Biomedical Engineering Reference
In-Depth Information
of nanomaterials is time consuming, expensive, and complex. As was pointed
out in Section 2.2, there are two different approaches to characterize nanopar-
ticles: individual (IPA) and ensemble-averaging (EAA) characterization. The
two approaches differ in accuracy and reliability and therefore need to be dis-
cussed in detail in the following. As a general rule, a reliable interpretation of
the particle properties will require applying both characterization approaches
whenever possible. Table 2.1 provides a list of analytical methods for nanoma-
terials together with their statistical character and information content.
2.4.1 Characterization Techniques for Individual Nanoparticles (IPA)
Individual particle characterization is based on signals acquired from dis-
tinct particles. This can be achieved either by nanometrically resolving
microscopy or by nonresolving techniques applied to spatially separated
particles (SSP). However, individual particle analysis is generally accompa-
nied by low strength of the measurement signals, and thus not all analy-
sis techniques may therefore be sensitive enough for individual particles.
Examples of microscopic techniques that are able to resolve features of indi-
vidual nanosized particles include, for example, STM, AFM, and TEM.
The spatial separation required for nanometrically nonresolving techniques
can, for instance, be achieved by dilution of suspensions, mobility-related
separation in gases (scanning mobility particle sizer [SMPS]) or liquids (AF4
[18,19]), or low-density seeding of particles on substrates. For nonresolving
techniques, a subsample must be microscopically characterized in order to
elucidate the nature of the particles and to verify spatial separation. Examples
of nonresolving analysis techniques include Raman microscopy of individual
carbon nanotubes [20] and NTA, which determines hydrodynamic particle
diameters by analyzing the Brownian motion of individual particle tracks [21].
Dispersion of particles by gases into aerosols is a frequently used technique
for particle counting or size-related transport properties by SMPS.
Characterization of many individual particles allows compiling of a num-
ber of distributions of the respective particle property. This does not only
provide more detailed information but, more important, allows discovering
unexpected structures that may result from artifacts during particle synthe-
sis or dispersion. In addition, individual particle analysis can be a model-free
approach, not based on assumptions on the mechanism of collective signal
synthesis, as is the case for ensemble-averaging techniques. However, for
state-of-the-art technology, individual characterization is still time consum-
ing. The number of analyzed individual particles will therefore generally be
small with regard to the nanoparticle ensemble size. This requires that the
representativeness of a subsample must be assessed by statistical methods.
The property distributions obtained from individual characterization must
therefore be tested for normality and pathologic minorities, which, as a bene-
fit of the approach, are not averaged-out, and can be studied in detail. Future
developments will focus on automated data acquisition and evaluation in
