Litcius/Paper detail

A 15-μW 105-dB 1.8-V<sub>pp</sub> Potentiostatic Delta-Sigma Modulator for Wearable Electrochemical Transducers in 65-nm CMOS Technology

Joan Aymerich, Augusto Márquez, Xavier Muñoz‐Berbel, F. Javier del Campo, Gonzalo Guirado, Lluís Terés, Francisco Serra-Graells, Michele Dei

2020IEEE Access28 citationsDOIOpen Access PDF

Abstract

Wearable electrochemical sensors represent a point of convergence between lab-on-a-chip technologies, advanced microelectronics and connected intelligence. These three pillars establish data flow from analytes present in body fluids, to the Cloud infrastructures towards next-generation personal healthcare and wellness. The design of electrode-embedded interfacing instrumentation in advanced CMOS technology nodes offer a number of challenges spanning from ultra-low power operation, small footprint, sufficient general purpose operability, and compatibility with advanced CMOS technology nodes. This paper presents a low-power frontend with extended amperometric dynamic range and wide potentiostatic range for electrochemical transducers with Delta-Sigma (ΔΣ) digital output. The second-order single-bit continuous-time ΔΣ modulator architecture reuses the electrochemical cell dynamic characteristics for quantization noise shaping, while the differential potentiostat enables 1.8 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pp</sub> of control range under single 1.2-V supply. The proposed frontend has been integrated in TSMC 65-nm CMOS technology occupying 0.07 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . From electrical and electrochemical tests, the micro potentiostat achieves a Signal-to-Distortion-and-Noise of 80 dB with 15-μW power consumption and a combined multi-scale dynamic range of 105 dB.

Topics & Concepts

PotentiostatCMOSDelta-sigma modulationDynamic rangeElectrical engineeringComputer scienceHigh dynamic rangeChipElectronic engineeringPhysicsEngineeringElectrodeElectrochemistryQuantum mechanicsAnalog and Mixed-Signal Circuit DesignNeuroscience and Neural EngineeringAdvanced Memory and Neural Computing