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Worcester College, Oxford 8 th March 2016. Integration of different sensors, detectors or instruments for multi-parameter analysis Challenge – integration.

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Presentation on theme: "Worcester College, Oxford 8 th March 2016. Integration of different sensors, detectors or instruments for multi-parameter analysis Challenge – integration."— Presentation transcript:

1 Worcester College, Oxford 8 th March 2016

2 Integration of different sensors, detectors or instruments for multi-parameter analysis Challenge – integration of multi-platform data output Chris Jones Head, Core Research Laboratories Natural History Museum, London

3 CRL – What do we do? Centre of excellence for state of the art imaging and analysis resources to facilitate heritage sector scientific research Imaging – 2D, 3D, light, electron and x-ray Analysis – major, minor and trace elements in inorganic and organic samples Interpretation – data analysis, interpretation, statistics Publication Largely naturally occurring samples

4 Imaging & Analysis Centre Electron microscopy – W, FE-SEM SEM-hosted CT Analytical electron microscopy Microprobe Inorganic chemical analysis – ICP AES (ppm), ICP MS (ppb), LA ICP MS, CHN + S, and more Micro CT tomography Laser scanning confocal microscopy X-ray diffraction – powder and single crystal Light microscopy – transmitted/reflected/polarised

5 Imaging Analysis Metadata Interpretation

6 4x Scanning electron microscopes + analytical detectors 1x Microprobe – EDX and WDX 1x Micro CT scanner 1x laser confocal light microscopy

7 Electron microscopy for surface imaging Looking at the series of high voltage to low voltage images of the same area, it is evident that the use of low voltage provides the most information about the area of contamination.

8 In-lens energy filtering at low voltages Catalyst (Pt/C) SE only SE + low energy BSE

9 Challenge – ‘fixed’ within one vendor’s group –ATLAS – industry example: –accurate XY coordinate transformation will bring full automation of the process within reach. –create comprehensive multi-scale, multi-modal images with a sample-centric correlative environment. –navigation and correlation of images from any source, e.g. light- and X-ray microscopes –Bring together images from multiple sources –data hub for images from SEM, FIB-SEM, X-ray, light microscopes and any optical images –Design a workflow tailored precisely to the complexity of your experiment –setup for automated acquisition to post processing and customized exports, and right on through to analysis.

10 SEM imaging – coated or uncoated material Head of a tropical ant

11 SEM photogrammetry – for 3D printing

12 2µm Flat Quad EDX detector 2cm

13 Nikon Micro-CT scanner

14 SEM and micro-CT data comparison – for ESA SEM (a) and µ-CT (b) cross- sections can be matched µ-CT data contains additional volumetric information (c) 3D distribution of minerals and voids in the sample (d) can be visualised

15 Plasticised circulatory system - rabbit Distribution of dendritic gold ore in quartzite host

16 Challenge: multi platform integration from multiple vendors bring together 2D images and 3D volume data from multiple instruments create comprehensive multi-scale, multi-modal images with a sample-centric correlative environment across vendor equipment import and align data from light, X-ray, electron and FIB-SEM microscopes, to produce a single, consistent picture of your sample calibration procedures and reference standards traceability of the validation/qualification effort linking with a Quality Management System (QMS)

17 Challenge – examples of fields of study data processing solutions to improve workflows from the EPMA and SEM-EDS systems. fundamental redesign of SEM to LA-ICP-MS data handling software combined with improved generic XY coordinate translation. creation of tools to assist processing data across multi-platform instruments homogenising data layouts. ZEN, 3Dxl Viewer, ATLAS

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