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e-Flash XS

Simplicity is the ultimate sophistication!

To significantly increase the number of labs able to acquire an integrated EDS & EBSD system, Bruker Nano Analytics has developed e-Flash XS, a unique EBSD detector dedicated to the affordable part of the SEM market. The e-Flash XS EBSD detector was purposely designed to be installed on low footprint SEMs, e.g. tabletop SEMs and standard SEMs with small chambers.

Our EBSD expertise has been tapped for developing the most reliable and most affordable EBSD detector ever, while providing excellent performance. Designed for maximum reliability, ease of use and pattern quality, e-Flash XS is powered by a binning capable CMOS camera, an innovative optical system for maximum light transmission and a high-performance user-replaceable phosphor screen. Its USB3.0 computer connection (power & data) makes e-Flash XS a truly plug-n-play instrument. When not in use, the in-SEM portion of the EBSD detector slides off for external storage, to eliminate any risk of the SEM stage colliding with the detector.

The new e-Flash XS EBSD detector is integrated with a 6th generation XFlash® EDS detector under the ESPRIT 2 software to create the QUANTAX ED-XS, a powerful combination of analytical techniques for the entry level SEM market.

Important specs

Imaging chip technology: CMOS
Native image resolution: 720 x 540 pixels
Supported binning modes: 2x2, 3x3, 4x4, 5x5, 6x6
Speed: 525 frames/second (fps) in all binning modes
User-removable detector head – slide-in & -out mechanism 
User-replaceable phosphor screen
EBSD data and power transfer via USB3.0 cable (no additional cables or boxes required)
Outer dimensions: Length ~ 84 mm, Diameter ~ 48 mm

e-Flash XS
New e-Flash XS, the most reliable and most affordable EBSD detector ever

Main benefits (hardware & software)

  • Ease of use

    • No calibration required – WD variation impact on pattern center is automatically corrected
    • Binning/pattern resolution change is not required; all binning modes are available if needed
    • Automatic camera gain
    • Automated crystal phase setup – no user-intervention required
    • No risks of accidental EBSD detector insertion into stage
    • User-replaceable phosphor screen
    • Stand-alone and simultaneous acquisition of EDS HyperMap and EBSD map, included
    • Automated data saving
    • Automatic EHT shutdown at the end of map acquisition is user-selectable

  • New users can be trained and practice EDS & EBSD with less time constraints
  • Sample preparation quality can be checked before an EBSD session on an expensive FE-SEM
  • Run routine EBSD analyses on affordable SEMs to reduce FE-SEM backlog

Application examples

Correlation of grain statistics with various properties on industrial alloys

Fig. 1.1 Pattern Quality Map depicting the microstructure of a Ni-alloy sample with a bimodal distribution of grain sizes; map was acquired using e-Flash XS EBSD detector mounted on JSM IT200 SEM
Fig. 1.1 Pattern Quality Map depicting the microstructure of a Ni-alloy sample with a bimodal distribution of grain sizes; map was acquired using e-Flash XS EBSD detector mounted on JSM IT200 SEM
Fig. 1.2 Crystal orientation map of the Ni-alloy sample, displaying the orientation of each grain by relating the color code described in the upper left corner with the sample surface normal; acquisition speed: 510frames/sec, zero solutions: 1.3%. No data
Fig. 1.2 Crystal orientation map of the Ni-alloy sample, displaying the orientation of each grain by relating the color code described in the upper left corner with the sample surface normal; acquisition speed: 510frames/sec, zero solutions: 1.3%. No data cleaning applied!
Fig. 1.3 Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter larger than 70microns; 1% of the total number of grains represent ~42% of the map area
Fig. 1.3 Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter larger than 70microns; 1% of the total number of grains represent ~42% of the map area
Fig. 1. 4 Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter smaller than 70microns; there are 2250 grains representing ~58% of the map area
Fig. 1. 4 Subset of the Ni-alloy EBSD map showing in random colors all grains with an equivalent diameter smaller than 70microns; there are 2250 grains representing ~58% of the map area
Fig.1.5.a): Grain size distribution histogram and mean grain diameter size calculated using arithmetic mean; the median value for grain diameter size is also calculated & displayed automatically as well as the total number of grains considered in statisti
Fig.1.5.a): Grain size distribution histogram and mean grain diameter size calculated using arithmetic mean; the median value for grain diameter size is also calculated & displayed automatically as well as the total number of grains considered in statistics
Fig.1.5.b): Grain size distribution histogram and mean grain diameter size calculated using area weighting, i.e. larger grains have a bigger influence on the mean diameter size value. For materials with a bimodal distribution of grain sizes, using area we
Fig.1.5.b): Grain size distribution histogram and mean grain diameter size calculated using area weighting, i.e. larger grains have a bigger influence on the mean diameter size value. For materials with a bimodal distribution of grain sizes, using area weighting is recommended when trying to correlate the mean grain diameter size value with mechanical properties, e.g. strength, stiffness, hardness, etc.

Characterization of microstructural features in stainless steels

Fig.2.1: Pattern Quality Map depicting the microstructure of a stainless steel sample; map was acquired using e-Flash XS EBSD detector mounted on JSM IT200 SEM.
Fig.2.1: Pattern Quality Map depicting the microstructure of a stainless steel sample; map was acquired using e-Flash XS EBSD detector mounted on JSM IT200 SEM.
Fig.2.2: Phase Distribution Map showing Ferrite phase in red and Austenite phase in green; phase ratio was 39% and 61% respectively; mapping time: 18:01min, Map size: 548,000pixels, zero solutions: 5.7%. No data cleaning applied!
Fig.2.2: Phase Distribution Map showing Ferrite phase in red and Austenite phase in green; phase ratio was 39% and 61% respectively; mapping time: 18:01min, Map size: 548,000pixels, zero solutions: 5.7%. No data cleaning applied!
Fig.2.3: Grain Average Misorientation (GAM) Map indicating that certain regions/grains contain larger orientation change than others with values increasing from blue to red (15 degrees)
Fig.2.3: Grain Average Misorientation (GAM) Map indicating that certain regions/grains contain larger orientation change than others with values increasing from blue to red (15 degrees)
Fig.2.4.a): Subset of GAM Map for Austenite phase indicating that most grains contain little to no internal orientation changes; as the orientation change within a grain is often related to its deformation state, one can use such results to study the effe
Fig.2.4.a): Subset of GAM Map for Austenite phase indicating that most grains contain little to no internal orientation changes; as the orientation change within a grain is often related to its deformation state, one can use such results to study the effect of parameters like temperature on the microstructure during thermomechanical manufacturing processes, e.g. hot rolling, extrusion or forging.
Fig. 2.4.b) Subset of GAM Map for Ferrite phase indicating that the Ferrite grains contain large internal orientation changes; when comparing with Fig.2.4.a) is appears like the stainless steel sample has been subjected to a thermomechanical forming proce
Fig. 2.4.b) Subset of GAM Map for Ferrite phase indicating that the Ferrite grains contain large internal orientation changes; when comparing with Fig.2.4.a) it appears like the stainless steel sample has been subjected to a thermomechanical forming process which led to dynamic recrystallization of the Austenite grains while the Ferrite grains experienced recovery only.

Phase identification and distribution analysis of little known multi-phase containing materials

Fig.3.1: Pattern Quality Map depicting the microstructure of highly alloyed Fe-Si ceramic composite; EBSD and EDS maps were acquired simultaneously using e-Flash XS and respectively XFlash EDS detector mounted on JSM IT200 SEM.
Fig.3.1: Pattern Quality Map depicting the microstructure of highly alloyed Fe-Si ceramic composite; EBSD and EDS maps were acquired simultaneously using e-Flash XS and respectively XFlash EDS detector mounted on JSM IT200 SEM.
Fig.3.2: Pattern Quality Map overlapped with phase map showing Si grains in red; to minimize the time required to setup the EBSD measurement on samples with unknown type and number of phases, one can launch the acquisition without identifying all phases;
Fig.3.2: Pattern Quality Map overlapped with phase map showing Si grains in red; to minimize the time required to setup the EBSD measurement on samples with unknown type and number of phases, one can launch the acquisition without identifying all phases; all other phases can be identified offline, at a latter time and complete the map using the extreme re-indexing power of ESPRIT software
Fig.3.3: Functioning principle of “Advaced Phase ID” feature used offline (Part I); a multitude of automatic and semiautomatic features assist the user in this process, e.g. semi-automatic search of phase candidates based on EDS results, automatic & u
Fig.3.3: Functioning principle of “Advaced Phase ID” feature used offline (Part I); a multitude of automatic and semiautomatic features assist the user in this process, e.g. semi-automatic search of phase candidates based on EDS results, automatic & ultrafast indexing of all candidate phases, automatic classification based on quality of fit to experimental pattern, etc.
Fig.3.4: Functioning principle of “Advaced Phase ID” feature used offline (Part II); regions colored in “aqua” represent grains of Zirconium Silicide (ZrSi2); map was reanalyzed in 13seconds at a speed of more than 24,000 points/sec.
Fig.3.4: Functioning principle of “Advaced Phase ID” feature used offline (Part II); regions colored in “aqua” represent grains of Zirconium Silicide (ZrSi2); map was reanalyzed in 13seconds at a speed of more than 24,000 points/sec.
Fig.3.5: Functioning principle of “Advanced Phase ID” feature used offline (Part III); complete phase map of highly alloyed Fe-Si ceramic material containing six different crystallographic phases; reanalysis with 6 phases took 48 seconds at a speed of
Fig.3.5: Functioning principle of “Advanced Phase ID” feature used offline (Part III); complete phase map of highly alloyed Fe-Si ceramic material containing six different crystallographic phases; reanalysis with 6 phases took 48 seconds at a speed of more than 6,500 points/sec. No data cleaning applied!
Fig.3.6: EDS HyperMap showing the distribution of Ti, Ca, Zr, Ag and C map in the highly alloyed Fe-Si ceramic; map contains one EDS spectrum for each of its 309,000 pixels and was acquired simultaneously with EBSD map at a speed of 50points/sec; Ag and C
Fig.3.6: EDS HyperMap showing the distribution of Ti, Ca, Zr, Ag and C map in the highly alloyed Fe-Si ceramic; map contains one EDS spectrum for each of its 309,000 pixels and was acquired simultaneously with EBSD map at a speed of 50points/sec; Ag and C rich regions are cracks or porosities in the sample filled with Ag paste and epoxy material during polishing.
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