Synthetic accessibility and stability rules of NASICONs

Yan Wang,Bin Ouyang,Gerbrand Ceder,Valentina Lacivita,Tanjin He,Haegyeom Kim,Haoyan Huo,Christopher J Bartel

doi:10.1038/s41467-021-26006-3

Abstract

In this paper we develop the stability rules for NASICON-structured materials, as an example of compounds with complex bond topology and composition. By first-principles high-throughput computation of 3881 potential NASICON phases, we have developed guiding stability rules of NASICON and validated the ab initio predictive capability through the synthesis of six attempted materials, five of which were successful. A simple two-dimensional descriptor for predicting NASICON stability was extracted with sure independence screening and machine learned ranking, which classifies NASICON phases in terms of their synthetic accessibility. This machine-learned tolerance factor is based on the Na content, elemental radii and electronegativities, and the Madelung energy and can offer reasonable accuracy for separating stable and unstable NASICONs. This work will not only provide tools to understand the synthetic accessibility of NASICON-type materials, but also demonstrates an efficient paradigm for discovering new materials with complicated composition and atomic structure.

Highlights

In this paper we develop the stability rules for NASICON-structured materials, as an example of compounds with complex bond topology and composition
To further narrow down the target for experimental validation, we focused on the Na3-NASICONs with mixed SiO4 and PO4 polyanions because such NASICON compositions are 1) more likely to be superionic conductors[46] and 2) more challenging to synthesize as they have both high Na content and mix polyanions (Fig. 2b, Table 1) which makes them good candidates to test the accuracy of our prediction
While simple modifications to a basic compound are prevalent in the literature, as is the case for NASICONs35,46,58,59, there is a lack of thorough understanding of the stability rules to help one navigate through the unexplored chemical space

Summary

Introduction

In this paper we develop the stability rules for NASICON-structured materials, as an example of compounds with complex bond topology and composition. A simple two-dimensional descriptor for predicting NASICON stability was extracted with sure independence screening and machine learned ranking, which classifies NASICON phases in terms of their synthetic accessibility This machine-learned tolerance factor is based on the Na content, elemental radii and electronegativities, and the Madelung energy and can offer reasonable accuracy for separating stable and unstable NASICONs. This work will provide tools to understand the synthetic accessibility of NASICON-type materials, and demonstrates an efficient paradigm for discovering new materials with complicated composition and atomic structure. To enable the prediction of stability from basic physical properties, we combined Sure Independence Screening (SIS)[40,41,42] and machine-learned ranking (MLR)[43,44] to identify the best 2D descriptors that can separate NASICONs that are likely to be synthesized features, t1 1⁄4

Methods

Results

Conclusion