X-ray fluorescence is a powerful technique for the qualitative and quantitative elemental analysis of samples. An X-ray fluorescence measurement involves irradiating the sample of interest with high-energy electromagnetic radiation in the X-ray region of the spectrum and detecting the photons that are emitted due to the energetic relaxation of the excited sample.
Image Credit: Phonlamai Photo/Shutterstock.com
One advantage of X-ray fluorescence is it is a highly versatile technique that is compatible with a number of different sample types, including powders or liquids. It is a non-destructive method, and so is often used for the analysis of precious artifacts. There is also no need for the use of any sample labeling as part of the experimental preparation, which makes X-ray fluorescence a highly interesting method for use in ‘field’ measurements, such as in robotics, where samples must be measured on the fly in their environment without further modification.
As long as the X-ray source can generate sufficiently high energy photons to excite or ionize the core electrons in an element of interest, X-ray fluorescence can be used to measure any element.
This is advantageous for robotics applications in mining and geology, where it may be desirable for the robot to detect the presence of previously unexpected elements.
For the light elements, such as carbon, oxygen and nitrogen, X-ray fluorescence is not a very efficient process. This is because the core-hole recombination process that occurs typically results in the emission of Auger electrons rather than photons for the low atomic mass elements.
The relative quantum yield of X-ray fluorescence versus Auger emission increases with the atomic mass. However, these challenges can be overcome with the use of specialized detection schemes that sometimes need to be used for performing X-ray fluorescence measurements on light elements.1
Many of these highly efficient detection schemes can help improve the limit of detection and sensitivity of X-ray fluorescence measurements, even those performed in the field where the spectrometer is mounted on an autonomous vehicle. Such improvements have meant X-ray fluorescence has become an increasingly popular technique for field measurements in soil analysis, even for highly complex moisture-rich soils, which other spectroscopic methods such as infra-red spectroscopy would find difficult to analyze.2
What makes X-ray fluorescence such a powerful technique is that the information obtained – the emission energy of the photon – is element-specific. As the excitation process with X-ray radiation normally involves the promotion of core electrons that are the most tightly bound to the nucleus, the exact energy of the emitted photon following core-hole relaxation is characteristic of the element it was emitted from.3
The element sensitivity and selectivity of X-ray fluorescence make it an idea for dealing with highly complex samples that may contain mixtures of many different elemental species.
Depending on the exact X-ray energy used and which energy level the electrons are excited from, different X-ray emission lines have varying degrees of sensitivity to the chemical environment so can also report information on bonding and the chemical structure of the overall molecular species.4
While many X-ray fluorescence measurements benefit from high-brilliance X-ray sources such as synchrotrons, there are a number of handheld portable devices available for field measurements.5
One of the advantages of X-ray fluorescence for automated robotics information is that the spectral information obtained is relatively straightforward compared with full machine vision applications.
In comparison with the need to process a full 2D image and use advanced image recognition algorithms - which would be necessary for optical imaging in machine vision - an X-ray fluorescence spectrum is relatively straightforward to interpret in an automated way.
Predicted emission energies and intensities can be taken from atomic spectral databases and be used to predict with reasonably good accuracy which energy range signals are likely to appear. For geological robotics applications, the emission energy information alone may be sufficient to detect whether or not minerals are present and, with the acquisition of multiple X-ray fluorescence spectra, this can be used to map out the mineral distribution in a region.
The highly element-specific information and the reduced cost of the automation of the computational analysis are very important for robotics applications in astrobiology surveys.6
An ideal instrument will be capable of some preliminary onboard analysis as data transfer for astronomical applications is a serious bottleneck and live information from the analysis can be important when deciding how to perform surveys during a mission.
The instrument integration time to acquire data with a reasonable signal to noise for analysis also needs to be as short as possible. X-ray fluorescence measurements integrate well with adaptive sampling schemes that use feedback systems to control the scanning process and movement of the instrument.6
The ability to mount X-ray fluorescence spectrometers onto remote vehicles to perform automated measurements in challenging environments such as underground mines or space is a significant development for this spectroscopic technique.
The element selectivity is also highly advantageous for soil and rock analysis and with brighter portable sources leading to reduce measurement times, it may be that such field measurements become more common in the future, particularly as devices become increasingly cost-effective.
References and Further Reading
- Streli, C., Aiginger, N. N. E., & Wobrauschek, P. (1992). Light element analysis with a new spectrometer for total-reflection fluorescence. Spectrochimica Acta, 48B(2), 163–170. https://doi.org/https://doi.org/10.1016/0584-8547(93)80020-U
- West, M., Ellis, A. T., Potts, P. J., & Streli, C. (2014). 2014 Atomic Spectrometry Update – a review of advances in X-ray fluorescence spectrometry. J. Anal. At. Spectrom., 29, 1516–1563. https://doi.org/10.1039/c4ja90038c
- Weindorf, D. C., Bakr, N., Zhu, Y., Mcwhirt, A., Ping, C. L., Michaelson, G., & Nelson, C. (2014). Influence of Ice on Soil Elemental Characterization via Portable X-Ray. Pedosphere: An International Journal, 24(1), 1–12. https://doi.org/10.1016/S1002-0160(13)60076-4
- Fahrni, C. J. (2007). Biological applications of X-ray fluorescence microscopy : exploring the subcellular topography and speciation of transition metals. Current Opinion in Chemical Biology, 11, 121–127. https://doi.org/10.1016/j.cbpa.2007.02.039
- Weindorf, D. C., Bakr, N., & Zhu, Y. (2014). Advances in Portable X-ray Fluorescence ( PXRF ) for Environmental , Pedological , and Agronomic Applications. Advances in Agronomy (Vol. 128). Elsevier. https://doi.org/10.1016/B978-0-12-802139-2.00001-9
- Thompson, D. R., Flannery, D. T., Lanka, R., Allwood, A. C., Bue, B. D., Clark, B. C., Elam, W. T., Estlin, T. A., Hodyss, R. P., Hurowitz, J. A., Liu, Y., & Wade, L. A. (2015). Automating X-ray Fluorescence Analysis. 15(11), 961–976. https://doi.org/10.1089/ast.2015.1349