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A combined methodical approach is tested with respect to the characterization of the inner structure of porous TiO2 layers as typically used in modern dye sensitized solar cells (DSSC). Their performance is directly linked to the surface area of the pore network. The micrometer thick layer employed was manufactured by screen-printing of a starting TiO2 powder constituted of shape-controlled, bipyramidal anatase nanoparticles on FTO/glass substrates. The analytical methods exploited in our study are Focused Ion Beam (FIB) slicing followed by 3D reconstruction as well as the new approach transmission Kikuchi diffraction (TKD) technology in the scanning electron microscope (SEM). Size and shape distribution of the TiO2 NPs within the layer can be extracted. SEM in transmission mode and atomic force microscopy (AFM) have been used to verify the dimensional data obtained by the new combined methodical approach. Its analytical benefits but also the challenges and limitations are highlighted.
Das EMPIR-Förderprogramm wird kurz erläutert und laufende Projekte aus der Nanotechnologie werden vorgestellt. Der Schwerpunkt liegt auf Standardisierungsprojekten, die gemeinsam mit ISO/TC 229 'Nanotechnologies' und CEN/TC 352 'Nanotechnologies' zu neuen Normen führen sollten. Als Beispiel für laufende Nanotechnologie-Projekte mit Koordination aus Deutschland werden MagNaStand (PTB) und nPSize (BAM) gegeben.
Evaluation of electron microscopy techniques for the purpose of classification of nanomaterials
(2016)
Electron microscopy techniques such as TEM, STEM, SEM or TSEM (transmission in SEM) are capable of assessing the size of individual nanoparticles accurately. Nevertheless, the challenging aspect is sample preparation from powder or liquid form on the substrate, so that a
homogeneous distribution of well-separated (deagglomerated) particles is attained. The systematic study in this work shows examples where the extraction of the critical, smallest particle dimension - as the decisive particle parameter for the classification as a NM - is possible by analysing the sample after ist simple, dry preparation. The consequences of additional typical issues like loss of information due to screening of smaller particles by larger ones or the (in)ability to access the constituent particles in aggregates are discussed.
The present series of reports, the NanoDefine Methods Manual, has been developed within the NanoDefine project 'Development of an integrated approach based on validated and standardized methods to support the implementation of the EC recommendation for a definition of nanomaterial'1 funded by the European Union's 7th Framework Programme, under grant agreement 604347.
In 2011 the European Commission (EC) published the recommendation (2011/696/EU) for a definition of the term 'nanomaterial'1, the EC NM Definition, as a reference to determine whether an unknown material can be considered as a 'nanomaterial' for regulatory purposes. One challenge is the development of methods that reliably identify, characterize and quantify nanomaterials (NM) both as substances and in various products and matrices.
The overall goal of NanoDefine was to support the implementation of the EC NM Definition. It can also support the implementation of any NM definition based on particle size. The project has developed an integrated approach, which allows identifying any material as a nano or non-nano material according to the EC NM Definition. NanoDefine explicitly supported the governance challenges associated with the implementation of legislation concerning nanomaterials by:
- addressing the issues on availability of suitable measuring techniques, reference materials, validated methods, acceptable to all - developing an integrated and interdisciplinary approach and a close international co-operation and networking with academia, commercial firms and standardization bodies.
Thus, the NanoDefine Methods Manual provides guidance on practical implementation of the EC NM Definition throughout the nanomaterial characterization process, and on the characterization techniques employed as well as their application range and limits. It assists the user in choosing the most appropriate measurement method(s) to identify any substance or mixture for a specific purpose, according to the EC NM Definition of a nanomaterial. The NanoDefine project also explored how to assess a material against the criteria of the definition through proxy solutions, i.e. by applying measurement techniques that indirectly determine the D50. Those findings were developed through empirically based scientific work and are included in Part 1 of this Manual. As they go beyond the text of the EC NM Definition, they may be used as practical approach to indicate whether a material is a nanomaterial or not, but keeping in mind that they should not be taken as recommendation for the implementation of the EC NM Definition in a regulatory context.
The NanoDefine Methods Manual consists of the following three parts:
Part 1: The NanoDefiner Framework and Tools
Part 2: Evaluation of Methods
Part 3: Standard Operating Procedures (SOPs)
Part 1 covers the NanoDefiner framework, general information on measurement methods and performance criteria and tools developed by NanoDefine such as a materials categorisation system, a decision support flow scheme and an e-tool.
Part 2 discusses the outcome of the evaluation of the nanomaterials characterisation methods for measuring size.
Part 3 presents the 23 Standard Operating Procedures developed within the NanoDefine project. The current document is part 3.
The present series of reports, the NanoDefine Methods Manual, has been developed within the NanoDefine project 'Development of an integrated approach based on validated and standardized methods to support the implementation of the EC recommendation for a definition of nanomaterial', funded by the European Union's 7th Framework Programme, under grant agreement 604347.
In 2011 the European Commission (EC) published a recommendation for a definition of the term 'nanomaterial', the EC NM Definition, as a reference to determine whether an unknown material can be considered as a 'nanomaterial' for regulatory purposes1. One challenge is the development of methods that reliably identify, characterize and quantify nanomaterials (NM) both as substances and in various products and matrices.
The overall goal of NanoDefine was to support the implementation of the EC NM Definition. It can also support the implementation of any NM definition based on particle size. The project has developed an integrated approach, which allows identifying any material as a nano- or not a nanomaterial according to the EC NM Definition. NanoDefine explicitly supported the governance challenges associated with the implementation of legislation concerning nanomaterials by:
- addressing the issues on availability of suitable measuring techniques, reference materials, validated methods, acceptable to all stakeholders (authorities, policy makers, commercial firms),
- developing an integrated and interdisciplinary approach and a close international co-operation and networking with academia, commercial firms and standardization bodies.
Thus, the NanoDefine Methods Manual provides guidance on practical implementation of the EC NM Definition throughout the nanomaterial characterization process, and on the characterization techniques employed as well as their application range and limits. It assists the user in choosing the most appropriate measurement method(s) to identify any substance or mixture for a specific purpose, according to the EC NM Definition of a nanomaterial. The NanoDefine project also explored how to assess a material against the criteria of the definition through proxy solutions, i.e. by applying measurement techniques that indirectly determine the x50. Those findings were developed through empirically based scientific work and are included in Part 1 of this Manual. As they go beyond the text of the EC NM Definition, they may be used as practical approach to indicate whether a material is a nanomaterial or not, but keeping in mind that they should not be taken as recommendation for the implementation of the EC NM Definition in a regulatory context.
The NanoDefine Methods Manual consists of the following three parts:
Part 1: The NanoDefiner Framework and Tools
Part 2: Evaluation of Methods
Part 3: Standard Operating Procedures (SOPs)
Part 1 covers the NanoDefiner framework, general information on measurement methods and performance criteria and tools developed by NanoDefine such as a materials categorisation system, a decision support flow scheme and an e-tool.
Part 2 discusses the outcome of the evaluation of the nanomaterials characterisation methods for measuring size.
Part 3 presents the 23 Standard Operating Procedures developed within the NanoDefine project.
The current document is part 2.
Most industrial nanoparticles have non-spherical shapes and also possess polydisperse size distributions, and due to their agglomeration/ aggregation state are difficult (or even impossible) to be addressed individually. Further, driven by regulatory purposes related to the identification of a material as a nanomaterial, the accurate measurement of the smallest dimension of a (nano)particulate material makes the analysis even more complex.
In the first phase of the EU Project nPSize - Improved traceability chain of nanoparticle size measurements (https://www.bam.de/Content/DE/Projekte/laufend/nPSize/npsize.html), the efforts are focused on synthesis of nanoparticles of well-defined, non-spherical shape. Following candidates of reference materials (CRM) with certifiable particle size (distribution) are under characterization with respect to their homogeneity and stability: (i) titania nanoplatelets (10-15 nm thickness x 50-60 nm lateral), (ii) titania bipyramides (~60 nm length x 40 nm width), (iii) titania acicular particles (100 nm length x 15-20 nm width; aspect ratio 5.5/6), (iv) gold nanorods (~10 nm width x 30 nm length), and (v) gold nanocubes (~55 nm x 55 nm x 55 nm).
The present study addresses the capability of measurement of relative particle number concentration by scanning electron microscopy for model bimodal silica and gold samples prepared in the frame of the European research project “nPSize - Improved traceability chain of nanoparticle size measurements” as candidate reference nanoparticles.
Extraction of true, 3D shape (and size) of non-spherical nanoparticles (NPs) is associated with errors by conventional 2D electron microscopy using projection images. Significant efforts within the ISO technical committee TC 229 ‘Nanotechnologies’ are aimed at establishing accurate TEM and SEM measurement of NP size and shape as robust, standard procedures. Study groups have been organizing inter-laboratory comparisons on well-selected NP systems according to the market needs, such as aggregated titania nano-powder for which size and shape distribution of primary crystallites of irregular shape must be measured accurately. To be noticed is e. g. the fact that the measurement procedure allows only manual selection of the particles clearly distinguishable for analysis as well as manual definition of the contour of the imaged NPs.
An inter-laboratory exercise on titania NPs (pure anatase, grown by hydrothermal synthesis) of well-defined non-spherical shape, i.e. bipyramidal has been recently started within ISO/TC 229 under similar conditions as for the irregular shaped titania. Overlapped particles were allowed to be considered, as long as they are clearly distinguishable. One decisive NP selection criterion was to analyze only those NPs with a roundness value below 0.7, i.e. the NPs laying on the support foil and, hence, with projection areas clearly deviating from perfect circles (R=1). The overall evaluation (for 15 labs) of the size descriptors (area, Feret, minFeret, perimeter) and shape descriptors (aspect ratio, roundness, compactness, extent) by analysis of variance is just to be finished and included in ISO/WD 21363 Nanotechnologies -- Protocol for particle size distribution by transmission electron microscopy.
Nanomaterials and nanoparticles are finding applications across a wide range of technology sectors, from medicine and food to transportation and construction. In order to assess these new materials for potential risks to health and the environment, they need to be well-characterised. The measurement of constituent nanoparticle size, shape, and size distribution are important factors for the risk evaluation process.
EMPIR project Improved traceability chain of nanoparticle size measurements (17NRM04, nPSize) is working to assess a range of traceable nanoparticle measurement approaches, including Scanning Electron Microscopy (also in Transmission Mode), Atomic Force Microscopy and Small Angle X-ray Scattering, and deliver improved calibration methods to users. For the techniques under investigation, physical models of their response to a range of nanoparticle types are developed. Validated reference materials will also be used for an inter-comparison of measurement systems, with an evaluation of the associated measurement uncertainty. With project contributions to standards development work, manufacturers will be better placed to assess the human and environmental risks posed by nanomaterials across a whole range of products.
he main objective of the nPSize project is to improve the measurement capabilities for nanoparticle size based on both measurement methods traceable to SI units and new reference materials. Two basic approaches have been used in order to develop measurement procedures resulting in traceable results of the nanoparticle size distribution: physical modelling for the methods used in the project (TSEM, SEM, AFM and SAXS) and machine learning.
Physical modelling: In this part, the physical models associated with different shape measurements for the techniques TSEM, SEM, AFM and SAXS have been collected and further developed with the aim to simulate the resulting signal as measured by the individual methods. Uncertainties and traceability associated with each model were investigated and evaluated. In the following, the progress on these physical models is reported for each individual method.
Machine Learning modelling: The aim of this part is to use machine learning to enable automatic measurement of nanoparticle shape from expert a-priori information only. No physical model will be used as a-priori information in this task.
The accuracy and traceability of the size results obtained by each technique will be analyzed and compared with the physical modelling. A machine learning database will then be used to create automatic detection algorithms.