A 0.0016 mm(2) 0.64 nJ leakage-based CMOS temperature sensor

This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes a capacitor to discharge through a transistor in the subthreshold regime. Furthermore, a novel charging mechanism for the capacitor is proposed to further increase the robustness against fabrication variability. The sensor, including digitization and interfacing, occupies 0.0016 mm2 and has an energy consumption of 47.7–633 pJ per sample. The resolution of the sensor is 0.28 °C, and the 3σ inaccuracy over the range 40–110 °C is 1.17 °C

Study of Radiation Effects on 28nm UTBB FDSOI Technology

With the evolution of modern Complementary Metal-Oxide-Semiconductor (CMOS) technology, transistor feature size has been scaled down to nanometers. The scaling has resulted in tremendous advantages to the integrated circuits (ICs), such as higher speed, smaller circuit size, and lower operating voltage. However, it also creates some reliability concerns. In particular, small device dimensions and low operating voltages have caused nanoscale ICs to become highly sensitive to operational disturbances, such as signal coupling, supply and substrate noise, and single event effects (SEEs) caused by ionizing particles, like cosmic neutrons and alpha particles. SEEs found in ICs can introduce transient pulses in circuit nodes or data upsets in storage cells. In well-designed ICs, SEEs appear to be the most troublesome in a space environment or at high altitudes in terrestrial environment. Techniques from the manufacturing process level up to the system design level have been developed to mitigate radiation effects. Among them, silicon-on-insulator (SOI) technologies have proven to be an effective approach to reduce single-event effects in ICs. So far, 28nm ultra-thin body and buried oxide (UTBB) Fully Depleted SOI (FDSOI) by STMicroelectronics is one of the most advanced SOI technologies in commercial applications. Its resilience to radiation effects has not been fully explored and it is of prevalent interest in the radiation effects community. Therefore, two test chips, namely ST1 and AR0, were designed and tested to study SEEs in logic circuits fabricated with this technology. The ST1 test chip was designed to evaluate SET pulse widths in logic gates. Three kinds of the on-chip pulse-width measurement detectors, namely the Vernier detector, the Pulse Capture detector and the Pulse Filter detector, were implemented in the ST1 chip. Moreover, a Circuit for Radiation Effects Self-Test (CREST) chain with combinational logic was designed to study both SET and SEU effects. The ST1 chip was tested using a heavy ion irradiation beam source in Radiation Effects Facility (RADEF), Finland. The experiment results showed that the cross-section of the 28nm UTBB-FDSOI technology is two orders lower than its bulk competitors. Laser tests were also applied to this chip to research the pulse distortion effects and the relationship between SET, SEU and the clock frequency. Total Ionizing Dose experiments were carried out at the University of Saskatchewan and European Space Agency with Co-60 gammacell radiation sources. The test results showed the devices implemented in the 28nm UTBB-FDSOI technology can maintain its functionality up to 1 Mrad(Si). In the AR0 chip, we designed five ARM Cortex-M0 cores with different logic protection levels to investigate the performance of approximate logic protecting methods. There are three custom-designed SRAM blocks in the test chip, which can also be used to measure the SEU rate. From the simulation result, we concluded that the approximate logic methodology can protect the digital logic efficiently. This research comprehensively evaluates the radiation effects in the 28nm UTBB-FDSOI technology, which provides the baseline for later radiation-hardened system designs in this technology

Characterization and analysis of process variability in deeply-scaled MOSFETs

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 137-147).Variability characterization and analysis in advanced technologies are needed to ensure robust performance as well as improved process capability. This thesis presents a framework for device variability characterization and analysis. Test structure and test circuit design, identification of significant effects in design of experiments, and decomposition approaches to quantify variation and its sources are explored. Two examples of transistor variability characterization are discussed: contact plug resistance variation within the context of a transistor, and AC, or short time-scale, variation in transistors. Results show that, with careful test structure and circuit design and ample measurement data, interesting trends can be observed. Among these trends are (1) a distinct within-die spatial signature of contact plug resistance and (2) a picosecond-accuracy delay measurement on transistors which reveals the presence of excessive external parasitic gate resistance. Measurement results obtained from these test vehicles can aid in both the understanding of variations in the fabrication process and in efforts to model variations in transistor behavior.by Karthik Balakrishnan.Ph.D

PROCESS AWARE ANALOG-CENTRIC SINGLE LEAD ECG ACQUISITION AND CLASSIFICATION CMOS FRONTEND

The primary objective of this research work is the development of a low power single-lead ECG analog front-end (AFE) architecture which includes acquisition, digitization, process aware efficient gain and frequency control mechanism and a low complexity classifier for the detecting asystole, extreme bardycardia and tachycardia. Recent research on ECG recording systems focuses on the design of a compact single-lead wearable/portable devices with ultra-low-power consumption and in-built hardware for diagnosis and prognosis. Since, the amplitude of the ECG signal varies from hundreds of µV to a few mV, and has a bandwidth of DC to 250 Hz, conventional front-ends use an instrument amplifier followed by a programmable gain amplifier (PGA) to amplify the input ECG signal appropriately. This work presents an mixed signal ECG fronted with an ultra-low power two-stage capacitive-coupled signal conditioning circuit (or an AFE), providing programmable amplification along with tunable 2nd order high pass and lowpass filter characteristics. In the contemporary state-of-the-art ECG recording systems, the gain of the amplifier is controlled by external digital control pins which are in turn dynamically controlled through a DSP. Therefore, an efficient automatic gain control mechanism with minimal area overhead and consuming power in the order of nano watts only. The AGC turns the subsequent ADC on only after output of the PGA (or input of the ADC) reaches a level for which the ADC achieves maximum signal-to-noise-ratio (SNR), hence saving considerable startup power and avoiding the use of DSP. Further, in any practical filter design, the low pass cut-off frequency is prone to deviate from its nominal value across process and temperature variations. Therefore, post-fabrication calibration is essential, before the signal is fed to an ADC, to minimize this deviation, prevent signal degradation due to aliasing of higher frequencies into the bandwidth for classification of ECG signals, to switch to low resolution processing, hence saving power and enhances battery lifetime. Another short-coming noticed in the literature published so far is that the classification algorithm is implemented in digital domain, which turns out to be a power hungry approach. Moreover, Although analog domain implementations of QRS complexes detection schemes have been reported, they employ an external micro-controller to determine the threshold voltage. In this regard, finally a power-efficient low complexity CMOS fully analog classifier architecture and a heart rate estimator is added to the above scheme. It reduces the overall system power consumption by reducing the computational burden on the DSP. The complete proposed scheme consists of (i) an ultra-low power QRS complex detection circuit using an autonomous dynamic threshold voltage, hence discarding the need of any external microcontroller/DSP and calibration (ii) a power efficient analog classifier for the detection of three critical alarm types viz. asystole, extreme bradycardia and tachycardia. Additionally, a heart rate estimator that provides the number of QRS complexes within a period of one minute for cardiac rhythm (CR) and heart rate variability (HRV) analysis. The complete proposed architecture is implemented in UMC 0.18 µm CMOS technology with 1.8 V supply. The functionality of each of the individual blocks are successfully validated using postextraction process corner simulations and through real ECG test signals taken from the PhysioNet database. The capacitive feedback amplifier, Σ∆ ADC, AGC and the AFT are fabricated, and the measurement results are discussed here. The analog classification scheme is successfully validated using embed NXP LPC1768 board, discrete peak detector prototype and FPGA software interfac