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  • Postdoc in engineering research - we’re using machine learning to predict chemical properties relevant to combustion, speeding up the discovery of cleaner liquid fuels as we transition away from fossil fuels!

    • interesting. how does that process work?

      • TL;DR, I throw a bunch of molecules at a pile of linear algebra, and hope predicted values line up with known experimental values; then I use the pile of linear algebra on novel molecules.

        There's a bit more to it than that, like how to represent molecules in a computer-readable format, generating additional input variables (molecular characteristics), input variable down-selection and/or dimensionality reduction, the specific ML models we use (feed-forward MLPs and graph convolution nets), and how to interpret results as they relate back to combustion.

        From a broad perspective, our work is just a small part of a larger push from the Department of Energy to find economically-viable alternative liquid fuels. ML speeds up the process of screening candidate molecules, for example those found in bio-oil resulting from pyrolizing and catalytically-upgrading lignocellulosic biomass or other renewable sources. Our colleagues don't have to synthesize large samples of many molecules just to test their properties and determine how they will behave in existing engines (a very costly and time-consuming process), instead we predict the properties and behaviors to highlight viable candidates so our colleagues can focus on analyzing those.

        These papers (1, 2, 3) best outline the procedures and motivations for this work. PM me if you can't get access and I'll send you them!

  • I agree with the NDA comment, it's difficult to give a lot of the cool details without breaking NDA.

    I feel pretty safe in saying that I'm working to come up with new ways to melt glass for our process in order to be more flexible about what compositions we're able to use. That's a pretty fun one for me.

  • I'm working on open source session replay tool (skipping the name not to promote it explicitly, but its quite easy to guess since our niche has not too many fully OS companies) as R&D/js library maintainer; at the same time I'm making my own lemmy app :)

    Very fun and quite the opposite experience (going in deep with browser specs and API vs thinking about mobile UI and features)

53 comments