Dec 6, 2024
2:00pm - 2:15pm
Hynes, Level 3, Ballroom C
Lauren Walters1,Yuxing Fei2,Bernardus Rendy2,KyuJung Jun2,Mouhamad Diallo2,Xiaochen Yang2,Tara Mishra1,Matthew McDermott1,David Milsted1,Gerbrand Ceder2,1
Lawrence Berkeley National Laboratory1,University of California, Berkeley2
Lauren Walters1,Yuxing Fei2,Bernardus Rendy2,KyuJung Jun2,Mouhamad Diallo2,Xiaochen Yang2,Tara Mishra1,Matthew McDermott1,David Milsted1,Gerbrand Ceder2,1
Lawrence Berkeley National Laboratory1,University of California, Berkeley2
The discovery of tunable superionic conducting frameworks is necessary for the development of next generation solid state batteries. To this end, we present a computational-experimental materials exploration strategy leveraged to comprehensively reintroduce the sodium conducting framework, Na<sub>4</sub>TiP<sub>2</sub>O<sub>9</sub> (NTP). We utilize high-throughput computational screening to probe chemical and structural substitutions on the text-mined NTP parent structure. We validate (meta)stable NTP candidates through application of synthesis selection algorithms employed by an experimental autonomous laboratory. Our expansive data set of synthesis trials allow us to propose simple but powerful generalized synthesis methodology rules for Na<sub>x</sub>MP<sub>2</sub>O<sub>9. </sub>Finally, we highlight the structural, chemical, and conductivity characterization of realized compounds. Our work is a testament to the powerful interplay of data-driven computation and experimentation, particularly when applied to research on new superionic conduction frameworks for energy storage advancement.