L2M – Printable electronic material evaluation using automated experimentation platform

Innovation in domains such as organic electronic materials is driven by experimental methods that are generally limited by the speed of human intervention in all the steps of the iterative R&D cycle. The emergence of AI tools and automated systems can now help to disrupt this paradigm by empowering the researcher to efficiently leverage their domain expertise while automating the repetitive high-accuracy tasks to reduce human error and increase R&D speed. To this end, our team has been developing an AI-driven automated experimentation platform to evaluate emerging materials in the field of printed electronics with the aim of accelerating the lab-to-market timeline while minimizing raw material wastage through optimal processing. The project proposed here is to assess the commercial viability of such an automated platform and understanding its potential impact on stakeholders across industry and academia. Such an approach is expected to provide valuable insights regarding how potential clients view our innovation from an unbiased perspective which will help us make improvements in our business hypothesis.

Faculty Supervisor:

Konrad Walus

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program: