ATOM-P: Atomic Tools for Optimizing Materials via Pixels
ATOM-P: ATOM-P explores how advanced electron microscopy reveals the atomic structure of materials for microelectronics and quantum technologies. Students develop Python-based workflows for image processing and data analysis to extract quantitative information from atomic-resolution microscopy data. The goal is to translate images into measurable metrics that connect materials quality to device performance.
Mentors:
Description:
This team explores how atomic-scale electron microscopy can be used to understand the structure and behavior of materials integrated into microelectronic devices and quantum systems. Students work with high-resolution datasets, particularly from scanning and transmission electron microscopy (STEM/TEM), to identify atomic columns, interfaces, defects, and structural variations in complex heterostructures.
The team develops computational workflows using Python-based coding, image processing, data analysis, and simulation to denoise images, extract quantitative measurements, and connect microscopy data to materials properties. Projects may include automated image analysis, organization of large microscopy datasets, benchmarking of filtering and denoising methods, simulation-assisted interpretation of atomic-resolution images, and visualization pipelines for semiconductor interfaces.
Through this work, students gain experience at the intersection of semiconductors, electron microscopy, computational modeling, data science, and research software development.
Relevant Technologies:
- Electron microscopy
- Computational image analysis
- Semiconductor materials characterization
- Atomic-scale metrology
Pre-requisite knowledge/skills:
- Students are expected to demonstrate enthusiasm for research, and a strong commitment to collaborative teamwork. Intermediate programming experience is recommended, preferably in Python, as team activities will involve image processing, data analysis, and simulation-based workflows. Foundational knowledge in physics, waves, optics, or electromagnetism is beneficial, particularly as it relates to electron microscopy concepts such as electron–matter interactions, diffraction, image formation, and contrast mechanisms. Prior experience in electron microscopy, semiconductor materials, or materials characterization is not required; however, students should be willing to develop these skills through guided readings and tutorials. Students interested in joining the team are encouraged to provide a brief statement describing their programming background, relevant coursework, research interests, and motivation for participating.