Field-Flow Fractionation techniques: state of the art

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Nanotechnology, metrology and size characterization

Generalities about nanomaterials


Nanomaterials (NMs) have been conceived and used by mankind since long time. One of the first use of nanomaterials goes back from ancient Egypt where the Egyptians used to dye their hair in black with a mixture constituted of past from lime, lead oxide and water. Nanoparticles (NPs) of galenite (lead sulfide) were formed during the mixing and offered an even and steady dying.
Another example is the Lycurgus cup made by the Romans in fourth century. Gold and silver NPs have been added during the fabrication of the cup glass giving to the cup the particularity to change color under certain lighting conditions (Bayda et al., 2020). Silver and gold NPs have also been used during the medieval age to give shining colors to the church windows. Figure 1 shows the effect of the size and the shape of NPs on the color reflected by the glass.
The concept/idea of nanotechnology was introduced in 1959 by the physicist and Nobel laureate Richard Feynman during a talk called “There’s plenty of room at the bottom”. The term “nanotechnology” was not pronounced but Feynman suggested the possibility of manipulating precisely the atoms and molecules. In 1974 the physicist Norio Taniguchi employed for the first time the term nanotechnology in a paper where he described the manufacturing of nanomaterials by breaking bigger material down until the nanoscale was reached (Taniguchi, 1974). The invention of the scanning tunneling microscope (STM) by Gerd Binnig and Heinrich Rohrer in 1981 allowed visualizing clusters of atoms. A few years later in 1990, a STM was used to manipulate 35 xenon atoms on a nickel surface and form the logo of the American company IBM. The nanotechnologies became popular with the discovery of carbon nanotubes and fullerene also known as “buckyball”. Since then, nanotechnologies continued their development and numerous applications in different fields (Bayda et al., 2020).


The term nano object has been defined by the International Standards Organization (ISO) as “a material which has one, two or three of their external dimensions in the nanoscale”. The nanoparticles are a category of nano object and are defined as “a nano object which have three of their external dimensions within the nanometric scale” (ISO/TS 80004-2:2015).
In the case of nanomaterials there is not, at this moment, a single definition adopted yet. A technical definition proposed by the ISO is “material with any external dimension in the nanoscale or having internal structure or surface structure in the nanoscale”. However, this definition based on size only may be insufficient for regulation purposes from safety point of view.
Yet, until now, there is no agreement between the different regulation agencies and this leads to multiple definitions or recommendations with different criteria(Boverhof et al., 2015). The recommendations proposed by the European Commission define a nanomaterial as “a natural, incidental or manufactured material containing particles, in an unbound state or as an aggregate or as an agglomerate and where, for 50% or more of the particles in the number size distribution, one or more external dimension is in the size range 1 nm-100 nm.” (Commission Recommendation of 18 October 2011 on the definition of nanomaterial Text with EEA relevance) The United States Environmental protection agency (EPA) chose a weight distribution criterion of 10%. EPA gives a list of criteria rather than a formal definition which is why it has not been quoted here (Boverhof et al., 2015). From the toxicology point of view, this difference of criteria is less relevant as the large particles will have a higher contribution in the distribution than the small one and shift the mean towards high value while it is precisely small particles that need to be monitored. However, weight distribution has the advantage to be easier to obtain as most of the analytical methods give a weight distribution.
The debate goes even further with the question: should we even define the term nanomaterial? Andrew D. Maynard wrote a paper named “Don’t define nanomaterials”(Maynard, 2011) where he exposed the risks of having a strict regulatory definition as exception may slip through the regulatory net. He proposed as replacement to establish a list of 9 or 10 attributes, which can represent nanomaterials with the particularity to be flexible enough to be adapted quickly depending on scientific knowledge.

Classification of nanomaterials

Whatever the exact definition is, every material is made up of arrangements of particular atoms in a specific way, which define its properties and behavior. A classification can be made with respect to the properties of these materials. In the case of nanomaterials, numerous classifications have been established (Tervonen et al., 2009; Stone et al., 2010; Glezer, 2011; Saleh, 2020). This section presents three different ways to classify nanomaterials.

Dimensional based classification

A classification has been made by ISO depending on the number of dimensions belonging in the nanoscale (1-100 nm). The Figure 2 shows the different dimensional based categories of nanomaterials.
Salesh and co-workers propose another classification based on the same principle of the number of dimensions but with a different terminology, where the NMs are divided in four classes (Saleh, 2020). The zero dimensional (0D) nanomaterials have its 3 dimensions in the nanoscale. This category includes NPs, quantum dots and atoms clusters. The one dimensional (1D) nanomaterials possess two dimensions in the nanoscale and the two dimensional (2D) NMs have only one dimension between 1 and 100 nm. The fourth category, the three dimensional nanomaterials (3D), include materials with no dimensions in the nanoscale but are constituted of nanocrystals which give them property belonging to the nanoscale (Saleh, 2020). The Figure 3 presents different examples of each category of NMs.

Classification based on chemical composition and structure

Based on the chemical composition and the structure, the NMs can be divided in five categories (López-Serrano et al., 2014):
1) Carbon based nanostructures: made up of carbon, this category is itself divided in two groups, which are the fullerenes, and the carbon nanotubes. The fullerene is an ensemble of 60 atoms of carbons at the minimum, which are assembled as a truncated icosahedron structure. Carbon based NMs have unique properties and are used in numerous fields. As an example, due to its good thermal and electrical conductivity the fullerene are applied in electronics and medicine (Sumi and Chitra, 2019).
2) Metal oxide NMs: this group include numerous transient metal oxides e.g. TiO2, SiO2, ZnO and CeO… Due to the decrease in size that influence the bandgap energy of materials, the metals oxide are applied can be applied as catalyst, chemical sensor or semiconductor(Saleh and Fadillah, 2019) .
3) Zero valent metal NMs: this group involves inorganic NMs composed of noble metal (Au, Ag) or transition metals (Fe, Zn). This category of nanomaterial is generally used as catalysers due to their reactivity (Kim and Lee, 2018)
4) Quantum dots: The quantum dots are semiconductor nanocrystal (CdSe, ZnS,PbS…)Their small size gives them unique optical and electronics properties. The electrical properties make them interesting in the construction of the solar panels while their optical properties are used in bioimaging (Bera et al., 2010)
5) Polymeric NMs: they are usually organic based nanomaterial, manly nanosphere or nanocapsular shaped. The nanospheres are matrix particles where molecules are adsorbed at the outer boundary of the particle surface. On the contrary, for the nanocapsular the molecules are trapped inside the NPs. This capacity to encapsulate molecules is widely used for drugs delivery (Khan, Saeed and Khan, 2019).

Origin based classification

According to this classification, NMs can be first divided in two categories: natural or anthropogenic. The anthropogenic category can also be divided in two groups depending if the NMs are created intentionally (engineered NMs) or unintentionally. NPs that have an involuntary or natural origin are generally called ultrafine particles(Dolez, 2015). Different emission sources of NMs have been classed in Table 1.

Fabrication methods

The different ways to synthetize NMs can be categorized into two types of processes: the top down and the bottom-up methods. Figure 4 shows the principle of these two processes (Ealias and Saravanakumar, 2017). The top-down method, also called destructive method, consists in reducing a bulk material to nanometric scale particles while the bottom-up or constructive methods consists to build NPs from the atoms.

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Top-down method

The most widely used synthesis methods belonging to this type of process are (Ealias and Saravanakumar, 2017):
– Mechanical milling: The bulk material is milled in an inert atmosphere down to the nanometric scale. Among the different types of milling, ball milling has been widely applied for the synthesis of various NMs. The principle consists to introduce a grinding material in a rotating chamber partially fill with balls. The process is easy to implement however the size distribution and morphology of the NMs produced can be very dispersed which orient the restrain the product application in fields where this polydispersity is not a problem (Ealias and Saravanakumar, 2017).
– Laser ablation: In laser ablation, a high-energy laser is used to vaporized material from a solid surface. The ionized particles ejected from the material combine each other to form the intended NMs. Even if the process is generally performed under vacuum it can also be performed in liquid solvents (Ealias and Saravanakumar, 2017)

Bottom-up method

The principal methods using this approach are(Ealias and Saravanakumar, 2017):
– Arc-discharge: A plasma is generated by an arc discharge between two electrodes. The plasma will then condense and form nanomaterial. As the plasma is generated from the electrode, The type of nanomaterial produced depends of the nature of the electrode e.g Carbon nanotube can be produced by graphite electrode (Tantra, 2015)
– Colloidal synthesis: In this method, metal complexes are reduced in dilute solutions. The solution will become supersaturated with metal atoms, which will nucleate to form NPs. The agglomeration of NPs is prevented by ensuring that the concentration of NPs is low enough or by adding a surfactant.
– Vapor vapour deposition: The principle of this method consists in depositing material on a surface from a precursor in vapor phase. The vapor phase deposition can be classified in 2 types: the chemical vapor phase deposition (CVD) and physical vapor phase deposition (PVD). In PVD the precursor only physically deposes the material on the surface while in CVD the precursor will also react chemically with the surface (Tantra, 2015).
– Flame synthesis: A precursor is evaporated and taken into a stream of inert gas. Fuel and an oxidizing agent are then added in the gas stream and then injected into a flame. NMs are then produced within the flame(Tantra, 2015).

Properties of nanoparticles

The NPs have the particularity to display different properties compared to the bulk material moreover, these properties can change in function of their size. We will explain in the following paragraph how the size can affect the properties of a material at the nanoscale by presenting two majors properties of the NPs, the surface effect and the quantum confinement and how they influence the others properties of the NPs (Ju-Nam and Lead, 2008; Khan, Saeed and Khan, 2019)

Surface effect

When a particle is at the nanoscale, the proportion of surface atoms compared to the total number of atoms is much bigger than a macroscopic object (Figure 5). This high ratio surface to volume increases the reactivity of NPs as they have more surface atoms available for a reaction, which makes them more sensitive to their environment than their bulk materials. This effect decreases significantly with the particle size. Figure 5 illustrates this tendency with a plot of the number of atoms at the surface of the particle in percent as a function of the particle size. The number of surface atom became non significant beyond 20 nm(Ju-Nam and Lead, 2008).

Table of contents :

Chapter I. Nanotechnology, metrology and size characterization
1. Generalities about nanomaterials
1.1. History
1.2. Definitions
1.3. Classification of nanomaterials
1.3.1. Dimensional based classification
1.3.2. Classification based on chemical composition and structure
1.3.3. Origin based classification
1.4. Fabrication methods
1.4.1. Top-down method
1.4.2. Bottom-up method
1.5. Properties of nanoparticles
1.5.1. Surface effect
1.5.2. Quantum confinement effect
1.6. Applications
1.6.1. Catalysis
1.6.2. Environmental applications
1.6.3. Medical applications
1.6.4. Optical applications
2. Characterization of nanomaterials
2.1. Size characterization techniques
2.1.1. Equivalent diameter
2.1.2. Dynamic light scattering
2.1.3. Single particle inductive coupled plasma mass spectrometry SP-ICP-MS
2.1.4. Multi angle light scattering
2.1.5. Electronic microscopy
2.1.6. Atomic force microscopy
2.1.7. Particle tracking analysis
2.1.8. Small-angle X-ray scattering
2.1.9. Tunable resistive pulse sensing (TRPS)
2.1.10. Numerous techniques and numerous mesurands
3. Fractionations techniques
3.1. Field Flow Fractionation
3.2. Size exclusion chromatography
3.3. Analytical ultracentrifugation and centrifugal liquid sedimentation
4. Metrology
4.1. International system of units
4.2. Metrological Traceability
4.3. Measurement uncertainties
Chapter II. Field-Flow Fractionation techniques: state of the art
1. FFF principle
1.1. Elution modes
1.2. Theoretical formalization
1.3. Working hypotheses of the FFF retention theory
1.4. Practice versus classical theory
1.5. Variants of the classical retention model
1.5.1. Steric model
1.5.2. Model tacking into account the interaction particle-wall
1.5.3. Experimental correction for particle−wall interaction
1.5.4. Models based on different assumptions
2. Flow-FFF and Asymmetrical Flow-FFF
2.1. The different steps in AF4 analysis
2.2. AF4 applications
2.3. Strength and weakness of AF4-multidetector
Scope of the work
Chapter III. Materials and methods
1. AF4-multidetector instrumentation
1.1. Determination of the effective channel thickness
1.2. Determination of the retention time
1.3. Determination of the void time
1.4. Determination of the focusing position
1.5. Determination of the recovery rate
2. Zeta potential analyses
2.1. Measurement of the zeta potential of particle suspensions
2.2. Measurement of the zeta potential of membranes
3. Scanning electron microscopy analyses
4. Particle standards
5. Experimental approach and method validation of AF4 method
Chapter IV: Study of the mechanisms governing the retention inside the AF4 channel and application of the δw model for the characterisation of nanoparticle hydrodynamic diameter
1. Study of the retention behaviour of spherical nanoparticles in AF4 channel using the classical model
1.1. Influence of the carrier ionic strength on the particle retention
1.2. Influence of the membrane nature on the particle retention and recovery rate
1.3. Influence of the particle size on the particle retention
1.4. Influence of the particle nature on the particle retention
1.5. Lessons retained from preliminary tests on retention behaviour of spherical nanoparticles in AF4 channel
2. Application of the δw model to AF4 for the size characterization of nanoparticles
2.1. Determination of the channel thickness in the case of the δw model
2.2. Effect of the ionic strength and of the particle size on δw
2.3. Validation of the model
Chapter V. Implementation and evaluation of a retention model taking into account particle-wall interactions for the measurement of nanoparticle hydrodynamic diameter by asymmetrical flow field-flow fractionation
1. Introduction
2. Theory
3. Materials and methods
3.1. Instrumentation
3.2. Reagents and Samples
4. Results and discussion
4.1. Zeta potential of the membrane
4.2. Characterization of the particles standard
4.3. Determination of the void time
4.4. Channel thickness determination
4.4.1. Effective channel thickness as a physical parameter
4.4.2. Effective thickness as a correction factor
Chapter VI. Metrological validation of a retention model taking in account particle-wall interactions for the measurement of nanoparticle hydrodynamic diameter by asymmetrical flow field-flow fractionation
1. Introduction
2. Theory
2.1 FFF theory
3. Materiel and methods
3.1. Nanoparticles Standards for size values
3.2. Instrumentation
4. Results and discussion
4.1. Program operation and uncertainty propagation
4.2. Determination of the standard uncertainty of the inputs parameters
4.3. Result of the rh probability density function
4.4. Metrological traceability
Chapter VII: A novel approach to directly determine the channel thickness: feasibility study
1. On the measurement of the effective channel thickness
2. Characteristics of the ideal method for the direct measurement of weff
2.1. Principle of chromatic confocal sensor
3. Evaluation of the experimental set-up
4. Future enhancements of the measurement set-up
Conclusions and perspectives
Résumé étendu en français
Annex I: Conference paper 19th International Congress of Metrology – CIM2019


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