714 research outputs found
A Biosensor-CMOS Platform and Integrated Readout Circuit in 0.18-μm CMOS Technology for Cancer Biomarker Detection
This paper presents a biosensor-CMOS platform for measuring the capacitive coupling of biorecognition elements. The biosensor is designed, fabricated, and tested for the detection and quantification of a protein that reveals the presence of early-stage cancer. For the first time, the spermidine/spermine N1 acetyltransferase (SSAT) enzyme has been screened and quantified on the surface of a capacitive sensor. The sensor surface is treated to immobilize antibodies, and the baseline capacitance of the biosensor is reduced by connecting an array of capacitors in series for fixed exposure area to the analyte. A large sensing area with small baseline capacitance is implemented to achieve a high sensitivity to SSAT enzyme concentrations. The sensed capacitance value is digitized by using a 12-bit highly digital successive-approximation capacitance-to-digital converter that is implemented in a 0.18 μm CMOS technology. The readout circuit operates in the near-subthreshold regime and provides power and area efficient operation. The capacitance range is 16.137 pF with a 4.5 fF absolute resolution, which adequately covers the concentrations of 10 mg/L, 5 mg/L, 2.5 mg/L, and 1.25 mg/L of the SSAT enzyme. The concentrations were selected as a pilot study, and the platform was shown to demonstrate high sensitivity for SSAT enzymes on the surface of the capacitive sensor. The tested prototype demonstrated 42.5 μS of measurement time and a total power consumption of 2.1 μW
A Wireless, Multi-Channel Printed Capacitive Strain Gauge System for Structural Health Monitoring
Structural health monitoring of soft structural textiles plays a key role within the space industry to ensure the safety and integrity of space habitats, parachutes, and decelerator systems. Strain monitoring could be an effective means to evaluate structural integrity, but conventional monitoring systems are not suitable because they are intended for large, rigid structures. To overcome the limitations of rigid sensors, we recently proposed using printed capacitive strain gauges (CSGs) on flexible substrates to monitor the structural health of soft structure materials. Here, we present a strategy and implementation of a wireless, multi-channel readout system for distributed monitoring of soft structural textiles with printed CSGs. The system is comprised of localized sensor motes and a wireless Bluetooth hub. The sensor mote employs a relaxation oscillator frontend to convert capacitance to frequency with a high dynamic range using only three interface wires per mote. The mote’s high dynamic range ensures compatibility with various gauge designs and accommodates significant process variation associated with printed gauges. Each hub enables users to read 8 channels of data wirelessly at a sampling rate of 100Hz and can be scaled to higher channel counts through the use of additional hubs. The sensor motes and wireless hub are miniaturized to accommodate flexible substrates, such as a Kevlar strap. The system is tested and exhibits excellent linearity and dynamic range
Development of a radiation hard version of the Analog Pipeline Chip APC128
The Analog Pipeline Chip (APC) is a low noise, low power readout chip for
silicon micro strip detectors with 128 channels containing an analog pipeline
of 32 buffers depth. The chip has been designed for operation at HERA with a
power dissipation of 300-400 muW per channel and has been used also in several
other particle physics experiments. In this paper we describe the development
of a radiation hard version of this chip that will be used in the H1 vertex
detector for operation at the luminosity upgraded HERA machine. A 128 channel
prototyping chip with several amplifier variations has been designed in the
radiation hard DMILL technology and measured. The results of various parameter
variations are presented in this paper. Based on this, the design choice for
the final production version of the APC128-DMILL has been made.Comment: 10 pages, 10 figure
A Time-Encoded Capacitance-to-Digital Converter Based on a Switched-Capacitor Feedback
An innovative method to perform capacitance-to-digital conversion without requiring sensor biasing circuitry is proposed. This letter is intended for the readout of MEMS capacitive microphones used in human-to-machine interface applications, where the main constraints are low power consumption and small chip area. The time-encoded sigma-delta ADC described here employs a switched-capacitor-based feedback to linearize the voltage-controlled oscillator and to couple the capacitive sensor to the readout. A prototype was fabricated to test the concept with a CMOS 130-nm process. The achieved relative capacitance resolution is 14.7 b with a rest capacitance value of 2.575pF and a total power consumption of 343μW . Linearity measurements ( SNDRpeak=51.5 dB in the bandwidth from 300Hz to 6.8kHz ) are limited by the test fixture due to the nonlinearity of the varactor introduced in lieu of a testing input sensor.The project funded from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 956601, involves the collaboration between Universidad Carlos III de Madrid and Infineon Technologies AG Austria
Low-Noise Energy-Efficient Sensor Interface Circuits
Today, the Internet of Things (IoT) refers to a concept of connecting any devices on network where environmental data around us is collected by sensors and shared across platforms. The IoT devices often have small form factors and limited battery capacity; they call for low-power, low-noise sensor interface circuits to achieve high resolution and long battery life. This dissertation focuses on CMOS sensor interface circuit techniques for a MEMS capacitive pressure sensor, thermopile array, and capacitive microphone.
Ambient pressure is measured in the form of capacitance. This work propose two capacitance-to-digital converters (CDC): a dual-slope CDC employs an energy efficient charge subtraction and dual comparator scheme; an incremental zoom-in CDC largely reduces oversampling ratio by using 9b zoom-in SAR, significantly improving conversion energy.
An infrared gesture recognition system-on-chip is then proposed. A hand emits infrared radiation, and it forms an image on a thermopile array. The signal is amplified by a low-noise instrumentation chopper amplifier, filtered by a low-power 30Hz LPF to remove out-band noise including the chopper frequency and its harmonics, and digitized by an ADC. Finally, a motion history image based DSP analyzes the waveform to detect specific hand gestures.
Lastly, a microphone preamplifier represents one key challenge in enabling voice interfaces, which are expected to play a dominant role in future IoT devices. A newly proposed switched-bias preamplifier uses switched-MOSFET to reduce 1/f noise inherently.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137061/1/chaseoh_1.pd
Linearization of Time-encoded ADCs Architectures for Smart MEMS Sensors in Low Power CMOS Technology
Mención Internacional en el título de doctorIn the last few years, the development of mobile technologies and machine learning
applications has increased the demand of MEMS-based digital microphones.
Mobile devices have several microphones enabling noise canceling, acoustic beamforming
and speech recognition. With the development of machine learning applications
the interest to integrate sensors with neural networks has increased.
This has driven the interest to develop digital microphones in nanometer CMOS
nodes where the microphone analog-front end and digital processing, potentially
including neural networks, is integrated on the same chip.
Traditionally, analog-to-digital converters (ADCs) in digital microphones have
been implemented using high order Sigma-Delta modulators. The most common
technique to implement these high order Sigma-Selta modulators is switchedcapacitor
CMOS circuits. Recently, to reduce power consumption and make them
more suitable for tasks that require always-on operation, such as keyword recognition,
switched-capacitor circuits have been improved using inverter-based operational
amplifier integrators. Alternatively, switched-capacitor based Sigma-
Delta modulators have been replaced by continuous time Sigma-Delta converters.
Nevertheless, in both implementations the input signal is voltage encoded
across the modulator, making the integration in smaller CMOS nodes more challenging
due to the reduced voltage supply.
An alternative technique consists on encoding the input signal on time (or
frequency) instead of voltage. This is what time-encoded converters do. Lately,
time-encoding converters have gained popularity as they are more suitable to
nanometer CMOS nodes than Sigma-Delta converters. Among the ones that have
drawn more interest we find voltage-controlled oscillator based ADCs (VCOADCs).
VCO-ADCs can be implemented using CMOS inverter based ring oscillators
(RO) and digital circuitry. They also show noise-shaping properties.
This makes them a very interesting alternative for implementation of ADCs in
nanometer CMOS nodes. Nevertheless, two main circuit impairments are present
in VCO-ADCs, and both come from the oscillator non-idealities. The first of them
is the oscillator phase noise, that reduces the resolution of the ADC. The second
is the non-linear tuning curve of the oscillator, that results in harmonic distortion
at medium to high input amplitudes.
In this thesis we analyze the use of time encoding ADCs for MEMS microphones
with special focus on ring oscillator based ADCs (RO-ADCs). Firstly, we
study the use of a dual-slope based SAR noise shaped quantizer (SAR-NSQ) in
sigma-delta loops. This quantizer adds and extra level of noise-shaping to the modulator, improving the resolution. The quantizer is explained, and equations
for the noise transfer function (NTF) of a third order sigma-delta using a second
order filter and the NSQ are presented.
Secondly, we move our attention to the topic of RO-ADCs. We present a high
dynamic range MEMS microphone 130nm CMOS chip based on an open-loop
VCO-ADC. This dissertation shows the implementation of the analog front-end
that includes the oscillator and the MEMS interface, with a focus on achieving
low power consumption with low noise and a high dynamic range. The digital
circuitry is left to be explained by the coauthor of the chip in his dissertation. The
chip achieves a 80dBA peak SNDR and 108dB dynamic range with a THD of 1.5%
at 128 dBSPL with a power consumption of 438μW.
After that, we analyze the use of a frequency-dependent-resistor (FDR) to implement
an unsampled feedback loop around the oscillator. The objective is to reduce
distortion. Additionally phase noise mitigation is achieved. A first topology
including an operational amplifier to increase the loop gain is analyzed. The design
is silicon proven in a 130 nm CMOS chip that achieves a 84 dBA peak SNDR
with an analog power consumption of 600μW. A second topology without the
operational amplifier is also analyzed. Two chips are designed with this topology.
The first chip in 130 nm CMOS is a full VCO-ADC including the frequencyto-
digital converter (F2D). This chip achieves a peak SNDR of 76.6 dBA with a
power consumption of 482μW. The second chip includes only the oscillator and
is implemented in 55nm CMOS. The peak SNDR is 78.15 dBA and the analog
power consumption is 153μW.
To finish this thesis, two circuits that use an FDR with a ring oscillator are
presented. The first is a capacity-to-digital converter (CDC). The second is a filter
made with an FDR and an oscillator intended for voice activity detection tasks
(VAD).En los últimos años, el desarrollo de las tecnologías móviles y las aplicaciones de
machine-learning han aumentado la demanda de micrófonos digitales basados
en MEMS. Los dipositivos móviles tienen varios micrófonos que permiten la cancelación
de ruido, el beamforming o conformación de haces y el reconocimiento
de voz. Con el desarrollo de aplicaciones de aprendizaje automático, el interés
por integrar sensores con redes neuronales ha aumentado. Esto ha impulsado el
interés por desarrollar micrófonos digitales en nodos CMOS nanométricos donde
el front-end analógico y el procesamiento digital del micrófono, que puede
incluir redes neuronales, está integrado en el mismo chip.
Tradicionalmente, los convertidores analógicos-digitales (ADC) en micrófonos
digitales han sido implementados utilizando moduladores Sigma-Delta de
orden elevado. La técnica más común para implementar estos moduladores Sigma-
Delta es el uso de circuitos CMOS de capacidades conmutadas. Recientemente,
para reducir el consumo de potencia y hacerlos más adecuados para las tareas que
requieren una operación continua, como el reconocimiento de palabras clave, los
convertidores Sigma-Delta de capacidades conmutadas has sido mejorados con
el uso de integradores implementados con amplificadores operacionales basados
en inversores CMOS. Alternativamente, los Sigma-Delta de capacidades conmutadas
han sido reemplazados por moduladores en tiempo continuo. No obstante,
en ambas implementaciones, la señal de entrada es codificada en voltaje durante
el proceso de conversión, lo que hace que la integración en nodos CMOS más
pequeños sea complicada debido a la menor tensión de alimentación.
Una técnica alternativa consiste en codificar la señal de entrada en tiempo (o
frecuencia) en lugar de tensión. Esto es lo que hacen los convertidores de codificación
temporal. Recientemente, los convertidores de codificación temporal
han ganado popularidad ya que son más adecuados para nodos CMOS nanométricos
que los convertidores Sigma-Delta. Entre los que más interés han despertado
encontramos los ADCs basados en osciladores controlados por tensión
(VCO-ADC). Los VCO-ADC se pueden implementar usando osciladores en anillo
(RO) implementados con inversores CMOS y circuitos digitales. Esta familia
de convertidores también tiene conformado de ruido. Esto los convierte en una
alternativa muy interesante para la implementación de convertidores en nodos
CMOS nanométricos. Sin embargo, dos problemas principales están presentes en
este tipo de ADCs debidos ambos a las no idealidades del oscilador. El primero
de los problemas es la presencia de ruido de fase en el oscilador, lo que reduce la resolución del ADC. El segundo es la curva de conversion voltaje-frecuencia no
lineal del oscilador, lo que causa distorsión a amplitudes medias y altas.
En esta tesis analizamos el uso de ADCs de codificación temporal para micrófonos
MEMS, con especial interés en ADCS basados en osciladores de anillo
(RO-ADC). En primer lugar, estudiamos el uso de un cuantificador SAR con conformado
de ruido (SAR-NSQ) en moduladores Sigma-Delta. Este cuantificador
agrega un orden adicional de conformado de ruido al modulador, mejorando la
resolución. En este documento se explica el cuantificador y obtienen las ecuaciones
para la función de transferencia de ruido (NTF) de un sigma-delta de tercer
orden usando un filtro de segundo orden y el NSQ.
En segundo lugar, dirigimos nuestra atención al tema de los RO-ADC. Presentamos
el chip de un micrófono MEMS de alto rango dinámico en CMOS de
130 nm basado en un VCO-ADC de bucle abierto. En esta tesis se explica la implementación
del front-end analógico que incluye el oscilador y la interfaz con
el MEMS. Esta implementación se ha llevado a cabo con el objetivo de lograr un
bajo consumo de potencia, un bajo nivel de ruido y un alto rango dinámico. La
descripción del back-end digital se deja para la tesis del couator del chip. La
SNDR de pico del chip es de 80dBA y el rango dinámico de 108dB con una THD
de 1,5% a 128 dBSPL y un consumo de potencia de 438μW.
Finalmente, se analiza el uso de una resistencia dependiente de frecuencia
(FDR) para implementar un bucle de realimentación no muestreado alrededor
del oscilador. El objetivo es reducir la distorsión. Además, también se logra la
mitigación del ruido de fase del oscilador. Se analyza una primera topologia de
realimentación incluyendo un amplificador operacional para incrementar la ganancia
de bucle. Este diseño se prueba en silicio en un chip CMOS de 130nm que
logra un pico de SNDR de 84 dBA con un consumo de potencia de 600μW en la
parte analógica. Seguidamente, se analiza una segunda topología sin el amplificador
operacional. Se fabrican y miden dos chips diseñados con esta topologia.
El primero de ellos en CMOS de 130 nm es un VCO-ADC completo que incluye
el convertidor de frecuencia a digital (F2D). Este chip alcanza un pico SNDR de
76,6 dBA con un consumo de potencia de 482μW. El segundo incluye solo el oscilador
y está implementado en CMOS de 55nm. El pico SNDR es 78.15 dBA y el
el consumo de potencia analógica es de 153μW.
Para cerrar esta tesis, se presentan dos circuitos que usan la FDR con un oscilador
en anillo. El primero es un convertidor de capacidad a digital (CDC). El
segundo es un filtro realizado con una FDR y un oscilador, enfocado a tareas de
detección de voz (VAD).Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Antonio Jesús Torralba Silgado.- Secretaria: María Luisa López Vallejo.- Vocal: Pieter Rombout
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Ultra-Low-Power Sensors and Receivers for IoT Applications
The combination of ultra-low power analog front-ends and CMOS-compatible transducers enable new applications, such as environmental monitors, household appliances, health trackers, etc. that are seamlessly integrated into our daily lives. Furthermore, wireless connectivity allows many of these sensors to operate both independently and collectively. These techniques collectively fulfil the recent surge of internet-of-things (IoT) applications that have the potential to fundamentally change daily life for millions of people.In this dissertation, the circuit and system design of wireless receivers and sensors is presented that explores the challenges of implementing long lifespan, high accuracy, and large coverage range IoT sensor networks. The first is a wake-up receiver (WuRX), which continuously monitors the RF environment to wake up a higher-power radio upon detection of a predetermined RF signature. This work both improves sensitivity and reduces power over prior art through a multi-faceted design featuring an impedance transformation network with large passive voltage gain, an active envelope detector with high input impedance to facilitate large passive voltage gain, a low-power precision comparator, and a low-leakage digital baseband correlator.Although pushing the prior WuRX performance boundary by orders of magnitude, the first work shows moderate sensitivity, inferior temperature robustness, and large area with external lumped components. Thus, the second work shows a miniaturized WuRX that is temperature-compensated, yet still consumes only nano-watt power and millimeter area while operating at 9 GHz. To further reduce the area, a global common-mode feedback is utilized across the envelope detector and baseband amplifier that eliminates the need for off-chip ac-coupling components. Multiple temperature-compensation techniques are proposed to maintain constant bandwidth of the signal path and constant clock frequency. Both WuRXs operate at 0.4 V supply, consume near-zero power and achieve ~-70 dBm sensitivity.Lastly, the first reported CMOS 2-in-1 relative humidity and temperature sensor is presented. A unified analog front-end interfaces on-chip transducers and converts the inputs into a frequency vis a high-linearity frequency-locked loop. An incomplete-settling switched-capacitor-based Wheatstone bridge is proposed to sense the inputs in a power-efficient fashion
A handheld high-sensitivity micro-NMR CMOS platform with B-field stabilization for multi-type biological/chemical assays
We report a micro-nuclear magnetic resonance (NMR) system compatible with multi-type biological/chemical lab-on-a-chip assays. Unified in a handheld scale (dimension: 14 x 6 x 11 cm³, weight: 1.4 kg), the system is capable to detect<100 pM of Enterococcus faecalis derived DNA from a 2.5 μL sample. The key components are a portable magnet (0.46 T, 1.25 kg) for nucleus magnetization, a system PCB for I/O interface, an FPGA for system control, a current driver for trimming the magnetic (B) field, and a silicon chip fabricated in 0.18 μm CMOS. The latter, integrated with a current-mode vertical Hall sensor and a low-noise readout circuit, facilitates closed-loop B-field stabilization (2 mT → 0.15 mT), which otherwise fluctuates with temperature or sample displacement. Together with a dynamic-B-field transceiver with a planar coil for micro-NMR assay and thermal control, the system demonstrates: 1) selective biological target pinpointing; 2) protein state analysis; and 3) solvent-polymer dynamics, suitable for healthcare, food and colloidal applications, respectively. Compared to a commercial NMR-assay product (Bruker mq-20), this platform greatly reduces the sample consumption (120x), hardware volume (175x), and weight (96x)
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