Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

241 to 250 of 300 Results
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.96 mol/L initial concentration
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.96 mol/L initial concentration
Sep 9, 2021 - Publication: Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation From Porous Media
Ruf, Matthias; Lee, Dongwon; Piotrowski, Joseph; Huisman, Johan Alexander; Steeb, Holger, 2021, "micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.96 mol/L initial concentration", https://doi.org/10.18419/DARUS-2003, DaRUS, V1
This data set contains data of scans of three separated dry salt crusts that formed by evaporation of magnesium sulfate solution with 0.96 mol/L initial concentration from F32 quartz sand at 40%, 30%, and 25% saturation inside the sand packing. The cylindrical sample holder from polymethyl methacrylat (PMMA) had a diameter of 31 mm and a wall thick...
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.32 mol/L initial concentration
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.32 mol/L initial concentration
Sep 9, 2021 - Publication: Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation From Porous Media
Ruf, Matthias; Lee, Dongwon; Piotrowski, Joseph; Huisman, Johan Alexander; Steeb, Holger, 2021, "micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.32 mol/L initial concentration", https://doi.org/10.18419/DARUS-2002, DaRUS, V1
This data set contains data of scans of three separated dry salt crusts that formed by evaporation of magnesium sulfate solution with 0.32 mol/L initial concentration from F32 quartz sand at 40%, 30%, and 20% saturation inside the sand packing. The cylindrical sample holder from polymethyl methacrylat (PMMA) had a diameter of 31 mm and a wall thick...
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.64 mol/L initial concentration
micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.64 mol/L initial concentration
Sep 6, 2021 - Publication: Porosity and Permeability of Subflorescent Salt Crusts Formed by Evaporation From Porous Media
Ruf, Matthias; Lee, Dongwon; Piotrowski, Joseph; Huisman, Johan Alexander; Steeb, Holger, 2021, "micro-XRCT data sets of subflorescent salt crusts from evaporation of MgSO4 solution with 0.64 mol/L initial concentration", https://doi.org/10.18419/DARUS-1848, DaRUS, V1
This data set contains data of scans of three separated dry salt crusts that formed by evaporation of magnesium sulfate solution with 0.64 mol/L initial concentration from F32 quartz sand at 40%, 30%, and 20% saturation inside the sand packing. The cylindrical sample holder from polymethyl methacrylat (PMMA) had a diameter of 31 mm and a wall thick...
Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces"
Aug 20, 2021 - Paper Nature Materials 2021
Schlaich, Alexander, 2021, "Simulation input scripts for "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces"", https://doi.org/10.18419/DARUS-2115, DaRUS, V1
This dataset includes the basic simulation scripts needed in order to reproduce the data shown in "Electronic screening using a virtual Thomas-Fermi fluid for predicting wetting and phase transitions of ionic liquids at metal surfaces". The folder structure corresponds to the individual parts of the paper, more detail is given in the individual REA...
Paper Nature Materials 2021(Universität Stuttgart)
Aug 18, 2021Imperfect metals, Thomas-Fermi screening
Supplementary information for the paper to be published in Nature Materials.
Imperfect metals, Thomas-Fermi screening(Universität Stuttgart)
Aug 18, 2021PN 1-8
Simulation input and data as well as analytical calculations and supplementary files regarding the behavior of charged/ionic matter at imperfect metal surfaces.
PN 1-8(Universität Stuttgart)
Aug 18, 2021PN 1
SimTech Project PN 1-8 "Bottom-up modeling of hierarchical porous electrode materials via molecular simulation"
EnzymeML Metadata Block Configuration for Dataverse
Aug 5, 2021 - RDM Tools
Range, Jan Peter; Iglezakis, Dorothea, 2021, "EnzymeML Metadata Block Configuration for Dataverse", https://doi.org/10.18419/DARUS-2105, DaRUS, V1
This dataset contains a TSV-File for the configuration of a metadata block for data repositories basing on Dataverse. The block helps to describe datasets with the concepts of the metadata scheme EnzymeML, which is a data model provided to facilitate the documentation and exchange of enzymological and biocatalytic research data. To add a metadata b...
Sampling Strategies of the Regime-and-memory model (RMM)
Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty
Gonzalez-Nicolas Alvarez, Ana, 2021, "Sampling Strategies of the Regime-and-memory model (RMM)", https://doi.org/10.18419/DARUS-2035, DaRUS, V1, UNF:6:JeAvfovoq369qtbASSmQjg== [fileUNF]
This excel file includes the observation time, Q, concentration, and lag-time used by the sampling strategies. Types of sampling strategies: Time frequency sampling strategies. River discharge frequency sampling strategies. Low Q sampling strategies. High Q sampling strategies. Low and High Q sampling strategies.
Regime-and-memory model (RMM) Code
Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty
Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/DARUS-2034, DaRUS, V1
We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime. This parameter can morph the model among chemostatic-type and chemodyn...
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.