X-ray fluorescence (XRF) offers element-selective information that can be used for the qualitative and quantitative analysis of various sample types. In this article, we explore how XRF spectroscopy can be combined with nanoscience.
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XRF is now used in many laboratories and performed on benchtop instruments around the world. Synchrotrons and other advanced light sources are also popular X-ray sources for XRF measurements due to their excellent energy tuneability, high photon dose and good focusing capabilities.
For nanoscience, XRF is commonly used as a characterization technique to identify what elements are present in a sample and is sometimes combined with microscopy approaches to give spatially resolved elemental composition information.1 For such experiments on nanoscale objects, the tight focusing capabilities of X-ray radiation are highly advantageous for being able to visualize even the smallest structures.2
What is XRF Spectroscopy?
XRF spectroscopy can also be called X-ray emission (XES) spectroscopy. Probably the most common kind of XRF experiment is what is known as a non-resonant experiment, where the photon energy used is greater than the core ionization threshold of the element of interest.
In non-resonant XRF or XES, the incident photon that irradiates the sample leads to the ejection of a core electron in the element of interest and the formation of a core-hole state.
Such core-hole states are highly unstable and rapidly undergo a core-hole relaxation process that leads to the reorganization of the electronic structure of the sample. To preserve the overall conversation of energy in the system, if a more energetic electron fills the core vacancy, a secondary particle is emitted.3 There is a probability that this particle emitted will either be an Auger electron or a fluorescent photon.
In XRF, it is the fluorescent photons that are detected to recover information on the electronic structure of the sample they have originated from. XRF is highly element selective because each element has relatively unique core binding energies; the resulting fluorescence emission is at a characteristic energy that can be used for element identification. With careful calibration, the overall fluorescent signal strength can be used to identify the number of atoms of a given element that are present.4
For many applications, understanding the elemental composition of the sample is sufficient. Still, XRF can also be used to recover information on the elements present and their local structure and bonding environments.3 This information, combined with high-quality quantum chemical simulations, can be used to recover very detailed electronic structure information on molecular or material samples.5
What Is XRF?
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Sizing Nanoparticles with XRF Spectroscopy
One of the reasons XRF has become such a popular analytical tool in many industries is its versatility for studying a number of different sample types. XRF can be used on a number of different sample types, including liquids and powders.
Nanoparticle sizing is one possible application of XRF as these nanoscale objects have size-dependent electronic structure properties, which XRF is sensitive to. These types of nanoscale measurements can also be extended to looking at uptake studies, where biological samples are imaged using XRF and the distribution of the nanoparticles in the biological issues is measured. One example of this is using nanoparticles as a tracer for plant uptake to better understand the physiological transport mechanisms involved in plant growth and function.6 The advantage of using XRF with nanoparticles containing heavy elements is they offer an excellent contrast between the tissue and the tracer, as only the tracer will emit in a given energy range.
Nanoparticle Tracers for XRF
There is now a highly active area of research in developing nanoparticle tracers for XRF and developing more complex scanning methods that allow for a full 3D reconstruction of the object of interest.7 The flexibility in the synthesis and properties of nanoparticles makes such techniques highly versatile for looking at a wide variety of tissue types and problems.
Another advantage of XRF over other wet lab analysis methods – which ultimately offer better sensitivity – is there does not need to be any acid digestion or preparation of the samples beforehand. This is essential for XRF to be a viable field measurement technique but also simplifies the analysis workflow for evaluating new samples.
XRF data acquisition and analysis has already been widely automated for mining applications and element or mineral identification, but such automation procedures are highly useful for evaluating nanomaterials and structures as the information gained from such experiments is largely unchanged from analysis of soils.
Automation improvements make it possible to scan larger areas of nanoscale objects while not sacrificing the very high spatial resolutions that X-rays can achieve but that contribute to overall longer scanning times.
Versatile Methodology
While XRF is very well-suited to detect heavy elements, there are some challenges when applying XRF to lighter elements due to the inherently low fluorescence quantum yield for detection. This limitation can be overcome with the use of specially designed detection schemes that have much higher collection efficiencies.8 As fluorescence is typically emitted isotropically, it can be challenging to design optics that allow for a large solid angle of collection.
Improvements in the sensitivity of detectors and brighter lab or portable X-ray sources are also helping XRF achieve new detection limits. Alongside the instrumentation improvements, a great deal of development in XRF is focusing on how to make good-quality measurements of complex samples.8
When attempting to gain additional spectral information in energy-dispersive X-ray fluorescence experiments, trying to isolate matrix effects from the sample environment of the element is challenging. Identifying meaningful ways to calibrate measurements to extract quantitative insights is also difficult.
Like many spectroscopies, XRF is undergoing a great deal of technical development in the automation of instrumentation and analysis. The lack of need for sample preparation for XRF measurements gives it a distinct advantage over many other measurement types for fieldwork and automated processing of samples, and the ability to recover element selective information also helps in recording comprehensible spectra on samples in the most complex sample environments.
References and Further Reading
Tiwari M. Recent trends in X-ray fluorescence spectrometry: precise investigation of nanomaterials. Spectrosc Eur. 2018;30(1):15. doi:10.1255/sew.2018.a1
Mantouvalou, I., Malzer, W., & Kanngießer, B. (2012). Quantification for 3D micro X-ray fluorescence. Spectrochimica Acta Part B: Atomic Spectroscopy, 77, 9-18. https://doi.org/10.1016/j.sab.2012.08.002
Singh, V. K., et al. (Eds.). (2022). X-Ray Fluorescence in Biological Sciences: Principles, Instrumentation, and Applications. John Wiley & Sons.
1. Li Y, Shaker K, Larsson JC, Vogt C, Hertz HM, Toprak MS. A library of potential nanoparticle contrast agents for X-ray fluorescence tomography bioimaging. Contrast Media Mol Imaging. 2018;2018. doi:10.1155/2018/8174820
Demir, L., et al. (2019). Investigating XRF parameters and valance electronic structure of the Co , Ni , and Cu spinel ferrites. Ceramics International, 45, pp.7748–7753. doi.org/10.1016/j.ceramint.2019.01.078
Frahm, E., & Doonan, R. C. P. (2013). The technological versus methodological revolution of portable XRF in archaeology. Journal of Archaeological Science, 40(2), pp.1425–1434. doi.org/10.1016/j.jas.2012.10.013
Servin AD, Castillo-Michel H, Hernandez-Viezcas JA, Diaz BC, Peralta-Videa JR, Gardea-Torresdey JL. Synchrotron micro-XRF and micro-XANES confirmation of the uptake and translocation of TiO2 nanoparticles in cucumber (Cucumis sativus) plants. Environ Sci Technol. 2012;46(14):7637-7643. doi:10.1021/es300955b
Weindorf, D. C., et al. (2014). Advances in Portable X-ray Fluorescence ( PXRF ) for Environmental , Pedological, and Agronomic Applications. In Advances in Agronomy (Vol. 128). Elsevier. doi.org/10.1016/B978-0-12-802139-2.00001-9
Thompson, D. R., et al. (2015). Automating X-ray Fluorescence Analysis. 15(11), pp.961–976. doi.org/10.1089/ast.2015.1349
Huang, F., Peng, S., Yang, H., Cao, H., Ma, N., & Ma, L. (2022). Development of a novel and fast XRF instrument for large area heavy metal detection integrated with UAV. Environmental Research, 214, p.113841. doi.org/10.1016/j.envres.2022.113841
Streli, C., et al. (1992). Light element analysis with a new spectrometer for total-reflection fluorescence. Spectrochimica Acta, 48, pp.163–170. doi.org/10.1016/0584-8547(93)80020-U
Gustinelli Arantes de Carvalho, G., et al. (2018). Recent advances in LIBS and XRF for the analysis of plants. Journal of Analytical Atomic Spectrometry, 33, p.919. doi.org/10.1039/c7ja00293a
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