Journal article
Modelling ultra-fast nanoparticle melting with the Maxwell–Cattaneo equation
- Abstract:
- The role of thermal relaxation in nanoparticle melting is studied using a mathematical model based on the Maxwell–Cattaneo equation for heat conduction. The model is formulated in terms of a two-phase Stefan problem. We consider the cases of the temperature profile being continuous or having a jump across the solid–liquid interface. The jump conditions are derived from the sharp-interface limit of a phase-field model that accounts for variations in the thermal properties between the solid and liquid. The Stefan problem is solved using asymptotic and numerical methods. The analysis reveals that the Fourier-based solution can be recovered from the classical limit of zero relaxation time when either boundary condition is used. However, only the jump condition avoids the onset of unphysical “supersonic” melting, where the speed of the melt front exceeds the finite speed of heat propagation. These results conclusively demonstrate that the jump condition, not the continuity condition, is the most suitable for use in models of phase change based on the Maxwell–Cattaneo equation. Numerical investigations show that thermal relaxation can increase the time required to melt a nanoparticle by more than a factor of ten. Thus, thermal relaxation is an important process to include in models of nanoparticle melting and is expected to be relevant in other rapid phase-change processes.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Accepted manuscript, pdf, 1.4MB, Terms of use)
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- Publisher copy:
- 10.1016/j.apm.2018.12.004
Authors
+ European Commission
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- Grant:
- Horizon2020research
- innovationprogrammeundertheMarieSkłodowska-CuriegrantagreementNo.707658
- Publisher:
- Elsevier
- Journal:
- Applied Mathematical Modelling More from this journal
- Volume:
- 69
- Pages:
- 201-222
- Publication date:
- 2018-12-15
- Acceptance date:
- 2018-12-06
- DOI:
- ISSN:
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0307-904X
- Keywords:
- Pubs id:
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pubs:929994
- UUID:
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uuid:c0e1a5e2-94ad-4bcd-9424-98cbef86832a
- Local pid:
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pubs:929994
- Source identifiers:
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929994
- Deposit date:
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2018-12-11
- ARK identifier:
Terms of use
- Copyright holder:
- Elsevier Inc
- Copyright date:
- 2018
- Notes:
- Copyright © 2018 Elsevier Inc. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.apm.2018.12.004
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