Sunday, October 16, 2022

Materials labs of the future + cost

The NSF Division of Materials Research has been soliciting input from the community about both the biggest outstanding problems in condensed matter and materials science, and the future of materials labs - what kind of infrastructure, training, etc. will be needed to address those big problems.  In thinking about this, I want to throw out a stretch idea.  

I think it would have transformative impact on materials research and workforce development if there were fabrication and characterization tools that offered great performance at far lower prices than currently possible.  I'd mentioned the idea of developing a super-cheap SEM a while ago. I definitely worry that we are approaching a funding situation where the separation between top universities and everyone else will continue to widen rapidly.  The model of a network of user facilities seems to be how things have been trending (e.g. go to Harvard and use their high-res TEM, if your institution can't afford one).  However, if we really want to move the needle on access and training for a large, highly diverse workforce, it would be incredible to find a way to bring more capabilities to the broadest sweep of universities.   Maybe it's worth thinking hard about what could be possible to radically reduce hardware costs for the suite of materials characterization techniques that would be most important.


3 comments:

  1. Anonymous5:36 PM

    Prof. Natelson, there is a startup focused on self contained smaller micro fabrication equipment called Inchfab. The idea is that you can cut a lot of the cost by focusing on smaller wafer sizes. Would this be relevant to what the NSF is going after? https://www.inchfab.com/contact

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  2. Anonymous8:15 PM

    The National Academy release a study today about DMREF. The report summarizes the DMREF structure in a diagram which at the center has three bubbles, computational physics

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  3. Anonymous8:20 PM

    Sorry, I pressed enter by mistake; computational tools, experimental tools and data science. The funny thing is that theoretical tools and mathematics was left out. Topological insulators we’re discovered with these tools and innovation in materials science continues to be powered by them (based on the Nature and Science publications).

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