A pico-ampere sensitive electrochemical sensor signal acquisition chain consisting of a multi-channel bidirectional current-mirror based potentiostat and a multiplexed current-input delta-sigma (AM) ADC is presented. Slice-based class-AB amplifiers with output stage current replication using reconfigurable current-mirrors enable bidirectional current sensing over a range of five decades. The replicated current is digitized by the ADC. The proposed circuit achieves a minimum detectable current of 91.7 pA, resulting in a dynamic range of 147 dB for sensor currents up to +1 mA. The potentiostat is operated at a 3 V supply, the ADC at 1.5 V. The static power consumption of a single interface channel depends on the number of active amplifier slices and is between 14.1 µW and 39.3 µW. The highest power efficiency among similar systems and the low voltage headroom consumption of less than 500 mV enables a versatile use of the interface for multiple sensing applications.
This paper introduces an approach of extracting process variations inside System-on-Chips (SoCs) to derive a Physical Unclonable Function (PUF). The process variations are extracted from the architecture of a Digital-to-Analog Converter (DAC). The DAC consists of two independent resistive ladders to provide one single or two output voltages. The resistive ladder is characterized by the SoC with the on-chip Analogto-Digital Converter (ADC) module. The developed PUF concept that exploits the process variations of the DAC is described and evaluated in this work. Due to the concept of not accepting an input challenge to the PUF, we designed a so-called weak-PUF. The final generated PUF response or also called fingerprint has a total length of 652 bits when using the maximum number of possible positions. In a typical operation condition, a worst-case intra-Hamming Distance (HD) of approximately 5% is achieved. Over a wide temperature range of -10°C to 70°C the intra-HD is increased to 13% in the worst-case. The inter-HD for all observed operating conditions is approximately 46%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.