Integration of a novel CMOS-compatible magnetoelectric antenna with a low-noise amplifier and a tunable input matching

Nasrollahpour, Mehdi; Romano, Anthony; Zaeimbashi, Mohsen; Liang, Xianfeng; Chen, Huaihao; Sun, Neville; Emam, Shadi; Onabajo, Marvin; Sun, Nian X.

doi:10.1007/s10470-020-01721-x

Cited by 12 publications

(3 citation statements)

References 26 publications

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“…WIRELESS Sensing has emerged as a viable option for implantable medical devices (IMDs) [ 1 ] with an essential need for power and device size minimizations. Numerous works and approaches for neural recording and wireless transmission/reception using integrated CMOS circuits have been reported with robust functionalities [ 2 ], [ 3 ], [ 4 ], [ 5 ], [ 6 ], [ 7 ], [ 8 ], [ 9 ], [ 10 ], [ 11 ], [ 12 ], [ 13 ]. Power-efficient brain machine interface circuits for neural recording with feature extraction have also been reported [ 14 ], [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Das

Nasrollahpour

et al. 2023

IEEE Open J. Circuits Syst.

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A magnetoelectric antenna (ME) can exhibit the dual capabilities of wireless energy harvesting and sensing at different frequencies. In this article, a behavioral circuit model for hybrid ME antennas is described to emulate the radio frequency (RF) energy harvesting and sensing operations during circuit simulations. The ME antenna of this work is interfaced with a CMOS energy harvester chip towards the goal of developing a wireless communication link for fully integrated implantable devices. One role of the integrated system is to receive pulsemodulated power from a nearby transmitter, and another role is to sense and transmit low-magnitude neural signals.The measurements reported in this paper are the first results that demonstrate simultaneous low-frequency wireless magnetic sensing and high-frequency wireless energy harvesting at two different frequencies with one dual-mode ME antenna. The proposed behavioral ME antenna model can be utilized during design optimizations of energy harvesting circuits. Measurements were performed to validate the wireless power transfer link with an ME antenna having a 2.57 GHz resonance frequency connected to an energy harvester chip designed in 65nm CMOS technology. Furthermore, this dual-mode ME antenna enables concurrent sensing using a carrier signal with a frequency that matches the second 63.63 MHz resonance mode. A wireless test platform has been developed for evaluation of ME antennas as a tool for neural implant design, and this prototype system was utilized to provide first experimental results with the transmission of magnetically modulated action potential waveforms. W

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Section: Introductionmentioning

confidence: 99%

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Das

Nasrollahpour

et al. 2023

IEEE Open J. Circuits Syst.

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“…Moreover, PEM MEMS/NEMS devices also have a very low ohmic loss and a narrow bandwidth. Radio frequency integrated circuits frequently use PEMT MEMSNEMS devices due to their compactness (Nasrollahpour et al [76]). Biomedical devices also have potential application areas for PEMT MEMS/NEMS devices.…”

Section: Introductionmentioning

confidence: 99%

Thermoelastic damping and frequency shift of different micro-scale piezoelectro-magneto-thermoelastic beams

Guha,

Singh,

Singh

2023

Phys. Scr.

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This work focuses on mathematically studying thermoelastic damping (TED) and frequency shift (FS) in micro-scale piezoelectro-magneto-thermoelastic (PEMT) composite beams composed of BaTiO3-CoFe2O4 combination. Pertaining to cutting-edge micro-technologies implemented in several engineering/scientific applications now-a-days, micro-scale doubly clamped (CC), doubly simply supported (SS), clamped-free (CF), and clamped-simply supported (CS) beams are extensively analyzed. The beams are modeled following the linear Euler–Bernoulli assumptions. The first two eigenvalues of all beams are numerically obtained using Newton-Raphson method. The closed-form expressions of TED and FS of all beams are derived analytically. The influences of Classical dynamical coupled (CL), Lord-Shulman (LS) & Green-Lindsay (GL) thermoelasticity theories, beam dimensions, BaTiO3 volume fraction (Ωf), and the first two modes M1 & M2) on the TED & FS are meticulously analyzed. Critical thickness (CrTh), critical length (CrLt), and TED (inverse Quality factor) of the beams are numerically obtained and studied. Among other key outcomes, the existence of a critical value of Ωf is established in the range Ωf∈ [ [0.5, 0.55], at which, the TED and FS display a drastic change in their natures. The outcomes of the present analysis may find immense potential uses in the design and development of PEMT composite micro-beams, and their applications in several areas such as supporting/stiffening other micro/nanostructures, construction works, sensitive sensing applications, etc.

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“…However, for the low-frequency NPR mode, it is feasible to fabricate an antenna array on one wafer such that each antenna has a different resonant frequency [6]. The first steps towards integrating ME antennas with complementary metal-oxide semiconductor (CMOS) circuits were reported in [10]. In this paper, we discuss a platform that is part of the design process to evaluate and establish wireless links with ME antennas for the development of nanoscale neural radio frequency identification (NanoNeuroRFID) devices for brain implantable devices (IMDs) [4].…”

Section: Introductionmentioning

confidence: 99%

A Radio Frequency Magnetoelectric Antenna Prototyping Platform for Neural Activity Monitoring Devices with Sensing and Energy Harvesting Capabilities

Das

Nasrollahpour

et al. 2020

Electronics

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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.

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Integration of a novel CMOS-compatible magnetoelectric antenna with a low-noise amplifier and a tunable input matching

Cited by 12 publications

References 26 publications

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Circuit-Level Modeling and Simulation of Wireless Sensing and Energy Harvesting With Hybrid Magnetoelectric Antennas for Implantable Neural Devices

Thermoelastic damping and frequency shift of different micro-scale piezoelectro-magneto-thermoelastic beams

A Radio Frequency Magnetoelectric Antenna Prototyping Platform for Neural Activity Monitoring Devices with Sensing and Energy Harvesting Capabilities

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