Abstract
The era of research on (engineered) nanomaterials (NM) has been thriving for more than a decade and has delivered many beneficial applications, but also raised concerns about potential negative impacts on human health and ecosystems. The precautionary principle, hence, calls for a regulation of certain types of NM, which in consequence requires their unambiguous identification. Most of the currently available definitions of NM rely on an evaluation of the size of the constituent particles and therefore methods have to be developed to measure this parameter. Transmission electron microscopy (TEM) is one of the most promising techniques, as its resolving power well covers the nanosize range. However, limited automation of TEM analyses and possible user bias are major drawbacks of the technique and currently put severe constraints on its broader applications in nanometrology.
Therefore, the goal of this study was to develop a software code, referred to as AutoEM, to automatically acquire TEM images, measure particle sizes and extract the respective particle size distributions (PSD) of (nano)-materials. The AutoEM software also incorporates methods for elemental analyses of individual particles using electron energy loss and energy dispersive X-ray spectroscopy (EELS/EDX) allowing the extraction of element-specific PSDs. Additionally automated acquisition of energy-filtered images (EFTEM) is implemented in the AutoEM software, which can be used, e.g., to derive thickness maps and, thus, to evaluate the thickness of individual (plate-like) particles.
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References
Babick F, Mielke J, Wohlleben W, Weigel S, Hodoroaba VD (2016) How reliably can a material be classified as a nanomaterial? Available particle-sizing techniques at work. J Nanopart Res 18:158. https://doi.org/10.1007/s11051-016-3461-7
Caballero-Guzman A, Nowack B (2016) A critical review of engineered nanomaterial release data: are current data useful for material flow modeling? Environ Pollut 213:502–517. https://doi.org/10.1016/j.envpol.2016.02.028
Cervera Gontard L, Ozkaya D, Dunin-Borkowski RE (2011) A simple algorithm for measuring particle size distributions on an uneven background from TEM images. Ultramicroscopy 111:101–106. https://doi.org/10.1016/j.ultramic.2010.10.011
Craven AJ, Bobynko J, Sala B, MacLaren I (2016) Accurate measurement of absolute experimental inelastic mean free paths and EELS differential cross-sections. Ultramicroscopy 170:113–127. https://doi.org/10.1016/j.ultramic.2016.08.012
Dudkiewicz A, Boxall ABA, Chaudhry Q, Mølhave K, Tiede K, Hofmann P, Linsinger TPJ (2015) Uncertainties of size measurements in electron microscopy characterization of nanomaterials in foods. Food Chem 176:472–479. https://doi.org/10.1016/j.foodchem.2014.12.071
European Commission (2011) Commission recommendation of 18 October 2011 on the definition of nanomaterial. Off J Eur Union L 275:38–40
Farre M, Gajda-Schrantz K, Kantiani L, Barcelo D (2009) Ecotoxicity and analysis of nanomaterials in the aquatic environment. Anal Bioanal Chem 393:81–95. https://doi.org/10.1007/s00216-008-2458-1
Franks K, Braun A, Charoud-Got J, Kestens V., Lamberty MA, Roebben G (2012) Certification of the equivalent spherical diameters of silica nanoparticles in aqueous solution - Certified Reference Material ERM®-FD304 - EU Science Hub - European Commission. EU Science Hub. [online]. https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/certification-equivalent-spherical-diameters-silica-nanoparticles-aqueous-solution-certified. Accessed 16 Nov 2018
Giese B, Klaessig F, Park B, Kaegi R, Steinfeldt M, Wigger H, von Gleich A, Gottschalk F (2018) Risks, release and concentrations of engineered nanomaterial in the environment. Sci Rep 8:1565. https://doi.org/10.1038/s41598-018-19275-4
Gottschalk F, Sun T, Nowack B (2013) Environmental concentrations of engineered nanomaterials: review of modeling and analytical studies. Environ Pollut 181:287–300. https://doi.org/10.1016/j.envpol.2013.06.003
Hassellöv M, Kaegi R (2009) Analysis and characterization of manufactured nanoparticles in aquatic environments. In: Lead JR, Smith E (eds) Environmental and human health impacts of nanotechnology. John Wiley & Sons, Ltd, pp 211–266
Hassellöv M, Readman JW, Ranville JF, Tiede K (2008) Nanoparticle analysis and characterization methodologies in environmental risk assessment of engineered nanoparticles. Ecotoxicology 17:344–361. https://doi.org/10.1007/s10646-008-0225-x
Hole P, Sillence K, Hannell C, Maguire CM, Roesslein M, Suarez G, Capracotta S, Magdolenova Z, Horev-Azaria L, Dybowska A, Cooke L, Haase A, Contal S, Manø S, Vennemann A, Sauvain JJ, Staunton KC, Anguissola S, Luch A, Dusinska M, Korenstein R, Gutleb AC, Wiemann M, Prina-Mello A, Riediker M, Wick P (2013) Interlaboratory comparison of size measurements on nanoparticles using nanoparticle tracking analysis (NTA). J Nanopart Res 15:UNSP 2101. https://doi.org/10.1007/s11051-013-2101-8
Iakoubovskii K, Mitsuishi K, Nakayama Y, Furuya K (2008) Mean free path of inelastic electron scattering in elemental solids and oxides using transmission electron microscopy: atomic number dependent oscillatory behavior. Phys Rev B 77:104102. https://doi.org/10.1103/PhysRevB.77.104102
ISO 13322-1 (2014) Particle size analysis — Image analysis methods — Part 1: Static image analysis methods. International Organization for Standardization, Geneva
Kanchi S, Ahmed S, Sabela M, Hussain C (2018) Nanomaterials: biomedical, environmental, and engineering applications/editors: Suvardhan Kanchi [and 3 more]. John Wiley & Sons, Hoboken
Keller AA, McFerran S, Lazareva A, Suh S (2013) Global life cycle releases of engineered nanomaterials. J Nanopart Res 15:1692
Laborda F, Bolea E, Cepriá G, Gómez MT, Jiménez MS, Pérez-Arantegui J, Castillo JR (2016a) Detection, characterization and quantification of inorganic engineered nanomaterials: a review of techniques and methodological approaches for the analysis of complex samples. Anal Chim Acta 904:10–32. https://doi.org/10.1016/j.aca.2015.11.008
Laborda F, Bolea E, Jimenez-Lamana J (2016b) Single particle inductively coupled plasma mass spectrometry for the analysis of inorganic engineered nanoparticles in environmental samples. Trends Environ Anal Chem 9:15–23. https://doi.org/10.1016/j.teac.2016.02.001
Lee C-W, Ikematsu Y, Shindo D (2002) Measurement of mean free paths for inelastic electron scattering of Si and SiO2. J Electron Microsc 51:143–148. https://doi.org/10.1093/jmicro/51.3.143
Malis T, Cheng SC, Egerton RF (1988) EELS log-ratio technique for specimen-thickness measurement in the TEM. J Electron Microsc Tech 8:193–200. https://doi.org/10.1002/jemt.1060080206
Mavrocordatos D, Perret D (1995) Non-artifacted specimen preparation for transmission electron-microscopy. Commun Soil Sci Plant Anal 26:2593–2602. https://doi.org/10.1080/00103629509369470
Meltzman H, Kauffmann Y, Thangadurai P et al (2009) An experimental method for calibration of the plasmon mean free path. J Microsc 236:165–173. https://doi.org/10.1111/j.1365-2818.2009.03214.x
Merkus HG (2009) Particle size measurements - fundamentals, practice, quality, 1st edn. Springer Netherlands, Dordrecht
Mitchell DRG (n.d.) Mean free path estimator. http://www.dmscripting.com/meanfreepathestimator.html. Accessed 21 Mar 2019
Mitchell DRG (2006) Determination of mean free path for energy loss and surface oxide film thickness using convergent beam electron diffraction and thickness mapping: a case study using Si and P91 steel. J Microsc 224:187–196. https://doi.org/10.1111/j.1365-2818.2006.01690.x
Mitchell DRG, Schaffer B (2005) Scripting-customised microscopy tools for digital micrograph™. Ultramicroscopy 103:319–332. https://doi.org/10.1016/j.ultramic.2005.02.003
Moldovan S, Arenal R, Ersen O (2015) 3D nanometric analyses via electron tomography: application to nanomaterials. In: Deepak FL, Mayoral A, Arenal R (eds) Advanced transmission electron microscopy: applications to nanomaterials. Springer International Publishing, Cham, pp 171–205
Mondini S, Ferretti AM, Puglisi A, Ponti A (2012) PEBBLES and PEBBLEJUGGLER: software for accurate, unbiased, and fast measurement and analysis of nanoparticle morphology from transmission electron microscopy (TEM) micrographs. Nanoscale 4:5356–5372. https://doi.org/10.1039/c2nr31276j
Nakafuji A, Murakami Y, Shindo D (2001) Effect of diffraction condition on mean free path determination by EELS. J Electron Microsc 50:23–28. https://doi.org/10.1093/jmicro/50.1.23
Nowack B, Bucheli TD (2007) Occurrence, behavior and effects of nanoparticles in the environment. Environ Pollut 150:5–22. https://doi.org/10.1016/j.envpol.2007.06.006
Pace HE, Rogers NJ, Jarolimek C, Coleman VA, Gray EP, Higgins CP, Ranville JF (2012) Single particle inductively coupled plasma-mass spectrometry: a performance evaluation and method comparison in the determination of nanoparticle size. Environ Sci Technol 46:12272–12280. https://doi.org/10.1021/es301787d
Park C, Huang JZ, Ji JX, Ding Y (2013) Segmentation, inference and classification of partially overlapping nanoparticles. IEEE Trans Pattern Anal Mach Intell 35:1–1. https://doi.org/10.1109/TPAMI.2012.163
ParticleLab (2019) How to prepare a TEM sample by centrifugation. https://www.youtube.com/watch?v=PplBlJ7zCCA. Accessed 3 Aug 2019
Plitzko JM, Mayer J (1999) Quantitative thin film analysis by energy filtering transmission electron microscopy. Ultramicroscopy 78:207–219. https://doi.org/10.1016/S0304-3991(99)00021-2
Potapov PL (2014) The experimental electron mean-free-path in Si under typical (S)TEM conditions. Ultramicroscopy 147:21–24. https://doi.org/10.1016/j.ultramic.2014.05.010
Potenza MAC, Krpetić Ž, Sanvito T, Cai Q, Monopoli M, de Araújo JM, Cella C, Boselli L, Castagnola V, Milani P, Dawson KA (2017) Detecting the shape of anisotropic gold nanoparticles in dispersion with single particle extinction and scattering. Nanoscale 9:2778–2784. https://doi.org/10.1039/C6NR08977A
Prasad A, Lead JR, Baalousha M (2015) An electron microscopy based method for the detection and quantification of nanomaterial number concentration in environmentally relevant media. Sci Total Environ 537:479–486. https://doi.org/10.1016/j.scitotenv.2015.07.117
Pyrz WD, Buttrey DJ (2008) Particle size determination using TEM: a discussion of image acquisition and analysis for the novice microscopist. Langmuir 24:11350–11360. https://doi.org/10.1021/la801367j
Reimer L (ed) (1995) Energy-filtering transmission electron microscopy. Springer-Verlag, Berlin Heidelberg
Roco MC, Bainbridge WS (2005) Societal implications of nanoscience and nanotechnology: maximizing human benefit. J Nanopart Res 7:1–13. https://doi.org/10.1007/s11051-004-2336-5
Savitzky A, Golay M (1964) Smoothing + differentiation of data by simplified least squares procedures. Anal Chem 36:1627–1639. https://doi.org/10.1021/ac60214a047
Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9:676–682. https://doi.org/10.1038/nmeth.2019
Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to ImageJ: 25 years of image analysis. Nat Methods 9:671–675. https://doi.org/10.1038/nmeth.2089
Schöpe HJ, Marnette O, van Megen W, Bryant G (2007) Preparation and characterization of particles with small differences in polydispersity. Langmuir 23:11534–11539. https://doi.org/10.1021/la7018132
Tan YZ, Cheng A, Potter CS, Carragher B (2016) Automated data collection in single particle electron microscopy. Microsc Oxf Engl 65:43–56. https://doi.org/10.1093/jmicro/dfv369
Thomas JM, Midgley PA, Ducati C, Leary RK (2013) Nanoscale electron tomography and atomic scale high-resolution electron microscopy of nanoparticles and nanoclusters: a short survey nanoscale electron tomography and atomic scale high-resolution electron microscopy of nanoparticles and nanoclusters: a short survey retain. Prog Nat Sci Mater Int 23:222–234. https://doi.org/10.1016/j.pnsc.2013.04.003
von der Kammer F, Legros S, Hofmann T et al (2011) Separation and characterization of nanoparticles in complex food and environmental samples by field-flow fractionation. TrAC Trends Anal Chem 30:425–436. https://doi.org/10.1016/j.trac.2010.11.012
Wagner T (2016) ij-particlesizer: ParticleSizer 1.0.1. Zenodo. https://doi.org/10.5281/zenodo.56457
Wagner T, Behnel P (2015) ij-non-local-means: ImageJ plugin for non-local-means filtering. Figshare. https://doi.org/10.6084/m9.figshare.878038.v6
Wick S, Baeyens B, Fernandes MM, Voegelin A (2018) Thallium adsorption onto illite. Environ Sci Technol 52:571–580. https://doi.org/10.1021/acs.est.7b04485
Wiesner MR, Lowry GV, Alvarez P, Dionysiou D, Biswas P (2006) Assessing the risks of manufactured nanomaterials. Environ Sci Technol 40:4336–4345. https://doi.org/10.1021/es062726m
Acknowledgments
The authors would like to thank ScopeM (ETH), Felmi-ZFE (TU Graz), Center for Microscopy and Image Analysis (UZH), Department of Materials and Environmental Chemistry (Stockholm University), Nanomicroscopy Center (Aalto University), and Electronmicroscopy Unit (University of Helsinki) for collaboration and technical support. A special appreciation belongs to Dr. Bernhard Schaffer (Gatan) for helpful discussions and support. Dr. Andreas Voegelin is acknowledged for providing illite suspensions.
Funding
This work was accomplished within the NanoDefine project—and has been made possible from the funding of European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604347 and grant agreement 312483—ESTEEM2 (Integrated Infrastructure Initiative I3).
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Uusimaeki, T., Wagner, T., Lipinski, HG. et al. AutoEM: a software for automated acquisition and analysis of nanoparticles. J Nanopart Res 21, 122 (2019). https://doi.org/10.1007/s11051-019-4555-9
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DOI: https://doi.org/10.1007/s11051-019-4555-9