A dramatic improvement in electrical conductivity is necessary to make conductive polymer fibers viable candidates in applications such as flexible electrodes, conductive textiles, and fast-response sensors and actuators. In this study, high-performance poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) (PEDOT/PSS) conjugated polymer microfibers were fabricated via wet-spinning followed by hot-drawing. Due to the combined effects of the vertical hot-drawing process and doping/de-doping the microfibers with ethylene glycol (EG), we achieved a record electrical conductivity of 2804 S · cm −1 . This is, to the best of our knowledge, a six-fold improvement over the best previously reported value for PEDOT/PSS fibers (467 S · cm −1 ) and a two-fold improvement over the best values for conductive polymer films treated by EG de-doping (1418 S · cm −1 ). Moreover, we found that these highly conductive fibers experience a semiconductor-metal transition at 313 K. They also have superior mechanical properties with a Young's modulus up to 8.3 GPa, a tensile strength reaching 409.8 MPa and a large elongation before failure (21%). The most conductive fiber also demonstrates an extraordinary electrical performance during stretching/unstreching: the conductivity increased by 25% before the fiber rupture point with a maximum strain up to 21%. Simple fabrication of the semimetallic, strong and stretchable wet-spun PEDOT/PSS microfibers described here could make them available for conductive smart electronics.

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Using enriched data such as displacement fields obtained from digital image correlation is a pathway to the local identification of material parameters. Up to now, most of the identification techniques for nonlinear models are based on Finite Element Updating Methods. This article explains how an appropriate use of the Dissipation Gap Method can help in this context and be an interesting alternative to these classical techniques. The Dissipation Gap Methods rely on the concept of error in dissipation that has been used mainly for the verification of finite element simulations. We provide here an original application of these founding developments to the identification of material parameters for nonlinear behaviors. The proposed technique and especially the main technical keypoint of building the admissible fields are described in detail. The approach is then illustrated through the identification of heterogeneous isotropic elasto-plastic properties. The basic numerical features highlighted through these simple examples demonstrate this approach to be a promising tool for nonlinear identification.

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