On a Database of Simulated TEM Images for In(Ga)As/GaAs Quantum Dots with Various Shape

Abstract

We present a database of simulated transmission electron microscopy (TEM) images for In(Ga)As quantum dots (QDs) embedded in bulk-like GaAs samples. The database contains series of TEM images for QDs with various shapes, e.g. pyramidal and lens-shaped, depending on the size and indium concentration as well as on the excitation conditions of the electron beam. This database is a key element of a novel concept for model-based geometry reconstruction (MBGR) of semiconductor QDs from TEM imaging and can be used to establish a statistical procedure for the estimation of QD properties and classification of QD types based on machine learning techniques.