symmetric lattice of channels on a Hele-Shaw cell. We show that the morphology transition in miscible fluids depends not only on the previously reported degree of anisotropy set by the lattice topography, but also on the viscosity ratio between the two fluids. Remarkably, the viscosity ratio and the degree of anisotropy also govern the global features of the dendritic patterns, inducing a systematic change from six-fold towards twelve-fold symmetric dendrites. Varying either control parameter provides a new method to tune the symmetry of complex patterns, which may also have relevance for analogous phenomena of gradient-driven interfacial dynamics, such as directional solidification or electrodeposition.

physics.flu-dyn↗

arXiv2020

Theory of Faradaically Modulated Redox Active Electrodes for Electrochemically Mediated Selective Adsorption Processes

Electrochemically mediated selective adsorption is an emerging electrosorption technique that utilizes Faradaically enhanced redox active electrodes, which can adsorb ions not only electrostatically, but also electrochemically. The superb selectivity (>100) of this technique enables selective removal of toxic or high-value target ions under low energy consumption. Here, we develop a general theoretical framework to describe the competitive electrosorption phenomena involving multiple ions and surface-bound redox species. The model couples diffusion, convection and electromigration with competitive surface adsorption reaction kinetics, consistently derived from non-equilibrium thermodynamics. To optimize the selective removal of the target ions, design criteria were derived analytically from physically relevant dimensionless groups and time scales, where the propagation of the target anions concentration front is the limiting step. Detailed computational studies are reported for three case studies that cover a wide range of inlet concentration ratios between the competing ions. And in all three cases, target anions in the electrosorption cell forms a self-sharpening reaction-diffusion wave front. Based on the model, a three-step stop-flow operation scheme with a pure stripping solution of target anions is proposed that optimizes the ion adsorption performance and increases the purity of the regeneration stream to almost 100%, which is beneficial for downstream processing.

physics.chem-ph↗

arXiv2020

Equivalent circuit model for electrosorption with redox active materials

Electrosorption is a promising technique for brackish water deionization and waste water remediation. Faradaic materials with redox activity have recently been shown to enhance both the adsorption capacity and the selectivity of electrosorption processes. Development of the theory of electrosorption with redox active materials can provide a fundamental understanding of the electrosorption mechanism and a means to extract material properties from small-scale experiments for process optimization and scale-up. Here, we present an intuitive, physics-based equivalent circuit model to describe the electrosorption performance of redox active materials, which is able to accurately fit experimental cyclic voltammetry measurements. The model can serve as an efficient and easy-to-implement tool to evaluate properties of redox active materials and help to distinguish between the transport-limited and reaction-limited regimes in electrosorption processes. And the extracted intrinsic material properties can be further incorporated into process models under lower supporting electrolyte concentrations for realistic electrosorption applications.

physics.chem-ph↗

arXiv2020

Theory of shock electrodialysis I: Water dissociation and electrosmotic vortices

Shock electrodialysis (shock ED), an emerging electrokinetic process for water purification, leverages the new physics of deionization shock waves in porous media. In previous work, a simple leaky membrane model with surface conduction can explain the propagation of deionization shocks in a shock ED system, but it cannot quantitatively predict the deionization and conductance (which determines the energy consumption), and it cannot explain the selective removal of ions in experiments. This two-part series of work establishes a more comprehensive model for shock ED, which applies to multicomponent electrolytes and any electrical double layer thickness, captures the phenomena of electroosmosis, diffusioosmosis, and water dissociation, and incorporates more realistic boundary conditions. In this paper, we will present the model details and show that hydronium transport and electroosmotic vortices (at the inlet and outlet) play important roles in determining the deionization and conductance in shock ED. We also find that the results are quantitatively consistent with experimental data in the literature. Finally, the model is used to investigate design strategies for scale up and optimization.

physics.flu-dyn↗

arXiv2020

Capillary filtering of particles during dip coating

An object withdrawn from a liquid bath is coated with a thin layer of liquid. Along with the liquid, impurities such as particles present in the bath can be transferred to the withdrawn substrate. Entrained particles locally modify the thickness of the film, hence altering the quality and properties of the coating. In this study, we show that it is possible to entrain the liquid alone and avoid contamination of the substrate, at sufficiently low withdrawal velocity in diluted suspensions. Using a model system consisting of a plate exiting a liquid bath, we observe that particles can remain trapped in the meniscus which exerts a resistive capillary force to the entrainment. We characterize different entrainment regimes as the withdrawal velocity increases: from a pure liquid film, to a liquid film containing clusters of particles, and eventually individual particles. This capillary filtration is an effective barrier against the contamination of substrates withdrawn from a polluted bath and finds application against biocontamination.

cond-mat.soft↗

arXiv2020

Electrochemical Ion Insertion: From Atoms to Devices

Electrochemical ion insertion involves coupled ion-electron transfer reactions, transport of guest species, and redox of the host. The hosts are typically anisotropic solids with two-dimensional conduction planes, but can also be materials with one-dimensional or isotropic transport pathways. These insertion compounds have traditionally been studied in the context of energy storage, but also find extensive applications in electrocatalysis, optoelectronics, and computing. Recent developments in operando, ultrafast, and high-resolution characterization methods, as well as accurate theoretical simulation methods, have led to a renaissance in the understanding of ion-insertion compounds. In this Review, we present a unified framework for understanding insertion compounds across time and length scales ranging from atomic to device levels. Using graphite, transition metal dichalcogenides, layered oxides, oxyhydroxides, and olivines as examples, we explore commonalities in these materials in terms of point defects, interfacial reactions, and phase transformations. We illustrate similarities in the operating principles of various ion-insertion devices ranging from batteries and electrocatalysts to electrochromics and thermal transistors, with the goal of unifying research across disciplinary boundaries.

cond-mat.mtrl-sci↗

arXiv2020

Theory of coupled ion-electron transfer kinetics

The microscopic theory of chemical reactions is based on transition state theory, where atoms or ions transfer classically over an energy barrier, as electrons maintain their ground state. Electron transfer is fundamentally different and occurs by tunneling in response to solvent fluctuations. Here, we develop the theory of coupled ion-electron transfer, in which ions and solvent molecules fluctuate cooperatively to facilitate electron transfer. We derive a general formula of the reaction rate that depends on the overpotential, solvent properties, the electronic structure of the electron donor/acceptor, and the excess chemical potential of ions in the transition state. For Faradaic reactions, the theory predicts curved Tafel plots with a concentration-dependent reaction-limited current. For moderate overpotentials, our formula reduces to the Butler-Volmer equation and explains its relevance, not only in the well-known limit of large electron-transfer (solvent reorganization) energy, but also in the opposite limit of large ion-transfer energy. The rate formula is applied to Li-ion batteries, where reduction of the electrode host material couples with ion insertion. In the case of lithium iron phosphate, the theory accurately predicts the concentration dependence of the exchange current measured by {\it in operando} X-Ray microscopy without any adjustable parameters. These results pave the way for interfacial engineering to enhance ion intercalation rates, not only for batteries, but also for ionic separations and neuromorphic computing.

physics.chem-ph↗

arXiv2020

Capillary Sorting of Particles by Dip Coating

In this letter, we describe the capillary sorting of particles by size based on dip coating. A substrate withdrawn from a liquid bath entrains a coating whose thickness depends on the withdrawal speed and the liquid properties. If the coating material contains particles, they will only be entrained when the viscous force pulling them with the substrate overcomes the opposing capillary force at the deformable meniscus. This force threshold occurs at different liquid thicknesses for particles of different sizes. Here, we show that this difference can be used to separate small particles from a mixed suspension through capillary filtration. In a bidisperse suspension, we observe three distinct filtration regimes. At low capillary numbers, Ca, no particles are entrained in the liquid coating. At high Ca, all particle sizes are entrained. For a range of capillary numbers between these two extremes, only the smallest particles are entrained while the larger ones remain in the reservoir. We explain how this technique can be applied to polydisperse suspension. We also provide an estimate of the range of capillary number to separate particles of given sizes. The combination of this technique with the scalability and robustness of dip coating makes it a promising candidate for high-throughput separation or purification of industrial and biomedical suspensions.

cond-mat.soft↗

arXiv2020

Correlated Ion Transport and the Gel Phase in Room Temperature Ionic Liquids

Here we present a theory of ion aggregation and gelation of room temperature ionic liquids (RTILs). Based on it, we investigate the effect of ion aggregation on correlated ion transport - ionic conductivity and transference numbers - obtaining closed-form expressions for these quantities.The theory depends on the maximum number of associations a cation and anion can form, and the strength of their association. To validate the presented theory, we perform molecular dynamics simulations on several RTILs, and a range of temperatures for one RTIL. The simulations indicate the formation of large clusters, even percolating through the system under certain circumstances, thus forming a gel, with the theory accurately describing the obtained cluster distributions in all cases. We discuss the possibility of observing a gel phase in neat RTILs, which has hitherto not been discussed in any detail.

physics.chem-ph↗

arXiv2020

Interfacial layering in the electric double layer of ionic liquids

Ions in ionic liquids and concentrated electrolytes reside in a crowded, strongly-interacting environment, leading to the formation of discrete layers of charges at interfaces. Here, we propose a continuum theory that captures the transition from overscreening-- alternating layers of excess charge at low surface potential, to overcrowding-- the formation of dense layers of charge of the same sign at high surface potential. The model outputs slowly-decaying oscillations in the charge density with a wavelength of single ion diameters, as shown by analysis of the gradient expansion. The gradient expansion suggests a new structure for partial differential equations describing the electrostatic potential at charged interfaces. We find quantitative agreement between the theory and molecular simulations in the differential capacitance and concentration profiles.

cond-mat.soft↗