A new technique allowed researchers to observe how water is able to dissolve crystalline structures, such as the ones found in cement and stone.
The method proved to be excellent at predicting dissolution rates and could be used for a number of applications including "water quality and planning, environmental sustainability, corrosion resistance and cement construction," a Rice University news release reported.
"We need to gain a better understanding of dissolution mechanisms to better predict the fate of certain materials, both in nature and in man-made systems," lead investigator Andreas Lüttge, a professor of mineralogy at MARUM and professor emeritus and research professor in Earth science at Rice, said.
Lüttge's team specializes in boundary layers that naturally occur between minerals and fluid, the phenomenon can be observed in events such as raindrops falling on a stone sidewalk.
Researchers have been working to fully understand how water degrades rock, and at what rate. This study has gotten them one step closer.
The team conducted their studies on quartz, which is one of most common naturally-occurring elements on Earth. They created a computerized model of the reactions that occur in the boundary layer,
"The new model simulates the dissolution kinetics at the boundary layer with greater precision than earlier stochastic models operating at the same scale," lead author Inna Kurganskaya, a research associate in Earth science at Rice, said. "Existing simulations rely on rate constants assigned to a wide range of possible reactions, and as a result, the total material flux from the surface have an inherent variance range -- a plus or minus factor that is always there."
The team employed "cutting-edge instruments and from high-tech materials, including glass ceramics and nanomaterials," to make their finding. They also used an image technique dubbed "vertical scanning interferometry." They then scanned crystal and mineral surfaces to create topographical maps.
"We found that dissolution rates that were predicted using rate constants were sometimes off by as much as two orders of magnitude," Lüttge said.
The new technique could revolutionize a number of industries.
"Further work is needed to prove the broad utility of the method," Lüttge said. "In the next phase of research, we plan to test our simulations on larger systems and over longer periods."
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