High-Transconductance,Highly Elastic,Durable and Recyclable All-Polymer Electrochemical Transistors with 3D Micro-Engineered Interfaces

Organic electrochemical transistors(OECTs)have emerged as versatile platforms for broad applications spanning from flexible and wearable integrated circuits to biomedical monitoring to neuromorphic computing.A variety of materials and tailored micro/nanostructures have recently been developed to realized stretchable OECTs,however,a solid-state OECT with high elasticity has not been demonstrated to date.Herein,we present a general platform developed for the facile generation of highly elastic all-polymer OECTs with high transconductance(up to 12.7 mS),long-term mechanical and environmental durability,and sustainability.Rapid prototyping of these devices was achieved simply by transfer printing lithium bis(trifluoromethane)sulfonimide doped poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS/LiTFSI)microstructures onto a resilient gelatin-based gel electrolyte,in which both depletion-mode and enhancement-mode OECTs were produced using various active channels.Remarkably,the elaborate 3D architectures of the PEDOT:PSS were engineered,and an imprinted 3D-microstructured channel/electrolyte interface combined with wrinkled electrodes provided performance that was retained(>70%)through biaxial stretching of 100%strain and after 1000 repeated cycles of 80%strain.Furthermore,the anti-drying and degradable gelatin and the self-crosslinked PEDOT:PSS/LiTFSI jointly enabled stability during>4 months of storage and on-demand disposal and recycling.This work thus represents a straightforward approach towards high-performance stretchable organic electronics for wearable/implantable/neuromorphic/sustainable applications.

Stress dependence of elastic wave dispersion and attenuation in fluid-saturated porous layered media

The fluid-saturated porous layered(FSPL)media widely exist in the Earth's subsurface and their overall mechanical properties,microscopic pore structure and wave propagation characteristics are highly relevant to the in-situ stress.However,the effect of in-situ stress on wave propagation in FSPL media cannot be well explained with the existing theories.To fill this gap,we propose the dynamic equations for FSPL media under the effect of in-situ stress based on the theories of poroacoustoelasticity and anisotropic elasticity.Biot loss mechanism is considered to account for the stress-dependent wave dispersion and attenuation induced by global wave-induced fluid flow.Thomsen's elastic anisotropy parameters are used to represent the anisotropy of the skeleton.A plane-wave analysis is implemented on dynamic equations yields the analytic solutions for fast and slow P waves and two S waves.Modelling results show that the elastic anisotropy parameters significantly determine the stress dependence of wave velocities.Vertical tortuosity and permeability have remarkable effects on fast and slow P-wave velocity curves and the corresponding attenuation peaks but have little effect on S-wave velocity.The difference in velocities of two S waves occurs when the FSPL medium is subjected to horizontal uniaxial stress,and the S wave along the stress direction has a larger velocity,which implies that the additional anisotropy other than that induced by the beddings appears due to horizontal stress.Besides,the predicted velocity results have the reasonable agreement with laboratory measurements.Our equations and results are relevant to a better understanding of wave propagation in deep strata,which provide some new theoretical insights in the rock physics,hydrocarbon exploration and stress detection in deep-strata shale reservoirs.

Predicting roof-surface wind pressure induced by conical vortex using a BP neural network combined with POD

This study aims to examine the feasibility of predicting surface wind pressure induced by conical vortex using a backpropagation neural network(BPNN)combined with proper orthogonal decomposition(POD),in which a 1:150 scaled model with a large-span retractable roof was tested in wind tunnel under both laminar and turbulent flow conditions.The distributions of mean and fluctuating wind pressure coefficients were first described,and the effects of inflow turbulence,wind direction,roof opening were examined separately.For the prediction of wind pressure,the POD-BPNN model was trained using measurement data from adjacent points.The prediction results are overall satisfactory.The root-mean-square-error(RMSE)between test and predicted data lies mostly within 10%.In particular,the prediction of mean wind pressure is found to be better than that of fluctuating wind pressure.The outcomes in this study highlight that the proposed POD-BPNN model can be well used as a useful tool to predict surface wind pressure.