Methods for an Electron Emission Digital Twin

TL;DR

This paper introduces MEEDiT, a digital twin framework that combines advanced electron emission models with experimental data to enable real-time, resource-efficient characterization of electron emitters, bridging experimental measurements with hidden physical parameters.

Contribution

The paper presents a novel digital twin approach for electron emitters that integrates models and data, providing real-time insights into physical quantities during operation.

Findings

MEEDiT accurately characterizes silicon electron emitters.

It bridges experimental data with hidden physical parameters.

Enables real-time, resource-efficient analysis.

Abstract

The effective design and operation of electron emitters is the core of critical technologies such as high-resolution electron imaging and spectroscopy or X-ray production for medical imaging. Despite 100 years of theoretical development in thermo- and field-electron emission models, the analysis of experimental data and design of electron emitters remains an art more than a science. This is due to the many processes that are involved in electron emission, which result in an extremely complex phenomenon. Here we describe and develop the Methods for an Electron Emission Digital Twin (MEEDiT), which integrates state-of-the-art thermo-field electron emission models and experimental data characterisation. By applying MEEDiT to silicon electron emitters, we demonstrate an approach that bridges the gap between simple experimental measurements and 'hidden' physical quantities like temperature and field enhancement. MEEDiT provides the physical consistency of a 3D simulation with the speed of a neural network, enabling resource-effective, real-time characterization and the extraction of critical data that is otherwise inaccessible during operation.