aiLight: Accelerating the Development of a Sustainable Light Source through Physics-Informed Neural Networks

Research question

The light-emitting electrochemical cell (LEC) is an emerging thin-film technology. The emission efficiency of LECs has proven to be highly dependent on a p-n junction doping structure obtained by electrochemical doping during its initial operation, which in turn is directly determined by a large set of material parameters. These material parameters are often unknown, and their acquisition depends on multiple measurements and highly time-consuming tedious analyses. The aiLight project therefore aims to address the generic problem of high-throughput material parameter acquisition and specifically accelerate LEC development through a tuned and systematic utilization of machine learning techniques.

Sustainability aspects

LEC can be fabricated by energy- and material-efficient ambient-air printing and be free from critical raw materials. This sustainability opportunity distinguishes the LEC from incumbent emissive technologies, notably inorganic and organic light-emitting diodes.