Enhanced Conductivity via Homopolymer-Rich Pathways in Block Polymer-Blended Electrolytes

Phase Morphology Dependence of Ionic Conductivity and Oxidative Stability in Fluorinated Ether Solid-State Electrolytes

Solid-state polymer electrolytes can enable the safe operation of high energy density lithium metal batteries; unfortunately, they have low ionic conductivity and poor redox stability at electrode interfaces. Fluorinated ether polymer electrolytes are a promising approach because the ether units can solvate and conduct ions, while the fluorinated moieties can increase oxidative stability. However, current perfluoropolyether (PFPE) electrolytes exhibit deficient lithium-ion coordination and ion transport. Here, we incorporate cross-linked poly(ethylene glycol) (PEG) units within the PFPE matrix and increase the polymer blend electrolyte conductivity by 6 orders of magnitude as compared to pure PFPE at 60 °C from 1.55 × 10-11 to 2.26 × 10-5 S/cm. Blending varying ratios of PEG and PFPE induces microscale phase separation, and we show the impact of morphology on ion solvation and dynamics in the electrolyte. Spectroscopy and simulations show weak ion-PFPE interactions, which promote salt phase segregation into-and ion transport within-the PEG domain. These polymer electrolytes show promise for use in high-voltage lithium metal batteries with improved Li|Li cycling due to enhanced mechanical properties and high-voltage stability beyond 6 V versus Li/Li+. Our work provides insights into transport and stability in fluorinated polymer electrolytes for next-generation batteries.

Data-Driven Methods for Accelerating Polymer Design

Optimal design of polymers is a challenging task due to their enormous chemical and configurational space. Recent advances in computations, machine learning, and increasing trends in data and software availability can potentially address this problem and accelerate the molecular-scale design of polymers. Here, the central problem of polymer design is reviewed, and the general ideas of data-driven methods and their working principles in the context of polymer design are discussed. This Review provides a historical perspective and a summary of current trends and outlines future scopes of data-driven methods for polymer research. A few representative case studies on the use of such data-driven methods for discovering new polymers with exceptional properties are presented. Moreover, attempts are made to highlight how data-driven strategies aid in establishing new correlations and advancing the fundamental understanding of polymers. This Review posits that the combination of machine learning, rapid computational characterization of polymers, and availability of large open-sourced homogeneous data will transform polymer research and development over the coming decades. It is hoped that this Review will serve as a useful reference to researchers who wish to develop and deploy data-driven methods for polymer research and education.

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

ConspectusIon-containing solid block polymer (BP) electrolytes can self-assemble into microphase-separated domains to facilitate the independent optimization of ion conduction and mechanical stability; this assembly behavior has the potential to improve the functionality and safety of lithium-ion batteries over liquid electrolytes to meet future demands (e.g., large capacities and long lifetimes) in various applications. However, significant enhancements in the ionic conductivity and processability of BPs must be realized for BP-based electrolytes to become robust alternatives in commercial devices. Toward this end, the controlled modification of BP electrolytes' intra-domain (nanometer-scale) and multi-grain (micrometer-scale) structure is one viable approach; intra-domain ion transport and segmental compatibility (related to the effective Flory-Huggins parameter, χ_eff) can be increased by tuning the ion and monomer-segment distributions, and the morphology can be selected such that the multi-grain transport is less sensitive to grain size and orientation.To highlight the characteristics of intra-domain structure that promote efficient ion transport, this Account begins by describing the relationship between BP thermodynamics (namely, χ_eff and the statistical segment length, b, which is indicative of chain stiffness) and local ion concentration. These thermodynamic insights are vital because they inform the selection of synthesis and formulation variables, such as polymer and ion chemistry, polymer molecular weight and composition, and ion concentration, which boost electrolyte performance. In addition to its relationship with local ion transport, χ_eff is also an important factor with respect to electrolyte processability. For example, a reduced χ_eff can allow BP electrolytes to be processed at lower temperatures (i.e., lower energy input), with less solvent (i.e., reduced waste), and/or for shorter times (i.e., higher throughput) yet still form desired nanostructures. This Account also examines the impact of electrolyte preparation and processing on the ion transport across nanostructured grains because of grain size and orientation. As morphologies with a 3D-connected versus 2D-connected conducting phase show different sensitivities to conductivity losses that can occur because of the fabrication methods, it is necessary to account for electrolyte processing effects when probing ion transport.The intra-domain and micrometer-scale structure also can be tuned using either tapered BPs (macromolecules with modified monomer-segment composition profiles between two homogeneous blocks) or blends of BPs and homopolymers, independent of the BP molecular weight and composition, as detailed herein. The application of TBPs or BP/HP blends as ion-conducting materials leads to improved ion transport, reduced χ_eff, and greater availability of morphologies with 3D connectivity relative to traditional (non-tapered and unblended) BP electrolytes. This feature results from the fact that ion transport is related more closely to the monomer-segment distributions within a domain than the overall nanoscale morphology or average polymer/ion mobilities. Taken together, this Account describes how ion transport and processability are influenced by BP architecture and nanostructural features, and it provides avenues to tune nanoassemblies that can contribute to improved lithium-ion battery technologies to meet future demands.

Block copolymers as (single-ion conducting) lithium battery electrolytes

Solid-state batteries are considered the next big step towards the realization of intrinsically safer high-energy lithium batteries for the steadily increasing implementation of this technology in electronic devices and particularly, electric vehicles. However, so far only electrolytes based on poly(ethylene oxide) have been successfully commercialized despite their limited stability towards oxidation and low ionic conductivity at room temperature. Block copolymer (BCP) electrolytes are believed to provide significant advantages thanks to their tailorable properties. Thus, research activities in this field have been continuously expanding in recent years with great progress to enhance their performance and deepen the understanding towards the interplay between their chemistry, structure, electrochemical properties, and charge transport mechanism. Herein, we review this progress with a specific focus on the block-copolymer nanostructure and ionic conductivity, the latest works, as well as the early studies that are fr"equently overlooked by researchers newly entering this field. Moreover, we discuss the impact of adding a lithium salt in comparison to single-ion conducting BCP electrolytes along with the encouraging features of these materials and the remaining challenges that are yet to be solved.

Sequence-Engineering Polyethylene-Polypropylene Copolymers with High Thermal Conductivity Using a Molecular-Dynamics-Based Genetic Algorithm

Polymer sequence engineering is emerging as a potential tool to modulate material properties. Here, we employ a combination of a genetic algorithm (GA) and atomistic molecular dynamics (MD) simulation to design polyethylene-polypropylene (PE-PP) copolymers with the aim of identifying a specific sequence with high thermal conductivity. PE-PP copolymers with various sequences at the same monomer ratio are found to have a broad distribution of thermal conductivities. This indicates that the monomer sequence has a crucial effect on thermal energy transport of the copolymers. A non-periodic and non-intuitive optimal sequence is indeed identified by the GA, which gives the highest thermal conductivity compared with any regular block copolymers, for example, diblock, triblock, and hexablock. In comparison to the bulk density, chain conformations, and vibrational density of states, the monomer sequence has the strongest impact on the efficiency of thermal energy transport via inter- and intra-molecular interactions. Our work highlights polymer sequence engineering as a promising approach for tuning the thermal conductivity of copolymers, and it provides an example application of integrating atomistic MD modeling with the GA for computational material design.

Intrinsic Ion Transport Properties of Block Copolymer Electrolytes

Knowledge of intrinsic properties is of central importance for materials design and assessing suitability for specific applications. Self-assembling block copolymer electrolytes (BCEs) are of great interest for applications in solid-state energy storage devices. A fundamental understanding of ion transport properties, however, is hindered by the difficulty in deconvoluting extrinsic factors, such as defects, from intrinsic factors, such as the presence of interfaces between the domains. Here, we quantify the intrinsic ion transport properties of a model BCE system consisting of poly(styrene-block-ethylene oxide) (SEO) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt using a generalizable strategy of depositing thin films on interdigitated electrodes and self-assembling fully connected parallel lamellar structures throughout the films. Comparison between conductivity in homopolymer poly(ethylene oxide) (PEO)-LiTFSI electrolytes and the analogous conducting material in SEO over a range of salt concentrations (r, molar ratio of lithium ion to ethylene oxide repeat units) and temperatures reveals that between 20% and 50% of the PEO in SEO is inactive. Using mean-field theory calculations of the domain structure and monomer concentration profiles at domain interfaces-both of which vary substantially with salt concentration-the fraction of inactive PEO in the SEO, as derived from conductivity measurements, can be quantitatively reconciled with the fraction of PEO that is mixed with greater than a few volume percent of polystyrene. Despite the detrimental interfacial effects for ion transport in BCEs, the intrinsic conductivity of the SEO studied here (ca. 10^-3 S/cm at 90 °C, r = 0.085) is an order of magnitude higher than reported values from bulk samples of similar molecular weight SEO (ca. 10^-4 S/cm at 90 °C, r = 0.085). Overall, this work provides motivation and methods for pursuing improved BCE chemical design, interfacial engineering, and processing.

Facile fabrication of a hybrid polymer electrolyte via initiator-free thiol–ene photopolymerization for high-performance all-solid-state lithium metal batteries

The article reports the facile fabrication of a solid polymer electrolyte via initiator-free thiol–ene photopolymerization for all-solid-state lithium metal batteries.

Covalently cross-linked polymer stabilized electrolytes with self-healing performance via boronic ester bonds

This article reported a facile fabrication of self-healing solid polymer electrolytes via boronic ester bonds.