Inorganic and Organic Solution-Processed Thin Film Devices

Thin films and thin film devices have a ubiquitous presence in numerous conventional and emerging technologies. This is because of the recent advances in nanotechnology, the development of functional and smart materials,conducting polymers, molecular semiconductors, carbon nanotubes, and graphene, and the employment of unique properties of thin films and ultrathin films, such as high surface area, controlled nanostructure for effective charge transfer, and special physical and chemical properties, to develop new thin film devices. This paper is therefore intended to provide a concise critical review and research directions on most thin film devices, including thin film transistors, data storage memory, solar cells, organic light-emitting diodes, thermoelectric devices, smart materials, sensors, and actuators. The thin film devices may consist of organic, inorganic, and composite thin layers, and share similar functionality, properties, and fabrication routes. Therefore, due to the multidisciplinary nature of thin film devices, knowledge and advances already made in one area may be applicable to other similar areas. Owing to the importance of developing low-cost, scalable, and vacuum-free fabrication routes, this paper focuses on thin film devices that may be processed and deposited from solution.

ACTIVE VIBRATION CONTROL AND SUPPRESSION FOR INTEGRATED STRUCTURES

The finite element dynamic model for integrated structures containing distributed piezoelectric sensors and actuators ( S/As ) is formulated with a new piezoelectric plate bending element in this paper. The problem of active vibration control and suppression of integrated structures is investigated under constant gain negative velocity feedback control law. A general method for active vibration control and suppression of integrated structures is presented. Finally, numerical example is given to illustrate the validity of the method proposed in this paper.

Sensor Hall Effect on Analyses Mechanical Stress

Measuring the magnetic field is a common practice in industrial processes. We can cite the voltage measurements through PTs （potential transformers）. This is a classic example of inductive field measuring, predicting to be measured quantity is of oscillatory nature, with the circuit instrumentation scaled and calibrated for a typical frequency of 50/60 Hz. For a long time, only the binary information： ＂this field＂ and ＂missing field＂ is needed. For example, only with this information can we identify the frequency of the rotating shaft. Currently, new technologies employ magnetic sensors for measuring positions （distances, angles, etc.） from the intensity of the magnetic field. Inductive sensors are inefficient on measurements of static fields, such as magnets, opening spaces for new linear Hall effect sensors, and static which deal with these situations without difficulty. The present study examines the behavior of the Hall sensor, making the measurement of the intensity of the static magnetic field of the rotating magnet and the same, verifying the effect of the speed at which the magnet passes the sensor in some way alter the measurement. The results are favorable manda and the versatility of these sensors in many different applications.

Shape estimation for a TPU-based multi-material 3D printed soft pneumatic actuator using deep learning models

Real-time proprioception presents a significant challenge for soft robots due to their infinite degrees of freedom and intrinsic compliance.Previous studies mostly focused on specific sensors and actuators.There is still a lack of generalizable technologies for integrating soft sensing elements into soft actuators and mapping sensor signals to proprioception parameters.To tackle this problem,we employed multi-material 3D printing technology to fabricate sensorized soft-bending actuators(SBAs)using plain and conductive thermoplastic polyurethane(TPU)filaments.We designed various geometric shapes for the sensors and investigated their strain-resistive performance during deformation.To address the nonlinear time-variant behavior of the sensors during dynamic modeling,we adopted a data-driven approach using different deep neural networks to learn the relationship between sensor signals and system states.A series of experiments in various actuation scenarios were conducted,and the results demonstrated the effectiveness of this approach.The sensing and shape prediction steps can run in real-time at a frequency of50 Hz on a consumer-level computer.Additionally,a method is proposed to enhance the robustness of the learning models using data augmentation to handle unexpected sensor failures.All the methods are efficient,not only for in-plane 2D shape estimation but also for out-of-plane 3D shape estimation.The aim of this study is to introduce a methodology for the proprioception of soft pneumatic actuators,including manufacturing and sensing modeling,that can be generalized to other soft robots.

Water presence detection in a concrete crack using smart aggregates

Liquid migrating into existing concrete cracks is a serious problem for the reliability of concrete structures and can sometimes induce full concrete structural failures.In this paper,the authors present recent research on water presence detection in concrete cracks using piezoceramic-based smart aggregate(SA)transducers.The active sensing approach,in which one piezoceramic transducer is used to generate stress waves and others are used to detect the stress wave responses,is adopted in this research.Cracks formed in concrete structures act as stress reliefs,which attenuate the energy of the signals received by the SAs.In case of a crack being filled with liquid,which changes the wave impedance,the piezoceramic transducers will report higher received energy levels.A wavelet packet-based approach is developed to provide calculated energy values of the received signal.These different values can help detect the liquid presence in a concrete crack.A concrete beam specimen with three embedded SAs was fabricated and tested.Experimental results verified that the SA-based active sensing approach can detect a concrete crack and further detect the liquid presence in the concrete crack.