Skip to main content Accessibility help
×
Home
Hostname: page-component-99c86f546-4hcbs Total loading time: 0.179 Render date: 2021-12-07T18:54:58.662Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

XpertEze : Developing Embedded Intelligence for the Scanning Electron Microscope

Published online by Cambridge University Press:  02 July 2020

NHM Caldwell
Affiliation:
Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK
BC Breton
Affiliation:
Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK
DM Holburri
Affiliation:
Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UK

Abstract

The second generation of computer-controlled scanning electron microscopes (SEMs), i.e. instruments directed by software executing on conventional personal computers (PC-SEMs), has become the industry standard. Although limited automation has been incorporated by most manufacturers, these features do not significantly alleviate the requirement for operator expertise to attain optimal performance from the microscope. Our approach to the expertise deficit has been to pursue a knowledge-based approach to microscope control, encapsulating human knowledge in software to achieve expert performance. The task of SEM operation was decomposed into five phases - Specimen Preparation, SEM Preparation, SEM Initialisation, SEM Optimisation and External Analysis - and the central three phases were modelled in detail. A stand-alone prototype system (XpertEze) was developed to utilise this model for the LEO 400 series. A web-based version was implemented to support intelligent remote microscopy.

A stand-alone knowledge-based system has several disadvantages: its user interface competes for screen space with the conventional control software, its speed of execution is reduced as its instructions must be transferred via application programming interfaces to the microscope, and the operator must learn and manage two sets of software. Our ongoing work has been to remove these problems by incorporating the XpertEze system directly within the control system.

Type
Instrument Automation (Organized by W. Deruijter and C. Potter)
Copyright
Copyright © Microscopy Society of America 2001

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Caldwell, NHMet al. Electron Microscopy and Analysis 1997, 53.Google Scholar
2.Caldwell, NHMet al. Applications and Innovations in Expert Systems V (1997), 127.Google Scholar
3.Caldwell, NHMet al. Proc. 12th European Congress on Electron Microscopy (2000), Vol. 3, 411.Google Scholar
4.Caldwell, NHM and Breton, BC acknowledge the financial support of LEO Electron Microscopy Ltd. and the Isaac Newton Trust. The authors acknowledge the work of David Hubbard (LEO) in creating the new user interface and thank him for fruitful discussions on system architecture.Google Scholar

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

XpertEze : Developing Embedded Intelligence for the Scanning Electron Microscope
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

XpertEze : Developing Embedded Intelligence for the Scanning Electron Microscope
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

XpertEze : Developing Embedded Intelligence for the Scanning Electron Microscope
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *