Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design

TL;DR

This paper reviews recent advances in inverse quantum approaches for chemical compound design, emphasizing heuristics, human intuition, and uncertainty quantification to enhance predictive accuracy and efficiency.

Contribution

It highlights the integration of heuristics and uncertainty quantification in inverse quantum methods for improved compound and catalyst design.

Findings

Heuristic rules are vital for rational compound design.

Uncertainty quantification enhances the reliability of computational predictions.

Recent developments improve the efficiency of exploring chemical space.

Abstract

The goal of inverse (quantum) approaches is to devise methods and approaches capable of efficiently searching chemical space in such a way that the design of novel materials and compounds with specific properties is as direct and efficient as possible. Here, we review the current state of the field with a focus on the most recent developments. We discuss the importance of heuristic rules and human intuition for rational compound design. Moreover, we elaborate on options for reliable uncertainty quantification for computational results, which is crucial for a truly predictive application of any in silico method.