Δ-machine learning of triplet excitation energies in organic chromophores

Physical Chemistry Chemical Physics 2026

View at publisher
Authors: ARKA PRATIM Pratim GHOSH, Koyal Roy, Kalishankar Bhattacharyya
DOI: 10.1039/d6cp01296e
Cited by: 1
References: 46

Abstract

Here, we report a Δ-machine learning approach for predicting triplet excitation energies (T 1 ) of diverse organic chromophores by combining high quality reference data with quantum chemical calculations.

Fields of Study & Subjects

Machine Learning in Materials Science Synthesis and Properties of Aromatic Compounds Luminescence and Fluorescent Materials

Publication details

Journal / source
Physical Chemistry Chemical Physics
Publisher
Royal Society of Chemistry (RSC)
Volume
28
Issue
19
Pages
11579–11586
Publication date
1 January 2026
Language
EN