Automated Control of Material Structure with Electrical Impedance Monitoring 

Final Design - Setup 

Final Design - Video Demonstration 

Background

The UC San Diego’s Electrochemical Materials Science Research Labs studies nanomaterials using their impedance. They specifically test nanoporous, metal-salt composites. They commonly use copper, cobalt, iron, gold/silver for metals and lithium sulfate, chloride, or bromide for the salt component. The current lab process is to heat up or synthesize (also known as sintering) this composite by putting a cell of the material into a convection oven to observe the changes in its impedance spectra.

Step-by-step Summary of Sintering Process

Orange solid: metal-salt composite 

Conversion: heating/sintering process where the atoms are rearranging

Purification: the chemical process to remove the non-conducting salt portion

3 Images Above: Leftover hollow nanoporous metal foam shown by Scanning Electron Microscope (SEM) imaging

The sintering process ends once the lab observes that the target impedance spectra has been met, occurring approximately 10-20 hours. SEM imaging takes a closer look at the porosity, ligament size, and surface area of the new material. With its narrow pore-size distribution, the metallic framework can increase the active area accessible and improve electron mobility. These metal-like qualities can be used for different applications such as batteries, carbon dioxide reduction for fuel, energy conversion/storage systems, and the production of electrochemical sensors such as ultrathin supercapacitors.

Project Objectives

Current data analysis method: 

• Inefficient - lab members have to wait for the sintering process to finish to analyze the impedance of the material

• Unable to monitor the temperature of the oven as the material is being heated

Goal: 

• Automate the temperature control by comparing the impedance spectra to a previous test that has already been done via a closed-loop control feedback system

•  Adjust the temperature real-time in comparison to the impedance spectra  

• Learn how to navigate Gamry software and hardware to interpret collected data and analyzing how open the communication is with the impedance analyzer

• Provide quantitative data to show that our model is valid by looking at:

  •  the deviation of spectra and microscopic SEM image analysis of the material  

• Allowing result replicability for future experimental runs with different nanocomposite materials

Link to Executive Summary