| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Marone, Federica
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (17/17 displayed)
- 2024X-ray scattering tensor tomography based finite element modelling of heterogeneous materialscitations
- 2024Experimental quantification of inward Marangoni convection and its impact on keyhole threshold in laser powder bed fusion of stainless steelcitations
- 2023Harmonizing sound and light: X-ray imaging unveils acoustic signatures of stochastic inter-regime instabilities during laser meltingcitations
- 2023Operando tomographic microscopy during laser-based powder bed fusion of aluminacitations
- 2022Macroscopic mapping of microscale fibers in freeform injection molded fiber-reinforced composites using X-ray scattering tensor tomographycitations
- 2022Crack-reduced alumina/aluminum titanate composites additive manufactured by laser powder bed fusion of black TiO 2−x doped alumina granulescitations
- 2020Cracks, porosity and microstructure of Ti modified polymer-derived SiOC revealed by absorption-, XRD- and XRF-contrast 2D and 3D imagingcitations
- 2020Additive micro-manufacturing of crack-free PDCs by two-photon polymerization of a single, low-shrinkage preceramic resincitations
- 2020Selective laser melting of thermal pre-treated METAL oxide doped aluminum oxide granulescitations
- 2019A general model for welding of ash particles in volcanic systems validated using in situ X-ray tomographycitations
- 2017Molecular and microstructural inventory of an isolated fossil bird feather from the Eocene Fur Formation of Denmarkcitations
- 2015Synchrotron X-ray radiography studies of pitting corrosion of stainless steel: Extraction of pit propagation parameterscitations
- 2014Implications of polymer electrolyte fuel cell exposure to synchrotron radiation on gas diffusion layer water distributioncitations
- 2013Interfacial phenomena during salt layer formation under high rate dissolution conditionscitations
- 2010Universality and self-similarity in pinch-off of rods by bulk diffusioncitations
- 2009In situ microtomographically monitored and electrochemically controlled corrosion initiation and propagation in AlMgSi alloy AA6016citations
- 2008Electrochemically controlled corrosion initiation and propagation in AlMgSi alloys in-situ monitored using X-ray microtomographycitations
Places of action
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article
A general model for welding of ash particles in volcanic systems validated using in situ X-ray tomography
Abstract
<p>Welding occurs during transport and deposition of volcanic particles in diverse settings, including pyroclastic density currents, volcanic conduits, and jet engines. Welding rate influences hazard-relevant processes, and is sensitive to water concentration in the melt. We characterize welding of fragments of crystal-free, water-supersaturated rhyolitic glass at high temperature using in-situ synchrotron-source X-ray tomography. Continuous measurement of evolving porosity and pore-space geometry reveals that porosity decays to a percolation threshold of 1–3 vol.%, at which bubbles become isolated and welding ceases. We develop a new mathematical model for this process that combines sintering and water diffusion, which fits experimental data without requiring empirically-adjusted parameters. A key advance is that the model is valid for systems in which welding is driven by confining pressure, surface tension, or a combination of the two. We use the model to constrain welding timescales in a wide range of volcanic settings. We find that volcanic systems span the regime divide between capillary welding in which surface tension is important, and pressure welding in which confining pressure is important. Our model predicts that welding timescales in nature span seconds to years and that this is dominantly dependent on the particle viscosity or the evolution of this viscosity during particle degassing. We provide user-friendly tools, written in Python™ and in Excel®, to solve for the evolution of porosity and dissolved water concentration during welding for user-defined initial conditions.</p>