We used fluorescence nonradiative energy transfer (NRET) to detect the interchain distances r at the overlapping regions of polymer chains. Freeze-dried polystyrene (PS) is found to have an increased r value and thus a reduced chain packing density, which shows an increased segmental mobility under uniaxial compression. We clarify that it is the interchain coupling that restricts the chain motion in a glassy oligomer in which chain entanglement is absent.
The promise of wearable and implantable devices has made stretchable organic semiconductors highly desirable. Though there are increasing attempts to design intrinsically stretchable conjugated polymers, their performance in terms of charge carrier mobility and maximum fracture strain is still lacking behind extrinsic approaches (i.e., buckling, Kirigami interconnects). Here, polymer crosslinking with flexible oligomers is applied as a strategy to reduce the tensile modulus and improve fracture strain, as well as fatigue resistance for a high mobility diketopyrrolopyrrole polymer. These polymers are crosslinked with siloxane oligomers to give stretchable films stable up to a strain ε = 150% and 500 strain‐and‐release cycles of 100% strain without the formation of nanocracks. Organic field‐effect transistors are prepared to assess the electrical properties of the crosslinked film under cyclic strain loading. An initial average mobility ( μ avg ) of 0.66 cm 2 V −1 s −1 is measured at 0% strain. A steady μ avg above 0.40 cm 2 V −1 s −1 is obtained in the direction perpendicular to the strain direction after 500 strain‐and‐release cycles of 20% strain. The μ avg in the direction parallel to strain, however, is compromised due to the formation of wrinkles.
Abstract Conjugated polymers are emerging as promising building blocks for a broad range of modern applications including skin‐like electronics, wearable optoelectronics, and sensory technologies. In the past three decades, the optical and electronic properties of conjugated polymers have been extensively studied, while their thermomechanical properties, especially the glass transition phenomenon which fundamentally represents the polymer chain dynamics, have received much less attention. Currently, there is a lack of design rules that underpin the glass transition temperature of these semirigid conjugated polymers, putting a constraint on the rational polymer design for flexible stretchable devices and stable polymer glass that is needed for the devices’ long‐term morphology stability. In this review article, the glass transition phenomenon for polymers, glass transition theories, and characterization techniques are first discussed. Then previous studies on the glass transition phenomenon of conjugated polymers are reviewed and a few empirical design rules are proposed to fine‐tune the glass transition temperature for conjugated polymers. The review paper is finished with perspectives on future directions on studying the glass transition phenomena of conjugated polymers. The goal of this perspective is to draw attention to challenges and opportunities of controlling, predicting, and designing polymeric semiconductors, specifically to accommodate their end use.
The next materials challenge in organic stretchable electronics is the development of a fully degradable semiconductor that maintains stable electrical performance under strain. Herein, we decouple the design of stretchability and transience by harmonizing polymer physics principles and molecular design in order to demonstrate for the first time a material that simultaneously possesses three disparate attributes: semiconductivity, intrinsic stretchability, and full degradability. We show that we can design acid-labile semiconducting polymers to appropriately phase segregate within a biodegradable elastomer, yielding semiconducting nanofibers that concurrently enable controlled transience and strain-independent transistor mobilities. Along with the future development of suitable conductors and device integration advances, we anticipate that these materials could be used to build fully biodegradable diagnostic or therapeutic devices that reside inside the body temporarily, or environmental monitors that are placed in the field and break down when they are no longer needed. This fully degradable semiconductor represents a promising advance toward developing multifunctional materials for skin-inspired electronic devices that can address previously inaccessible challenges and in turn create new technologies.
Modulating the segmental order in the morphology of conjugated polymers is widely recognized as a crucial factor for achieving optimal electronic properties and mechanical deformability. However, it is worth noting that the segmental order is typically associated with the crystallization process, which can result in rigid and brittle long-range ordered crystalline domains. To precisely control the morphology, a comprehensive understanding of how highly anisotropic conjugated polymers form segmentally ordered structures with ongoing crystallization is essential, yet currently elusive. To fill this knowledge gap, we developed a novel approach with a combination of stage-type fast scanning calorimetry and micro-Raman spectroscopy to capture the series of specimens with a continuum in the polymer percent crystallinity and detect the segmental order in real-time. Through the investigation of conjugated polymers with different backbones and side-chain structures, we observed a generally existing phenomenon that the degree of segmental order saturates before the maximum crystallinity is achieved. This disparity allows the conjugated polymers to achieve good charge carrier mobility while retaining good segmental dynamic mobility through the tailored treatment. Moreover, the crystallization temperature to obtain optimal segmental order can be predicted based on
In the field of natural language processing, entity extraction, relation extraction, and entity linking are important tools for processing unstructured data. However, the mainstream methods are to carry out each task alone, ignoring the connection between these tasks. In the paper, we propose the pipeline model (PALC-R, POStag-Attention-LSTM-CRF Relation Extraction) of knowledge extraction to complete the extraction of entities and relations. We also propose a joint learning model of entity extraction and entity linking named PALC-DCA (PALC-Dynamic Context Augmentation), to improve the accuracy by sharing local scores obtained in the entity linking module and learning the description information in the third-party knowledge base. The experiments show that entity extraction can achieve the accuracy of 90.84% on CONLL03 dataset, the accuracy of relation extraction is 81.77%, and the accuracy of entity linking on the AIDA CONLL dataset is 94.18%.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)