Scripted Automation for Efficient Control and Autonomous Experimentation with AFM
Automated AFM Experimentation and Materials Discovery
In this webinar, presenters demonstrate the use of NanoScope API for safe and flexible control of Bruker Dimension series AFMs. They also show how integrating this API with machine learning and agentic AI automates the SPM for materials discovery while reducing the coding burden on users.
Join us for this webinar to see:
- The new nanoscope_api interface that provides access to control Dimension AFMs
- Examples of scripted instrument control for lithography, parameter control, and more
- Integrations and implementations for added utility and usability, from external instrumentation to machine learning and agentic AI.
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Scripted Automation for Efficient Control and Autonomous Experimentation with AFM
The sensitivity, resolution and multi-modal capabilities of the atomic force microscope make it attractive in development and characterization of devices and materials. NanoScope API, a new application programming interface (API), has been developed for safe and efficient measurement of large samples and/or sets of samples with Dimension AFM systems.
We consider the use of this API to control system parameters, conduct nanolithography, check system status, collect data, change modes, and move the stage to access different samples or locations on a 200 mm sample. By integrating this new API with machine learning–driven experimental control we further demonstrate how the SPM can be automated for materials discovery. Finally, we discuss how agentic AI can be harnessed to access this API and reduce or eliminate the burden of coding for the user.
- Introduction to nanoscope_api: a new interface that provides safe and flexible access to control of Bruker Dimension series AFMs
- Examples of scripted instrument control for applications ranging from lithography to control of key instrument parameters during scanning
- Integration of scripted AFM with external instrumentation to expand system capabilities
- Automated experimentation for efficient exploration of combinatorial libraries for materials discovery
- Agentic AI for easy script development
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