Towards Predictive Synthesis of Inorganic Materials Using Network Science

Alex Aziz,Javier Carrasco

doi:10.3389/fchem.2021.798838

Abstract

Accelerating materials discovery is the cornerstone of modern technological competitiveness. Yet, the inorganic synthesis of new compounds is often an important bottleneck in this quest. Well-established quantum chemistry and experimental synthesis methods combined with consolidated network science approaches might provide revolutionary knowledge to tackle this challenge. Recent pioneering studies in this direction have shown that the topological analysis of material networks hold great potential to effectively explore the synthesizability of inorganic compounds. In this Perspective we discuss the most exciting work in this area, in particular emerging new physicochemical insights and general concepts on how network science can significantly help reduce the timescales required to discover new materials and find synthetic routes for their fabrication. We also provide a perspective on outstanding problems, challenges and open questions.

Highlights

Advanced materials are key enablers across many industries aimed at addressing the global challenges of economic security, renewable and sustainable energy, and human welfare
In this perspective we focus on a strategy based on the application of network science (Barabási, 2016) that is starting to gain momentum, using the power of network-based representations and topological analysis to examine solid-state chemical reactivity for materials discovery, a graph based approach to mapping the thermodynamic relationships between different materials
Advances in network models complemented with the recent explosion of materials databases presents an opportunity to develop a new pioneering research area in materials discovery and synthesis

Summary

INTRODUCTION

Advanced materials are key enablers across many industries aimed at addressing the global challenges of economic security, renewable and sustainable energy, and human welfare. In a computational approach the consideration of both thermodynamics and kinetics along reaction pathways could target the synthesis of any hypothetical material with properties of interest, but leads to the exploration of large chemical spaces and requires the use of sophisticated and computationally demanding methods. In this perspective we focus on a strategy based on the application of network science (Barabási, 2016) that is starting to gain momentum, using the power of network-based representations and topological analysis to examine solid-state chemical reactivity for materials discovery, a graph based approach to mapping the thermodynamic relationships between different materials. The identification of possible synthesis routes would help experimentalists reduce the number of reactions pathways to consider even if the network failed to predict the optimal reaction pathway

DISCUSSION

DATA AVAILABILITY STATEMENT