Electron-vibrational renormalization in fullerenes through ab initio and machine learning methodsShow others and affiliations
2024 (English)In: Physical Chemistry, Chemical Physics - PCCP, ISSN 1463-9076, E-ISSN 1463-9084, Vol. 26, no 30, p. 20310-20324Article in journal (Refereed) Published
Abstract [en]
The effect of nuclear vibrations on the electronic eigenvalues and the HOMO-LUMO gap is known for several kinds of carbon-based materials, like diamond, diamondoids, carbon nanoclusters, carbon nanotubes and others, like hydrogen-terminated oligoynes and polyyne. However, it has not been widely analysed in another remarkable kind which presents both theoretical and technological interest: fullerenes. In this article we present the study of the HOMO, LUMO and gap renormalizations due to zero-point motion of a relatively large number (163) of fullerenes and fullerene derivatives. We have calculated this renormalization using density-functional theory with the frozen-phonon method, finding that it is non-negligible (above 0.1 eV) for systems with relevant technological applications in photovoltaics and that the strength of the renormalization increases with the size of the gap. In addition, we have applied machine learning methods for classification and regression of the renormalizations, finding that they can be approximately predicted using the output of a computationally cheap ground state calculation. Our conclusions are supported by recent research in other systems.
Place, publisher, year, edition, pages
Royal Society of Chemistry (RSC) , 2024. Vol. 26, no 30, p. 20310-20324
National Category
Physical Chemistry
Identifiers
URN: urn:nbn:se:kth:diva-366415DOI: 10.1039/d4cp00632aISI: 001272209400001PubMedID: 38984472Scopus ID: 2-s2.0-85198113294OAI: oai:DiVA.org:kth-366415DiVA, id: diva2:1982402
Note
QC 20250708
2025-07-082025-07-082025-07-08Bibliographically approved