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2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Stefan Nedelcu ◽  
Kishan Thodkar ◽  
Christofer Hierold

AbstractCustomizable, portable, battery-operated, wireless platforms for interfacing high-sensitivity nanoscale sensors are a means to improve spatiotemporal measurement coverage of physical parameters. Such a platform can enable the expansion of IoT for environmental and lifestyle applications. Here we report a platform capable of acquiring currents ranging from 1.5 nA to 7.2 µA full-scale with 20-bit resolution and variable sampling rates of up to 3.125 kSPS. In addition, it features a bipolar voltage programmable in the range of −10 V to +5 V with a 3.65 mV resolution. A Finite State Machine steers the system by executing a set of embedded functions. The FSM allows for dynamic, customized adjustments of the nanosensor bias, including elevated bias schemes for self-heating, measurement range, bandwidth, sampling rate, and measurement time intervals. Furthermore, it enables data logging on external memory (SD card) and data transmission over a Bluetooth low energy connection. The average power consumption of the platform is 64.5 mW for a measurement protocol of three samples per second, including a BLE advertisement of a 0 dBm transmission power. A state-of-the-art (SoA) application of the platform performance using a CNT nanosensor, exposed to NO2 gas concentrations from 200 ppb down to 1 ppb, has been demonstrated. Although sensor signals are measured for NO2 concentrations of 1 ppb, the 3σ limit of detection (LOD) of 23 ppb is determined (1σ: 7 ppb) in slope detection mode, including the sensor signal variations in repeated measurements. The platform’s wide current range and high versatility make it suitable for signal acquisition from resistive nanosensors such as silicon nanowires, carbon nanotubes, graphene, and other 2D materials. Along with its overall low power consumption, the proposed platform is highly suitable for various sensing applications within the context of IoT.


Author(s):  
Mingyuan Ren ◽  
Huijing Yang ◽  
Beining Zhang ◽  
Guoxu Zheng

This paper constructs and simulates the interface circuit of a temperature sensor based on SMIC 0.18 [Formula: see text]m CMOS. The simulation results show that when the power supply voltage is 1.8 V, the chopper op-amp gain is 89.44 dB, the low-frequency noise is 71.83 nV/Hz,[Formula: see text] and the temperature coefficient of the core temperature sensitive circuit is 1.7808 mV/[Formula: see text]C. The sampling rate of 10-bit SAR ADC was 10 kS/s, effective bit was 9.0119, SNR was 59.3256 dB, SFDR was 68.7091 dB, and THD was −62.5859 dB. The measurement range of temperature sensor interface circuit is −50[Formula: see text]C[Formula: see text]C, the relative temperature measurement error is ±0.47[Formula: see text]C, the resolution is 0.2[Formula: see text]C/LSB, and the overall average power consumption is 434.9 [Formula: see text]W.


Author(s):  
Arsalan Ghasemian ◽  
Ebrahim Abiri ◽  
Kourosh Hassanli ◽  
Abdolreza Darabi

Abstract By using CNFET technology in 3a 2 nm node using a proposed SQI gate, two split bit-lines QSRAM architectures have been suggested to address the issue of increasing demand for storage capacity in IoT/IoVT applications. Peripheral circuits such as a novel quaternary to binary decoder for QSRAM have been offered. Various simulations on temperature, supply voltage, and access frequency have been done to evaluate and ensure the performance of the proposed SQI gate, suggested cells, and quaternary to binary decoder. Moreover, 1000 Monte-Carlo analyses on the fabrication parameters have been done to classify read and write delay and standby power of proposed cells along with PDP of proposed quaternary to binary decoder. It is worth mentioning that the PDP of the proposed SQI gate, decoder, and average power consumption of suggested HF-QSRAM cell reached 0.92 aJ, 4.13 aJ, and 0.15 µW, respectively, which are approximately 80%, 91%, and 33% improvements in comparison with the best existing designs in the literature.


2021 ◽  
Vol 3 (4) ◽  
pp. 208-218
Author(s):  
K. Muralidharan ◽  
S. Uma Maheswari

In the modern world, high performance embedded applications in the field of multimedia, networking, and imaging are increasing day by day. These applications require high performance and more complex out-of-order superscalar processor. These complex dynamic instructions scheduling superscalar processors need higher levels of on-chip integration designs which are often associated with power dissipation. These out-of-order superscalar processors achieve higher performance compared to other processors by simultaneous fetching, decoding and execution for multiple instructions in out-of-order that are used in the next generation network processors. The main data path resources of the processor use CAM+RAM structure which is the major power consuming unit in the overall out-of-order processor design. The proposed new design of CAM+RAM with power-gating technique reduces the overall average power consumption compared to the conventional design without any significant impact on their performance.


Chemosensors ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 340
Author(s):  
Nikolay Samotaev ◽  
Pavel Dzhumaev ◽  
Konstantin Oblov ◽  
Alexander Pisliakov ◽  
Ivan Obraztsov ◽  
...  

A reduced size thermocatalytic gas sensor was developed for the detection of methane over the 20% of the explosive concentration. The sensor chip is formed from two membranes with a 150 µm diameter heated area in their centers and covered with highly dispersed nano-sized catalyst and inert reference, respectively. The power dissipation of the chip is well below 70 mW at the 530 °C maximum operation temperature. The chip is mounted in a novel surface mounted metal-ceramic sensor package in the form-factor of SOT-89. The sensitivity of the device is 10 mV/v%, whereas the response and recovery times without the additional carbon filter over the chip are <500 ms and <2 s, respectively. The tests have shown the reliability of the new design concerning the hotplate stability and massive encapsulation, but the high degradation rate of the catalyst coupled with its modest chemical power limits the use of the sensor only in pulsed mode of operation. The optimized pulsed mode reduces the average power consumption below 2 mW.


2021 ◽  
Vol 11 (23) ◽  
pp. 11117
Author(s):  
Dmytro S. Kozak ◽  
Maria Tonti ◽  
Patricia Cuba ◽  
Julian Espitia ◽  
Vladimir S. Tsepelev ◽  
...  

A lab-scale low-power free-running radio frequency (RF) oscillator operating at a frequency of 27.12 ± 0.50 MHz was developed to be suitable for fundamental microbiological research topics. Calibration and validation were conducted for two common foodborne pathogens in relevant microbiological growth media, i.e., Salmonella Typhimurium and Listeria monocytogenes in Tryptic Soy Broth and Brain–Heart Infusion broth, respectively. The evolution of temperature, frequency, and power consumption was monitored during treatments, both with and without bacterial cells. The setup operated within the predefined frequency range, reaching temperatures of 71–76 °C after 15 min. The average power consumption ranged between 12 and 14 W. The presence of bacteria did not significantly influence the operational parameters. The inactivation potential of the RF setup was validated, demonstrating the absence of viable cells after 8 and 10 min of treatment, for S. Typhimurium and L. monocytogenes, respectively. In future studies, the setup can be used to conduct fundamental microbiological studies on RF inactivation. The setup can provide added value to the scientific field, since (i) no consensus has been reached on the inactivation mechanisms of RF inactivation of pathogens in foods and (ii) most commercial RF setups are unsuitable to adopt for fundamental studies.


Author(s):  
Maryam Rafati ◽  
Seyed Ruhallah Qasemi ◽  
Atila Alvandpour

AbstractThis paper presents an ultra-low power, high sensitivity configurable CMOS fluorescence sensing front-end for implantable biosensors at single-cell level measurements. The front-end is configurable by a set of switches and consists of three integrated photodiodes (PD), three transimpedance amplifiers (TIA) for detecting a current range between 1 pA up to 10 mA. Also, an ambient light canceling technique is proposed to make the sensor operate under different environmental conditions. The proposed front-end could be configured for ultra-low light detection or ultra-low power consumption. The circuit is designed and fabricated in a 0.35 µm standard CMOS technology, and the measurement results are presented. The minimum integrated input-referred current noise is measured as 1.07 pA with the total average power consumption of 61.8 µW at an excitation frequency of 80 Hz. For ultra-low-power configuration, the front-end has an average power consumption of 119 nW and input integrated current noise of 210 pA at an excitation frequency of 20 kHz.


2021 ◽  
Vol 15 ◽  
Author(s):  
Chenglong Zou ◽  
Xiaoxin Cui ◽  
Yisong Kuang ◽  
Kefei Liu ◽  
Yuan Wang ◽  
...  

Artificial neural networks (ANNs), like convolutional neural networks (CNNs), have achieved the state-of-the-art results for many machine learning tasks. However, inference with large-scale full-precision CNNs must cause substantial energy consumption and memory occupation, which seriously hinders their deployment on mobile and embedded systems. Highly inspired from biological brain, spiking neural networks (SNNs) are emerging as new solutions because of natural superiority in brain-like learning and great energy efficiency with event-driven communication and computation. Nevertheless, training a deep SNN remains a main challenge and there is usually a big accuracy gap between ANNs and SNNs. In this paper, we introduce a hardware-friendly conversion algorithm called “scatter-and-gather” to convert quantized ANNs to lossless SNNs, where neurons are connected with ternary {−1,0,1} synaptic weights. Each spiking neuron is stateless and more like original McCulloch and Pitts model, because it fires at most one spike and need be reset at each time step. Furthermore, we develop an incremental mapping framework to demonstrate efficient network deployments on a reconfigurable neuromorphic chip. Experimental results show our spiking LeNet on MNIST and VGG-Net on CIFAR-10 datasetobtain 99.37% and 91.91% classification accuracy, respectively. Besides, the presented mapping algorithm manages network deployment on our neuromorphic chip with maximum resource efficiency and excellent flexibility. Our four-spike LeNet and VGG-Net on chip can achieve respective real-time inference speed of 0.38 ms/image, 3.24 ms/image, and an average power consumption of 0.28 mJ/image and 2.3 mJ/image at 0.9 V, 252 MHz, which is nearly two orders of magnitude more efficient than traditional GPUs.


Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2769
Author(s):  
Mohamed Atef ◽  
Osman Hassan ◽  
Falah Awwad ◽  
Moien A. B. Khan

In this article, we present a new photocurrent sensory circuit with a three-transistor background light cancellation. We describe our innovative photocurrent sensor-based blood pressure measuring device using a resistor-based current-to-voltage converter with a background light cancellation (BLC) loop. The photocurrent sensor is implemented using 0.35 μm standard CMOS technology and has zero average power consumption. The post-layout simulation for the photocurrent sensor shows a 1.3 MΩ transimpedance gain, a referred input noise current of 11 pA, and can reject a DC photocurrent up to 200 μA. This high DC rejection has been achieved due to the newly proposed multi-transistor BLC loop integrated with the sensor.


Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7472
Author(s):  
Marc Lazaro ◽  
Antonio Lazaro ◽  
Ramon Villarino ◽  
David Girbau

The COVID-19 pandemic has highlighted a large amount of challenges to address. To combat the spread of the virus, several safety measures, such as wearing face masks, have been taken. Temperature controls at the entrance of public places to prevent the entry of virus carriers have been shown to be inefficient and inaccurate. This paper presents a smart mask that allows to monitor body temperature and breathing rate. Body temperature is measured by a non-invasive dual-heat-flux system, consisting of four sensors separated from each other with an insulating material. Breathing rate is obtained from the temperature changes within the mask, measured with a thermistor located near the nose. The system communicates by means of long-range (LoRa) backscattering, leading to a reduction in average power consumption. It is designed to establish the relative location of the smart mask from the signal received at two LoRa receivers installed inside and outside an access door. Low-cost LoRa transceivers with WiFi capabilities are used in the prototype to collect information and upload it to a server. Accuracy in body temperature measurements is consistent with measurements made with a thermistor located in the armpit. The system allows checking the correct placement of the mask based on the recorded temperatures and the breathing rate measurements. Besides, episodes of cough can be detected by sudden changes in thermistor temperature.


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