Recent advances in semiconductor technology provide us with the resources to explore alternative methods for fabricating transistors with the goal of further reducing their sizes to increase transistor density and enhance performance. Conventional transistors use semiconductor junctions; they are formed by doping atoms on the silicon substrate that makes p-type and n-type regions. Decreasing the size of such transistors means that the junctions will get closer, which becomes very challenging when the size is reduced to the lower end of the nanometer scale due to the requirement of extremely high gradients in doping concentration. One of the most promising solutions to overcome this issue is realizing junctionless transistors. The first junctionless device was fabricated in 2010 and, since then, many other transistors of this kind (such as FinFET, Gate-All-Around, Thin Film) have been proposed and investigated. All of these semiconductor devices are characterized by junctionless structures, but they differ from each other when considering the influence of technological parameters on their performance. The aim of this review paper is to provide a simple but complete analysis of junctionless transistors, which have been proposed in the last decade. In this work, junctionless transistors are classified based on their geometrical structures, analytical model, and electrical characteristics. Finally, we used figure of merits, such as $I_{on}/I_{off}$ , $DIBL$ , and $SS$ , to highlight the advantages and disadvantages of each junctionless transistor category.

In this article, we present our research achievements regarding the development of a remote sensing system for motor pulse acquisition, as a first step towards a complete neuroprosthetic arm. We present the fabrication process of an implantable electrode for nerve impulse acquisition, together with an innovative wirelessly controlled system. In our study, these were combined into an implantable device for attachment to peripheral nerves. Mechanical and biocompatibility tests were performed, as well as in vivo testing on pigs using the developed system. This testing and the experimental results are presented in a comprehensive manner, demonstrating that the system is capable of accomplishing the requirements of its designed application. Most significantly, neural electrical signals were acquired and transmitted out of the body during animal experiments, which were conducted according to ethical regulations in the field.

In this paper, we investigate the accuracy of the approximated analytical model currently utilized, by many researchers, to describe the depletion region width in planar junctionless transistors (PJLT). The proposed analysis was supported by numerical simulations performed in COMSOL Multiphysics software. By comparing the numerical results and the approximated analytical model of the depletion region width, we calculated that the model introduces a maximum RMS error equal to $90\%$ of the donor concentration in the substrate. The maximum error is achieved when the gate voltage approaches the threshold voltage ( $V_{th}$ ) or when it approaches the flat band voltage ( $V_{FB}$ ) of the transistor. From these results, we concluded that this model cannot be used to determine accurately the flat-band and the threshold voltage of the transistor, although it represents a straightforward method to estimate the depletion region width in PJLT. By using the approximated analytical model, we extracted an analytical formula, which describes the electron concentration at the ideal boundary of the depletion region. This formula approximates the numerical data extracted from COMSOL with a relative error lower than $1\%$ . The proposed formula is in our opinion, as useful as the formula of the approximated analytical model because it allows for estimating the position of the depletion region also when the drain and source terminals are not grounded. We concluded that the analytical formula proposed at the end of this work could be useful to determine the position of the depletion region boundary in numerical simulations and in graphical representations provided by COMSOL Multiphysics software.

In this paper, we characterize and model a bidirectional front-end based on pseudo-floating gate amplifier (PFGA) for actuation and read-out of resonating sensors. The basic idea consists of swapping the power supply of the PFGA in order to change the directionality of the front-end. A detailed description of the system has been discussed in this paper and supported by simulations and measurement results. A prototype has been fabricated using discrete components and tested with a real transducer (Murata MA40S4) and a Butterworth Van Dyke (BvD) load, which has proved to be proved to be a well approximated model for resonant sensors. The bidirectional amplifier has been implemented with the integrated circuit CD4007UB, which is a commercial discrete component containing low leakage MOSFET. The values chosen for the BvD load are $R_b=330$ $\Omega$ , $L_m=60$ mH, $C_s=450$ pF, $C_E=2.2$ nF, which are approximately the same values of the lumped parameters reported in the data-sheet of the real sensor. This transducer is characterized by a nominal resonant frequency of 40 kHz. Measurement results show good fitting with the models developed in this work and the possibility to predict the sensor response by using the BvD load.

Novel research results of an ongoing development of a personalized forearm neuroprosthesis are being presented. A complete design process shows how the mechanical structure is developed from 3D scanning to 3D printing. With an individual DC motor for each finger and one for the palm, the neuroprosthesis achieves 15 degrees of freedom. Artificial skin cover fingers and palm, acting as resistive pressure sensors, giving a linear full range readout voltage proportional to the applied pressure. Fabrication steps and first-generation implantable electrodes are presented together with analog front-end electronics and an implantable wireless communication system. Arduino is used to process received neural motor signals, control the mechanical hand and process the received feedback signals from the artificial skin. The feedback signals will be wirelessly transmitted to implantable electrode actuators, for stimulation of sensorial nerves. Thus, the work of a bidirectional neuroprosthesis system integration is presented.