A new AI-controlled robotic probe developed at the Massachusetts Institute of Technology (MIT) is set to automate and significantly expedite the process of measuring the properties of novel materials, particularly those used in solar panels.

Previously, determining key characteristics such as photoconductivity necessitated numerous laborious manual measurements involving physical contact. This process considerably slowed down research due to the unique and heterogeneous nature of each sample.

The newly developed system integrates material scientists' expertise into a machine learning model, enabling the robot to autonomously identify the most informative points on a sample for measurement. The platform employs an integrated camera and computer vision to analyze perovskite samples, while a self-monitoring neural network selects optimal contact points without requiring prior data training. An optimized path-planning algorithm ensures rapid movement of the probe.

During testing, the robot conducted over 125 unique measurements per hour, demonstrating substantially higher speed and reliability compared to previous methods. This breakthrough is intended to accelerate the development of more efficient solar panels and other electronic devices.

ORIENT