# Atomscale Documentation

## Docs

- [Atomscale Documentation](https://docs.atomscale.ai/platform/index.md): Real-time process intelligence for advanced materials manufacturing
- [Solutions](https://docs.atomscale.ai/platform/solutions.md): Atomscale delivers value for organizational leadership, manufacturing operations, and research teams
- [Use Cases](https://docs.atomscale.ai/platform/use-cases.md): Specific tasks and workflows that Atomscale enables
- [Case Studies](https://docs.atomscale.ai/platform/case-studies.md): Validated demonstrations of Atomscale capabilities across deposition processes and characterization methods
- [Overview](https://docs.atomscale.ai/platform/get-started/index.md): Get up and running with Atomscale in three steps
- [Connect](https://docs.atomscale.ai/platform/get-started/connect.md): Integrate your growth and characterization data with Atomscale
- [Analyze](https://docs.atomscale.ai/platform/get-started/analyze.md): Compare runs, track active growths, and extract process understanding from your data
- [Act](https://docs.atomscale.ai/platform/get-started/act.md): Turn real-time process intelligence into decisions, interventions, and control
- [Guides Overview](https://docs.atomscale.ai/platform/guides/index.md): Goal-oriented workflows for process monitoring, analysis, and optimization
- [Detect and Respond to Anomalies](https://docs.atomscale.ai/platform/guides/detect-anomalies.md): Detect process anomalies across instruments, predict quality outcomes, and take corrective action
- [Diagnose Why Runs Differ](https://docs.atomscale.ai/platform/guides/diagnose-run-differences.md): Understand what changed when a run doesn't match expectations by inspecting it over time and comparing it across your dataset
- [Identify Uniformity Issues](https://docs.atomscale.ai/platform/guides/identify-uniformity-issues.md): Find consistency problems within a single run by inspecting it over time and comparing its segments across your dataset
- [Characterization Overview](https://docs.atomscale.ai/platform/characterization/index.md): Automated analysis workflows for thin film characterization techniques
- [RHEED](https://docs.atomscale.ai/platform/characterization/rheed.md): Surface structure analysis from diffraction patterns and intensity oscillations
- [XPS](https://docs.atomscale.ai/platform/characterization/xps.md): Elemental composition analysis from X-ray photoelectron spectroscopy survey spectra
- [Ellipsometry](https://docs.atomscale.ai/platform/characterization/ellipsometry.md): Timeseries extraction from spectroscopic ellipsometry measurements
- [Optical Images](https://docs.atomscale.ai/platform/characterization/optical-images.md): Video segmentation and morphology tracking from optical microscopy
- [Photoluminescence](https://docs.atomscale.ai/platform/characterization/photoluminescence.md): Spectral analysis of photoluminescence emission measurements
- [Raman](https://docs.atomscale.ai/platform/characterization/raman.md): Vibrational spectroscopy for material composition and crystal quality
- [SEM](https://docs.atomscale.ai/platform/characterization/sem.md): Object segmentation and morphological analysis from electron micrographs
- [SIMS](https://docs.atomscale.ai/platform/characterization/sims.md): Depth profiling of elemental composition from secondary ion mass spectrometry
- [Onboarding](https://docs.atomscale.ai/platform/reference/onboarding.md): Account creation, organization setup, and user management
- [Desktop App](https://docs.atomscale.ai/platform/reference/desktop-app.md): Install and use the Atomscale desktop app for Windows
- [Manual Upload](https://docs.atomscale.ai/platform/reference/connecting-data/manual-upload.md): Upload files to Atomscale through the web interface
- [Screen Capture](https://docs.atomscale.ai/platform/reference/connecting-data/screen-capture.md): Stream instrument data by recording your screen
- [File Watcher](https://docs.atomscale.ai/platform/reference/connecting-data/file-watcher.md): Automatically upload files from a local directory
- [Integrations](https://docs.atomscale.ai/platform/reference/connecting-data/integrations.md): Connect instruments and workstations with managed integrations
- [Programmatic Integration](https://docs.atomscale.ai/platform/reference/connecting-data/programmatic.md): Upload data and stream frames using the Python SDK
- [Overview](https://docs.atomscale.ai/platform/reference/models/index.md): Understanding Atomscale's data model and core concepts
- [Projects](https://docs.atomscale.ai/platform/reference/models/projects.md): Grouping physical samples for comparison and analysis
- [Physical Samples](https://docs.atomscale.ai/platform/reference/models/samples.md): Representing growth runs and grouping related data
- [Data Items](https://docs.atomscale.ai/platform/reference/models/data-items.md): Individual instrument and characterization files
- [Workflows](https://docs.atomscale.ai/platform/reference/workflows/index.md): Composable analysis pipelines that process your data
- [Similarity](https://docs.atomscale.ai/platform/reference/workflows/similarity.md): Embed characterization timeseries for visual comparison and track similarity to reference items over time
- [Changepoint Detection](https://docs.atomscale.ai/platform/reference/workflows/changepoint-detection.md): Real-time changepoint detection on RHEED streams, with labels inherited from reference changepoints in a project
- [Tool State](https://docs.atomscale.ai/platform/reference/workflows/tool-state.md): Parse, clean, and analyze instrument log files from synthesis tools
- [Monitoring](https://docs.atomscale.ai/platform/reference/monitoring/index.md): Watch growths in real time and review completed sessions on the Monitor page
- [Starting a Growth](https://docs.atomscale.ai/platform/reference/monitoring/starting-a-growth.md): Begin a new monitoring session by streaming live growth data
- [Session View](https://docs.atomscale.ai/platform/reference/monitoring/session-view.md): Read the live and completed session view, panel by panel
- [Security](https://docs.atomscale.ai/platform/reference/security.md): Data isolation, encryption, and organizational safeguards
- [IP and Data](https://docs.atomscale.ai/platform/reference/ip-and-data.md): Data ownership, privacy controls, and IP protection
- [Terms of Service](https://docs.atomscale.ai/platform/reference/terms-of-service.md): The terms governing access to and use of the Atomscale platform, APIs, SDKs, and related services
- [Accessibility](https://docs.atomscale.ai/platform/reference/accessibility.md): Atomscale's commitment to accessible design
- [FAQ](https://docs.atomscale.ai/platform/reference/faq.md): Frequently asked questions about Atomscale
- [Python SDK](https://docs.atomscale.ai/sdk/index.md): Programmatic access to Atomscale for automation and custom analysis
- [Quickstart](https://docs.atomscale.ai/sdk/quickstart.md): Install the SDK and create your first client
- [Upload Data](https://docs.atomscale.ai/sdk/upload-data.md): Send instrument files for automated analysis
- [Search the Catalogue](https://docs.atomscale.ai/sdk/search-data.md): Find uploaded data with filters and keywords
- [Inspect Results](https://docs.atomscale.ai/sdk/inspect-results.md): Work with analysis outputs, time series data, and extracted frames
- [RHEED Features and Masks](https://docs.atomscale.ai/sdk/rheed-features.md): Query low-level RHEED features and per-frame segmentation masks
- [Similarity and Embeddings](https://docs.atomscale.ai/sdk/similarity.md): Compare growths with embedding vectors, matches, and trajectories
- [Samples and Projects](https://docs.atomscale.ai/sdk/samples-projects.md): Work with physical samples, projects, and aligned timeseries
- [Stream RHEED Video](https://docs.atomscale.ai/sdk/stream-rheed.md): Push frames from your instrument for real-time analysis
- [Stream Metrology Data](https://docs.atomscale.ai/sdk/stream-metrology.md): Push instrument readings for real-time analysis
- [Poll Time Series Updates](https://docs.atomscale.ai/sdk/poll-timeseries.md): Monitor streaming RHEED analysis with sync and async polling
- [Poll Similarity Trajectory](https://docs.atomscale.ai/sdk/poll-trajectory.md): Monitor similarity trajectory updates from streaming analysis
- [Client](https://docs.atomscale.ai/sdk/reference/client.md): Complete API reference for the atomscale Client class
- [Streaming](https://docs.atomscale.ai/sdk/reference/streaming.md): Complete API reference for RHEEDStreamer and TimeseriesStreamer
- [MCP Server](https://docs.atomscale.ai/mcp-server.md): Access Atomscale from Claude, IDEs, and other AI agents over the Model Context Protocol
- [API Reference](https://docs.atomscale.ai/api-reference/index.md): Programmatic access to the Atomscale platform
- [Authentication](https://docs.atomscale.ai/api-reference/authentication.md): Secure your API requests with API keys
- [List Data Entries](https://docs.atomscale.ai/api-reference/data-catalogue/list.md): Retrieve data catalogue entries with filtering
- [Update Data Entry](https://docs.atomscale.ai/api-reference/data-catalogue/update.md): Update the metadata of a data catalogue entry
- [Delete Data Entries](https://docs.atomscale.ai/api-reference/data-catalogue/delete.md): Delete one or more data entries from the catalogue
- [Associate Data with Sample](https://docs.atomscale.ai/api-reference/data-catalogue/associate-sample.md): Attach data entries to a physical sample
- [Get Raw Data](https://docs.atomscale.ai/api-reference/data-catalogue/get-raw.md): Retrieve raw data for a specific data entry
- [Get Processed Data](https://docs.atomscale.ai/api-reference/data-catalogue/get-processed.md): Retrieve processed data for a data entry
- [Get Processing Status](https://docs.atomscale.ai/api-reference/data-catalogue/status.md): Poll the processing pipeline status for a data entry
- [Export Data](https://docs.atomscale.ai/api-reference/data-catalogue/export.md): Export one or more data entries
- [Get Upload URLs](https://docs.atomscale.ai/api-reference/upload/get-upload-urls.md): Generate pre-signed URLs for multi-part file uploads
- [Complete Upload](https://docs.atomscale.ai/api-reference/upload/complete-upload.md): Finalize a multi-part upload
- [Complete Single-Part Upload](https://docs.atomscale.ai/api-reference/upload/complete-single-upload.md): Finalize a single-part staged upload
- [Get Staged Timeseries](https://docs.atomscale.ai/api-reference/upload/get-timeseries.md): Retrieve timeseries data from a staged upload
- [List Projects](https://docs.atomscale.ai/api-reference/projects/list.md): Retrieve all projects in your organization
- [Create Project](https://docs.atomscale.ai/api-reference/projects/create.md): Create a new project in your workspace
- [Update Project](https://docs.atomscale.ai/api-reference/projects/update.md): Update an existing project
- [Delete Project](https://docs.atomscale.ai/api-reference/projects/delete.md): Delete a project
- [Get Project Samples](https://docs.atomscale.ai/api-reference/projects/get-samples.md): List all physical samples associated with a project
- [Update Project Samples](https://docs.atomscale.ai/api-reference/projects/update-samples.md): Update the physical samples associated with a project
- [Get Project Last Updated](https://docs.atomscale.ai/api-reference/projects/last-updated.md): Get the most recent update time for a project
- [List Physical Samples](https://docs.atomscale.ai/api-reference/samples/list.md): Retrieve physical samples in your organization
- [Create Physical Sample](https://docs.atomscale.ai/api-reference/samples/create.md): Register a new physical sample
- [Update Physical Sample](https://docs.atomscale.ai/api-reference/samples/update.md): Update fields on an existing physical sample
- [Delete Physical Samples](https://docs.atomscale.ai/api-reference/samples/delete.md): Delete one or more physical samples
- [Get Physical Sample Timeseries](https://docs.atomscale.ai/api-reference/samples/timeseries.md): Retrieve aggregated timeseries data for a physical sample
- [Update Sample Growth Instrument](https://docs.atomscale.ai/api-reference/samples/update-growth-instrument.md): Set or clear the growth instrument for a physical sample
- [Update Sample Target Material](https://docs.atomscale.ai/api-reference/samples/update-target-material.md): Set or clear the target material for a physical sample
- [List Sample Annotations](https://docs.atomscale.ai/api-reference/samples/annotations-list.md): Retrieve spatial annotations for a physical sample
- [Create Sample Annotation](https://docs.atomscale.ai/api-reference/samples/annotations-create.md): Record a spatial annotation on a physical sample
- [Bulk Create Sample Annotations](https://docs.atomscale.ai/api-reference/samples/annotations-bulk.md): Create multiple spatial annotations on a physical sample in one request
- [Update Sample Annotation](https://docs.atomscale.ai/api-reference/samples/annotations-update.md): Update fields on an existing spatial annotation
- [Delete Sample Annotations](https://docs.atomscale.ai/api-reference/samples/annotations-delete.md): Delete spatial annotations from a physical sample
- [Get RHEED Timeseries](https://docs.atomscale.ai/api-reference/rheed/timeseries.md): Retrieve processed RHEED timeseries data
- [Get RHEED Timeseries Batch](https://docs.atomscale.ai/api-reference/rheed/timeseries-batch.md): Retrieve RHEED timeseries for multiple data entries in a single request
- [Get RHEED Mask](https://docs.atomscale.ai/api-reference/rheed/mask.md): Retrieve the RLE-encoded mask for a RHEED image
- [Get RHEED Frame Masks](https://docs.atomscale.ai/api-reference/rheed/frame-masks.md): Retrieve per-frame RLE-encoded masks for a processed RHEED video
- [Get RHEED Fingerprint](https://docs.atomscale.ai/api-reference/rheed/fingerprint.md): Retrieve the RHEED pattern fingerprint as a serialized graph
- [Get RHEED Overlay](https://docs.atomscale.ai/api-reference/rheed/overlay.md): Download the RHEED image with the detected mask overlaid
- [Compare RHEED Images](https://docs.atomscale.ai/api-reference/rheed/compare.md): Compare two RHEED images to measure changes in spot count, strain, and mask
- [Get RHEED Processed Metadata](https://docs.atomscale.ai/api-reference/rheed/processed-metadata.md): Retrieve frame rate, total frames, and analysis window bounds for RHEED videos
- [Start RHEED Stream](https://docs.atomscale.ai/api-reference/rheed/start-stream.md): Start a new RHEED streaming session
- [Get RHEED Stream Settings](https://docs.atomscale.ai/api-reference/rheed/stream-settings.md): Retrieve the configuration for a RHEED streaming session
- [Pause RHEED Stream](https://docs.atomscale.ai/api-reference/rheed/pause-stream.md): Pause an active RHEED streaming session
- [Resume RHEED Stream](https://docs.atomscale.ai/api-reference/rheed/resume-stream.md): Resume a paused RHEED streaming session
- [End RHEED Stream](https://docs.atomscale.ai/api-reference/rheed/end-stream.md): End a RHEED streaming session and finalize processing
- [Get RHEED Stream Latency](https://docs.atomscale.ai/api-reference/rheed/stream-latency.md): Retrieve the real-time latency of a RHEED stream
- [Get RHEED Stream Video URLs](https://docs.atomscale.ai/api-reference/rheed/stream-video-urls.md): Retrieve presigned URLs for the clustered video of a RHEED stream
- [Get RHEED Stream Total Frames](https://docs.atomscale.ai/api-reference/rheed/stream-total-frames.md): Retrieve the total number of frames the client attempted to send for a RHEED stream
- [Warm Up RHEED Stream Worker](https://docs.atomscale.ai/api-reference/rheed/stream-warmup.md): Check whether a RHEED processing worker is ready and trigger a warm-up if not
- [Get SEM Fingerprint](https://docs.atomscale.ai/api-reference/sem/fingerprint.md): Retrieve the SEM image fingerprint for surface morphology analysis
- [Get SEM Mask](https://docs.atomscale.ai/api-reference/sem/mask.md): Retrieve the RLE-encoded segmentation mask for an SEM image
- [Get SEM Overlay](https://docs.atomscale.ai/api-reference/sem/overlay.md): Download the SEM image with the detected mask overlaid
- [Get Processed SEM Image](https://docs.atomscale.ai/api-reference/sem/processed.md): Retrieve the processed SEM image with the segmentation overlay
- [Get SEM Histograms](https://docs.atomscale.ai/api-reference/sem/histograms.md): Retrieve feature distribution histograms for an SEM image
- [Get XPS Data](https://docs.atomscale.ai/api-reference/spectroscopy/xps.md): Retrieve X-ray photoelectron spectroscopy data and analysis
- [Get Raman Data](https://docs.atomscale.ai/api-reference/spectroscopy/raman.md): Retrieve Raman spectroscopy data
- [Get Photoluminescence Data](https://docs.atomscale.ai/api-reference/spectroscopy/photoluminescence.md): Retrieve photoluminescence spectroscopy data
- [Get XRD Data](https://docs.atomscale.ai/api-reference/spectroscopy/xrd.md): Retrieve X-ray diffraction data and analysis
- [Get OES Data](https://docs.atomscale.ai/api-reference/oes/get.md): Retrieve optical emission spectroscopy data and analysis
- [Get All OES Results](https://docs.atomscale.ai/api-reference/oes/get-all.md): Retrieve all OES spectra for a data entry
- [Update OES Peak Assignment](https://docs.atomscale.ai/api-reference/oes/update-peaks.md): Manually reassign an OES emission peak to a candidate element
- [Get SIMS Data](https://docs.atomscale.ai/api-reference/sims/get.md): Retrieve secondary ion mass spectrometry depth profiles
- [Get SIMS Species Profile](https://docs.atomscale.ai/api-reference/sims/get-species.md): Retrieve a single SIMS depth profile by species
- [Get Optical Timeseries](https://docs.atomscale.ai/api-reference/optical/timeseries.md): Retrieve optical monitoring timeseries data
- [Get Optical Video Frames](https://docs.atomscale.ai/api-reference/optical/frames.md): Retrieve individual frames from optical video recordings
- [Get Ellipsometry Timeseries](https://docs.atomscale.ai/api-reference/optical/ellipsometry-timeseries.md): Retrieve ellipsometry measurement timeseries data
- [Get Metrology Timeseries](https://docs.atomscale.ai/api-reference/metrology/timeseries.md): Retrieve metrology measurement timeseries data
- [Initialize Metrology Stream](https://docs.atomscale.ai/api-reference/metrology/initialize-stream.md): Initialize a new metrology time series stream
- [Ingest Chunk](https://docs.atomscale.ai/api-reference/metrology/ingest-chunk.md): Ingest a single chunk of time series data for one channel
- [Ingest Multi-Channel Chunk](https://docs.atomscale.ai/api-reference/metrology/ingest-chunk-multi.md): Ingest a chunk with multiple channels at once
- [Finalize Metrology Stream](https://docs.atomscale.ai/api-reference/metrology/finalize-stream.md): Finalize a stream, marking it as complete
- [List Tags](https://docs.atomscale.ai/api-reference/tags/list.md): Retrieve all tags for your organization
- [Create Tag](https://docs.atomscale.ai/api-reference/tags/create.md): Create a new tag
- [Update Tags](https://docs.atomscale.ai/api-reference/tags/update.md): Update one or more tags
- [Delete Tags](https://docs.atomscale.ai/api-reference/tags/delete.md): Delete one or more tags
- [List Tag Categories](https://docs.atomscale.ai/api-reference/tags/list-categories.md): Retrieve all tag categories for your organization
- [Create Tag Category](https://docs.atomscale.ai/api-reference/tags/create-category.md): Create a new tag category
- [Update Tag Category](https://docs.atomscale.ai/api-reference/tags/update-category.md): Update a tag category
- [Delete Tag Categories](https://docs.atomscale.ai/api-reference/tags/delete-categories.md): Delete one or more tag categories
- [Get Tags on Data Item](https://docs.atomscale.ai/api-reference/tags/get-data-item-tags.md): Retrieve the tags applied to a data item
- [Add Tags to Data Items](https://docs.atomscale.ai/api-reference/tags/add-to-data-items.md): Apply tags to data items in bulk
- [Remove Tags from Data Items](https://docs.atomscale.ai/api-reference/tags/remove-from-data-items.md): Remove tags from data items in bulk
- [List Target Materials](https://docs.atomscale.ai/api-reference/target-materials/list.md): Retrieve target materials with their layer stacks
- [Create Target Material](https://docs.atomscale.ai/api-reference/target-materials/create.md): Create a target material with an optional layer stack
- [Update Target Material](https://docs.atomscale.ai/api-reference/target-materials/update.md): Update the sample details of a target material
- [Delete Target Materials](https://docs.atomscale.ai/api-reference/target-materials/delete.md): Delete one or more target materials
- [Parse Target Material](https://docs.atomscale.ai/api-reference/target-materials/parse.md): Parse a natural-language material description into a structured stack
- [Create Target Material Layer](https://docs.atomscale.ai/api-reference/target-materials/create-layer.md): Add a single layer to a target material
- [Update Target Material Layer](https://docs.atomscale.ai/api-reference/target-materials/update-layer.md): Update a single layer of a target material
- [Replace Target Material Layers](https://docs.atomscale.ai/api-reference/target-materials/update-layers.md): Replace the full layer stack of a target material
- [Delete Target Material Layer](https://docs.atomscale.ai/api-reference/target-materials/delete-layer.md): Delete a single layer from a target material
- [List Synthesis Instruments](https://docs.atomscale.ai/api-reference/instruments/list.md): Retrieve synthesis instruments in your organization
- [Create Synthesis Instrument](https://docs.atomscale.ai/api-reference/instruments/create.md): Register a new synthesis instrument
- [Get Synthesis Instrument](https://docs.atomscale.ai/api-reference/instruments/get.md): Retrieve a single synthesis instrument by ID
- [Update Synthesis Instrument](https://docs.atomscale.ai/api-reference/instruments/update.md): Update an existing synthesis instrument
- [Delete Synthesis Instruments](https://docs.atomscale.ai/api-reference/instruments/delete.md): Delete one or more synthesis instruments