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Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning

Reiser, Patrick 1,2; Konrad, Manuel 2; Fediai, Artem 2; Léon, Salvador; Wenzel, Wolfgang 2; Friederich, Pascal ORCID iD icon 1,2
1 Institut für Theoretische Informatik (ITI), Karlsruher Institut für Technologie (KIT)
2 Institut für Nanotechnologie (INT), Karlsruher Institut für Technologie (KIT)

Abstract:
Organic semiconductors are indispensable for today’s display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000133687
Veröffentlicht am 07.06.2021
Originalveröffentlichung
DOI: 10.1021/acs.jctc.1c00191
Scopus
Zitationen: 5
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Nanotechnologie (INT)
Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1549-9618, 1549-9626
KITopen-ID: 1000133687
HGF-Programm 43.31.01 (POF IV, LK 01) Multifunctionality Molecular Design & Material Architecture
Erschienen in Journal of chemical theory and computation
Verlag American Chemical Society (ACS)
Seiten acs.jctc.1c00191
Vorab online veröffentlicht am 04.05.2021
Nachgewiesen in Dimensions
Web of Science
Scopus
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