Developed at KAUST (King Abdullah University of Science and Technology), machine learning differentiates the gases according to the way they induce slight temperature changes in the sensor as they interact with it. Smart electronic sensors have applications from medical diagnostics to the detection of industrial gas leaks. The challenge is to accurately detect the target gas among the complex mixture of chemicals typically found in the air, said Usman Yaqoob, a postdoc in the labs of Mohammad Younis, who led the research. "Existing sensing technologies still suffer from cross-sensitivity," Yaqoob said in a statement. On the hardware side is a heated strip of silicon called a microbeam resonator.