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Microstructural data for rocks in the Shiant Isles Main Sill, presented as a function of stratigraphic height in the sill. The data were published: Holness et al. (2017) Contributions to Mineralogy and Petrology, 172:7. OI 10.1007/s00410-016-1325-x
Synchrotron X-radiography (images) and diffraction data collected to measure rheology of olivine and ringwoodite structured Co2SiO4.
These data files represent simulations of hydrated cation vacancies in the mantle mineral forsterite (Mg2SiO4) undertaken using the CASTEP atomic scale simulation code (http://www.castep.org/). Results from these simulations allow the structure relative stability of different defect configurations to be compared. Three types of cation vacancies are considered (M1, M2 and Si) each decorated by hydrogen in order to charge balance the system. For M1 and M2 this results in multiple configurations (with hydrogen bonded to different oxygen atoms around the vacant site). For Si there is only one configuration as all four oxygen atoms are bonded to hydrogen for the charge neutral defect. For each configuration input files detail the initial atomic structure of the defect along with simulation parameters. Output files record the progress of the simulation, the final atomic structure, the energy of this structure, and various predicted properties of the structure. Only ASCII output data is included as binary data created by CASTEP is not intended to be portable, and can easily be recreated using the ASCII files.
Experimental mechanical data for single crystal shear experiments. Grant abstract: In 2011, NERC began a scoping exercise to develop a research programme based around deep Earth controls on the habitable planet. The result of this exercise was for NERC to commit substantial funding to support a programme entitled "Volatiles, Geodynamics and Solid Earth Controls on the Habitable Planet". This proposal is a direct response to that call. It is widely and generally accepted that volatiles - in particular water - strongly affect the properties that control the flow of rocks and minerals (their rheological properties). Indeed, experiments on low-pressure minerals such as quartz and olivine show that even small amounts of water can weaken a mineral - allowing it to flow faster - by as much as several orders of magnitude. This effect is known as hydrolytic weakening, and has been used to explain a wide range of fundamental Earth questions - including the origin of plate tectonics and why Earth and Venus are different. The effect of water and volatiles on the properties of mantle rocks and minerals is a central component of this NERC research programme. Indeed it forms the basis for one of the three main questions posed by the UK academic community, and supported by a number of international experts during the scoping process. The question is "What are the feedbacks between volatile fluxes and mantle convection through time?" Intuitively, one expects feedbacks between volatiles and mantle convection. For instance, one might envisage a scenario whereby the more water is subducted into the lower mantle, the more the mantle should weaken, allowing faster convection, which in turn results in even more water passing into the lower mantle, and so on. Of course this is a simplification since faster convection cools the mantle, slowing convection, and also increases the amount of volatiles removed from the mantle at mid-ocean ridges. Nevertheless, one can imagine many important feedbacks, some of which have been examined via simple models. In particular these models indicate a feedback between volatiles and convection that controls the distribution of water between the oceans and the mantle, and the amount topography created by the vertical movement of the mantle (known as dynamic topography). The scientists involved in the scoping exercise recognized this as a major scientific question, and one having potentially far reaching consequences for the Earth's surface and habitability. However, as is discussed in detail in the proposal, our understanding of how mantle rocks deform as a function of water content is remarkably limited, and in fact the effect of water on the majority of mantle minerals has never been measured. The effect of water on the flow properties of most mantle minerals is simply inferred from experiments on low-pressure minerals (olivine, pyroxenes and quartz). As argued in the proposal, one cannot simply extrapolate between different minerals and rocks because different minerals may react quite differently to water. Moreover, current research is now calling into question even the experimental results on olivine, making the issue even more pressing. We propose, therefore, a comprehensive campaign to quantify the effect of water on the rheological properties of all the major mantle minerals and rocks using a combination of new experiments and multi-physics simulation. In conjunction with 3D mantle convection models, this information will allow us to understand how the feedback between volatiles and mantle convection impacts on problems of Earth habitability, such as how ocean volumes and large-scale dynamic topography vary over time. This research thus addresses the aims and ambitions of the research programme head on, and indeed, is required for the success of the entire programme.
High precision electron-probe analysis of olivine compositions from a set of ocean island basalts. Accompanied by thin section scans and QEMSCAN (Quantitative Evaluation of Minerals by SCANning) compositional maps.
A worldwide compilation of 189 analyses of U and Pb concentrations in olivine-hosted melt inclusions from ocean island magmas. These data were used in Delavault et al. (2016, Geology 44, 819-822) to calculate the present-day distribution of the U/Pb ratios in magmas generated in intraplate setting.
This is supporting data for the manuscript entitled 'DFENS: Diffusion chronometry using Finite Elements and Nested Sampling' by E. J. F. Mutch, J. Maclennan, O. Shorttle, J. F. Rudge and D. Neave. Preprint here: https://doi.org/10.1002/essoar.10503709.1 Data Set S1. ds01.csv Electron probe microanalysis (EPMA) profile data of olivine crystals used in this study. Standard deviations are averaged values of standard deviations from counting statistics and repeat measurements of secondary standards. Data Set S2. ds02.csv Plagioclase compositional profiles used in this study, including SIMS, EPMA and step scan data. Standard deviations for EPMA analyses are averaged values of standard deviations from counting statistics and repeat measurements of secondary standards. Standard deviations for SIMS and step scan analyses are based on analytical precision of secondary standards. Data Set S3. ds03.csv Angles between the EPMA profile and the main olivine crystallographic axes measured by electron backscatter diffraction (EBSD). 'angle100X' is the angle between the  crystallographic axis and the x direction of the EBSD map, 'angle100Y' is the angle between  crystallographic axis and the y direction of the EBSD map, and 'angle100Z' is the angle between the  crystallographic axis and the z direction in the EBSD map etc. 'angle100P' is the angle between the EPMA profile and the  crystallographic axis, 'angle010P' is the angle between the EPMA profile and the  crystallographic axis, and 'angle100P' is the angle between the EPMA profile and the  crystallographic axis. All angles are in degrees. Data Set S4. ds04.csv Median timescales and 1 sigma errors from the olivine crystals of this study. The +1 sigma (days) is the quantile value calculated at 0.841 (i.e. 0.5 + (0.6826 / 2)). The -1 sigma (days) is therefore the quantile calculated at approximately 0.158 (which is 1 - 0.841). The 2 sigma is basically the same but it is 0.5 + (0.95/2). The value quoted as the +1 sigma (error) is the difference between the upper 1 sigma quantile and the median. Likewise the -1 sigma (error) is the difference between the median and the lower 1 sigma quantile. Data Set S5. ds05.xlsx Median timescales and 1 sigma errors from the plagioclase crystals of this study. Results from each of the parameterisations of the Mg-in-plagioclase diffusion data are included: Faak et al, (2013), Van Orman et al., (2014) and a combined expression. Data Set S6. ds06.xlsx Spreadsheet containing the regression parameters and covariance matrices used in this study and in Mutch et al. (2019). Additional versions of the olivine regressions where the ln fO2 is expressed in Pa have been made for completeness. We recommend using the versions where ln fO2 is expressed in its native form (bars).
Petrological and geochemical analysis of samples from Aluto volcano, Ethiopia. Data are referenced in Gleeson et al., 2017: Constraining magma storage conditions at a restless volcano in the Main Ethiopian Rift using phase equilibria models; https://doi.org/10.1016/j.jvolgeores.2017.02.026.
Primary data, model initial conditions, model results, a compiled database of olivine diffusivity experiments and supplementary tables used in the paper: 'Mutch, E. J. F., Maclennan J., Shorttle, O., Edmonds, M. & Rudge, J. F., (2019), Rapid trans-crustal magma movement under Iceland, Nature Geoscience'. Data_S1 contains electron probe microanalysis (EPMA) profile data of olivine crystals used in this study. This file also includes all of the initial conditions for forsterite content (XFo), Ni and Mn used in the diffusion modelling. Standard deviations are averaged values of standard deviations from counting statistics and repeat measurements of secondary standards. Data_S2 is a compiled database of olivine diffusion experiments used to derive multiple linear regressions for diffusion coefficients and associated covariance matrices. Regressions were only made through  data. Data_S3 contains median values for all of the inverted parameters estimated for each crystal profile from the Nested Sampling Bayesian inversion for each type of initial condition and model equation. All of the Monte Carlo realisations for each model are also included in this file. Table_S1 is a supplementary table that contains olivine diffusion equation regression parameters derived and used as part of this study. Table_S2 is a supplementary table that contains covariance matrices for olivine diffusion equations derived in this study. Table_S3 is a supplementary table that contains covariance matrices for aSiO2 (silica activity) dependent olivine diffusion equations derived in this study. Table_S4 is a supplementary table that contains angles between the EPMA profile and the main crystallographic axes in olivine as measured by EBSD. These angles are incorporated into the anisotropy calculation used to determine the apparent diffusivity parallel to the measured profile. angle100P, angle010P and angle001P are the angles between the profile and ,  and  respectively. Table_S5 is a supplementary table that contains ,median timescales and 1 sigma errors obtained from the posterior distributions of the Nested Sampling Bayesian inversion conducted on each olivine profile. The results using Al-based initial conditions, constant initial conditions (diffusion only), and aSiO2 based equations using Al-based initial conditions are presented here. The classification of each profile (growth-dominated vs. Al-decoupled) is also shown. See paper (Mutch, E. J. F., Maclennan J., Shorttle, O., Edmonds, M. & Rudge, J. F., (2019), Rapid trans-crustal magma movement under Iceland, Nature Geoscience) for more details.