Accelerate & optimize your
RHEED analysis.

Automatically quantify RHEED patterns and generate materials structure datasets with zero engineering effort.

Use it yourself within 24 hours.

AtomCloud provides a workflow that analyzes RHEED patterns from images and videos by quantifying the relative position, shape, and intensity of scattering features, providing a fingerprint of the material.

Image of a RHEED pattern
RHEED fingerprint

Benefits of RHEED Fingerprints

Detects subtle scattering features without introducing operator subjectivity.

Quantified scattering features improves the rigor, consistency, and speed of operator analysis.

Quantified scattering features can be stored to build a repository of analyzable data.

RHEED fingerprints can be compared to assess the quantitative differences between patterns and visualize differences in scattering intensity.

RHEED fingerprint comparisonRHEED fingerprint difference

Benefits of Fingerprint Comparison

Understand in a glance what changed between two RHEED patterns, and quantify those changes.

Infer characteristics of the material's state based on the quantified changes in RHEED patterns.

RHEED videos are analyzed by extracting fingerprints from each pattern that arises over the course of the video and plotting the pattern's quantified properties in a graph against time.

RHEED video analysis process

Benefits of Fingerprint Timeseries

Analyze every unique pattern from a RHEED growth video to understand with granularity how the material changes during its growth.

Correlate pattern and material properties to process parameters from instrument logs to identify actionable relationships.

The typical approach of analyzing RHEED patterns where operators visually inspect patterns and draw conclusions via intuition is challenging and time-consuming.

A solely visual inspection can miss subtle feature changes, introduces bias and inconsistencies, and can't be scaled easily.

By highlighting pattern features visually and quantifying their properties, AtomCloud helps operators draw conclusions faster and more consistently, and helps organizations build a reusable repository of their materials data.

Upload RHEED images and videos to AtomCloud via the web platform.

AtomCloud RHEED file upload

Uploaded files are added to your data catalogue and AtomCloud begins analyzing them automatically.

AtomCloud RHEED file upload

Once analyzed, results can be viewed using the data catalogue. If the item is an image of a RHEED pattern, its fingerprint is shown.

AtomCloud RHEED file upload

If the item is a video of a RHEED growth, the fingerprints over the growth are extracted and plotted as a timeseries.

AtomCloud RHEED video analysis

The fingerprint of a specific pattern in the video can also be viewed, similar to if an image of it was uploaded directly.

AtomCloud RHEED file upload

AtomCloud helps operators extract insights from RHEED patterns across broad material systems.

CoSi material system RHEED pattern image

Detecting Kinetic Transitions

A video of a CoSi material system with complex patterns, low-contrast, and long duration is difficult to analyze by eye.AtomCloud's RHEED analysis workflow was able to automatically detect a subtle but validated pattern change
CoSi material system RHEED pattern image

Analysis Technology

Analyzing RHEED patterns by eye is time-consuming and prone to errors.AtomCloud uses unsupervised learning algorithms and materials science-specifc clustering techniques to automatically analyze RHEED patterns.
CoSi material system RHEED pattern image

Analyzing Rotating Growths

RHEED videos of rotating growths are difficult to analyze.AtomCloud's RHEED analysis workflow accounts for rotation, unlocking rotating RHEED videos as a source of insight.

Try AtomCloud yourself.

Book a demo to see how AtomCloud can accelerate your RHEED analysis.

Response within 24 hours.