Abstract: The present disclosure provides electron source devices, electron source assemblies, and/or methods for generating electrons. The generated electrons can be used to facilitate spectroscopy, such as mass spectrometry, including mass selection or ion mobility.

Abstract: Various techniques are provided for training a neural network to classify chemical spectra data, such as Ion Mobility Spectrometry data. Machine learning models are trained using a training dataset comprising labeled chemical spectra data. The training process tracks chemical classification-related metrics and other informative metrics as the training dataset is processed. The trained models are tested using a validation dataset of chemical spectra data to generate performance results. A model analysis engine extracts and analyzes the informative metrics and performance results, generates parameters for a modified training dataset and features to improve model performance, and generates corresponding instructions to generate a new training dataset. The process repeats in an iterative fashion to build a final training dataset and set of models of classifying one or more chemicals.