Robust Circuit Design for Low-Voltage VLSI.

Voltage scaling is an effective way to reduce the overall power consumption, but the major challenges in low voltage operations include performance degradation and reliability issues due to PVT variations. This dissertation discusses three key circuit components that are critical in low-voltage VLSI. Level converters must be a reliable interface between two voltage domains, but the reduced on/off-current ratio makes it extremely difficult to achieve robust conversions at low voltages. Two static designs are proposed: LC2 adopts a novel pulsed-operation and modulates its pull-up strength depending on its state. A 3-sigma robustness is guaranteed using a current margin plot; SLC inherently reduces the contention by diode-insertion. Improvements in performance, power, and robustness are measured from 130nm CMOS test chips. SRAM is a major bottleneck in voltage-scaling due to its inherent ratioed-bitcell design. The proposed 7T SRAM alleviates the area overhead incurred by 8T bitcells and provides robust operation down to 0.32V in 180nm CMOS test chips with 3.35fW/bit leakage. Auto-Shut-Off provides a 6.8x READ energy reduction, and its innate Quasi-Static READ has been demonstrated which shows a much improved READ error rate. A use of PMOS Pass-Gate improves the half-select robustness by directly modulating the device strength through bitline voltage. Clocked sequential elements, flip-flops in short, are ubiquitous in today’s digital systems. The proposed S2CFF is static, single-phase, contention-free, and has the same number of devices as in TGFF. It shows a 40% power reduction as well as robust low-voltage operations in fabricated 45nm SOI test chips. Its simple hold-time path and the 3.4x improvement in 3-sigma hold-time is presented. A new on-chip flip-flop testing harness is also proposed, and measured hold-time variations of flip-flops are presented.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111525/1/yejoong_1.pd

Analyzing Income and Welfare in South Korea

How can machine learning classification models be utilized to correlate socioeconomic conditions with income? What kinds of insights could be generated from the unsupervised clustering of data? This paper aims to find clear and accurate correlations between socioeconomic factors and mean income, as well as cluster seemingly unrelated data together to find hidden trends or patterns in data. The machine-learning classification models provided some insights into the socioeconomic conditions of South Korea and other global countries, suggesting that several socioeconomic factors, most notably education level and number of family members, gave somewhat strong levels of correlation on whether an individual would meet or exceed the average income. This was further reinforced by unsupervised clustering performed on both datasets, where clear differences especially in education level and family members were perceived among cluster outputs, indicating its importance in the socioeconomic analysis of this paper. However, given some potential limitations and some low evaluation metrics, more research is certainly welcome to paint an even clearer picture

A 635pW battery voltage supervisory circuit for miniature sensor nodes

We propose a low power battery voltage supervisory circuit for micro-scale sensor systems that provides power-on reset, brown-out detection, and recovery detection to prevent malfunction and battery damage. Ultra-low power is achieved using a 57pA, fast stabilizing two-stage voltage reference and an 81pA leakage-based oscillator and clocked comparator. The supervisor was fabricated in 180nm CMOS and integrated with a complete 1 mm3 sensor system. It consumes 635pW at 3.6V supply voltage, which is an 850 × reduction over the best prior work

5.2 Energy-Efficient Low-Noise CMOS Image Sensor with Capacitor Array-Assisted Charge-Injection SAR ADC for Motion-Triggered Low-Power IoT Applications

As IoT is increasingly integrated into our everyday life, the demand for different sensor modalities, especially imaging, is rising. IoT imagers are often compact and have small form-factor batteries and thus must be designed with both low power (improving battery life) and high image quality (maximizing utility). Previously reported sensors [1, 2], along with this work, adopt motion-detection (MD) triggering of full-array capture where MD is performed on a heavily subsampled frame to enable continuous low-power operation. MD limits energy-hungry full-array captures to cases where activity is detected. To further reduce power consumption, the full-frame capture energy itself needs to be addressed, which is typically dominated by the ADC

An Ultra-Low-Power Biomedical Chip for Injectable Pressure Monitor

11Nsciescopu

A 1.74.12 mm3 Fully Integrated pH Sensor for Implantable Applications using Differential Sensing and Drift-Compensation

This paper presents a 1.7 ?? 4.1 ?? 2 mm3 pH sensor that is a fully integrated, stand-alone and implantable system. Instead of a bulky cm size Ag/AgCl electrode, we use a mm-size integrated platinum electrode, and differential sensing using ISFET and REFET pair to compensate for unstable fluid potential. We also propose a drift compensation technique in which the leakage from the source and drain through the gate oxide is canceled, reducing drift > 100 ?? . ?? 2019 JSAP

A 286nW, 103V High Voltage Generator and Multiplexer for Electrostatic Actuation in Programmable Matter

International audienceWe present a high-voltage-generation-and-multiplexing (HVGM) chip, specifically designed for electrostatic actuation of micro-robots. It can individually control 12 pairs of +/- electrodes using a positive and negative charge pump and mux-structure, consumes 286nW in steady state and 533nW when transitioning a 10pF electrode at 155V/s, and produces a differential voltage of 103V (29× voltage gain from 3.6V) in measurement. We also show a complete microsystem of stacked die, measuring 3×1.4×1.1mm, including HVGM, processor, radio, and harvester for energy autonomous operation