New paper out in @ACSPublications introducing some topological descriptors of electron density for inorganic materials! We hope these can supplement existing descriptors like Bader charges and serve as compact inputs for machine learning
https://t.co/1QvnaFoThg
Some new work from Shilong Wang in the @cedergroup on a method for efficient and acid-free extraction of Li from spodumene, a common mineral used in battery manufacturing - happy to be a part of this!
https://t.co/HHHiI8U8G9
Our latest work on understanding solid-state synthesis is out now in @ScienceAdvances where we use in-situ XRD to show that initial reaction products can (*sometimes*) be predicted using DFT-computed thermochemical data! https://t.co/vdMrHO4E3D
And this proposed threshold was calibrated using 37 different reaction pathways targeting alkali metal oxides - more work is needed to confirm how this might vary in different chemistries!
The caveat here is that reliable predictions can only be made when the driving force to form one product is much larger (we propose a threshold of ~60 meV/atom) than any other competing driving forces
🚨 Preprint Alert 🚨
How to manage experiment workflows in an autonomous lab just like managing computational workflows?
We proposed a general framework to manage devices and experiments in the lab, with human-in-the-loop feature built in.
https://t.co/Y9WWMNxDHu
New perspective out in @ACSEnergyLett where @ChrisJBartel and I share our thoughts on how computations have and will continue to play a role in guiding the synthesis of battery materials. Check it out! https://t.co/5zpyOd56VS
Check out our latest work on Selective formation of metastable polymorphs in solid-state synthesis | Science Advances https://t.co/W4dGA3yUVr
We introduce a framework that uses both reaction energy and surface energy for effective polymorph selection.
@NJSzymanski@cedergroup
Excited to share our work in @Nature on the A-Lab, an AI-driven robotic platform that automates materials synthesis. It discovered 41 new compounds in 17 days of closed-loop experiments! Thanks to @cedergroup and @YanHelenZENG for leading this effort!
https://t.co/GLc8cHhoYh
@charlesxjyang@NatureComms Yep, these were all done manually by Pragnay, our very ambitious undergrad. More work on integrating this algorithm with automated experiments will be coming soon!
Our method to automate the optimization of solid-state synthesis is out now in @NatureComms! It uses DFT data but also learns from experiments to find the best precursors for a given material. We hope this can help guide future autonomous platforms 🤖 😃
https://t.co/T9CVT3Q8jt
Short-range order plays an important role in the performance of DRX cathodes 🔋 check out our latest work in @ChemMater where we show how pair distribution function data can be used to study this property!
Thanks to @Bin_Ouyang_CMS and @ChrisJBartel
https://t.co/JsSZdtd2cs
Proud to present our recent work on the evaluation of neural network architectures for classifying spectroscopic data. The article is available in @Nature_NPJ.
https://t.co/fzpvUH8iet
Excited to share our recent work in @Nature_NPJ, where we show that machine learning can be used to "drive" XRD measurements and identify phases in real time!
Thanks to @ChrisJBartel @YanHelenZENG@delmouha
https://t.co/eSb8ZgDC6l
For those interested in synthesis science and DRX cathodes, check out our latest article in @ChemMater showing several factors that govern fluorination.
Big thanks to all the great collaborators! @YanHelenZENG@cedergroup @ChrisJBartel @ClementGroupSB
https://t.co/qWqc1vgZfb