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James A. Dawson

Publications and source records attributed to James A. Dawson.

3 recordsLinked to original sources

The Persistence of Memory in Ionic Conduction Probed by Nonlinear Optics

Predicting practical rates of ion transport from atomistic descriptors enables the rational design of materials, devices, and processes, which is especially critical to developing low-carbon energy technologies such as rechargeable batteries. The correlated mechanisms of ionic conduction, variation of conductivity with timescale and confinement, and ambiguity in the vibrational origin of translation, the attempt frequency, call for a direct atomic probe of the most fundamental steps of ionic diffusion: ion hops. However, such hops are rare-event large-amplitude translations, and are challenging to excite and detect. Here we use single-cycle terahertz pumps to impulsively trigger ionic hopping in battery solid electrolytes. This is visualized by an induced transient birefringence enabling direct probing of anisotropy in ionic hopping on the picosecond timescale. The relaxation of the transient signal measures the decay of orientational memory, and the production of entropy in diffusion. We extend experimental results using in silico transient birefringence to identify attempt frequencies for ion hopping. Using nonlinear optical methods, we probe ion transport at its fastest limit, distinguish correlated conduction mechanisms from a true random walk at the atomic scale, and demonstrate the connection between activated transport and the thermodynamics of information.

cond-mat.mtrl-sci

Defect-Driven Anomalous Transport in Fast-Ion Conducting Solid Electrolytes

Solid-state ionic conduction is a key enabler of electrochemical energy storage and conversion. The mechanistic connections between material processing, defect chemistry, transport dynamics, and practical performance are of considerable importance, but remain incomplete. Here, inspired by studies of fluids and biophysical systems, we re-examine anomalous diffusion in the iconic two-dimensional fast-ion conductors, the $β$- and $β^{\prime\prime}$-aluminas. Using large-scale simulations, we reproduce the frequency dependence of alternating-current ionic conductivity data. We show how the distribution of charge-compensating defects, modulated by processing, drives static and dynamic disorder, which lead to persistent sub-diffusive ion transport at macroscopic timescales. We deconvolute the effects of repulsions between mobile ions, the attraction between the mobile ions and charge-compensating defects, and geometric crowding on ionic conductivity. Our quantitative framework based on these model solid electrolytes connects their atomistic defect chemistry to macroscopic performance with minimal assumptions and enables mechanism-driven 'atoms-to-device' optimization of fast-ion conductors.

cond-mat.mtrl-sci

Particle Morphology and Lithium Segregation to Surfaces of the Li$_7$La$_3$Zr$_2$O$_{12}$ Solid Electrolyte

Solid electrolytes for solid-state Li-ion batteries are stimulating considerable interest for next-generation energy storage applications. The Li$_7$La$_3$Zr$_2$O$_{12}$ garnet-type solid electrolyte has received appreciable attention as a result of its high ionic conductivity. However, several challenges for the successful application of solid-state devices based on Li$_7$La$_3$Zr$_2$O$_{12}$ remain, such as dendrite formation and maintaining physical contact at interfaces over many Li intercalation/extraction cycles. Here, we apply first-principles density functional theory to provide insights into the Li$_7$La$_3$Zr$_2$O$_{12}$ particle morphology under various physical and chemical conditions. Our findings indicate Li segregation at the surfaces, suggesting Li-rich grain boundaries at typical synthesis and sintering conditions. On the basis of our results, we propose practical strategies to curb Li segregation at the Li$_7$La$_3$Zr$_2$O$_{12}$ interfaces. This approach can be extended to other Li-ion conductors for the design of practical energy storage devices.

cond-mat.mtrl-sci