I think this follwing article might have answer to your question:

DESIGN OF CMOS READOUT FRONTEND CIRCUIT FOR MEMS CAPACITIVE MICROPHONES Daniel Arbet, Viera Stopjaková, Martin Kováč, Lukáš Nagy, Gabriel Nagy Slovak University of Technology in Bratislava Faculty of Electrical Engineering and Information Technology Institute of Electronics and Photonics Department of IC Design and Test

Abstract. This paper deals with a frontend part of the readout circuit developed as an integrated circuit that after bonding together with a MEMS capacitive microphone (MCM) chip will be used in a noise dosimeter applicable in very noisy and harsh environment, e.g. mine. Therefore, the main attention has been paid to the high dynamic range, low offset and low noise of the developed readout interface as well as its lowpower consumption feature. For conversion of the MCM’s capacitance variation into voltage, an approach based on the buffered input conversion stage biased by a voltage divider was used. The advantage of this approach is that the voltage divider formed by MOS transistors can be connected to the high-impedance node (i.e. the output of the MCM, in this case). The whole frontend part of the readout interface was designed in a standard 0.35m CMOS technology. Finally, the achieved results are discussed and

Soad Mohialdin

There are many purpose built MEMS microphones. But what I was asking if anyone had heard of using an ordinary image sensors, such as found in billions of cameras, as a way to capture fine details of interactions of air and gas molecules with the pixels in a sensitive images sensor.

The point being. Not to measure a single time series like regular microphones of any kind -- but to measure the tiny spatial and temporal variations of collisions and vorticity at the image sensor pixel level. That is a few microns usually.

I guess I will just have to try it. But I have no way to draw a vacuum for a control. I will see if I can monitor and vary the temperature and pressure and humidity, then see if the dark current and noise in the image sensor data stream correlates with nearby MEMS and other microphones. I can get 10,000 frames per second from a camera sensor and working to cover the low ultrasonic (up to a million samples/frames/regions/pixel collections per second roughly) frequencies.

I want to see the patterns of small regions. I think what I learn will fit with what the many aeronomy sensors gather. The fine details of vorticity and fluctuations at micron scale are interesting. Using the camera sensor (especially now there are so many inexpensive and fast ones), to capture that information is intriguing.

One final note. Since the image sensors are arrays, it might be possible to image or estimate the velocities and accelerations of the air above the sensor.

I will look at all the micron sized arrays (or the possibility of fabricating them) using rather ordinary piezoelectric arrays, but CMOS amplifiers and ADCs. In my way of looking at these things, all that is changing is the analog properties of the pixels. "Optical", "acoustic", "pressure", "resistor", "magnetic" -- are all just the details of what it is looking at and what the pixel can pick up. Everything beyond that - the amplifiers, thresholds, ADCs, data storage, data streams statistical profiles, archiving and global communities sharing and working together -- is the same.

The paper you mention is pretty well written. It pains me they did not publish on the Internet with the equations, models and data streams live so I could just run samples. Putting this nice method in words means having to read more incomplete word descriptions and having to translate that back into programs and tools and tests and data handling.

Richard Collins, Director, The Internet Foundation