by Dirk Mittelstraß | Last update: Jul 20, 2023
Luminescence dating might be the best tool to determine the age of Pleistocene landscapes and archaeological artefacts. Over the last years, I have been researching on new data analysis methods for some specific luminescence dating applications as private side projects in my free time. This blog is intended to give you access and further information about those projects
You can hire me on a fee basis to perform detailed data analyses with R of your OSL, TL or IR-RF measurements. I provide the calculation of equivalent dose statistics and paleodoses including the evaluation of test steps and rejection criteria. You will also get a detailed PDF report and the source code of the data analysis. Write me a mail if you are interested: dirk.mittelstrass@luminescence.de
If you like to outsource sample preparation and/or the luminescence measurements itself, I recommend to use the services of the LUNA luminescence laboratory at the Helmholtz Institute Freiberg for Resource Technology (HZDR) in Germany. The LUNA lab is lead by Dr. Margret Fuchs (m.fuchs@hzdr.de) and is specialized on spectroscopic investigations for mineral exploration and characterization. It is also well-equipped for geochronological investigations including OSL and TL dating and spectrometry. One special capability of the LUNA lab is the high-quality mineral separation in sediments through froth flotation.
Dating application | Data analysis software |
---|---|
CW-OSL component separation at quartz | Introduction & Tutorial |
Examples for quartz CW-OSL component identification and separation | |
Spatially resolved IR-RF at K-feldspars | Research article published in the scientific journal Geochronology. |
Download and installation | |
Example data and sequences | |
SR-RF macro Handbook and GitHub page | |
Last month I visited the Luminescence and ESR dating conference in Copenhagen and was surprised and happy to find out that my R package OSLdecomposition is already used (or at least tested) by some work groups while others are interested to use it in the future. I was not aware of that because I got no feedback so far. However, that gave me renewed motivation to finish the scientific paper about the OSLdecomposition R package.
If you like to cite the package before the paper is available please use the reference you get if you type this in R:
By the way, I outlined the future update to 1.1.0:
Method.control
argument and K.min
to
fit_OSLcurve()
to allow more tweaking of the genetic
algorithm.fit_OSLcurve()
to enable interesting new fitting
approaches.plot_OSLcurve()
, especially add the option to
draw the signal components as stacked areas.RLum.OSL_correction()
.RLum.RF_correction()
and
RLum.RF_fitting()
.get_RLum.sequence()
to return the
measurement sequences used in a data set as
knitr
-compatible table and include it in
RLum.OSL_correction()
. and
RLum.RF_correction()
.sum_OSLcurves()
, especially speed up the far too
slow plot output.Much of the above points were already coded and tested for other projects and just need to be merged into the main branch of OSLdecomposition. However, as this update has not the highest priority for me right now and the whole development is a hobbiest project anyway, please do not expect that the update will be released within the next months. Nonetheless, I will keep you updated and invite everyone to write their comments and wishes in the associated GitHub thread.
In my latest side project, I analysed the shapes of IR-RF signal curves of a variety of K-feldspar samples with methods from OSLdecomposition. Apparently, IR-RF curves can be sufficiently described by multi-exponential fittings, see the example below. Although further investigations are necessary, I summarized my findings in my poster for the LED conference 2023.
A new scientific paper I co-authored is published: Wavelength calibration and spectral sensitivity correction of luminescence measurements for dosimetry applications: Method comparison tested on the IR-RF of K-feldspar written by Mariana Sontag-Gonzales who is part of Markus Fuchs’s work group in Giessen. Mariana did an excellent job in describing multiple approaches for wavelength and sensitivity calibration of for luminescence spectroscopy and comparing them. As case study, the paper includes also IR-RF peak analyses of two K-feldspar samples. doi: 10.1016/j.radmeas.2022.106876.
Finally, my OSLdecomposition function library for R is released on CRAN. The package can now be installed using the RStudio package manager or by simply typing this into your R environment:
If you are not familiar with what it is all about or how to use the package, check out the Introduction & Tutorial page.
My biggest scientific child, the OSLdecomposition
package, is about to be released at CRAN soon. I already submitted the
package to CRAN in May this year. The review process revealed a few
minor issues and one big one: The necessary computing time to perform
the fitting of the global OSL curve with fit_OSLcurve()
exceeded the allowed limits for the code examples. Even with minimum
examples, I could not get the computing time below 10 seconds while only
5 seconds are allowed for CRAN releases. As it turned out, my approach
to calculate the residual sum of squares (RSS) did a lot of memory
allocations and these are highly inefficient in R. By
incorporating the RSS calculation directly into to
decompose_OSLcurve()
and taking care to create only as many
vectors and data.frame columns as truly necessary, I could speed up the
curve fitting between 3 and 5 times.
The research article presenting the method of grain-wise IR-RF dating of K-feldspars developed by Sebastian Kreutzer and myself has passed the review process in Geochronology and is now officially available at doi.org/10.5194/gchron-3-299-2021.
If you would like to discuss the future of IR-RF dating with me or Sebastian, why not register for the vDEUQUA 2021 online conference? The vDEUQUA is about quaternary climate and environmental changes, the methods to investigate them and how quarternary processes shaped our todays world. The conference is virtual, free of charge and happens from 2021-09-30 to 2021-10-01. See you there!
The package OSLdecomposition got an update, see the
Changelog for details.
The function RLum.OSL_correction()
includes now an
algorithm that checks if the records contain not stimulated periods at
beginning aor end of the measurement and removes them. This is for
example useful to enable component separation in single-grain
measurements.
I’m happy to anounce that our manuscript about spatially
resolved IR-RF dating is accepted for discussion in the journal
Geochronology. The preprint is available at gchron.copernicus.org.
Short comments are allowed until March 11.
Just in time for the DLED2020,
we released our R package OSLdecomposition for
signal component identification and separation in multi-exponentially
decaying measurements. Our focus laid on continous-wave optically
stimulated luminescence (CW-OSL) measurements of quartz samples for
dosimetry purposes. But you might find the package helpful for other
applications too. Check out our DLED
poster for a quick introduction into the Why and
How.
Welcome to my site about new data analysis methods for luminescence dating measurements. Since about 2013, I worked at number of methods on this issue. This blog is meant to give you access to some of my findings and the software I developed. As this blog will slowly get more content over the next months, I hope to see you around sometime!
© Dirk Mittelstraß, 2020 - 2023 | This website was created with Rmarkdown