Spotlight: How to… find, classify and identify microparticles

Materials World magazine
,
27 Sep 2019
WITec GmbH

Explore the process of automated microparticle analysis using Raman microscopy.

Scientific standards for establishing the level of microplastic pollution in environmental samples are rapidly evolving in response to public concern and demands for regulatory oversight. The process of determining microparticle concentrations is not yet codified in terms of filter or substrate material, rinsing procedure, and many other details.

There are, however, certain elemental steps common to any effort to analyse microparticles – they need to be found, classified, individually investigated, identified and quantified. Several methods exist for carrying out these steps, with an automated combination of confocal white-light microscopy and Raman spectroscopy, offering the clearest advantages in speed and precision.

Evaluating microparticle samples

Particulate samples generally contain a large number of different materials, of which only a subset is interesting to the researcher. Sifting through particles with conventional means is tedious and time consuming, so advanced optical and algorithmic techniques are necessary to expedite the process.

Ideally, the particle analysis workflow proceeds as follows. First, a large-area survey is first carried out to recognise all the particles in a sample. Next, criteria are specified to isolate particles that have features consistent with the materials under investigation. Then, the selected category of particles is further examined at the individual level, with each particle of interest being chemically identified. Finally, the identities of each particle are compiled in a table that provides the researcher with a comprehensive and quantitative sample overview.

Speed up difficult investigations

A white-light microscope with high confocality can survey a sample using bright or dark field illumination to see particles in contrast to the substrate or filter on which they are located. Often, particles will be distributed over an area larger than the microscope lens’s objective’s field of view. Image stitching automatically combines many measured areas into a single image to maintain precision while effectively enlarging the field of view. Particles of widely varying height can be accommodated by focus stacking, which acquires images at several focal distances and compiles them to ensure that all particles show a sharply defined edge for recognition by the analysis software.

After the particles have been located, the software enables them to be categorised by physical properties such as area, perimeter, minimum and maximum Feret diameter, or aspect ratio. The particles can also be sorted by any of these features into a ranked list. The outlines of particles that meet the specified criteria are used to create a mask that guides the subsequent measurement while omitting all other particles and the empty space in between, which drastically reduces measurement time.   

Following the selection of particles of interest, they need to be systematically and individually categorised. Raman spectroscopy, which is based on the scattering of light by molecules, can detect photons with energies that are shifted slightly from that of the excitation wavelength. Represented as Raman spectra, these shifts can serve as a unique fingerprint to distinguish each chemical component.

The method is non–destructive and requires no dyeing or specialised sample preparation. Its ability to quickly and easily identify materials from even small sample volumes or low concentrations makes it ideal for investigating microparticles. The mask guides the excitation light to the particles of interest in rapid succession and the microscope acquires a Raman spectrum from each one.

The Raman spectra can be investigated individually or with automated software routines. For researchers looking for a particular material, or those who already have a good idea of which materials to expect in a sample, the spectra, with their distinctive peaks and contours, will provide all the information necessary to identify the particles. When the composition of a sample is not as well established, or there are many materials of interest, an integrated Raman spectral database management software can help in reducing the time required for chemical characterisation.

An advanced particle analysis tool that has surveyed, located, examined and identified the microparticles in a sample can quantify its results in the form of a table or histogram. This summary shows the researcher what is in their sample, broken down into the categories they selected. It is the detailed and comprehensive answer to the question, ‘What does this sample consist of, and in what proportions?’.

Measuring a microparticle sample

The following measurement was carried out on a mixed microplastics sample using a WITec alpha300 R confocal Raman microscope, equipped with the ParticleScout particle analysis tool and the integrated TrueMatch Raman database management software.

Large-area bright field and dark field views of a mixture of microplastic particles were generated by image stitching. Criteria were specified to select particles of interest, which were then automatically located and displayed as a two-colour mask. From every particle, a single Raman spectrum was acquired. The chemical compositions of the particles were identified using TrueMatch. This data could be summarised in a table, providing a clear description of the quantity, size and molecular composition of particles in the sample.