Costly erosion could be avoided with new computational method
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A new approach technique developed by researchers at Oregon State University and the University of California Berkeley can predict the precise reaction of metals with water, improving understanding of the risk of erosion.
With the exception of precious metals such as gold, every metal reacts with water. This renders corrosion inescapable and expensive; it is thought to be a multi-trillion dollar problem. Any technology to help improve estimate of when and where erosion may occur in a structure could help reduce these enormous losses.
“We’d like to predict the specific reactions of metal and combinations of metals with water and what the products of those reactions are, by computational methods first, as opposed to determining them experimentally,” said Professor Doug Keszler, distinguished professor of chemistry at Oregon State University.
When scientists observe metals dissolving in water, they assume that they form simple salts, he says, although this is not always the case.
“In many cases, it initially dissolves to form a complex cluster that contains many metal atoms. We can now predict the types of clusters that exist in solution, therefore furthering the understanding of metal dissolution from a computational point of view.”
The new computational method combines two techniques to make predictions: quantum mechanical calculations and a ‘group additivity’ method to create Pourbaix diagrams. These are the gold standard for describing the reaction of metals with water, and have allowed researchers to evaluate quantitatively the stability of some metals (aluminium, gallium, indium and thalium) as a function of pH and concentration.
Most Pourbaix diagrams do not include the metal clusters that the researchers turned their attention to in this Nature Communications study. This had left a significant gap in our understanding of erosion.
“We have now uncovered a fast and accurate formalism for simulating these clusters in the computer, which will transform our abilities to predict how metals react in water,” said Professor Kristin Persson, a materials scientist at UC Berkeley.
This could allow for predictions of erosion to be made more quickly and less expensively, and could have applications in the engineering of bridges and aircraft engines. These are particularly susceptible to corrosion, and require extensive testing to prevent dangerous accidents. Last year, a Japanese airline, ANA, found that corrosion of turbine blades in its Boeing 787 Dreamliner fleet was responsible for engine failures, and they were forced to refurbish all 100 engines at enormous expense.
“If you’re designing a new steel for a bridge, for example, you’d like to include the potential for corrosion in a computational design process,” said Professor Keszler. “Or if you have a new metal for an aircraft engine, you’d like to be able to determine if it’s going to corrode.”