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Mixed conductors-materials that can efficiently conduct both ionic and electronic species-are an important class of functional solids. Here we demonstrate an organic nanocomposite that spontaneously forms when mixing an organic semiconductor with an ionic liquid and exhibits efficient room-temperature mixed conduction. We use a polymer known to form a semicrystalline microstructure to template ion intercalation into the side-chain domains of the crystallites, which leaves electronic transport pathways intact. Thus, the resulting material is ordered, exhibiting alternating layers of rigid semiconducting sheets and soft ion-conducting layers. This unique dual-network microstructure leads to a dynamic ionic/electronic nanocomposite with liquid-like ionic transport and highly mobile electronic charges. Using a combination of operando X-ray scattering and in situ spectroscopy, we confirm the ordered structure of the nanocomposite and uncover the mechanisms that give rise to efficient electron transport. These results provide fundamental insights into charge transport in organic semiconductors, as well as suggesting a pathway towards future improvements in these nanocomposites.

The properties of organic solids depend on their structure and morphology, yet direct imaging using conventional electron microscopy methods is hampered by the complex internal structure of these materials and their sensitivity to electron beams. Here, we manage to observe the nanocrystalline structure of two organic molecular thin-film systems using transmission electron microscopy by employing a scanning nanodiffraction method that allows for full access to reciprocal space over the size of a spatially localized probe (~2 nm). The morphologies revealed by this technique vary from grains with pronounced segmentation of the structure-characterized by sharp grain boundaries and overlapping domains-to liquid-crystal structures with crystalline orientations varying smoothly over all possible rotations that contain disclinations representing singularities in the director field. The results show how structure-property relationships can be visualized in organic systems using techniques previously only available for hard materials such as metals and ceramics.

A neuromorphic device based on the stable electrochemical fine-tuning of the conductivity of an organic ionic/electronic conductor is realized. These devices show high linearity, low noise and extremely low switching voltage. The brain is capable of massively parallel information processing while consuming only ∼1–100 fJ per synaptic event1,2. Inspired by the efficiency of the brain, CMOS-based neural architectures3 and memristors4,5 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 ( 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 systems6,7. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

The properties of organic solids depend on their structure and morphology, yet direct imaging using conventional electron microscopy methods is hampered by the complex internal structure of these materials and their sensitivity to electron beams. Here, we manage to observe the nanocrystalline structure of two organic molecular thin-film systems using transmission electron microscopy by employing a scanning nanodiffraction method that allows for full access to reciprocal space over the size of a spatially localized probe (~2 nm). The morphologies revealed by this technique vary from grains with pronounced segmentation of the structure-characterized by sharp grain boundaries and overlapping domains-to liquid-crystal structures with crystalline orientations varying smoothly over all possible rotations that contain disclinations representing singularities in the director field. The results show how structure-property relationships can be visualized in organic systems using techniques previously only available for hard materials such as metals and ceramics.

Interfaces between organic electron-donating (D) and electron-accepting (A) materials have the ability to generate charge carriers on illumination. Efficient organic solar cells require a high yield for this process, combined with a minimum of energy losses. Here, we investigate the role of the lowest energy emissive interfacial charge-transfer state (CT1) in the charge generation process. We measure the quantum yield and the electric field dependence of charge generation on excitation of the charge-transfer (CT) state manifold via weakly allowed, low-energy optical transitions. For a wide range of photovoltaic devices based on polymer:fullerene, small-molecule:C60 and polymer:polymer blends, our study reveals that the internal quantum efficiency (IQE) is essentially independent of whether or not D, A or CT states with an energy higher than that of CT1 are excited. The best materials systems show an IQE higher than 90% without the need for excess electronic or vibrational energy. © 2014 Macmillan Publishers Limited.

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. The recent demonstration that highly disordered polymer films can transport charges as effectively as polycrystalline semiconductors has called into question the relationship between structural order and mobility in organic materials. It is now shown that, in high-molecular-weight polymers, efficient charge transport is allowed due to a network of interconnected aggregates that are characterized by short-range order.

Solution-processable organic semiconductors are central to developing viable printed electronics, and performance comparable to that of amorphous silicon has been reported for films grown from soluble semiconductors. However, the seemingly desirable formation of large crystalline domains introduces grain boundaries, resulting in substantial device-to-device performance variations. Indeed, for films where the grain-boundary structure is random, a few unfavourable grain boundaries may dominate device performance. Here we isolate the effects of molecular-level structure at grain boundaries by engineering the microstructure of the high-performance n-type perylenediimide semiconductor PDI8-CN2 and analyse their consequences for charge transport. A combination of advanced X-ray scattering, first-principles computation and transistor characterization applied to PDI8-CN2 films reveals that grain-boundary orientation modulates carrier mobility by approximately two orders of magnitude. For PDI8-CN2 we show that the molecular packing motif (that is, herringbone versus slip-stacked) plays a decisive part in grain-boundary-induced transport anisotropy. The results of this study provide important guidelines for designing device-optimized molecular semiconductors.

The coupling of the electronic structure of organic semiconductors with the electromagnetic field in the vacuum by means of plasmonic antennas allows for a mobility boost.

Because of its simple composition, vast availability in pure form and ease of processing, vitreous silica is often used as a model to study the physics of amorphous solids. Research in amorphous silica is also motivated by its ubiquity in modern technology, a prominent example being as bulk material in transmissive and diffractive optics for high-power laser applications such as inertial confinement fusion (ICF)1,2. In these applications, stability under high-fluence laser irradiation is a key requirement3, with optical breakdown occurring when the fluence of the beam is higher than the laser-induced damage threshold (LIDT) of the material3. The optical strength of polished fused silica transmissive optics is limited by their surface LIDT3. Surface optical breakdown is accompanied by densification4, formation of point defects5, cratering, material ejection, melting and cracking3. Through a combination of electron diffraction and infrared reflectance measurements we show here that synthetic vitreous silica transforms partially into a defective form of the high-pressure stishovite phase under high-intensity (GW cm−2) laser irradiation. This phase transformation offers one suitable mechanism by which laser-induced damage grows catastrophically once initiated, thereby dramatically shortening the service lifetime of optics used for high-power photonics.

Brain-inspired computing paradigms have led to substantial advances in the automation of visual and linguistic tasks by emulating the distributed information processing of biological systems1. The similarity between artificial neural networks (ANNs) and biological systems has inspired ANN implementation in biomedical interfaces including prosthetics2 and brain-machine interfaces3. While promising, these implementations rely on software to run ANN algorithms. Ultimately, it is desirable to build hardware ANNs4,5 that can both directly interface with living tissue and adapt based on biofeedback6,7. The first essential step towards biologically integrated neuromorphic systems is to achieve synaptic conditioning based on biochemical signalling activity. Here, we directly couple an organic neuromorphic device with dopaminergic cells to constitute a biohybrid synapse with neurotransmitter-mediated synaptic plasticity. By mimicking the dopamine recycling machinery of the synaptic cleft, we demonstrate both long-term conditioning and recovery of the synaptic weight, paving the way towards combining artificial neuromorphic systems with biological neural networks.