Data publications found:

119

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yoda-repository

Evaluating Self-Healing on Mortars by Coupling Water Permeability Assessments to X-ray Micro-Computed Tomography

Franco Grosso Giordano

2024

This dataset contains 18 reconstructed Micro-computed tomography (µCT) scans. These scans belong to nine samples (50 x 45 mm) and the reconstructed images from these scans represent a 3D volume of cracked lime mortar. Of each sample one scan was taken before (Day 0) and one scan after 28 days...

SWELliNG (Sulphates With Expansion: the roLe of New crystals’ Growth) and SWELliNG_2 (Sulphates With Expansion: voLume and phase chaNGes over long periods) - Excite projects

Chiara Caselle | Laurenz Schröer

2026

Each folder contains a stack of .tiff files achieved after reconstructing a µCT scan. The scans were performed as part of the SWELLiNG and SWELLiNG2 project (Excite Network). The main purpose of the performed experiment was to measure the changes in volume and observe the changes in the...

EXCITE_C1_2022_31_SOUP

Orlando Sébastien Olivieri

2025

S.O.U.P. EXCITE Project: Unconventional energy Sources production, storage and release linked to subduction serpentinization: evidence from methane and hydrogen-rich fluid inclusions from the exhumed serpentinized peridotite of Monte Maggiore, Corsica

Data for Generative AI Modeling of Serpentinte Dehydration Veins in Subduction Zones

Austin Arias

2026

We used hand specimens of Erro-Tobbio meta-serpentinite (ET-MS) and outcrop surface images of olivine dehydration veins to train generative models to generate unique and varied dehydration vein network structures. These models coupled with thermodynamic calculations allowed us to predict...

Data for Generative AI Modeling of Serpentinte Dehydration Veins in Subduction Zones

Austin Arias

2026

We used hand specimens of Erro-Tobbio meta-serpentinite (ET-MS) and outcrop surface images of olivine dehydration veins to train generative models to generate unique and varied dehydration vein network structures. These models coupled with thermodynamic calculations allowed us to predict...

Data for Generative AI Modeling of Serpentinte Dehydration Veins in Subduction Zones

Austin Arias

2025

We used hand specimens of Erro-Tobbio meta-serpentinite (ET-MS) and outcrop surface images of olivine dehydration veins to train generative models to generate unique and varied dehydration vein network structures. These models coupled with thermodynamic calculations allowed us to predict...

Data for coupled brittle-viscous deformation of folded olivine veins in metaserpentinite: implications for slow slip and tremor

Austin Arias

2026

We documented the microstructural and geochemical characteristics of partially dehydrated and deformed metaserpentinite rocks from Erro-Tobbio, Voltri Massif, Italy. A thin section was prepared from a hand specimen taken from Erro-Tobbio. The thin section contains a folded olivine vein...

Data Supplement to Erosion by CO2 driven flows on Mars

Lonneke Roelofs

2025

The data presented and described here is a supplement to the following manuscript: Roelofs, L., Conway, S.J., van Dam, B., van Eijk, A., Merrison, J.P., Iversen, J.J., Markies, H., van Maarseveen, M., de Haas, T. - Flow dynamics and volume growth during erosion of different substrates by...

Data supplement to "The dynamics of CO2-driven granular flows in gullies on Mars" [UPDATED]

Lonneke Roelofs

2024

The data presented in this package stems from two sets of experiments with CO2-driven granular flows under Martian atmospheric conditions. These experiments were conducted two Mars chambers (Mars Chamber at the Open University, Milton Keynes, UK and the Aarhus Mars Simulation Wind Tunnel at...

Replication data for "Increasing the Accuracy and Efficiency of 2 Micromagnetic Tomography by Double Sided Scanning"

Frenk Out

2024

This Dataset contains all data and scripts required to replicate the results presented in the manuscript. All data processing is carried out in jupyter notebooks and python scripts. Required python packages are listed in the requirements.txt file, found in the codes folder. We employed NanoCT...