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When designing and optimizing mechanical systems, scientists understand the physical laws around them well enough to create computer models that can predict their properties and behavior. However, scientists working on the design of better electrochemical systems, such as batteries or supercapacitors, do not yet have a complete model of the driving forces that govern complex electrochemical behaviors.
After eight years of research on the behavior of these materials and their properties, scientists from the Argonne National Laboratory of the US Department of Energy (DOE), the DOE National Renewable Energy Laboratory, and the University of Colorado-Boulder have developed a conceptual model to form a more general theory of electrochemistry that predicts previously unexplained behavior.
The new model, called the Unified Electrochemical Strip Diagram (UEB) Framework, merges basic electrochemical theory with theories used in different contexts, such as the study of photoelectrochemistry and semiconductor physics, to describe the phenomena that occur in any electrode.
The research began with the study of alpha-manganese oxide, a material capable of charging and discharging quickly, making it ideal for some batteries. Scientists wanted to understand the mechanism behind the unique properties of the material in order to be able to improve it.
"There was no satisfactory answer to the way the material worked," said Argonne scientist Matthias Young, "but after doing a lot of calculations on the system, we discovered that by combining theories we could understand the mechanism.
In-depth testing of several other materials has helped scientists develop the model and demonstrate its usefulness in predicting exceptional phenomena.
"The model describes how the properties of a material and its environment interact with each other and result in transformations and degradation," said Mr. Young. "This helps us predict what will happen to a material in a specific environment.Is it going to collapse? Will it store loads?"
Computer models using UEB not only allow scientists to predict the behavior of materials, but they can also indicate material changes that may improve their performance.
"There are models that make correct predictions, but they do not give you the tools to improve the material," said Young. "This model gives you the conceptual handles you can transform to determine what needs to be changed to improve the performance of the material."
As the model is general and fundamental, it has the potential to help scientists develop any electrode, including those used for batteries, catalysis, supercapacitors and even desalination.
"We win something that exceeds the sum of its parts," said Young. "We took a lot of brilliant work from many different people, and we unified them to produce information that did not exist before."
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Material provided by DOE / Argonne National Laboratory. Note: Content can be changed for style and length.
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