Materials Analytics with Jupyter and Galyleo

Thomas Edison was a materials scientist.

He didn’t invent the electric light – that had been done over 75 years before Edison by Humphry Davy.  What Edison did do was invent the first electric light with a lifetime of more than a few minutes.  And the secret to that lightbulb was a filament – a thin thread – that would glow when electric current was passed through it and wouldn’t burn up or break for a long time.

Coming up with that filament was extremely challenging – Edison tried over 6,000 different materials until he finally found one that burned for 17 hours.

Coreshell Technologies makes materials that make lithium-ion batteries last much longer and charge much better.  Lithium-ion batteries stop holding charge because there are chemical reactions that occur within the battery that consume lithium over time. Coreshell’s technology coats electrode surfaces within the battery with novel, protective thin films that prevent these reactions from occurring, and the end result is a battery that doesn’t lose charge as rapidly.  Using our technology, every battery from your watch to your cellphone to your car to your Tesla wall will last much longer and possess higher energy density.

And, just as Edison had to run experiment after experiment to find a filament that wouldn’t break or burn, Coreshell has to run experiments to find the right coating  materials that will give us a battery that will last a long time and possess high energy density.

But Coreshell has a big advantage over Edison. We have information technology and data analytics, and that makes our hunt for a long-lasting battery much faster and more rigorous.  Thanks to engageLively’s Galyleo platform, we can rapidly organize, analyze, and visualize the data from thousands of experiments to rapidly isolate the most promising candidates for the materials that will make the batteries of the future.

And we didn’t have to do a thing. Thanks to engageLively’s Galyleo technology, we didn’t have to set up a database; we didn’t have to hook up analytics to a database; we didn’t have to do the plumbing to build a web dashboard. We just signed up for enterprise Galyleo, and we were able to easily convert our testing spreadsheets into a database, easily write Jupyter Notebooks and store and evaluate them in the Cloud, and build the dashboards we need using drag-and-drop operations. Thanks to Galyleo, we’re able to turn our data into insights, and that lets us build the batteries of the future much better, faster, and cheaper.

In a few years, your cellphone and car batteries will last a lot longer – thanks to Coreshell, and thanks to Galyleo.