Optimize advanced materials synthesis.
Accelerate commercialization.
Unlock innovation with an AI-native, materials science-specific workspace for all your characterization data.
Trusted by scientists
and engineers at
Introducing the AtomCloud.
Generate first-of-their-kind datasets for materials science with AI.
AtomCloud transforms data from nano-instruments into actionable insights
to help you make better, faster decisions in R&D and manufacturing.
Collect Data
As-is from all your instruments: images, videos, and logs, etc. No setup changes needed.
Upload to AtomCloud
Web platform available anywhere, anytime. Broad file format support - no fussing with converting.
Apply Analyses
Automated AI-powered workflows analyze your data scalably. Use the state of the art in a single click.
View Insights
Interactive images and charts to understand your data better and iterate faster. Exports easily to share or store.
Accessible, automated,
state of the art analysis.
Unlock faster validation
and shorter cycle times.
Unified Platform -
An AI-native workspace for the future of materials.
Extract information from files and other sources to build digital fingerprints of the processing environment, material properties, and experiment targets.
Integrate experimental information within a connected and flexible repository, ready for today's analysis and future workflows.
Collaborate seamlessly on raw and analyzed data across your organization by linking directly to interactive results and data exports.
Pattern Discovery -
Synthesize data across multiple data sources.
Efficient cross-data-stream pattern discovery enabled by a unified data model uncovers valuable insights.
Scalable automated analysis supports broad inquiry into data relationships and reduces operator bias.
Accelerate development by identifying patterns that reduce trials, improve synthesis control, and saves measurement runs.
Integrate Data Streams
Store and understand materials information acquired from any data source.
RHEED -
Enhanced insights delivered in seconds.
Detect important pattern changes automatically to quickly drill in on features of interest.
Quantify key properties of patterns to understand the underlying material changes rigorously.
Visualize quantified patterns through interactive images and charts, empowering operator intuition.
XPS -
Elemental analysis without manual peak fitting.
Extract atomic concentrations from spectra in one click without needing to apply laborious peak fitting procedures.
Compare analyzed XPS spectra of multiple samples interactively to understand differences.
Reanalyze spectra data easily by selecting atomic elements to focus on.
Instrument Logs -
Understand characterization data with context.
Parse processing history directly from instrument data.
Track actual environment data rather than relying on recipe notes.
Analyze processing conditions directly alongside characterization data for tighter process control.
Case Studies
AtomCloud accelerates time-to-insight for complex data across broad material systems.
The AI-driven platform for the
future of materials R&D.
Build physics-rich datasets for bottom-up materials manufacturing.
Accelerate R&D and manufacturing progress
Transfer insights between characterization techniques using feature correlation. Automated workflows scale materials validation and experiment iteration.
Unlock more insights from the same data
Apply state of the art materials-specific analyses with one click to empower domain expertise.
Build an analytical reference library
Generate machine-readable, physics-rich datasets from actual materials characterization. Easily compare multiple characterization results to leverage historical findings.
Improve data integration and accessibility
Store all your materials data in a single, structured repository. Share rich analysis results with context.
