(192k) Leveraging Thermodynamic Calculations Towards Predictive Solid-State Materials Synthesis | AIChE

(192k) Leveraging Thermodynamic Calculations Towards Predictive Solid-State Materials Synthesis

Authors 

Bartel, C. J. - Presenter, University of California-Berkeley
Miura, A., Hokkaido University
Sun, W., University of Michigan
Ceder, G., Massachusetts Institute of Technology
Computational approaches, such as density functional theory, play a larger and larger role in materials design with each passing year. However, a major gap in the existing computational pipeline is the ability to predict synthesizability or synthesis pathways, precluding truly theory-driven discovery of novel materials. Solid-state synthesis is the bedrock of inorganic materials chemistry, yet this approach is typically a “black box”, where the only observation is what formed from the precursor materials after a reaction at a predetermined set of conditions (typically chosen by intuition). In order to rationally synthesize new inorganic materials, it is critical to not only understand but predict what intermediates form and how they influence the reaction towards the synthesized phase(s). In this talk, I’ll provide two examples [1,2] where we use readily computable thermodynamic quantities as inputs to conceptual models to understand phase evolution during synthesis. The models we develop are validated through experimental synthesis experiments along with in situ X-ray diffraction and in situ electron microscopy measurements. Finally, I will discuss the limitations of our models and what steps are needed to truly reach a paradigm of predictive and prescriptive materials synthesis.

[1] A. Miura, H. Ito, C. Bartel, W. Sun, N.C. Rosero-Navarro, K. Tadanaga, H. Nakata, K. Maeda, G. Ceder, Materials Horizons, 2020, 7, 1310-1316, DOI: 10.1039/C9MH01999E

[2] A. Miura^, C. Bartel^, Y. Goto, Y. Mizuguchi, C. Moriyoshi, Y. Kuroiwa, Y. Wang, T. Yaguchi, M. Shirai, M. Nagao, N.C. Rosero-Navarro, K. Tadanaga, G. Ceder, W. Sun, Advanced Materials, 2021, Accepted, DOI: 10.1002/adma.202100312