# A Phenomenological Perturbation-like Approach for Prediction of Molecular Properties in Large Libraries of Polysubstituted Derivatives: Application to Molecular Solar Thermal Systems

## TL;DR

This paper introduces a new method to predict molecular properties efficiently, using a small number of calculations to guide the design of solar energy storage systems.

## Contribution

A novel phenomenological perturbation-like framework is introduced to predict molecular properties from small compound sets.

## Key findings

- The method successfully predicted the energy of 350 derivatives using data from only 5 or 50 compounds.
- The approach is applied to optimize molecular solar thermal systems for solar energy storage.
- The method enables low-cost exploration of large chemical libraries for practical applications.

## Abstract

The prediction of a specific chemical property across
a vast library
of derivatives represents a formidable challenge. Conventional computational
methodologies typically rely on brute-force calculations involving
the computation of the property of interest for the entire library
or a significant subset. In this study, we present a novel phenomenological
approach to address this challenge, employing a perturbation theory-like
framework to describe substituent effects. This proposed methodology
has the potential to forecast the molecular properties of millions
of compounds based on information derived from just a few hundred.
This method is applied to the design of molecular solar thermal (MOST)
systems, which are devices permitting harvesting solar energy and
storing it in a chemical form. The optimization of MOST performance
is a critical issue in practical applications of this technology,
so exploration of large libraries of derivatives at low computational
cost is an interesting approach to tackle the problem. To accomplish
this objective, we explore the functionalization of the norbornadiene/quadricyclane
(NBD/QC) system utilizing the proposed perturbational approach predicting
the
energy of 350 derivatives from small sets of 5 and 50 calculated compounds.