Database Creation, Visualization, and Statistical Learning for Polymer Li⁺-Electrolyte Design

Abstract

Visualization and statistical regression of compiled datasets is emerging as a powerful tool in understanding and screening the design space of materials properties, rapidly providing insights that would not be readily gained from studies of individual systems. We describe here, the curation and analysis of a database of polymer Li + electrolyte conductivity performance, manually extracted from the published literature.We focus on solid, dry polymer electrolytes without additives. Data was extracted from 65 publications, resulting in 655 unique polymer-anion-salt concentration entries and 5225 individual conductivity data points to create an interactive database:PEDatamine.org. Visualization of the collective dataset suggested that individual features, other than the activation energy, are poor predictors of conductivity performance across the wide range of polymer chemistries, Li salts, and salt concentrations examined. The Meyer-Neldel rule suggesting a correlation between the conductivity prefactor and activation energy is shown to hold universally for both Arrhenius and Vogel-Fulcher-Tammann representations. Statistical regression techniques were employed to extract the most important features relevant in determining Li + -ion conductivity.These include polymer molecular weight, glass transition temperature, existence of electronegative heteroatoms in the monomer, and anion size. However, experimental features can be omitted from the regression model without impacting predictive performance, reinforcing the importance of monomer electronegativity, hydrogen bonding, and anion molecular bulk.

Decoupling Ion Transport and Matrix Dynamics to Make High Performance Solid Polymer Electrolytes

“…Even this rather crude analysis of rescaling ionic conductivity by T-T g provides a basic means to parametrize the effect of ion dynamics and can be interpreted crudely within a Walden framework as we describe below. 2,49 Due to the coupling of ion mobility and τ α , theories of glassy dynamics in polymers can be used to model conductivity trends in SPEs. Although the glass transition is not precisely understood in polymers, the semiphenomenological Williams-Landau-Ferry (or equivalent Vogel−Tamman−Fulcher) equation (eq 5) can be modified to model ion dynamics.…”

Dry Polymer Electrolyte Concepts for Solid‐State Batteries

“…Even though often used as a materials’ design principle, direct correlation between low T g and low E a with high σ RT has not been found by recent data mining approach in a wide variety of polymer electrolyte systems. [ 44 ]…”

“…Even though often used as a materials' design principle, direct correlation between low T g and low E a with high 𝜎 RT has not been found by recent data mining approach in a wide variety of polymer electrolyte systems. [44] The measured ionic conductivity is related to the total motion of different molecular species including cations, anions, and their solvent-containing or solvent-free aggregates (both charged and noncharged, depending on the character of the electrodes used). Under current, various mobile species form concentration gradients, adding to the additional detrimental potential drops in a cell, or may even induce electrodeposition.…”

Nanostructured Block Polymer Electrolytes: Tailoring Self-Assembly to Unlock the Potential in Lithium-Ion Batteries

“…Solid polymer electrolytes are solvent-free, mechanically and chemically resilient, and inherently flexible materials that can address the aforementioned concerns of LIBs. , Salt-doped (in which neither the Li + nor anion is chemically tethered to the polymer) polyethers are a commonly studied class of electrolytes and are discussed herein. However, various salt-doped and single-ion (in which the anion is immobilized such that the Li + transference number can be increased relative to salt-doped electrolytes) polymer systems are viable ion conductors; these systems have been described elsewhere in the literature. , Although the optimization of both ion transport and mechanical performance is challenging in homopolymers (HPs), nanostructured block polymers (BPs), such as polystyrene- block -poly­(ethylene oxide) (PS- b -PEO), can decouple these competing constraints. ,, However, BP electrolytes can suffer from poor ion transport within a domain as a result of reduced segmental motion (as proxied by the conducting-phase glass transition temperature [ T g ]) and decreased ion solvation near the conducting/non-conducting domain interface. − Electrolyte processing effects also can orient ion-conducting pathways in an unfavorable direction, such that the ions must be transported over a longer path between electrodes (i.e., tortuosity is increased). ,, Additionally, most ion-containing BP electrolytes often require high temperatures, large amounts of solvent, and/or long processing times to form nanostructured membranes, which can make the fabrication efforts inefficient. These processing challenges are typically related to the high effective segregation strength ( χ eff N , in which χ eff is the effective Flory–Huggins interaction parameter and N is the degree of polymerization) of BP electrolytes.…”

“…However, various salt-doped and single-ion (in which the anion is immobilized such that the Li + transference number can be increased relative to salt-doped electrolytes) polymer systems are viable ion conductors; these systems have been described elsewhere in the literature. 15,16 Although the optimization of both ion transport and mechanical performance is challenging in homopolymers (HPs), nanostructured block polymers (BPs), such as polystyrene-blockpoly(ethylene oxide) (PS-b-PEO), can decouple these competing constraints. 14,16,17 However, BP electrolytes can suffer from poor ion transport within a domain as a result of reduced segmental motion (as proxied by the conducting-phase glass transition temperature [T g ]) and decreased ion solvation near the conducting/non-conducting domain interface.…”