Charged Particle Microscope Configuration for Distributed Sample Acquisition
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Solution Overview
Problem
Conventional charged particle microscopes are not easily configurable and require on-site user input for settings, making them impractical for distributed microscopy systems, which limits their ability to process a large number of samples efficiently and uniformly.
Innovation Solution
A network of shareable microscopes is configured to operate in parallel, using a cloud-based framework with software containers that unify microscope environments and automate sample acquisition, allowing samples to be distributed across multiple locations for processing, with unique IDs for sample identification and application containers that store processing instructions securely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional charged particle microscopes are used with on-site user input for settings, then the device can be operated, but it requires extensive manual configuration time and cannot be easily deployed in distributed systems
Solution Approach 1:
The patent applies preliminary action by pre-configuring microscope settings and parameters before deployment. Configuration data is prepared in advance and stored for automatic retrieval, eliminating the need for on-site manual configuration. The system automatically applies pre-defined settings when processing samples, resolving the contradiction between ease of operation and configuration time.
Solution Approach 2:
The patent uses copying by creating and storing configuration data that can be replicated across multiple distributed systems. Instead of manually configuring each microscope individually, the same configuration data is copied and applied across the distributed network, enabling easy deployment and consistent operation across multiple locations without repeated manual setup.
2Productivity
If a single microscope processes samples sequentially, then configuration is simple, but processing a large number of samples takes years
Solution Approach 1:
The patent applies segmentation by dividing the sample processing task across multiple distributed microscopes instead of using a single microscope sequentially. The system segments the workload and distributes samples across the network, transforming a single-point bottleneck into a parallel processing architecture. This dramatically increases throughput from years to days or weeks while managing complexity through centralized coordination.
Solution Approach 2:
The patent transitions from a single-dimension sequential processing model to a multi-dimensional parallel processing architecture by adding spatial distribution across multiple locations. Samples are processed simultaneously across different microscopes in different locations, utilizing the spatial dimension to increase throughput without proportionally increasing operational complexity.
3Productivity
If microscopes are distributed across multiple locations, then processing capacity increases, but maintaining uniform processing standards and data integrity becomes difficult
Solution Approach 1:
The patent applies universality by implementing a standardized configuration data framework that ensures all distributed microscopes operate with consistent parameters and protocols. The universal configuration system maintains processing standards across different locations and equipment, ensuring data uniformity and reliability while enabling increased processing capacity through distribution.
Solution Approach 2:
The patent uses feedback mechanisms to monitor and verify processing consistency across distributed microscopes. Configuration data and processing parameters are tracked and validated to ensure uniformity, with feedback loops that detect and correct deviations. This maintains data integrity and reliability across the distributed network while preserving the productivity benefits of parallel processing.
Data Source
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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.