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In this paper we present spatio-temporally controlled electrochemical stimulation of aqueous samples using an integrated CMOS microelectrode array with 131,072 pixels. We demonstrate programmable gold electrodeposition in arbitrary spatial patterns, controllable electrolysis to produce microscale hydrogen bubbles, and spatially targeted electrochemical pH modulation. Dense spatially-addressable electrochemical stimulation is important for a wide range of bioelectronics applications. 

Acid-base reactions are ubiquitous, easy to prepare, and execute without sophisticated equipment. Acids and bases are also inherently complementary and naturally map to a universal representation of “0” and “1.” Here, we propose how to leverage acids, bases, and their reactions to encode binary information and perform information processing based upon the majority and negation operations. These operations form a functionally complete set that we use to implement more complex computations such as digital circuits and neural networks. We present the building blocks needed to build complete digital circuits using acids and bases for dual-rail encoding data values as complementary pairs, including a set of primitive logic functions that are widely applicable to molecular computation. We demonstrate how to implement neural network classifiers and some classes of digital circuits with acid-base reactions orchestrated by a robotic fluid handling device. We validate the neural network experimentally on a number of images with different formats, resulting in a perfect match to thein-silicoclassifier. Additionally, the simulation of our acid-base classifier matches the results of thein-silicoclassifier with approximately 99% similarity.

 

Biotechnology applications are increasingly turning to CMOS integrated biosensor arrays for massive parallelism and increased throughput in biomolecular diagnostics. Yet many opportunities still remain to take advantage of the spatially-resolved nature of dense semiconductor platforms to open up new imaging dimensions which complement traditional microscopy. To better understand the emergence of spatial organization in living systems, we require techniques that dynamically probe the spatial structure of assemblies of millions of cells or more. Optical microscopy is the dominant technique, but large field-of-view microscopes have an inherent tradeoff with resolving fine features. Confocal microscopes can image cellular-scale 3D structures, but their bright illumination can impart severe phototoxicity, and observing large areas can be prohibitively slow. Here we present an integrated CMOS sensor array with 131,072 pixels, which is designed to electrochemically image and interface with bacterial biofilms. 

While classical electrochemical impedance spectroscopy (EIS) focuses on measurements from a single working electrode, dense active microelectrode arrays offer opportunities for new modes of sensing. Here we present experimental results with an integrated sensor array for electrochemical imaging. The system uses a 100 x 100 custom CMOS electrode array with 10 micron pixels, which measures impedance at frequencies up to 100 MHz. The sensor chip is uniquely designed to take advantage of the electrostatic coupling between groups of nearby pixels to re-shape the local electric field. Multiple bias voltages and clock phases create new types of signal diversity that will enable enhanced sensing modes for computational imaging and impedance tomography. 

This paper presents a 100 x 100 super-resolution integrated sensor array for microscale electrochemical impedance spectroscopy (EIS) imaging. The system is implemented in 180 nm CMOS with 10 x 10 micron pixels. Rather than treating each electrode independently, the sensor is designed to measure the mutual capacitance between programmable sets of pixels. Multiple spatially-resolved measurements can then be computationally combined to produce super-resolution impedance images. Experimental measurements of sub-cellular permittivity distributions within single algae cells demonstrate the potential of this new approach. 

Abstract Data encoded in molecules offers opportunities for secret messaging and extreme information density. Here, we explore how the same chemical and physical dimensions used to encode molecular information can expose molecular messages to detection and manipulation. To address these vulnerabilities, we write data using an object’s pre-existing surface chemistry in ways that are indistinguishable from the original substrate. While it is simple to embed chemical information onto common objects (covers) using routine steganographic permutation, chemically embedded covers are found to be resistant to detection by sophisticated analytical tools. Using Turbo codes for efficient digital error correction, we demonstrate recovery of secret keys hidden in the pre-existing chemistry of American one dollar bills. These demonstrations highlight ways to improve security in other molecular domains, and show how the chemical fingerprints of common objects can be harnessed for data storage and communication. 

Microorganisms account for most of the biodiversity on earth. Yet while there are increasingly powerful tools for studying microbial genetic diversity, there are fewer tools for studying microorganisms in their natural environments. In this paper, we present recent advances in CMOS electrochemical imaging arrays for detecting and classifying microorganisms. These microscale sensing platforms can provide non-optical measurements of cell geometries, behaviors, and metabolic markers. We review integrated electronic sensors appropriate for monitoring microbial growth, and present measurements of single-celled algae using a CMOS sensor array with thousands of active pixels. Integrated electrochemical imaging can contribute to improved medical diagnostics and environmental monitoring, as well as discoveries of new microbial populations.