Developer: The Virtual Explorer Pty Ltd
Current Version: 10.1.3
Last Updated: 2 days ago
Download Size: 1.4 MB - Download
This program has been written to facilitate the analysis and interpretation of argon geochronology data from step-heating experiments in vacuo in a furnace attached to a mass spectrometer. The program allows corrections for excess argon, using the analysis of York Plots to recognise trends. The program allows analysis of complex age spectra using the method of asymptotes and limits. Cumulated plots allow recognition of Frequently Measured Ages (FMAs). Gaussian plots present data using probability. Arrhenius Plots and Relative Radius Plots allow estimates for the diffusion parameters for individual samples. Data is input in XML format with data tags available for individual laboratories by request. The output document is in an XML format intended to become an industry standard, ensuring data interoperability between different programs and different laboratories.
Version 10 of eArgon takes advantage of the document architecture facilitated by MacOS. Data from all samples is now converted into an XML format intended to become an industry standard. The document allows recreation of the analysis by which frequently measured ages (FMAs) were recognised, along with analysis of asymptotes and limits for individual spectra. Conjoint inversion to define diffusion parameters for an individual sample can be achieved by exporting data to the Wunderkind program, which is one of the family of three argon geochronology data analysis programs (eArgon, Wunderkind and MacArgon). Wunderkind uses 39Ar release data from furnace-controlled temperature-step-heating ultra-high-vacuum (UHV) diffusion experiments analysed with eArgon. The diffusion parameters, along with the furnace schedule used in measurement, and a reference age spectrum, can then be exported to allow forward modelling of the effect of arbitrary pressure-temperature-time histories on the age spectrum using the MacArgon program. The Wunderkind routines use Monte Carlo routines to determine the least-squares best fit to a set of selected Arrhenius data points and/or to points in a r/r0 plot. Conjoint inversion is enabled, with variable weighting of particular points in either diagram able to be imposed in order to encourage compliance with the Fundamental Asymmetry Principle. Selected steps are memorised, for each dataset, along with any window specific information for that dataset, and recalled when the dataset is reloaded.
Version §10.1.3 of eArgon addresses issues raised by the user community in respect to the use of the local versus the global datastore in respect to the transfer of colour information between windows.