Rational Design of Flexible and Stretchable Electronics based on 3D Printing

Flexible and stretchable electronics have been considered as the key component for the next generation of flexible devices. There are many approaches to prepare the devices, such as dip coating, spin coating, Mayer bar coating, filtration and transfer, and printing, etc. The effectiveness of these methods has been proven, but some drawbacks cannot be ignored, such as lacking pattern control, labor consuming, requiring complex pretreatment, wasting conductive materials, etc. In this investigation, we propose to adopt 3D printing technology to design flexible and stretchable electronics. The objective is to rationally design flexible and stretchable sensors, simplify the preparation process, form the sample with the complex desirable patterns, and promote the performance of the samples. The dissertation comprises of three major parts: water-induced polymer swelling and its application in soft electronics, utilizing 3D printing to transfer conductive layer into elastomer for building soft electronics, and 3D printing of functional devices. In the first part, we developed the soft electronics with wrinkled structure via 3D printing and water-induced polymer swelling, which can avoid some disadvantages in conventional method, e.g., pre-stretching and organic solvent-induced polymer swelling, including mechanical loss, negative effect to human health, and unidirectionally response to external deformation. Water-induced polymer swelling was achieved by introducing soluble particles into silicone matrixes and soaking the polymer composites in aqueous solution. We have investigated the characteristics and mechanisms of water-induced polymer swelling. Then, the conductive materials were deposited on the swollen sample to form the desired wrinkled structures for stretchable sensors. Furthermore, a dopamine layer was adopted to enhance the adhesion of matrix and conductive layer. The improvement was a key enabler to achieve superior electrical properties of 3D printed stretchable sensors for long-term cyclic stretching. We have demonstrated a series of human motion detection by using these stretchable strain sensors. Another part is designing flexible electrodes with desirable complex pattern by transferring a conductive layer into soft substrates during a 3D printing process. Taking advantage of extrusion pressure and polymer adhesion, the thin conductive layers were embedded into the printed polymer patterns, which can achieve conductive flexible electronics with desirable complex patterns. High-quality transfer has been achieved through adjusting conductive layer thickness, nozzle-to-substrate distance, and printing parameters, etc. Moreover, various printing patterns were created, and their properties were exhibited. The stretchable sensors showed an outstanding stress-strain relationship and electrical response to external deformations. The third part is about 3D printing of functional devices. In the collaborated study, the drug particles were introduced into silicone matrix to prepare the drug-eluting devices. When water molecules transported into the silicone matrix, the loaded drug particles decomposed and released nitric oxide (NO) enabling antibacterial properties. It is noted that 3D printing is creatively employed to form the desirable patterns. We also observed a self-wiring effect in the printing process, i.e., the printed device is covered by a drug-free layer due to the diffusion of a low viscosity silicone component during printing, which can be utilized to prevent drug release bursts and to form a gradient drug-loaded device. The printed samples showed a sustainable NO release and good antibacterial property. Furthermore, the water-induced polymer swelling was possible to be used as actuator in humidity environment. There are some highlights deserving emphasis in the dissertation. Firstly, the water-induced polymer swelling is proposed to develop the flexible and stretchable electronics. The findings have a wide potential application. Additionally, a drug-eluting polymer device with a drug-loaded bulk and a drug-free coating is prepared via leveraging self-wiring effect in 3D printing. The structure can regulate the drug release rate. On the other hand, the additive manufacturing platform offers unique opportunities to produce drug-eluting silicone devices in a customized manner. Finally, 3D printing is employed to encapsulate the conductive layers to achieve the flexible electronics with patterned structure and high performances. The facile and effective approach provides a distinctive view in advancing the development of stretchable electronics

Norm and time optimal control problems of stochastic heat equations

This paper investigates the norm and time optimal control problems for stochastic heat equations. We begin by presenting a characterization of the norm optimal control, followed by a discussion of its properties. We then explore the equivalence between the norm optimal control and time optimal control, and subsequently establish the bang-bang property of the time optimal control. These problems, to the best of our knowledge, are among the first to discuss in the stochastic case

Optimal Actuator Location of the Norm Optimal Controls for Degenerate Parabolic Equations

This paper focuses on investigating the optimal actuator location for achieving minimum norm controls in the context of approximate controllability for degenerate parabolic equations. We propose a formulation of the optimization problem that encompasses both the actuator location and its associated minimum norm control. Specifically, we transform the problem into a two-person zero-sum game problem, resulting in the development of four equivalent formulations. Finally, we establish the crucial result that the solution to the relaxed optimization problem serves as an optimal actuator location for the classical problem

Null controllability of two kinds of coupled parabolic systems with switching control

The focus of this paper is on the null controllability of two kinds of coupled systems including both degenerate and non-degenerate equations with switching control. We first establish the observability inequality for measurable subsets in time for such coupled system, and then by the HUM method to obtain the null controllability. Next, we investigate the null controllability of such coupled system for segmented time intervals. Notably, these results are obtained through spectral inequalities rather than using the method of Carleman estimates. Such coupled systems with switching control, to the best of our knowledge, are among the first to discuss

Observability inequalities for the backward stochastic evolution equations and their applications

The present article delves into the investigation of observability inequalities pertaining to backward stochastic evolution equations. We employ a combination of spectral inequalities, interpolation inequalities, and the telegraph series method as our primary tools to directly establish observability inequalities. Furthermore, we explore three specific equations as application examples: a stochastic degenerate equation, a stochastic fourth order parabolic equation and a stochastic heat equation. It is noteworthy that these equations can be rendered null controllability with only one control in the drift term to each system

Some controllability results of a class of N-dimensional parabolic equations with internal single-point degeneracy

This paper investigates the controllability of a class of $N$-dimensional degenerate parabolic equations with interior single-point degeneracy. We employ the Galerkin method to prove the existence of solutions for the equations. The analysis is then divided into two cases based on whether the degenerate point $x=0$ lies within the control region $\omega_0$ or not. For each case, we establish specific Carleman estimates. As a result, we achieve null controllability in the first case $0\in\omega_0$ and unique continuation and approximate controllability in the second case $0\notin\omega_0$

When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods

With increasing privacy concerns on data, recent studies have made significant progress using federated learning (FL) on privacy-sensitive natural language processing (NLP) tasks. Much literature suggests fully fine-tuning pre-trained language models (PLMs) in the FL paradigm can mitigate the data heterogeneity problem and close the performance gap with centralized training. However, large PLMs bring the curse of prohibitive communication overhead and local model adaptation costs for the FL system. To this end, we introduce various parameter-efficient tuning (PETuning) methods into federated learning. Specifically, we provide a holistic empirical study of representative PLMs tuning methods in FL. The experimental results cover the analysis of data heterogeneity levels, data scales, and different FL scenarios. Overall communication overhead can be significantly reduced by locally tuning and globally aggregating lightweight model parameters while maintaining acceptable performance in various FL settings. To facilitate the research of PETuning in FL, we also develop a federated tuning framework FedPETuning, which allows practitioners to exploit different PETuning methods under the FL training paradigm conveniently. The source code is available at \url{https://github.com/iezhuozhuo/FedETuning/tree/deltaTuning}