AI trained on photos of salt ‘stains’ can predict their chemical composition
Imaging could become a simple way to identify inorganic salt crystals on other planets
When salt solutions evaporate, deposits of intricate and often beautiful crystallisation patterns are formed which may seem random and unpredictable. But now a machine learning technique has shown how images of such patterns from aqueous inorganic salt deposits can be used to predict their chemical composition. The approach could find various uses, from space exploration to deposit-identifying smartphone apps.
‘The processes that form deposit patterns during drop drying are very complicated and computing the diverse stain patterns from just the crystallising salt type is challenging, perhaps impossible,’ says Oliver Steinbock, whose lab conducted the work at Florida State University, US. ‘We looked at this problem in the opposite direction and asked whether it is possible to find the composition solely from a photo of the drop stain.’