KIT | KIT-Bibliothek | Impressum | Datenschutz

Artificial Design of Organic Emitters via a Genetic Algorithm Enhanced by a Deep Neural Network

Nigam, AkshatKumar; Pollice, Robert; Friederich, Pascal ORCID iD icon 1,2; Aspuru-Guzik, Alán
1 Institut für Theoretische Informatik (ITI), Karlsruher Institut für Technologie (KIT)
2 Institut für Nanotechnologie (INT), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

The design of molecules requires multi-objective optimizations in high-dimensional chemical space with often conflicting target properties. To navigate this space, classical workflows rely on the domain knowledge and creativity of human experts, which can be the bottleneck in high-throughput approaches. Herein, we present an artificial molecular design workflow relying on a genetic algorithm and a deep neural network to find a new family of organic emitters with inverted singlet-triplet gaps and appreciable fluorescence rates. We combine high-throughput virtual screening and inverse design infused with domain knowledge and artificial intelligence to accelerate molecular generation significantly. This enabled us to explore more than 800,000 potential emitter molecules and find more than 10,000 candidates estimated to have inverted singlet-triplet gaps (INVEST) and appreciable fluorescence rates, many of which likely emit blue light. This class of molecules has the potential to realize a new generation of organic light-emitting diodes.


Volltext §
DOI: 10.5445/IR/1000165105
Veröffentlicht am 30.11.2023
Originalveröffentlichung
DOI: 10.26434/chemrxiv-2023-nrxtl
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Nanotechnologie (INT)
Institut für Theoretische Informatik (ITI)
Publikationstyp Forschungsbericht/Preprint
Publikationsjahr 2023
Sprache Englisch
Identifikator KITopen-ID: 1000165105
HGF-Programm 43.31.01 (POF IV, LK 01) Multifunctionality Molecular Design & Material Architecture
Verlag American Chemical Society (ACS)
Umfang 36 S.
Vorab online veröffentlicht am 03.08.2023
Nachgewiesen in Dimensions
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page