Charged Particle Microscope Configuration via Application Containers
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Solution Overview
Problem
Conventional charged particle microscopes are not easily configurable and require manual on-site settings, making them impractical for distributed microscopy systems, which necessitate different hardware and software configurations, and result in inefficient processing of large volumes of samples.
Innovation Solution
A network of shareable microscopes is configured via software control and analysis, using application containers with unique sample IDs for automated acquisition and unified microscope environments, enabling parallel data acquisition across multiple locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional charged particle microscopes are configured manually on-site, then each microscope can be customized for specific needs, but the configuration time and complexity increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-configuring microscope parameters, software settings, and acquisition protocols through application containers before deployment. These pre-packaged configurations can be rapidly instantiated at different locations without manual setup, resolving the contradiction between adaptability and configuration time.
Solution Approach 2:
The patent uses copying by creating reusable application container templates that encapsulate complete microscope configurations. These templates can be copied and deployed across multiple microscopes, allowing consistent replication of optimized settings without reconfiguring each device individually.
2Ease of operation
If manual on-site settings are used for charged particle microscopes, then local adjustments can be made, but distributed microscopy systems become impractical
Solution Approach 1:
The patent applies universality by designing application containers that can run on any charged particle microscope regardless of specific hardware variations. The standardized container format enables the same configuration to be universally deployed across diverse microscope systems, making distributed networks practical while maintaining local adaptability through container selection.
Solution Approach 2:
The patent introduces an intermediary layer (the application container and management system) between the user and the microscope hardware. This intermediary handles configuration management, allowing users to select and deploy pre-configured applications without directly manipulating microscope settings, thus enabling distributed operation while preserving ease of use.
3Adaptability or versatility
If multiple microscopes with different configurations are used, then diverse processing capabilities are available, but data integrity and compatibility become difficult to maintain
Solution Approach 1:
The patent applies homogeneity by standardizing the software environment through application containers that provide consistent operating conditions across different microscope hardware. This containerization ensures that data processing, analysis, and formatting follow uniform protocols, maintaining data integrity and compatibility even when diverse microscope configurations are deployed.
4Device complexity
If conventional microscopes are used without parallel acquisition, then system complexity remains low, but processing time for large volumes of samples extends to years
Solution Approach 1:
The patent applies segmentation by dividing the sample processing workload across multiple microscopes that can operate in parallel. Each microscope processes a portion of the total sample volume simultaneously, dramatically reducing overall processing time from years to days or weeks while maintaining manageable system complexity through standardized interfaces.
Solution Approach 2:
The patent combines multiple microscope systems into a coordinated network managed through a centralized platform. This merging allows parallel acquisition from multiple devices while presenting a unified interface to users, achieving high productivity without proportionally increasing operational complexity.
Data Source
AI summary
Disclosed herein are scientific instrument support systems, as well as related methods, computing devices, and computer-readable media. For example, in some embodiments, an example method may comprise receiving, by a first device located at a premises and from a second device located external to the premises, and via a network, configuration data for a charged particle microscope located at the premises. The method may comprise updating, by the first device and based on the configuration data, one or more configuration settings associated with the charged particle microscope. The method may comprise causing, based on the updated one or more configuration settings, one or more operations associated with the charged particle microscope to be performed.