U.S. Researchers have developed a new computational method to predict how metals react with water.
The findings, published in Nature Communications, could have a wide range of applications, including in the design of bridges and aircraft engines, both of which are susceptible to corrosion.
The wide reach of corrosion, a multi-trillion-dollar global problem, may someday be narrowed considerably thanks to the new, better approach to make predictions faster, less costly and more effective, according to researchers at Oregon State University (OSU) and the University of California, Berkeley.
"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," Doug Keszler, professor of chemistry in OSU's College of Science, said in a statement.
"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," he said.
Last August, the Japanese airline ANA had to refurbish all 100 Rolls-Royce engines, selling for 20 million U.S. dollars each, on its fleet of Boeing 787 Dreamliners after three engine failures in 2016 caused by corrosion and cracking of turbine blades.
Every metal except precious metals like gold and silver reacts with water. "We'd like to predict the specific reactions of metals and combinations of metals with water and what the products of those reactions are, by computational methods first as opposed to determining them experimentally," Keszler said.
Traditionally, when looking at metals dissolved in water, the chemical assumption has been that a metal dissolves to form a simple salt. However, that's not always what happens, Keszler noted.
In many cases, it initially dissolves to form a complex cluster that contains many metal atoms. In a news release of OSU, researchers say they can now predict the types of clusters that exist in solution, therefore furthering the understanding of metal dissolution from a computational point of view.
Studying aqueous metal oxide and hydroxide clusters from Group 13 elements - aluminum, gallium, indium and thallium - researchers coupled quantum mechanical calculations with a "group additivity" approach to create Pourbaix diagrams, the gold standard for describing dissolved metal species in water.
"Applying this new approach, we arrive at a quantitative evaluation of cluster stability as a function of pH and concentration," said study co-author Paul Ha-Yeon Cheong, associate professor of chemistry at OSU.
Understanding clusters is critical because of the role they play in chemical processes ranging from biomineralization to solution-deposition of thin films for electronics applications. And characterizing corrosion stems from being able to depict metals' stable phases in water.
"Most Pourbaix diagrams do not include these metal clusters and hence our understanding of metal dissolution and reaction with water has been lacking," said study co-author Kristin A. Persson, professor of materials science at UC Berkeley.
"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."