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Document type:
Zeitschriftenaufsatz 
Author(s):
Lederer, J.; Kaiser, W.; Mattoni, A.; Gagliardi, A. 
Title:
Machine Learning–Based Charge Transport Computation for Pentacene 
Abstract:
Insight into the relation between morphology and transport properties of organic semiconductors can be gained using multiscale simulations. Since computing electronic properties, such as the intermolecular transfer integral, using quantum chemical (QC) methods requires a high computational cost, existing models assume several approximations. A machine learning (ML)–based multiscale approach is presented that allows to simulate charge transport in organic semiconductors considering the static dis...    »
 
Keywords:
charge transport machine learning multiscale approach organic semiconductors pentacene 
Journal title:
Advanced Theory and Simulations, Volume2, Issue2 February 2019 1800136 2019-02 
Year:
2019 
Year / month:
2019-02 
Quarter:
2. Quartal 
Month:
Feb 
Pages contribution:
1-11 
Language:
en 
Publisher:
Wiley Online Library