Mulholland: Citrine founders used AI to invent new thermoelectric materials
Greg Mulholland · How AI is rapidly advancing new materials for clean energy · Jan 23, 2024 · at 2:07
Greg Mulholland is the CEO and co-founder of Citrine Informatics, an enterprise software platform applying AI to materials development.
0:00 / 0:07exact quote · 7.8s
720p mp4 · rendered on demand · StarZero watermark
“We actually invented a new class of thermoelectric materials using sort of some combination of machine learning, artificial intelligence, depending on how you define these things.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Greg Mulholland
Mulholland: Room-temperature superconductors will require new physics
“My prediction is that it will require at least a variant on known physics, if not entirely new physics, to make happen, just because that's sort of the nature of those massive breakthroughs, especially, I mean, room temperature superconductor is, A guaranteed …”
Mulholland: Energy transition will fail without accelerated materials innovation
“Candidly, I don't think we get there by a long shot. Even with new materials, it's a heavy lift because there are those cultural and cost and systemic issues we need to overcome.”
Mulholland: China pushes LFP batteries while US relies on high-risk cobalt chemistries
“In China, there's a big push for lithium iron phosphate. In the U.S., we have, you know, sort of standard lithium ion batteries that have a lot of nickel, manganese, and cobalt in the materials, and those things are hard to source, and rising in cost, and some…”
Mulholland: High lab experiment costs prevent large data volumes in materials
“One of the things that we don't have in the materials industry is huge volumes of data because everything costs money, right? You know, there is no free experiment.”
Mulholland: Scientific AI gains most value from unpublished negative experiment results
“Unfortunately, from a scientific standpoint, the most valuable thing to AI is the two examples. But you know that those scientists did not just do two experiments. You know that those scientists did months and months and months of work and refinement and faile…”