FprCEN/TS 18267

SLOVENSKI STANDARD
01-februar-2026
Nanotehnologije - Smernice za pripravo vzorcev, odkrivanje, identifikacijo in
karakterizacijo nanoobjektov v anorganskih dodatkih, vključenih v živilske
matrice, s spICP-MS in EM-EDX
Nanotechnologies - Guidelines for sample preparation, detection, identification and
characterization by spICP-MS and EM-EDX of nano-objects in inorganic additives
incorporated in food matrices
Nanotechnologien - Richtlinien zur Charakterisierung von nanoobjekthaltigen
Zusatzstoffen in Lebensmitteln
Nanotechnologies - Directives pour la caractérisation d'additifs contenant des nanoobjets
dans des denrées alimentaires
Ta slovenski standard je istoveten z: FprCEN/TS 18267
ICS:
07.120 Nanotehnologije Nanotechnologies
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

FINAL DRAFT
TECHNICAL SPECIFICATION
SPÉCIFICATION TECHNIQUE
TECHNISCHE SPEZIFIKATION
November 2025
ICS 07.120
English Version
Nanotechnologies - Guidelines for sample preparation,
detection, identification and characterization by spICP-MS
and EM-EDX of nano-objects in inorganic additives
incorporated in food matrices
Nanotechnologies - Directives pour la caractérisation Nanotechnologien - Richtlinien zur Charakterisierung
d'additifs contenant des nanoobjets dans des denrées von nanoobjekthaltigen Zusatzstoffen in Lebensmitteln
alimentaires
This draft Technical Specification is submitted to CEN members for Vote. It has been drawn up by the Technical Committee
CEN/TC 352.
CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,
Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway,
Poland, Portugal, Republic of North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and
United Kingdom.
Recipients of this draft are invited to submit, with their comments, notification of any relevant patent rights of which they are
aware and to provide supporting documentation.

Warning : This document is not a Technical Specification. It is distributed for review and comments. It is subject to change
without notice and shall not be referred to as a Technical Specification.

EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION

EUROPÄISCHES KOMITEE FÜR NORMUNG

CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels
© 2025 CEN All rights of exploitation in any form and by any means reserved Ref. No. FprCEN/TS 18267:2025 E
worldwide for CEN national Members.

Contents Page
European foreword . 5
Introduction . 6
1 Scope . 8
2 Normative references . 8
3 Terms and definitions . 8
4 General considerations . 10
5 Overview of the applicability and limitations of EM and spICP-MS . 12
5.1 General. 12
5.2 EM-EDX . 12
5.2.1 General. 12
5.2.2 Scanning electron microscope (SEM) . 13
5.2.3 Transmission electron microscopy (TEM) . 13
5.2.4 Energy Dispersive X-ray Spectroscopy (EDX). 14
5.2.5 Image acquisition and calibration . 14
5.2.6 Image analysis . 14
5.2.7 Data analysis and reporting . 15
5.2.8 Measurement uncertainties . 15
5.3 spICP-MS . 16
5.3.1 General considerations . 16
5.3.2 Considerations for specific food additives . 17
5.3.3 Data analysis and reporting . 18
5.3.4 Measurement uncertainties . 18
5.4 Method selection . 18
6 Guidance on sample preparation . 20
6.1 General. 20
6.2 Extraction or digestion protocols for different types of food matrices . 20
6.3 Removal of matrix components and residues . 21
6.3.1 General. 21
6.3.2 Removal of matrix components and residues for spICP-MS analysis . 21
6.3.3 Removal of matrix components and residues for EM analysis . 21
6.4 Dispersion stabilisation . 21
6.5 Specific considerations for EM-EDX measurements . 22
6.5.1 Particle concentration . 22
6.5.2 Deposition of the particles on the grids or on the substrate . 22
6.6 Specific consideration for spICP-MS measurements . 22
6.6.1 Specific sample preparation steps . 22
6.6.2 Detector saturation . 23
6.6.3 Data processing and data reporting . 23
7 Examples of specific protocols for the extraction and the analysis of E 171 and E 172
in different food matrices . 24
Annex A (informative) Context of food additives and nano-objects . 25
A.1 General. 25
A.2 Titanium dioxide (E 171) . 25
A.3 Iron oxides and hydroxides (E 172) . 26
A.4 Synthetic Amorphous Silica (E 551) . 26
Annex B (informative) Protocol for the analysis of E 171 in sugar shell confectionary
products by spICP-MS . 27
B.1 Introduction . 27
B.2 Apparatus and Equipment. 27
B.3 Chemicals and reagents . 28
B.4 Analysis . 28
B.5 Case study: E 171 in Sugar Shell Confectionary by spICP-MS . 33
Annex C (informative) Protocols for the analysis of E 171 in complex
food matrices by EM-EDX . 36
C.1 Introduction . 36
C.2 Food samples . 36
C.3 Apparatus, equipment and consumables. 37
C.4 Chemicals and reagents . 37
C.5 Preparation of the stock solutions . 37
C.6 Calculations and preliminary information . 38
C.7 Procedure . 38
C.8 Results . 40
Annex D (informative) Protocol for the analysis of E 172 in sugar shell confectionary
products by EM-EDX . 44
D.1 Introduction . 44
D.2 Equipment . 44
D.3 Chemicals and reagents . 44
D.4 Analysis of the additive incorporated in sugar shell confectionary. 44
D.5 Optional: Analysis of the pristine additive . 47
D.6 Case study: E 172 included in sugar-based cake decorations . 48
Annex E (informative) Protocol for the analysis of E 172 in sugar shell confectionary
products by spICP-MS . 51
E.1 Introduction . 51
E.2 Apparatus and equipment . 51
E.3 Chemicals and reagents . 52
E.4 Sample preparation . 52
E.5 Case study: E 172 (ii) and E 172 (iii) in Sugar-based Confectionary by spICP-MS . 56
Annex F (informative) Preliminary measurement of unknown samples . 61
F.1 General . 61
F.2 Chemical and physical properties of the additive of interest . 61
F.3 Total mass of the additive in the matrix . 61
F.4 Stability of the pristine additive in liquid-based media . 61
Annex G (informative) Best practice for the sonication of the particles . 62
G.1 Determination of the acoustic power delivered by the sonication device . 62
G.2 Precautions to be taken if you use the direct tip sonication approach . 64
Annex H (informative) Calculation of the centrifugation speed . 66
Annex I (informative) Example of particle deposition protocols for EM measurements . 67
I.1 Static deposition of negatively charged nanoparticles on a positively charged grid . 67
I.2 Deposition of negatively charged nanoparticles on a positively charged silicium
substrate by spin-coating . 67
Bibliography . 68

European foreword
This document (FprCEN/TS 18267:2025) has been prepared by Technical Committee CEN/TC 352
“Nanotechnologies”, the secretariat of which is held by AFNOR.
This document is currently submitted to the Vote on TS.
This document has been prepared under a standardization request addressed to CEN by the European
Commission. The Standing Committee of the EFTA States subsequently approves these requests for its
Member States.
The purpose of this document is to assist in the use of the following standards in the context of extraction,
detection identification and quantification of nano-objects-in pure additives and in additives contained
in food matrices:
— EN ISO 3696:1995, Water for analytical laboratory use — Specification and test methods
(ISO 3696:1987)
— CEN/TS 17273:2018, Nanotechnologies — Guidance on detection and identification of nano-objects in
complex matrices
— CEN ISO/TS 19590:2024, Nanotechnologies — Characterization of nano-objects using single particle
inductively coupled plasma mass spectrometry (ISO/TS 19590:2024)
— EN ISO 19749:2023, Nanotechnologies — Measurements of particle size and shape distributions by
scanning electron microscopy (ISO 19749:2021)
— EN ISO 21363:2022, Nanotechnologies — Measurements of particle size and shape distributions by
transmission electron microscopy (ISO 21363:2020)
— CEN ISO/TS 23302:2022, Nanotechnologies — Requirements and recommendations for the
identification of measurands that characterise nano-objects and materials that contain them
(ISO/TS 23302:2021)
Introduction
Nano-objects can be present in food/feed matrices and have various origins, such as certain additives and
processing aids. These substances containing nano-objects can be categorized as:
— ‘engineered nanomaterial’ as defined in Regulation (EU) 2015/2283 on novel foods and in
Regulation (EU) No 1169/2011 of the European Parliament and of the Council on the provision of
food information to consumers;
— ‘nanomaterial’ as defined by the Commission Recommendation (2022/C 229/01) on the definition of
nanomaterial;
— materials not meeting a regulatory definition of a nanomaterial but which contain a fraction of
nano-objects or small particles, as for example defined by the EFSA [1] [2].
However, it should be noted that nano-objects can also arise e.g. as by-products of the production process,
or during handling and processing of foods, or they can be of natural origin. This document focuses on
nano-objects in food matrices regardless of their origin, as the current analytical methodologies do not
allow a reliable determination of the origin of nano-objects. The presented approaches, useful for analysis
of nano-objects in food, are equally applicable to analysis of small particles defined in the EFSA Guidance
on Particle – Technical Requirements [1].
To improve information on the presence of nano-objects in food originating from additives, industrial
players along the value chain and the EU Member State (MS) control laboratories need to be able to
evaluate their presence and to characterize the number-based particle size distribution of the food
additive after it has been incorporated in food matrices. This will enable a more efficient implementation
of the regulatory requirements applicable to food ingredients that fall within the scope of the ‘engineered
nanomaterial’ definition. Additionally, it will also be of general value in assessing particles at the
nanoscale.
Existing guidance and standards may be general e.g. CEN/TS 17273:2018, CEN ISO/TS 19590:2024,
EN ISO 19749, EN ISO 21363:2022, which strongly focus on the provision of general measurement
principles for several techniques. Details on e.g. sample preparation are not included, although this step
has a critical impact on the (nano)particles size distribution measurements.
This document focuses on describing method-specific sample preparation approaches required to extract
nano-objects from food matrices and providing a library of specific protocols for ex situ characterization
of nanoparticles. It addresses approaches that destruct and remove various types of food matrices, purify
and concentrate the nanoparticles of interest, and disperse them so that individual particles can be
measured, without altering their physicochemical properties. This information can be complementary to
the guidance on detection and identification of nano-objects in complex matrices provided
in CEN/TS 17273:2018. Please note that sample preparation approaches for organic food additives are
not covered, as the state-of-the-art analytical methods do not reliably allow the separation and
identification of such substances.
Once extracted, the “constituent particles” composing the material can be identified and counted. It
should be noted that the terminologies between ISO, CEN and European Commission regulatory
framework are different as detailed in sublause 6.3 of FprCEN/TS 18269, “Nanotechnologies - Guidance
on the determination of the aggregation and agglomeration state of nano-objects”. The counting of
constituent particles in various legislation varies in different countries and application domains [3].
Electron microscopy (EM) is important as it can measure the size of constituent particles in agglomerates
and aggregates, in contrast to most other techniques (e.g. ensemble techniques, single particle inductively
coupled plasma mass spectrometry (spICP-MS)) [4]. spICP-MS and EM coupled to Energy-dispersive
X-ray spectroscopy -(EDX) are key techniques to determine the number size distribution of a given
particulate substance in complex samples where several substances may be present, since they can target
a given chemical composition. spICP-MS cannot distinguish constituent particles in agglomerates/
aggregates.
In this document, spICP-MS and EM-EDX methods are therefore selected as they provide complementary
information on the key chemical and physical attributes required to support the implementation of the
food legislation. The measurement performance of the methods presented in this document has been
assessed through inter-laboratory comparison on selected inorganic food additives contained in food
matrices present on the market, used as case studies.
The procedures reported in this document can also be applied to the characterization of nano-objects in
pristine additives. This document can also be considered as a starting point to develop methodologies for
measuring other substances containing nano-objects that are either i) added to food, but that are not
classified as food additives (e.g. minerals, vitamins, enzymes, flavourings), or ii) inorganic additives
contained in medicinal products, feed additives and cosmetics.
1 Scope
This document provides guidance to the food industry, service providers and control laboratories on
methodologies to be used for sample preparation, detection, identification and measurement of
nano-objects in inorganic food additives incorporated in food matrices.
Electron microscopy combined with energy dispersive X-ray spectroscopy (EM-EDX) and inductively
coupled plasma mass spectrometry (ICP-MS) operated in single particle mode (spICP-MS) are the
selected measurement methodologies to provide information on (i) the chemical composition
and (ii) number-based particle size distribution of the nano-objects.
Special attention is given to the sample preparation, including matrix digestion, sample extraction and
dilution steps to be used according to the combination of (i) the chemical nature of the food additive,
(ii) the type of food matrix and (iii) the analytical technique of choice (EM-EDX or spICP-MS).
2 Normative references
There are no normative references in this document.
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp/
— IEC Electropedia: available at https://www.electropedia.org/
3.1
agglomerate
collection of weakly or medium strongly bound particles where the resulting external surface area is
similar to the sum of the surface areas of the individual components
Note 1 to entry: The forces holding an agglomerate together are weak forces, for example van der Waals forces
or simple physical entanglement.
Note 2 to entry: Agglomerates are also termed secondary particles and the original source particles are termed
primary particles.
[SOURCE: EN ISO 80004-1:2023, 3.2.4]
3.2
aggregate
particle comprising strongly bonded or fused particles where the resulting external surface area is
significantly smaller than the sum of surface areas of the individual components
Note 1 to entry: The forces holding an aggregate together are strong forces, for example, covalent or ionic bonds,
or those resulting from sintering or complex physical entanglement.
Note 2 to entry: Aggregates are also termed secondary particles and the original source particles are termed
primary particles.
[SOURCE: EN ISO 80004-1:2023, 3.2.5]
3.3
constituent particle
identifiable, integral component of a larger particle
Note 1 to entry: The constituent particle structures can be primary particles or aggregates.
Note 2 to entry: According to the EC Recommendation 2022/C 229/01, constituent particles can be present,
either as particles that are present on their own or as identifiable particles in aggregates and agglomerates.
Note 3 to entry: The EC defines the constituent particle as ‘the (morphologically) identifiable particles, including
those inside an aggregate or agglomerate. In agglomerates the constituent particles are only weakly bound. In
aggregates the constituent particles are strongly bound. Ensemble-based techniques cannot be used to measure the
size of constituent particles in aggregates and agglomerates [4, 5].
[SOURCE: EN ISO 80004-1:2023, 3.2.3, modified – added Notes 2 and 3 to entry.]
3.4
minimum feret diameter
minimum length of an object whatever its orientation
Note 1 to entry: The Feret diameter or Feret's diameter is a measure of an object size along a specified direction;
it is applied to projections of a three-dimensional object on a two-dimensional plane. It is also called the caliper
diameter.
Note 2 to entry: The maximum Feret diameter (xFmax) is the “length” of the particle. The minimum Feret
diameter (xFmin) is the “breadth” of the particle.
Note 3 to entry: The Feret diameter depends on the orientation of the particle with respect to tangents, so a single
measurement cannot always be representative. If all possible orientations are considered, for a convex particle with
the particle perimeter P: P = π xFmean (Cauchy theorem). There is no such relation between P and xFmean for a concave
object.
[SOURCE: EN ISO 19749:2023]
3.5
food additive
substance that is not normally consumed as a food by itself and that is not normally used as a typical
ingredient of food, but are intentionally added to food to exert a technological purpose in the
manufacture, processing, preparation, treatment, packing, packaging, transport or holding of such food
Note 1 to entry: In the European Union all food additives are identified by an E number. Food additives are always
included in the ingredient lists of foods in which they are used. Product labels must identify both the function of the
additive in the finished food (e.g. colour, preservative) and the specific substance used either by referring to the
appropriate E number or its name (e.g. E 415 or Xanthan gum). The most common additives to appear on food labels
are antioxidants (to prevent deterioration caused by oxidation), colours, emulsifiers, stabilisers, gelling agents and
thickeners, preservatives and sweeteners.
Note 2 to entry: See Annex A (informative).
[SOURCE: Codex Alimentarius — General Standard for the Labelling of Prepackaged Food (CODEX
STAN 1-1985)]
3.6
nano-object
discrete piece of material with one, two or three external dimensions in the nanoscale
[SOURCE: EN ISO 80004-1:2023, 3.1.5]
3.7
nanoscale
length range approximately from 1 nm to 100 nm
[SOURCE: EN ISO 80004-1:2023, 3.1.1]
3.8
particle
minute piece of matter with defined physical boundaries
Note 1 to entry: A physical boundary can also be described as an interface.
Note 2 to entry: This general particle definition applies to nano-objects.
[SOURCE: EN ISO 80004-1:2023, 3.2.1]
3.9
processing aid
substance which is added during food processing to confer particular characteristics; for example, yeast
added to bread
[SOURCE: EFSA glossary [6]]
4 General considerations
Over the past decade an increasing number of food additives and processing aids has been shown to
contain a fraction of nano-objects, in particular due to the progress of analytical techniques.
Nano-objects in food can be a part of engineered/manufactured ingredients, such as certain food
additives, or they can be of natural origin, as for example the nanostructured amorphous silica found in
rice [8], or in plant fibres [9].
The European Food Safety Authority (EFSA) released a Guidance on technical requirements for regulated
food and feed product applications to establish the presence of small particles including nanoparticles [1]
which sets out mandatory information requirements in accordance with Regulation (EC) No 1925/2006.
It indicates when the EFSA Guidance on risk assessment of nanomaterials in the food and feed chain [2]
needs to be applied. Information regarding the fraction of nanoparticles, such as their number-based size
distribution, is required to help assess possible risks that can be related to the particulate character of a
food additive, and to evaluate compliance with its specifications.
However, standardized methods for sample preparation, detection, identification and measurement of
particles in inorganic additives incorporated in food are missing today. These are required for monitoring
exposure levels to nano-objects and small particles in regulated food and feed applications and verifying
associated regulatory requirements. Such methods require that the particles of interest are identified
among the food matrix material which often also consists of other particles, and that their relevant
properties, including their size, can be accurately measured.
CEN/TS 17273:2018 provides guidance on detection and identification of nano-objects in complex
matrices. It addresses specifically their detection in complex food matrices which might contain an
elevated level of inorganic salts, organic contaminants and larger organic and inorganic particles. It
stipulates that for each type of particle two measurands have to be considered: the size is needed for
classification of particles as nano-objects, and the elemental composition is needed to discriminate the
target particles with an a priori known elemental composition from the matrix and background particles.
CEN/TS 17273:2018 proposes as applicable characterization methods: i) the use of EM equipped with
energy dispersive X-ray spectroscopy (EDX) to determine the elemental composition of the particles,
additionally to their geometrical measures and ii) single particle inductively coupled plasma – mass
spectrometry (spICP-MS) as an elemental specific detection system that gives as well size related
information. EM-EDX and spICP-MS are most suitable for the analysis of inorganic nano-objects. The
techniques cannot determine the origin of the detected inorganic particles, i.e. whether the particles are
of natural origin or engineered/manufactured particles. Field Flow Fractionation (FFF) based techniques,
proposed in CEN/TS 17273:2018, are not considered within the scope of this technical specification
because they require extensive optimisation for each particle/food matrix combination.
The analysis requires a priori information regarding the elemental composition of the particles of
interest. This can be obtained from the ingredients list, which is mandatory and includes food additives,
or, in a control setting, from chemical analysis measuring total element content (e.g. ICP-MS). The sample
preparation is key in all cases as the particles should be extracted from the food matrices before their
characterization.
The approach for sample preparation prior to the analysis of the nano-objects incorporated in food
matrices should be considered as a step-by-step process as described in the flow chart presented
in Figure 1.
It includes the following main steps:
1. matrix dissolution or destruction and extraction of the particles from the food matrix;
2. removal of matrix components and residues;
3. particles deagglomeration;
4. specific sample preparation steps, associated to the measurement technique(s) and measurands
selected.
Those steps should be optimized depending on the physicochemical properties of the additives to be
analysed and its concentration in the food matrix, the composition of the food matrices and the
measurement technique selected (see Clause 7).
Purified water refers to the following specifications: resistivity of 18,2 MΩ*cm at 25 °C and additionally
passed through a filter with cut-off of 0,2 µm or lower.
Figure 1 — Guidance chart for the sample preparation, detection, identification and
measurement by spICP-MS and EM-EDX
5 Overview of the applicability and limitations of EM and spICP-MS
5.1 General
EM and spICP-MS described in this document are amongst the most established analytical approaches,
able to detect and identify inorganic nano-objects extracted from food matrices.
5.2 EM-EDX
5.2.1 General
Electron microscopy (EM) is a versatile technique to analyse the morphology, chemical composition and
crystallographic structure of a wide range of particles.
It can be considered highly suitable for the characterization of nano-objects for several reasons [5]. First,
EM analysis is one of the few methods that can reliably provide a spatial resolution covering the complete
nanoscale size range from 1 nm to 100 nm. The combination of EM imaging with image analysis allows
determining the physical properties (size, shape and surface morphology) of constituent particles
quantitatively, based on the characteristics of their 2D projections.
Multiple properties can be measured simultaneously for each constituent particle, from which
descriptive statistics and corresponding number-based distributions can be determined, as requested in
legislation and guidelines [5, 10]. EM allows assessing in a qualitative way whether a material contains
aggregates/agglomerates, e.g. in relation to the efficacy of the dispersion protocol. Spectroscopy methods
such as EDX and electron energy loss spectroscopy (EELS) can be incorporated in the electron microscope
for elemental analysis of nano-objects allowing characterization of subpopulations of nano-objects in
mixtures, and nano-objects in the context of a complex matrix.
Despite the wealth of information that can be obtained, the applicability of EM to characterize particles
is currently limited by the following factors:
a) The particles transferred to the grid or substrate should be representative for the population of
particles present in the original food/feed product. This is influenced by the sample preparation,
including removal of matrix components and residues and concentration steps, and by the particle
deposition on the grid or substrate used for EM observations [11, 12].
b) EM methods typically measure the two dimensions of particles perpendicular to the electron beam,
but do not assess the dimension parallel to the beam. As a result, measurements of particles that have
a preferential orientation on the EM-grid, such as platelets, can lead to biased results. For such cases,
more advanced EM based methods, such as tomography, or alternative sample preparation methods
can be considered [13].
This TS focuses on approaches for EM characterization of nano-objects using SEM, TEM and STEM
equipped with EDX. More advanced EM methodologies are excluded from this TS.
5.2.2 Scanning electron microscope (SEM)
Scanning electron microscopy (SEM) produces images by scanning the surface of a sample with a focused
electron beam. The electrons interact with atoms in the sample, producing various signals that contain
information about the surface topography and composition of the sample. The energy exchange between
the electron beam and the sample results in the reflection of high-energy electrons by elastic scattering,
emission of secondary electrons by inelastic scattering and the emission of electromagnetic radiation,
each of which can be detected independently by specialized detectors. The dimensional parameters can
be derived from SEM images by the observation and counting of isolated and constituent particles. More
detailed information on the measurement principle and the related equations can be found
in EN ISO 19749:2023.
Some SEM instruments can be equipped with a transmission detector placed underneath the specimen
to detect transmitted primary electrons [14]. For some materials this method, which is called TSEM, can
provide an economical and efficient alternative for obtaining micrographs with a higher resolution than
achieved with SEM in normal scanning mode.
5.2.3 Transmission electron microscopy (TEM)
A transmission electron microscope (TEM) uses an electron source to generate a primary electron beam,
which is accelerated by an electric potential and projected onto a thin specimen through a set of lenses
and apertures. Part of the electron beam can pass through the specimen without interacting with it. Other
electrons will be scattered by the specimen. The information contained in the electron waves that exit
from the specimen is used to create an image. At low magnifications, TEM image contrast originates from
the absorption and scattering of electrons in the specimen, due to the thickness and composition of the
material (i.e. mass-thickness contrast), and from the crystal orientation (i.e. diffraction contrast). By
analysing the image determined by the mass-thickness contrast of the nano-objects, information on the
number-based size and shape distributions can be obtained. Electron diffraction can be applied to
determine their crystal structure. More detailed information on the measurement principle and the
related equations can be found in EN ISO 19749:2023.
TEM can be operated in scanning mode (STEM), where the electron beam is focused into a (sub-)
nanometer-sized probe and scans over the specimen. Various signals produced by the scattering of the
electrons can be detected and displayed as a function of the probe position. The interactions with the
specimen give accurate localized physical and chemical information. Often images are created using a
geometrically large ring-shaped detector, placed in the optical far field beyond the specimen. This is
called a high angle annular dark-field (HAADF) detector. Because of the detector geometry, only electrons
that are scattered at high angle, which are predominantly incoherent are detected [15]. Since high angle
incoherent scattering is associated with scattering from the atomic nuclei, it gives an intensity
1.6-2
approximately proportional with the squared atomic number (I~Z ), as expected on the basis of
Rutherford scattering. This imaging mode is therefore also called Z-contrast imaging. One of the
advantages of HAADF-STEM imaging is the possibility to visually distinguish materials with a different
chemical composition. Furthermore, if the elements contained in the specimen are known, an
HAADF-STEM image gives directly a qualitative 2D distribution of the different materials in the specimen.
5.2.4 Energy Dispersive X-ray Spectroscopy (EDX)
The elemental composition of each individual particle can be obtained by analysing the energy of
the X-rays emitted from the EM specimen during irradiation by the electron beam. Because the X-ray
energy is characteristic for the electronic structure of the atom, it can be used for both qualitative and
quantitative elemental analysis. Energy Dispersive X-ray spectroscopy (EDX) can be incorporated in most
TEM and SEM systems. In a TEM, EDX is usually performed in STEM mode to obtain high spatial
resolution. EDX spectral imaging combines the spatial information obtained in S(T)EM mode with
the X-ray signals to construct elemental distributions of each detected element in a pre-defined region.
As an alternative to EDX, electron energy loss spectroscopy (EELS) can be applied (out of scope of this
document).
Elemental analysis by EM-EDX allows the identification of the nano-objects of interest. Based on their
EDX signal, other types of particles present in the sample, such as Ti-Al flakes originating from the
sonicator probe (Annex G), can also be identified and, when necessary, deleted from the datasets.
5.2.5 Image acquisition and calibration
A set of calibrated images that representatively show the particles on the EM specimen should be
recorded, following EN ISO 19749:2023 or EN ISO 21363:2022.
Recording of at least 10 images at positions pre-defined in the microscope stage by the operator and
evenly distributed over the entire grid area is suggested to avoid subjectivity in the selection of particles
by the analyst.
The useful working range of EM is defined by the lower and upper size quantification limits. The lower
size quantification limit is calculated based on an objective criterion which assures precise measurement.
Merkus [16], for example, showed that large (> 10 %) systematic deviations in size measurements can be
avoided if the particle area consists of at least hundred pixels, which corresponds to a circle diameter of
approximately 11 pixels. For non-spherical particles such as rods and fibres, a minimal external
dimension of 10 pixels is suggested. Based on this criterion, taking into account the pixel size of the CCD
camera, the minimal magnification can be calculated as described in CEN/TS 17273:2018. The
corresponding upper limit of quantification (ULOQ) should be limited to one tenth of the image size,
(i.e. the upper limit of detection (ULOD)), supporting on ISO 13322-1:2014.
5.2.6 Image analysis
Particle detection is evaluated by visual inspection of annotated images. If they influence the
measurement result significantly, wrongfully detected particles and detected food matrix compounds
other than the particles of interest should be removed (manually) from the datasets, taking care not to
remove the particles belonging to the additive analysed.
The size and shape properties of the constituent particles of the food additives should be measured based
on the properties of their 2D projections either manually or (semi)-automatically using dedicated
software, such as the ParticleSizer software following the SOP “Measurement of the minimal external
dimension of the constituent particles of particulate materials from TEM images by the NanoDefine
ParticleSizer software” [17]. Automated routines are preferred. Manual interventions regarding particle
detection should be limited as much as possible, and only considered when automated routines are not
applicable, as illustrated by the analysis of SEM images of E 172 nano-objects (Annex D). In the future,
machine-learning based approaches will probably be useful for particle detection.
One of the factors that determine the robustness of the measurements is the number of analysed particles.
By the numerical method of Masuda and Gotoh described in ISO 13322-1:2014 which assumes a log-
normal distribution of the relevant measurand, and by determining the relation between the number of
measured particles and the measure
...