The Predictive Power of Chemical Bonding Analysis in Materials: a Perspective on Optoelectronic Properties

TL;DR

This paper reviews how chemical bonding analysis can predict and explain the optoelectronic properties of materials, especially metal halide perovskites and chalcohalides, highlighting its evolving models and future potential.

Contribution

It provides a comprehensive perspective on the role of chemical bonding analysis in understanding and predicting optoelectronic material properties, emphasizing recent advances and future directions.

Findings

Chemical bonding features influence optoelectronic properties.

Models predict effects of lone pairs and antibonding states.

Chemical bonding analysis complements machine learning approaches.

Abstract

Chemical bonding governs how atoms interact to form compounds, thereby determining their physicochemical properties. Despite being an elusive concept, chemical bonding has led to the development of models and tools to explain and predict the behavior of chemical species. This perspective addresses the adoption of chemical bonding analysis to the study of optoelectronic materials, emphasizing the im-portance of its predictive aspect. After reviewing the evolution of chemical bonding models from the first Lewis formulation to the present day, the perspective discusses material classes and chemical bonding phenomena most relevant for light harvesting and emission. We delve into metal halide perovskites and structurally related materials, given their central role in optoelectronic research. Various aspects of chemical bonding in these materials are surveyed, from the structure-property relationship to the rationalization of their electronic properties through molecular orbital diagrams. Two chemical bonding features are particularly important for optoelectronic materials: the ns2 lone pairs of the cations typically found in these materials (e.g. Pb, Sb, Bi) and the antibonding nature of valence and/or conduction bands. We discuss in depth the models to predict the implications of these two phenomena on optoelectronic properties. We also explore chalcohal-ides, a class of materials whose optoelectronic properties are recently emerging. From the chemical bonding perspective, these materials display intriguing phenomena due to the interplay of various types of chemical bonds. Finally, we discuss our vision on the role of chemical bonding analysis in the future of materials science, including synergies and antitheses with machine learning.