Abstract2,2′,3,3′‐Oxydiphthalic dianhydride (2,2′,3,3′‐ODPA) and 2,3,3′,4′‐ODPA were synthesized from 3‐chlorophthalic anhydride with 2,3‐xylenol and 3,4‐xylenol, respectively. Their structures were determined via single‐crystal X‐ray diffraction. A series of polyimides derived from isomeric ODPAs with several diamines were prepared in dimethylacetamide (DMAc) with the conventional two‐step method. Matrix‐assisted laser desorption/ionization time‐of‐flight spectra showed that the polymerization of 2,2′,3,3′‐ODPA with 4,4′‐oxydianiline (ODA) has a greater trend to form cyclic oligomers than that of 2,3,3′,4′‐ODPA. Both 2,2′,3,3′‐ODPA and 2,3,3′,4′‐ODPA based polyimides have good solubility in polar aprotic solvents such as DMAc, dimethylformamide, and N‐methylpyrrolidone. The 5% weight‐loss temperatures of all polyimides were obtained near 500 °C in air. Their glass‐transition temperatures measured by dynamic mechanical thermal analysis or differential scanning calorimetry decreased according to the order of polyimides on the basis of 2,2′,3,3′‐ODPA, 2,3,3′,4′‐ODPA, and 3,3′,4,4′‐ODPA. The wide‐angle X‐ray diffraction of all polyimide films from isomeric ODPAs and ODA showed some certain extent of crystallization after stretching. Rheological properties revealed that polyimide (2,3,3′,4′‐ODPA/ODA) has a comparatively lower melt viscosity than its isomers, which indicated its better melt processability. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 3249–3260, 2003

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Neuromorphic computing memristors are attractive to construct low-power- consumption electronic textiles due to the intrinsic interwoven architecture and promising applications in wearable electronics. Developing reconfigurable fiber-based memristors is an efficient method to realize electronic textiles that capable of neuromorphic computing function. However, the previously reported artificial synapse and neuron need different materials and configurations, making it difficult to realize multiple functions in a single device. Herein, a textile memristor network of Ag/MoS2/HfAlOx/carbon nanotube with reconfigurable characteristics was reported, which can achieve both nonvolatile synaptic plasticity and volatile neuron functions. In addition, a single reconfigurable memristor can realize integrate-and-fire function, exhibiting significant advantages in reducing the complexity of neuron circuits. The firing energy consumption of fiber-based memristive neuron is 1.9 fJ/spike (femtojoule-level), which is at least three orders of magnitude lower than that of the reported biological and artificial neuron (picojoule-level). The ultralow energy consumption makes it possible to create an electronic neural network that reduces the energy consumption compared to human brain. By integrating the reconfigurable synapse, neuron and heating resistor, a smart textile system is successfully constructed for warm fabric application, providing a unique functional reconfiguration pathway toward the next-generation in-memory computing textile system.