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Simultaneous transport and coupling of ionic and electronic charges is fundamental to electrochemical devices used in energy storage and conversion, neuromorphic computing and bioelectronics. While the mixed conductors enabling these technologies are widely used, the dynamic relationship between ionic and electronic transport is generally poorly understood, hindering the rational design of new materials. In semiconducting electrodes, electrochemical doping is assumed to be limited by motion of ions due to their large mass compared to electrons and/or holes. Here, we show that this basic assumption does not hold for conjugated polymer electrodes. Using operando optical microscopy, we reveal that electrochemical doping speeds in a state-of-the-art polythiophene can be limited by poor hole transport at low doping levels, leading to substantially slower switching speeds than expected. We show that the timescale of hole-limited doping can be controlled by the degree of microstructural heterogeneity, enabling the design of conjugated polymers with improved electrochemical performance.

Electronic transport models for conducting polymers (CPs) and blends focus on the arrangement of conjugated chains, while the contributions of the nominally insulating components to transport are largely ignored. In this work, an archetypal CP blend is used to demonstrate that the chemical structure of the non-conductive component has a substantial effect on charge carrier mobility. Upon diluting a CP with excess insulator, blends with as high as 97.4 wt % insulator can display carrier mobilities comparable to some pure CPs such as polyaniline and low regioregularity P3HT. In this work, we develop a single, multiscale transport model based on the microstructure of the CP blends, which describes the transport properties for all dilutions tested. The results show that the high carrier mobility of primarily insulator blends results from the inclusion of aromatic rings, which facilitate long-range tunneling (up to ca. 3 nm) between isolated CP chains. This tunneling mechanism calls into question the current paradigm used to design CPs, where the solubilizing or ionically conducting component is considered electronically inert. Indeed, optimizing the participation of the nominally insulating component in electronic transport may lead to enhanced electronic mobility and overall better performance in CPs.

Efficient transport of both ionic and electronic charges in conjugated polymers (CPs) has enabled a wide range of novel electrochemical devices spanning applications from energy storage to bioelectronic devices. In this Perspective, we provide an overview of the fundamental physical processes which underlie the operation of mixed conducting polymer (MCP) devices. While charge injection and transport have been studied extensively in both ionic and electronic conductors, translating these principles to mixed conducting systems proves challenging due to the complex relationships among the individual materials properties. We break down the process of electrochemical (de)doping, the basic feature exploited in mixed conducting devices, into its key steps, highlighting recent advances in the study of these physical processes in the context of MCPs. Furthermore, we identify remaining challenges in further extending fundamental understanding of MCP-based device operation. Ultimately, a deeper understanding of the elementary processes governing operation in MCPs will drive the advancement in both materials design and device performance. Funding Agencies|European Union [101022365]; Knut and Alice Wallenberg Foundation; Wallenberg Wood Science Center; Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Linkoping University [2009-00971]; Swedish Foundation for Strategic Research; H2020-EU-FET Open MITICS [964677]

Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this Roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The Roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this Roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community., Neuromorphic Computing and Engineering, 2, ISSN:2634-4386