Researchers at the Oak Ridge National Laboratory in the US have developed a new technique for high speed voltage measurements at the atomic level using machine learning. The technique has reportedly been used for mapping surface voltage dynamics of a perovskite solar cell for the first time.
Atomic force microscopy can usually investigate slow or static material structures and functions. In AFM, a rastering probe maps a material's surface and captures physical and chemical properties but the probe is slow to respond to what it detects. Instead, the ORNL team created a fast free force recovery technique that uses advanced machine learning algorithms to analyze instantaneous tip motion to produce high-resolution images 3,500 times faster than standard AFM detection methods.
