Methods and apparatuses for identifying defective electrical connections, and methods for generating a trained computational model

A method of generating a trained computational model for identifying defective electrical connections of a substrate, comprising:

• charging a first surface contact by directing an electron beam on the first surface contact;
• detecting a secondary electron signal as a function of time during the charging of the first surface contact;
• determining associated defect information about a first electrical connection that extends from the first surface contact;
• providing a first training data set comprising input data that includes or is based on the secondary electron signal and the associated defect information;
• and
• generating the trained computational model by training a computational model with the first training data set and with a plurality of further training data sets provided analogously for a plurality of further surface contacts having a respective electrical connection extending therefrom.

An apparatus for identifying defective electrical connections of a substrate, comprising:

• a vacuum chamber that houses a stage for placement of the substrate;
• an electron source configured to generate an electron beam;
• a scan deflector for directing the electron beam on a first surface contact for charging the first surface contact;
• an electron detector configured to detect a first secondary electron signal as a function of time during the charging of the first surface contact;
• and a data processing unit with a memory storing a trained computational model that is configured to receive input data comprising or being based on the first secondary electron signal and to provide defect information about a first electrical connection that extends from the first surface contact as an output.