Compilation of igneous rock compositions from Iran and SE Anatolia Meso-Cenozoic (ISA), including major, trace element and Sr-Nd-Pb isotopic data as published in Lustrino et al. (2021).
Major and trace element concentrations and Sr, Nd, Hf, Pb isotope ratios of global mid ocean ridge and ocean island basalt whole-rock compositions from the GEOROC and PetDB databases (2021-2022). Key publications: Stracke, A., Willig, M., Genske, F., Béguelin, P., & Todd, E. (2022). Chemical Geodynamics Insights From a Machine Learning Approach. In Geochemistry, Geophysics, Geosystems (Vol. 23, Issue 10). https://doi.org/10.1029/2022GC010606 Stracke, A., Willig, M., Genske, F., Béguelin, P., & Todd, E. (2022). Chemical and radiogenic isotope data of ocean island basalts from Tristan da Cunha, Gough, St. Helena, and the Cook-Austral Islands [dataset]. GRO.data. https://doi.org/10.25625/BQENGN
This data publication provides data from 96 experiments from 2020 to 2022 in the gas-mixing lab at the Ludwig-Maximilians-Universität München (Germany). The experiments were conducted to investigate the influence of grain size distribution, especially the influence of very fines [<10 µm] on the generation of experimental volcanic lightning (VL). The influence of grain size distribution was tested for three different materials. Experimental discharges during rapid decompression were evaluated by their number and their total magnitude. The three materials used in this study are a tholeiitic basalt (TB), industrial manufactured soda-lime glass beads (GB) and a phonolitic pumice from the lower Laacher See unit (LSB). The samples were sieved into several grain size fractions, and coarse and fines were mixed to test the influence of the added fines on the discharge behaviour. For the tholeiitic basalt, the coarse grain size fraction is 180-250 µm, for the glass beads 150-250 µm and for the phonolitic pumice, two coarse grain size fractions, 180-250 µm and 90-300 µm were tested. The experiments were carried out in a new experimental setup, a modification of the shock tube experiments first described by Alidibirov and Dingwell (1996) and its further modifications (Cimarelli et al., 2014; Gaudin & Cimarelli, 2019; Stern et al., 2019). A mixture of coarse and fine sample material is placed into an autoclave and continuously set under pressure with argon gas up to the desired decompression pressure (⁓10 MPa). Then, rapid decompression is initialized, and the sample material is ejected from the autoclave through a nozzle into a gas-tight particle collector tank. The particle collector tank is insulated from the nozzle and the ground and serves as a Faraday cage (FC). All discharges going from the erupting gas-particle mixture, the jet, to the nozzle will be recorded by a datalogger. All the discharges measured during the first 5 ms of ejection were taken into the evaluation of the discharge behaviour. The raw signals of the experiments were evaluated by a processing code developed by Gaudin and Cimarelli (2019). Additionally, the jet behaviour was recorded by a high-speed camera: the gas-exit angle and the exit angle of the gas-particle mixture were determined. The background of the high-speed video was divided into a black side and a white side. The gas-exit angle and the exit angle gas-particle-mixture were determined as the mean of the deviation angle of a straight trajectory angle of both sides.
Global database of >20, 000 geochemical analyses of Neogene-Quaternary intraplate volcanic rocks. The database collates major, trace element and Sr-Nd-Pb isotopic data for whole-rock samples <20 Ma old that were published between 1990 and 2020. Database as published in Ball et al. (2021). Key publication: Ball, P. W., White, N. J., Maclennan, J., & Stephenson, S. N. (2021). Global influence of mantle temperature and plate thickness on intraplate volcanism. Nature Communications, 12(1), 2045. https://doi.org/10.1038/s41467-021-22323-9
Collection of published and new major and trace element and Sr–Nd–Pb isotopic data (more than 7800 samples) for the magmatic rocks from the Circum-Mediterranean Anorogenic Cenozoic Igneous province compiled by Lustrino & Wilson (2007).
This data publication provides data from 42 experiments from 2018 and 2019 in the Fragmentation Lab at the Ludwig-Maximilians University Munich (Germany). The experiments were taken out to analyse the influence of the water content and the initial temperature of the pre-experimental sample on the produced electrification in rapid decompression, shock-tube experiments. All samples used in this study are 90-300 μm loose ash samples from the lower Laacher See unit.To carry out this study, we have built up on previous studies by Cimarelli et al. (2014) and Gaudin & Cimarelli (2019b, dataset to be found in Gaudin & Cimarelli, 2019a). A sample of loose ash gets placed in an autoclave. In our study, we have added water in some experiments. Also, a furnace was often used to heat the sample to up to 320 °C. After both water addition and heating, the autoclave gets pressurized using argon gas. Once a target pressure of 9 MPa is reached, the experiment gets triggered by rupturing metal diaphragms, which rapid decompresses the sample and ejects it into a collector tank. This collector tank is made out of steel and electrically insulated from its surrounding, thus working as a Faraday cage (FC), which is able to detect the net charge within at any point during the experiment. We detect discharges on that net charge up to 10 ms after the ejection of the particles.This dataset contains:- an overview .xlsx file (ExperimentOverview) containing key information for the 42 experiments used for analysis in this study- raw .csv files for all experiments- .pdf files showing the key elements of the analysed experiments, incl. data from Faraday cage and pressure sensorsFor more information please refer to the data description and the associated publication (Stern et al., 2019).
This data publication includes particle size distribution data of natural volcanic ash samples used as starting material for laboratory experiments simulating the aggregation/disaggregation of colliding volcanic ash particles. Full details of the experimental method can be found in Del Bello et. al. (2015) and in the data description file provided here.Here we report raw particle size distribution data obtained through separation analysis. Two types of volcanic ash were analysed: i) andesitic ash from the Sakurajima volcano (Japan), collected from July 2013 deposits (named Sak sample); ii) phonolitic ash collected from the basal fallout layer of the ~10 ka old Pomici Principali eruptive unit [Di Vito et al., 1999]) of the Campi Flegrei (named Ppa). For both compositions, 3 different starting materials were obtained by hand sieving the natural samples into three main particle size classes: (i) <32 μm, (ii) 32–63 μm, and (iii) 63–90 μm. For the phonolitic composition Ppa two additional starting materials were obtained by mixing the <32 μm and the 32–63 μm classes in known proportions. For each starting material, the grain size distribution of the sample was measured by a multiwavelength separation analyzer (LUMIReader®, https://www.lum-gmbh.com/lumireader_en.html). This device measures space and time resolved profiles of the transmitted light across the water-diluted sample (5% solid content) during sedimentation of particles. The cumulative volume-weighted particle size distribution is obtained from the extinction profiles using the multi-wavelength Particle size Analyser modulus (PSA). Details on the sample preparation procedure can be found in Detloff et al. (2006). For each measurement performed (see Table 1), a pdf file and a excel file are provided. The pdf file lists the analysis summary, including a description of the analysis settings and conditions, materials used, and distribution model adopted for the fit. It also provides graphs of the obtained volume weighted cumulative grain size distribution, and of the measured transmission profiles for each wavelength (870 nm, 630 nm and 470 nm, respectively). The Excel (*.xlsx format) file include 4 datasheets, listing the results (sheet name ending *_R) and the fit data (sheet names ending *_F01,*_F02, *_F03) obtained for the different instrument wavelength. In each datasheet the following data are listed in the columns: particle grain size (x3 in µm), volume weighted distribution (Q3(x) in %), Martin diameter (x3m in µm), volume weighted density distribution (q3(x) in 1/µm). The fit datasheets also include information on the fit such as distribution model used and distribution parameters (quantiles, median, standard deviation, span, etc..).A full list of the files included is given in List_of_files_DelBello et al 2017.pdf.
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