Electrochemical Exfoliation of Graphene

Graphene Electrochem Exfoliation

“Whilst electrochemistry has been around for a long time it is a powerful tool for nanotechnology because it’s so finely tuneable” A simple electrochemical method has been used to tune the electrical and mechanical properties of graphene. AsianScientist (Aug. 11, 2015) – Graphene has been called the miracle material but the single-atomic layer material is Read more about Graphene Electrochem Exfoliation[…]

Converting chemical energy into electrical energy

Fuel Cells: Chemical to Electrical Energy

Converting chemical energy into electrical energy can be done in different ways, but for chemical energy stored in various fuels like hydrogen, electrochemical fuel cells are the most direct, and have the potential to be very efficient.

The electrochemistry side of fuel cells is rather straightforward.  Hydrogen, possibly with some carbon, on one side combines with oxygen on the other to produce water and possibly carbon dioxide.  The half reactions are separated so that the energy difference between reagents and products can be harvested as electrical energy.

Fuel Cells-EIS ApplicationElectrochemical Impedance Spectroscopy can identify problems that limit a fuel cell’s efficiency, by helping to optimize a cell, it can determine anodic and cathodic process mechanisms.  EIS is particularly good for measuring the equivalent series resistance of fuel cells, a major source of power loss in a low impedance device. Because of the modeling capability of EIS, you can also extract information on kinetics and mass transport in the fuel cell, both of which are crucial factors to fuel cell performance.  EIS is useful in both research and QC applications. EIS of fuel cells runs into some of the same low impedance device and setup limitations that also show up in batteries and supercapacitors.


References on Corrosion Theory and Electrochemical Corrosion Tests

Many of the following ‘references’ are available at Amazon.com and can be viewed at our Bookstore. DC Electrochemical Test Methods, N.G. Thompson and J.H. Payer, National Association of Corrosion Engineers, 1440 South Creek Drive, Houston, TX 77084-4906. Phone: 281-228-6200. Fax: 281-228-6300. ISBN: 1-877914-63-0. Recommended! Principles and Prevention of Corrosion, Denny A. Jones, Prentice-Hall, Upper Saddle Read more about References on Corrosion Theory and Electrochemical Corrosion Tests[…]

Electrochemical Quantitative Corrosion Theory

Quantitative Corrosion Theory

In the previous post (Electrochemical Corrosion Measurements Primer) we pointed out that Icorr cannot be measured directly. In many cases, you can estimate it from current versus voltage data. You can measure a log current versus potential curve over a range of about one half volt. The voltage scan is centered on Eoc. You then fit the measured data to a theoretical model of the corrosion process.

The model we will use for the corrosion process assumes that the rates of both the anodic and cathodic processes are controlled by the kinetics of the electron transfer reaction at the metal surface. This is generally the case for corrosion reactions. An electrochemical reaction under kinetic control obeys Equation 1-1, the Tafel Equation.

the Tafel Equation

Equation 1-1


There is a description of potentiostat stability (written by DK Roe) in the Kissinger & Heineman book (

Fitting EIS Data – Adding Components

Dr. Bob on  EISOne guideline that I have heard recommended (although I cannot give a reference for it) is that data over a decade range of frequency is required to support each circuit component.

All curve-fitting software should report some measure of the “goodness of fit.” Often this is the chi-squared parameter ( X2 ) or a value related to it. Boukamp makes the recommendation that the value of X2 should decrease by tenfold if a new circuit element is introduced into the circuit model. The tenfold decrease provides the justification for including the new circuit element. If the inclusion of an additional circuit element does not substantially improve the goodness-of-fit (as evidenced by the decrease in the X2 value), then based on Occam’s Razor, you should keep the simpler model, or continue your search for an improved one.

The old joke about the ability to “fit an elephant” if you use enough parameters is all too true with impedance data. Each component added to the model should have a physical explanation. Adding components only because they make the fit look better (smaller X2) without a physical interpretation is the equivalent to “fitting an elephant.”

What is X2?


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