Spintronic Nanodevices for Neuromorphic Sensing Chips

Recent developments in spintronics materials and physics are promising to develop a new type of magnetic sensors which can be embedded into the silicon chips. These neuromorphic sensing chips will be designed to capture the biomagnetic signals from active biological tissue exploited as brain-machine interface. They lead to machines that are able to sense and interact with the world in humanlike ways and able to accelerate years of fitful advance in artificial intelligence. To detect the weak biomagnetic signals, this work aims to develop a CMOS-compatible spintronic sensor based on the magnetoresistive (MR) effect. As an alternative to bulky superconducting quantum interference device (SQUID) systems, the miniaturised spintronic devices can be integrated with standard CMOS technologies makes it possible to detect weak biomagnetic signals with micron-sized, non-cooled and low-cost. Fig. 1 shows the finite element method (FEM)-based simulation results of a Tunnelling-Magnetoresistive (TMR) sensor with an optimal structure in COMSOL Multiphysics. The finest geometry and material are demonstrated and compared with the state-of-the-art. The proposed TMR sensor achieves a linear response with a high TMR ratio of 172% and sensitivity of 223 μV/Oe. The results are promising for utilizing the TMR sensors in future miniaturized brain-machine interface, such as Magnetoencephalography (MEG) systems for neuromorphic sensing

Modelling of Spintronic Nanodevices for Neuromorphic Sensing Chips

No abstract available

Modelling of Spintronic Nanodevices for Neuromorphic Sensing Chips

No abstract available

Device modelling of MgO-barrier tunnelling magnetoresistors for hybrid spintronic-CMOS

Spintronic sensors, that are based on the tunnellingmagnetoresistive (TMR) effect, have been utilized in detecting low magnetic fields. However, still no computer-based model of these devices is available to integrated circuit designer to implement them in a hybrid spintronic-CMOS system. We developed a finite element method (FEM)-based model of a MgO-barrier TMR device in COMSOL Multiphysics®. The parameters of this model were extracted from the state-of-the-art fabrication and experimental data. Results were compared with respect to the model geometry and the used material. The proposed TMR sensor model offers a linear response with a high TMR ratio of 233% at 10 mV power supply. The model was exported to Cadence© Spectre to create a compact model using Verilog-A language. The developed sensor model was simulated with its analog front-end in same environment. This model provided a reliable benchmark for modelling of the future hybrid spintronic-CMOS developments

High-precision biomagnetic measurement system based on tunnel magneto-resistive effect

This paper presents a novel low-noise and high-precision readout circuit for tunnelling magnetoresistive (TMR) array to evaluate the suitability of biomagnetic measurement platform for detection of weak biomagnetic fields. We propose a three operational-amplifier architecture with a high input impedance and an adjustable gain for the fabricated TMR sensor that is highly miniaturized and can be operated at room temperature. The proposed system was designed using standard 0.18 µm CMOS technology and achieved a good performance with regard to gain, linearity, power consumption, and noise by employing a chopper stabilization technique and common mode feedback. The gain can reach 80 dB through adjusting two 5-bit programmable resistors and the input-referred noise voltage only has 44.6 nV/√Hz with 10 nA input bias over a wide range of frequency. Moreover, the whole readout dissipates 58 µW of power with a 1.8 V supply voltage. Benefiting from the CMOS compatibility of the TMR sensor, it offers monolithic integration directly on a silicon substrate as a TMR-on-chip sensing system. This will enable a new scientific and engineering paradigm to revitalize the biomagnetism field as an alternative way to understand the underlying mechanism of the human body

Spintronic Nanodevices for Neuromorphic Sensing Chips

Recent developments in spintronics materials and physics are promising to develop a new type of magnetic sensors which can be embedded into the silicon chips. These neuromorphic sensing chips will be designed to capture the biomagnetic signals from active biological tissue exploited as brain-machine interface. They lead to machines that are able to sense and interact with the world in humanlike ways and able to accelerate years of fitful advance in artificial intelligence. To detect the weak biomagnetic signals, this work aims to develop a CMOS-compatible spintronic sensor based on the magnetoresistive (MR) effect. As an alternative to bulky superconducting quantum interference device (SQUID) systems, the miniaturised spintronic devices can be integrated with standard CMOS technologies makes it possible to detect weak biomagnetic signals with micron-sized, non-cooled and low-cost. Fig. 1 shows the finite element method (FEM)-based simulation results of a Tunnelling-Magnetoresistive (TMR) sensor with an optimal structure in COMSOL Multiphysics. The finest geometry and material are demonstrated and compared with the state-of-the-art. The proposed TMR sensor achieves a linear response with a high TMR ratio of 172% and sensitivity of 223 μV/Oe. The results are promising for utilizing the TMR sensors in future miniaturized brain-machine interface, such as Magnetoencephalography (MEG) systems for neuromorphic sensing

Smart Multi-Sensory Ball for Water Quality Monitoring

Electronic sensors and wireless communications have enabled a long-distance and real-time monitoring of water quality. In this paper, we present a smart multi-sensory device, remotely measuring and monitoring physical parameters of the water in real time. The proposed device is a 10 cm-diameter enclosure, consisting of an embedded battery, a voltage regulator, an Inertial Measurement Unit (IMU), and a communication chip with the 3D-printing cases. This smart multi-sensory enclosure or smart "ball" can successfully communicate with a personal computer in the real-time via wireless communication. Finally, the collected data can be directly displayed and post-processed to show real-time changes in the parameters

A CMOS Analog Front-End for Tunnelling Magnetoresistive Spintronic Sensing Systems

This paper presents a CMOS readout circuit for an integrated and highly-sensitive tunnel-magnetoresistive (TMR) sensor. Based on the characterization of the TMR sensor in the finite-element simulation, using COMSOL Multiphysics, the circuit including a Wheatstone bridge and an analogue front-end (AFE) circuit, were designed to achieve low-noise and low-power sensing. We present a transimpedance amplifier (TIA) that biases and amplifies a TMR sensor array using switched-capacitors external noise filtering and allows the integration of TMR sensors on CMOS without decreasing the measurement resolution. Designed using TSMC 0.18 μm 1V technology, the amplifier consumes 160 nA at 1.8 V supply to achieve a dc gain of 118 dB and a bandwidth of 3.8 MHz. The results confirm that the full system is able to detect the magnetic field in the pico-Tesla range with low circuit noise (2.297 pA/√Hz) and low power consumption (86 μW). A concurrent reduction in the power consumption and attenuation of noise in TMR sensors makes them suitable for long-term deployment in spintronic sensing systems

On Chip Counting and Localisation of Magnetite Pollution Nanoparticles

Magnetic nanoparticles are generally smaller than 200 nm surrounding our environment and can easily enter the human brain through the respiratory system. The harm of such nanoparticles may endanger people’s health. This paper focuses on modelling and simulation based on a new kind of magnetic sensors, which can count and localize these magnetite nanoparticles. The proposed sensors could help to prevent these nanoparticles from the polluted environment and undoubtedly reduce their adverse risks to humans. The modelled magnetic system consists of a tunnelling magnetoresistive (TMR) sensor array, a conducting line, and the detected magnetite nanoparticles. The localization and quantization of these nanoparticles can be achieved by analysing total output voltages from the TMR sensor array

CMOS Magnetic Sensors for Wearable Magnetomyography

Magnetomyography utilizes magnetic sensors to record small magnetic fields produced by the electrical activity of muscles, which also gives rise to the electromyogram (EMG) signal typically recorded with surface electrodes. Detection and recording of these small fields requires sensitive magnetic sensors possibly equipped with a CMOS readout system. This paper presents a highly sensitive Hall sensor fabricated in a standard 0.18 μm CMOS technology for future low-field MMG applications. Compared with previous works, our experimental results show that the proposed Hall sensor achieves a higher current mode sensitivity of approximately 2400 V/A/mT. Further refinement is required to enable measurement of MMG signals from muscles