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.

RT @JalanMbeLab: Just published in @NanoLetters In close collaboration with Chris Bartel's group, We reveal growth mechanisms of rutile Ge….

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!.

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

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!

RT @yuxing_fei: 🚨 Preprint Alert 🚨. How to manage experiment workflows in an autonomous lab just like managing computational workflows?. We….

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!

RT @YanHelenZENG: Check out our latest work on Selective formation of metastable polymorphs in solid-state synthesis | Science Advances htt….

RT @cedergroup: Joining the A-Lab conversation:

Here's a video of the A-lab in action, courtesy of @BerkeleyLab

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!.

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 🤖 😃.

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.

Happy to be a part of this work! Check it out if you're interested in using neural networks to analyze data from XRD, NMR, or Raman spectroscopy 🔬.

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.

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 .

RT @jschuetzke: We present a synthetic dataset generator to benchmark machine learning models on spectroscopic data. Spoiler: No neural ne….

Happy to share our recent work in @ChemMater on automating phase identification for XRD spectra with a probabilistic CNN!. Thanks to @cedergroup @ChrisJBartel . Code: Paper:

Check out our review on autonomous experimentation for novel inorganic materials synthesis, now published in @MaterHoriz! . @cedergroup @ChrisJBartel @BerkeleyLab .