Transient Response and Ionic Dynamics in Organic Electrochemical Transistors

The rapid development of organic electrochemical transistors(OECTs)has ushered in a new era in organic electronics,distinguishing itself through its application in a variety of domains,from high-speed logic circuits to sensitive biosensors,and neuromorphic devices like artificial synapses and organic electrochemical random-access memories.Despite recent strides in enhancing OECT performance,driven by the demand for superior transient response capabilities,a comprehensive understanding of the complex interplay between charge and ion transport,alongside electron–ion interactions,as well as the optimization strategies,remains elusive.This review aims to bridge this gap by providing a systematic overview on the fundamental working principles of OECT transient responses,emphasizing advancements in device physics and optimization approaches.We review the critical aspect of transient ion dynamics in both volatile and non-volatile applications,as well as the impact of materials,morphology,device structure strategies on optimizing transient responses.This paper not only offers a detailed overview of the current state of the art,but also identifies promising avenues for future research,aiming to drive future performance advancements in diversified applications.

Research on the Interactive Impact of Transportation Systems on Socio-Economic Development

This paper aims to explore the interactive impact between transportation systems and socio-economic development,employing Structural Equation Modeling(SEM)to analyze data from 31 provincial-level administrative regions in China from 2013 to 2022.It comprehensively considers key indicators from the economic,social,and transportation sectors.The paper constructs a model encompassing 5 latent variables and 15 observed variables.Through in-depth analysis,it reveals the promoting role of transportation systems on economic growth and social development,as well as the demand for transportation system construction and optimization driven by socio-economic development levels.The results indicate that an efficient transportation system can not only directly drive economic growth but also indirectly promote social development by improving social welfare and enhancing quality of life.This paper provides new insights into understanding the complex relationship between transportation systems and socio-economic development and holds significant implications for policymakers in optimizing transportation infrastructure to foster economic and social development.

Direct writing-in and visualizing reading-out data storage with high capacity in low-cost plastics

The explosive growth of the global data volume demands new and advanced data storage methods.Here,we report that data storage with ultrahigh capacity(~1 TB per disc)can be realized in low-cost plastics,including polycarbonate(PC),precipitated calcium carbonate(PCC),polystyrene(PS),and polymethyl methacrylate(PMMA),via direct fs laser writing.The focused fs laser can modify the fluorescence of written regions on the surface and in the interior of PMMA,enabling threedimensional(3D)information storage.Through the 3D laser processing platform,a 50-layer data record with low bit error(0.96%)is archived.Visual reading of data is empowered by the fluorescence contrast.The broad variation of fluorescence intensity assigns 8 gray levels,corresponding to 3 bits on each spot.The gray levels of each layer present high stability after longterm aging cycles,confirming the robustness of data storage.Upon single pulse control via a high-frequency electro-optic modulator(EOM),a fast writing speed(~1 kB/s)is achieved,which is limited by the repetition frequency of the fs laser.

Dynamical learning of non-Markovian quantum dynamics

We study the non-Markovian dynamics of an open quantum system with machine learning.The observable physical quantities and their evolutions are generated by using the neural network.After the pre-training is completed,we fix the weights in the subsequent processes thus do not need the further gradient feedback.We find that the dynamical properties of physical quantities obtained by the dynamical learning are better than those obtained by the learning of Hamiltonian and time evolution operator.The dynamical learning can be applied to other quantum many-body systems,non-equilibrium statistics and random processes.

Joint Effects and Spatiotemporal Characteristics of the Driving Factors of Landslides in Earthquake Areas

Understanding the joint effects of earthquakes and driving factors on the spatial distribution of landslides is helpful for targeted disaster prevention and mitigation in earthquake-prone areas.By far,little work has been done on this issue.This study analyzed the co-seismic landslide of the Ms8.0 Wenchuan earthquake in 2008 and 2014.The joint effects and spatiotemporal characteristics of the driving factors in seismic regions were revealed.Results show that(a)between 2008 and 2014,the dominant driving-factor for landslides has changed from earthquake to rock mass;(b)driving factors with weak driving force have a significant enhancement under the joint effects of other factors;(c)the joint effects of driving factors and earthquake decays with time.The study concluded that the strong vibration of the Wenchuan earthquake and the rock mass strength are the biggest contributors to the spatial distribution of landslides in 2008 and 2014,respectively.It means that the driving force of the earthquake is weaker than that of the rock mass after six years of the Wenchuan earthquake.Moreover,the landslide spatial distribution can be attributed to the joint effects of the Wenchuan earthquake and driving factors,and the earthquake has an enhanced effect on other factors.