Simulating TEM and STEM images is an essential tool for understanding experiments at the nano and atomic scales. These simulations bridge the gap between theoretical models and experimental observations, offering deeper insights into materials’ structure and behavior. Through this guide, we hope we have demystified the process of performing these simulations, providing practical examples and a clear framework for using open-source tools like abTEM.

By standardizing approaches and integrating these tools with broader computational frameworks, microscopy experiments can be more tightly linked to simulations, enabling researchers to tackle increasingly complex problems. We have aimed to deliver a concise and accessible introduction to the key mathematical, physical, and computational principles of TEM and STEM simulations. While the examples here are geared toward learners and newcomers, the methods can address some of the most advanced challenges in materials science.

Looking ahead, improvements in computational power, algorithms, and experimental instrumentation will continue to enhance the fidelity and speed of TEM simulations. Wider adoption of open-source tools and emerging machine learning methods will likely make these techniques even more accessible. These advancements could streamline workflows, automate routine tasks, and unlock new possibilities for real-time simulation and data analysis.

We hope this guide has given readers the tools and confidence to incorporate simulations into their work. By building on these foundations, future research can expand microscopy’s capabilities, from characterizing beam-sensitive materials to solving previously intractable challenges in in situ and other complex experiments. The integration of computational and experimental approaches is essential, and we look forward to seeing how these tools evolve to shape the field. We also hope to inspire future researchers to develop their own simulation methods and share them with the microscopy community as open source tools.