Conjugated polymer chains have many degrees of conformational freedom and interact weakly with each other, resulting in complex microstructures in the solid state. Understanding charge transport in such systems, which have amorphous and ordered phases exhibiting varying degrees of order, has proved difficult owing to the contribution of electronic processes at various length scales. The growing technological appeal of these semiconductors makes such fundamental knowledge extremely important for materials and process design. We propose a unified model of how charge carriers travel in conjugated polymer films. We show that in high-molecular-weight semiconducting polymers the limiting charge transport step is trapping caused by lattice disorder, and that short-range intermolecular aggregation is sufficient for efficient long-range charge transport. This generalization explains the seemingly contradicting high performance of recently reported, poorly ordered polymers and suggests molecular design strategies to further improve the performance of future generations of organic electronic materials.

Organic electrochemical transistors (OECTs) leverage ion injection from an electrolyte into an organic semiconductor film to yield compelling advances in biological interfacing, printed logic circuitry and neuromorphic devices. Their defining characteristic is the coupling between electronic and ionic charges within the volume of an organic film. In this review we discuss the mechanism of operation and the 2 materials that are being used, overview the various form factors, fabrication technologies and proposed applications, and take a critical look at the future of OECT research and development.

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The brain is capable of massively parallel information processing while consuming only ∼1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10 pJ for 10 μm devices), displays >500 distinct, non-volatile conductance states within a ∼1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.