An artificial finger can identify different materials with more than 90 per cent accuracy by sensing their surface. The technology could be useful for automating robotic manufacturing tasks, such as sorting and quality control. Touch sensors that can gain information about surfaces, such as pressure or temperature, aren't new, but sensors that can recognise the type and roughness of surfaces are less common. Dan Luo at the Chinese Academy of Sciences's Beijing Institute of Nanoenergy and Nanosystems and his colleagues have developed a finger that can identify what a material is made from by using "triboelectric" sensors to test its ability to gain or lose electrons, and discern its roughness, without causing damage to it. When trialled on hundreds of samples of 12 substances such as wood, glass, plastic and silicon, and combined with a machine learning-based data analysis, the finger achieved an average accuracy of 96.8% and at least 90 per cent accuracy for all of the materials. The device consists of four small square sensors, each made of a different plastic polymer, chosen for their different electrical properties.