A major obstacle during the design of brain- computer interfaces is the unavailability of a neural implantable device that is μ-scale in size and is wireless, self-powered, and long-lasting. The current state-of-the-art implantable devices suffer from various limitations. Electromagnetic-based wireless devices are big in size because of their large antenna, which must be larger than one-tenth of the wavelength of the operational frequency. Ultrasound-based wireless devices, in addition to their low data rate, have massive loss in the skull and need an intermediate electromagnetic transceiver under the skull. Furthermore, almost all state-of-the-art wireless devices use micro-electrodes for neuronal recording, which are not reliable in long-term monitoring applications because of the direct contact between the tissue and metal electrodes. In this paper, we propose a novel, wireless, and ultra-compact implantable device termed NanoNeuroRFID. At the core of this device, there is a magnetoelectric (ME) antenna array. ME antennas are smart and ultra-miniaturized (<;200 μm diameter) and can perform multiple tasks. First, can harvest electromagnetic energy to power the NanoNeuroRFID system. Their limit of the detection for RF magnetic fields is 40 pT; second, they can sense quasi-static neuronal magnetic fields as small as 200 pT without direct contact to the tissue, allowing a long lifetime and reliable neural recording; and third, they can communicate with an external transceiver, and their operational frequency could be 10 to 100 s of MHz, where tissue loss is small.

An ultra-low power (ULP), energy-harvesting system-on-chip, that can operate in various application scenarios, is needed for enabling the trillions of Internet-of-Things (IoT) devices. However, energy from the ambient sources is little and system power consumption is high. Circuits and system development require an optimal use of available energy. In this paper, we present circuits that can improve the energy utilization in an IoT device by providing improvements at critical points of the flow of harvested energy. A boost converter circuit, that can harvest energy from 10-mV input voltage and a few nanowatt of input power, makes more harvested energy available for the IoT device. A single-inductor-multiple-output buck-boost converter provides high-efficiency and low-voltage power management solution to put most of the harvested energy for system use. A real time clock and ULP bandgap reference circuit significantly reduce the standby power consumption. The proposed ULP circuits are developed in 130-nm CMOS technology. The combined effects of these circuits and the system design technique can improve the life-time of an example IoT device by over four times in higher power consumption mode and over 70 times in ULP mode.

This paper reviews and analyses the design of popular radio frequency energy harvesting systems and proposes a method to qualitatively and quantitatively analyze their circuit architectures using new square-wave approximation method. This approach helps in simplifying design analysis. Using this analysis, we can establish no load output voltage characteristics, upper limit on rectifier efficiency, and maximum power characteristics of a rectifier. This paper will help guide the design of RF energy harvesting rectifier circuits for radio frequency identification (RFIDs), the Internet of Things (IoTs), wearable, and implantable medical device applications. Different application scenarios are explained in the context of design challenges, and corresponding design considerations are discussed in order to evaluate their performance. The pros and cons of different rectifier topologies are also investigated. In addition to presenting the popular rectifier topologies, new measurement results of these energy harvester topologies, fabricated in 65nm, 130nm and 180nm CMOS technologies are also presented.

This article presents a fully integrated RF energy harvester (EH) with 30% end-to-end power harvesting efficiency (PHE) and supports high-output voltage operation, up to 9.3 V, with a 1.07-GHz input and under the electrode model for neural applications. The EH is composed of a novel ten-stage self-biased gate (SBG) rectifier with an on-chip matching network (MN). The SBG topology elevates the gate-bias of transistors in a nonlinear manner to enable higher conductivity. The design also achieves $>$ 20% PHE range of 12 dB. The design was fabricated in 65-nm CMOS technology and occupies an area of 0.0732 mm2 with on-chip MN. In addition to standalone EH characterization measurement results, animal tissue stimulation test was performed to evaluate its performance in a realistic neural implant application.

This paper presents a temperature compensated RC oscillator (TC-RCO) designed in 130 nm CMOS technology using regular $V_{TH}$ transistors. The TC-RCO uses constant transconductance ( $g_{m}$ ) biasing for first order temperature compensation. Device mismatch based offset correction and delay compensation techniques in the comparator are used to improve temperature instability by cancelling out second order effects. The oscillator achieves a minimum temperature stability down to 21 ppm/° C for a temperature range of −20 to $100 ^{\circ} \text{C}$ . In the lowest power mode, the oscillator consumes 254 nW power from a 1 V supply. The TC-RCO is operated in two modes, a low power mode that consumes an average of 254 nW and a high stability mode that consumes an average of 345 nW. A duty-cycling technique is used to correct offset after four cycles of oscillation. The oscillator exhibits long term stability of 10 ppm after 1 s integration time.

This article describes the development of a radio frequency (RF) platform for electromagnetically modulated signals that makes use of a software-defined radio (SDR) to receive information from a novel magnetoelectric (ME) antenna capable of sensing low-frequency magnetic fields with ultra-low magnitudes. The platform is employed as part of research and development to utilize miniaturized ME antennas and integrated circuits for neural recording with wireless implantable devices. To prototype the reception of electromagnetically modulated signals from a sensor, a versatile Universal Software Radio Peripheral (USRP) and the GNU Radio toolkit are utilized to enable real-time signal processing under varying operating conditions. Furthermore, it is demonstrated how a radio frequency signal transmitted from the SDR can be captured by the ME antenna for wireless energy harvesting.