Carbon nanomaterials with various nanostructures (carbon nanotubes, graphene, graphene oxide, fullerene, nano diamonds, carbon quantum dots, carbon nanofibers, graphitic carbon nitrides, and nano porous carbons) are the decade’s most distinguishing and popular materials. They have distinctive physicochemical qualities such as chemical stability, mechanical strength, hardness, thermal and electrical conductivities, and so on. Furthermore, they are easily surface functionalized and tweaked, modifying them for high-end specific applications. Carbon nanostructures’ properties and surface

A novel kind of non-integer order bilinear filters, named double-order bilinear filters, is introduced in this work. They are based on the employment of two non-integer orders, offering the maximum design flexibility in comparison with their fractional-order and power-law counterparts. An attractive offered benefit is that this is achieved without increasing the circuit complexity, since the proposed structure is capable of realizing all non-integer kinds of filters. Two design examples are provided, where it is shown that lead/lag compensators utilized in control applications and low/high

The main objective of this chapter is to bring together studies addressing the current research and history of memristive device evolution available in the literature. The chapter highlights the methodologies and frameworks relevant to the development of nonlinear memristor models suitable for future nanoscale circuit design. An elaborate study of memristor device physics, structure, operation, mathematical modeling, and TCAD simulations is carried out for better understanding of nonlinear models of memristive devices. The memristive device features and content related to memristor nonlinear

This study presents the simultaneous generation of two uncorrelated and continuous high-quality random bitstreams originating from a single physical system based on confined, nonthermal electrochemical microplasma operating under atmospheric conditions. The randomness is intrinsically inherited from the time-resolved electrical current and optical emission intensities of the microplasma system, which were collected using wide bandwidth current probe and photodetection device. The parallel bitstreams pass unambiguously all 15 NIST SP 800-22 statistical tests without the need for any data post

Large deep neural network (DNN) models are computation and memory intensive, which limits their deployment especially on edge devices. Therefore, pruning, quantization, data sparsity and data reuse have been applied to DNNs to reduce memory and computation complexity at the expense of some accuracy loss. The reduction in the bit-precision results in loss of information, and the aggressive bit-width reduction could result in noticeable accuracy loss. This paper introduces Scaling-Weight-based Convolution (SWC) technique to reduce the DNN model size and the complexity and number of arithmetic

In this work, we generate and use a total of six different wideband signals for joint time-frequency characterization of nonlinear time-invariant [N-shaped differential resistor (NDR)] and linear time-varying (thermistor) circuits. A data acquisition board is used for applying the signals in the form of a voltage excitation and reading the induced current. The input signals have flat power spectra, thus avoiding the need for iterative calibration loops required to obtain signals with low crest factor. Such iterative loops are unavoidable when using random, pseudorandom, or chaotic signals all

The approximation of the frequency behavior of fractional-order, power-law, and double-order filters can be performed by the same rational integer-order transfer function. This can be achieved through the utilization of a curve fitting based approximation. Moreover, their implementation can be performed by the same core, by only changing the corresponding time constants and scaling factors. The aforementioned findings are experimentally verified using a Field Programmable Analog Array device. © 2023 by the authors.

The growing need for manipulators capable of handling delicate objects with care and coexisting safely with humans has brought soft robots to the forefront as a practical and cost-effective solution. In this context, this paper aims to explore soft grippers, a unique and versatile subset of soft robots. It provides an overview of various soft grasping techniques and materials, highlighting their respective advantages and limitations, along with showcasing several designed and tested models. As medicine and agriculture are acknowledged as pivotal domains required for basic human survival, this

In this article an adaptive decentralised sliding mode controller and observer for asynchronous nonlinear large-scale systems with backlash is proposed. In the literature, only the synchronous case for input nonlinearities such as dead-zone and saturation is found. In this article, the asynchronous case for systems with backlash is studied considering the backlash effect. Owing to the complexity of the backlash nonlinearity, an adaptive decentralised controller is proposed because of the capability of this strategy to deal with uncertainties and to improve the system performance when this

We propose a class of fully differential filters based on a common-gate differential amplifier cell in three different topologies. Our focus is on the synthesis of second-order band-pass filters and we found 53 possible circuits. All filters are resonance-based and have electronically tunable gain. Post layout simulations in 65-nm CMOS technology are provided to validate the proper function of these filters. © 2022 Elsevier B.V.