Directly drawn top-gate semiconducting carbon nanotube thin-film transistors and complementary inverters.

As the emerging demand for electronic devices that are simple, cost effective and capable of rapid fabrication has increased, novel fabrication techniques for designing and manufacturing such devices have attracted remarkable research interest. One method for prototyping these electronic devices is to draw them using a handwriting tool that is commonly available. In this work, we demonstrate a transistor and complementary logic inverter that are directly drawn using a brush and that are based on solution-based materials such as semiconducting carbon nanotubes (CNTs), silver ink and paste, and cross-linked poly(4-vinylphenol) (cPVP).

Synaptic Device Network Architecture with Feature Extraction for Unsupervised Image Classification.

For the efficient recognition and classification of numerous images, neuroinspired deep learning algorithms have demonstrated their substantial performance. Nevertheless, current deep learning algorithms that are performed on von Neumann machines face significant limitations due to their inherent inefficient energy consumption. Thus, alternative approaches (i.

Three-Dimensional Printed Poly(vinyl alcohol) Substrate with Controlled On-Demand Degradation for Transient Electronics.

Electronics that degrade after stable operation for a desired operating time, called transient electronics, are of great interest in many fields, including biomedical implants, secure memory devices, and environmental sensors. Thus, the development of transient materials is critical for the advancement of transient electronics and their applications. However, previous reports have mostly relied on achieving transience in aqueous solutions, where the transience time is largely predetermined based on the materials initially selected at the beginning of the fabrication.

Three-Dimensionally Printed Micro-electromechanical Switches.

Three-dimensional (3D) printers have attracted considerable attention from both industry and academia and especially in recent years because of their ability to overcome the limitations of two-dimensional (2D) processes and to enable large-scale facile integration techniques. With 3D printing technologies, complex structures can be created using only a computer-aided design file as a reference; consequently, complex shapes can be manufactured in a single step with little dependence on manufacturer technologies. In this work, we provide a first demonstration of the facile and time-saving 3D printing of two-terminal micro-electromechanical (MEM) switches.

Impact of Synaptic Device Variations on Pattern Recognition Accuracy in a Hardware Neural Network.

Neuromorphic systems (hardware neural networks) derive inspiration from biological neural systems and are expected to be a computing breakthrough beyond conventional von Neumann architecture. Interestingly, in neuromorphic systems, the processing and storing of information can be performed simultaneously by modulating the connection strength of a synaptic device (i.e.