Artificially Intelligent Manufacturing of Flexible Electronics

Advanced materials and manufacturing are important pillars and drivers of today’s economy. They have made consumer devices like TVs and computers ubiquitous by enabling cheap mass production of reliable products, and enabled industrial applications on a scale not seen before. However, designing new materials is a slow and laborious process, requiring significant investments in capital and labor. Recent advances in artificial intelligence allow to improve and speed up this process. In particular, machine learning techniques can replace expensive and time-consuming laboratory processes and computational simulations to quickly and reliably predict how to create materials with desired properties and how materials will behave in specific circumstances. So-called surrogate models learn how properties of materials and experimental parameters relate to experimental results. We propose to apply these techniques to materials engineering and manufacturing, to reduce cost and improve performance. In this work we propose to merge synergistic expertise in materials development and computer science for the development of powerful methods to design and model the behavior of advanced materials and manufacture of advanced devices.

This is a mature technology (TRL 7+) — the realistic path in is usually NASA's Technology Transfer Program: licensing an existing NASA patent, or a Space Act Agreement to use NASA facilities/expertise directly. NASA also runs a startup licensing program with no upfront fee for companies formed to commercialize a specific NASA technology.

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