Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-05-20T11:12:39.673Z Has data issue: false hasContentIssue false
  • English
  • Français

Analysis of Electron Transparent Beam-Sensitive Samples Using Scanning Electron Microscopy Coupled With Energy-Dispersive X-ray Spectroscopy

Published online by Cambridge University Press:  01 June 2020

Anders Brostrøm Open the ORCID record for Anders Brostrøm [Opens in a new window] ,
Kirsten Inga Kling ,
Karin Sørig Hougaard  and
Kristian Mølhave
Anders Brostrøm
Affiliation:
Technical University of Denmark, DTU Nanolab – National Centre for Nano Fabrication and Characterization, Fysikvej, Building 307, Kgs Lyngby2800, Denmark National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen2100, Denmark
Kirsten Inga Kling
Affiliation:
Technical University of Denmark, DTU Nanolab – National Centre for Nano Fabrication and Characterization, Fysikvej, Building 307, Kgs Lyngby2800, Denmark SAXOCON A/S, Bredevej 2D, Virum2830, Denmark
Karin Sørig Hougaard
Affiliation:
National Research Centre for the Working Environment, Lersø Parkallé 105, Copenhagen2100, Denmark
Kristian Mølhave*
Affiliation:
Technical University of Denmark, DTU Nanolab – National Centre for Nano Fabrication and Characterization, Fysikvej, Building 307, Kgs Lyngby2800, Denmark
*
*Authors for correspondence: Kristian Mølhave, E-mail: krmo@dtu.dk, Anders Brostrøm, E-mail: abbl@dtu.dk
Get access

Abstract

Scanning electron microscopy, coupled with energy-dispersive X-ray spectroscopy (EDS), is a powerful tool used in many scientific fields. It can provide nanoscale images, allowing size and morphology measurements, as well as provide information on the spatial distribution of elements in a sample. This study compares the capabilities of a traditional EDS detector with a recently developed annular EDS detector when analyzing electron transparent and beam-sensitive NaCl particles on a TEM grid. The optimal settings for single particle analysis are identified in order to minimize beam damage and optimize sample throughput via the choice of acceleration voltage, EDS acquisition time, and quantification model. Here, a linear combination of two models is used to bridge results for particle sizes, which are neither bulk nor sufficiently thin to assume electron transparent. Additionally, we show that the increased count rate obtainable with the annular detector enables mapping as a viable analysis strategy compared with feature detection methods, which only scan segmented regions. Finally, we discuss advantages and disadvantages of the two analysis strategies.

Keywords

aerosolelectron microscopyenergy-dispersive X-ray spectroscopyparticle
Type
Materials Science Applications
Information
Microscopy and Microanalysis , Volume 26 , Issue 3 , June 2020 , pp. 373 - 386
Copyright
Copyright © Microscopy Society of America 2020

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

Allen, HC, Mecartney, ML & Hemminger, JC (1998). Minimizing transmission electron microscopy beam damage during the study of surface reactions on sodium chloride. Microsc Microanal 4(1), 23–33.CrossRefGoogle Scholar
Arepalli, S, Nikolaev, P, Gorelik, O, Hadjiev, VG, Holmes, W, Files, B & Yowell, L (2004). Protocol for the characterization of single-wall carbon nanotube material quality. Carbon 42(8–9), 1783–1791.CrossRefGoogle Scholar
Armstrong, JT & Buseck, PR (1975). Quantitative chemical analysis of individual microparticles using the electron microprobe: Theoretical. Anal Chem 47(13), 2178–2192.CrossRefGoogle Scholar
Brodusch, N, Demers, H & Gauvin, R (2018). X-ray imaging with a silicon drift detector energy dispersive spectrometer. In SpringerBriefs in Applied Sciences and Technology, pp. 67–84. doi: 10.1007/978-981-10-4433-5_7.Google Scholar
Brostrøm, A, Kling, KI, Hougaard, KS & Mølhave, K (2020). Complex aerosol characterization by scanning electron microscopy coupled with energy dispersive x-ray spectroscopy. Sci Rep. doi: 10.1038/s41598-020-65383-5.CrossRefGoogle ScholarPubMed
Brostrøm, A, Kling, KI, Koponen, IK, Hougaard, KS, Kandler, K & Mølhave, K (2019). Improving the foundation for particulate matter risk assessment by individual nanoparticle statistics from electron microscopy analysis. Sci Rep 9(1), 8093.CrossRefGoogle ScholarPubMed
Cazaux, J (1995). Correlations between ionization radiation damage and charging effects in transmission electron microscopy. Ultramicroscopy 60(3), 411–425.CrossRefGoogle Scholar
Cliff, G & Lorimer, GW (1975). The quantitative analysis of thin specimens. J Microsc 103(2), 203–207.CrossRefGoogle Scholar
Demers, H, Poirier-Demers, N, Couture, AR, Joly, D, Guilmain, M, de Jonge, N & Drouin, D (2011). Three-dimensional electron microscopy simulation with the CASINO Monte Carlo software. Scanning 33(3), 135–146.CrossRefGoogle ScholarPubMed
Duncumb, P & Reed, SJB (1968). The calculation of stopping power and backscatter effects in electron probe microanalysis. Quant Electron Probe Microanal (298), 133–154.Google Scholar
Egerton, RF, Li, P & Malac, M (2004). Radiation damage in the TEM and SEM. Micron 35(6), 399–409.CrossRefGoogle ScholarPubMed
Fletcher, RA, Ritchie, NWM, Anderson, IM & Small, JA (2011). Microscopy and microanalysis of individual collected particles. In Aerosol Measurement: Principles, Techniques, and Applications, 3rd ed., Kulkarni P, Baron PA, & Willeke K (eds), pp. 179–232. John Wiley and Sons. doi:10.1002/9781118001684.ch10.CrossRefGoogle Scholar
Friel, JJ & Lyman, CE (2006). X-ray mapping in electron-beam instruments. Microsc Microanal 12, 2–25.CrossRefGoogle ScholarPubMed
Hovington, P, Timoshevskii, V, Burgess, S, Demers, H, Statham, P, Gauvin, R & Zaghib, K (2016). Can we detect Li K X-ray in lithium compounds using energy dispersive spectroscopy? Scanning 38(6), 571–578.CrossRefGoogle Scholar
Kandler, K, Schneiders, K, Ebert, M, Hartmann, M, Weinbruch, S, Prass, M & Pöhlker, C (2018). Composition and mixing state of atmospheric aerosols determined by electron microscopy: Method development and application to aged Saharan dust deposition in the Caribbean boundary layer. Atmos Chem Phys 18(18), 13429–13455.CrossRefGoogle Scholar
Kandler, K, Schütz, L, Deutscher, C, Ebert, M, Hofmann, H, Jäckel, S, Jaenicke, R, Knippertz, P, Lieke, K, Massling, A & Petzold, A (2009). Size distribution, mass concentration, chemical and mineralogical composition and derived optical parameters of the boundary layer aerosol at Tinfou, Morocco, during SAMUM 2006. Tellus B 61(1), 32–50.CrossRefGoogle Scholar
Kling, KI, Levin, M, Jensen, ACØ, Jensen, KA & Koponen, IK (2016). Size-resolved characterization of particles and fibers released during abrasion of fiber-reinforced composite in a workplace influenced by ambient background sources. Aerosol Air Qual Res 16(1), 11–24.CrossRefGoogle Scholar
Koh, AL, Shachaf, CM, Elchuri, S, Nolan, GP & Sinclair, R (2008). Electron microscopy localization and characterization of functionalized composite organic-inorganic SERS nanoparticles on leukemia cells. Ultramicroscopy 109(1), 111–121.CrossRefGoogle ScholarPubMed
Laskin, A & Cowin, JP (2001). Automated single-particle SEM/EDX analysis of submicrometer particles down to 0.1 μm. Anal Chem 73(5), 1023–1029.CrossRefGoogle Scholar
Laskin, A, Cowin, JP & Iedema, MJ (2006). Analysis of individual environmental particles using modern methods of electron microscopy and X-ray microanalysis. J Electron Spectrosc Relat Phenom 150(2–3), 260–274.CrossRefGoogle Scholar
Lee, JS, Choi, YC, Shin, JH, Lee, JH, Lee, Y, Park, SY, Baek, JE, Park, JD, Ahn, K & Yu, IJ (2015). Health surveillance study of workers who manufacture multi-walled carbon nanotubes. Nanotoxicology 9(6), 802–811.CrossRefGoogle ScholarPubMed
Lee, KM, Cai, Z, Griggs, JA, Guiatas, L, Lee, DJ & Okabe, T (2004). SEM/EDS evaluation of porcelain adherence to gold-coated cast titanium. J Biomed Mater Res B 68(2), 165–173.CrossRefGoogle ScholarPubMed
Newbury, DE & Ritchie, NWM (2013). Is scanning electron microscopy/energy dispersive X-ray spectrometry (SEM/EDS) quantitative? Scanning 35(3), 141–168.CrossRefGoogle ScholarPubMed
Newbury, DE & Ritchie, NWM (2014). Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS). J Mater Sci 50(2), 493–518.CrossRefGoogle Scholar
Philibert, J (1963). A method for calculating the absorption correction in electron-probe microanalysis. X-Ray Opt X-Ray Microanal 379–392.Google Scholar
Potts, PJ (1987). A Handbook of Silicate Rock Analysis, p. 336.CrossRefGoogle Scholar
Reed, SJB (1965). Characteristic fluorescence corrections in electron-probe microanalysis. Br J Appl Phys 16(7), 913–926.CrossRefGoogle Scholar
Ro, CU, Osán, J, Szalóki, I, De Hoog, J, Worobiec, A & Van Grieken, R (2003). A Monte Carlo program for quantitative electron-induced X-ray analysis of individual particles. Anal Chem 75(4), 851–859.CrossRefGoogle ScholarPubMed
Sathirachinda, N, Pettersson, R, Wessman, S & Pan, J (2010). Study of nobility of chromium nitrides in isothermally aged duplex stainless steels by using SKPFM and SEM/EDS. Corros Sci 52(1), 179–186.CrossRefGoogle Scholar
Stebounova, LV, Adamcakova-Dodd, A, Kim, JS, Park, H, T O'Shaughnessy, P, Grassian, VH & Thorne, PS (2011). Nanosilver induces minimal lung toxicity or inflammation in a subacute murine inhalation model. Part Fibre Toxicol 8. doi:10.1186/1743-8977-8-5CrossRefGoogle ScholarPubMed
Teng, C, Demers, H, Brodusch, N, Waters, K & Gauvin, R (2018). Use of an annular silicon drift detector (SDD) versus a conventional SDD makes phase mapping a practical solution for rare earth mineral characterization. Microsc Microanal 24(3), 238–248.CrossRefGoogle ScholarPubMed
Watanabe, M & Williams, DB (2006). The quantitative analysis of thin specimens: A review of progress from the Cliff-Lorimer to the new ζ-factor methods. J Microsc 221(2), 89–109.CrossRefGoogle ScholarPubMed
Wendt, M (1978). Advances in energy dispersive X-ray microanalysis. Krist Technol 13(11), 1259–1275.CrossRefGoogle Scholar
Wendt, M & Schmidt, A (1978). Improved reproducibility of energy-dispersive X-ray microanalysis by normalization to the background. Phys Status Solidi A 46(1), 179–183.CrossRefGoogle Scholar
Supplementary material: File

Brostrøm et al. Supplementary Materials

Brostrøm et al. Supplementary Materials

Download Brostrøm et al. Supplementary Materials(File)
File 5.7 MB