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Luca Messina

Royal Institute of Technology

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Publication

Featured researches published by Luca Messina.

Physical Review B | 2014

Exact ab initio transport coefficients in bcc Fe-X (X=Cr, Cu, Mn, Ni, P, Si) dilute alloys

Luca Messina; Maylise Nastar; Thomas Garnier; C. Domain; Pär Olsson

Physical Review B | 2016

Systematic electronic-structure investigation of substitutional impurity diffusion and flux coupling in bcc iron

Luca Messina; Maylise Nastar; Nils Sandberg; Pär Olsson

Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms | 2013

Ab initio modelling of vacancy-solute dragging in dilute irradiated iron-based alloys

Luca Messina; Zhongwen Chang; Pär Olsson

Physical Review B | 2015

Modeling of the magnetic free energy of self-diffusion in bcc Fe

Nils Sandberg; Zhongwen Chang; Luca Messina; Pär Olsson; Pavel A. Korzhavyi

Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms | 2015

Stability and mobility of small vacancy–solute complexes in Fe–MnNi and dilute Fe–X alloys: A kinetic Monte Carlo study

Luca Messina; Lorenzo Malerba; Pär Olsson

Nuclear Instruments & Methods in Physics Research Section B-beam Interactions With Materials and Atoms | 2017

Nanostructure evolution of neutron-irradiated reactor pressure vessel steels: Revised Object kinetic Monte Carlo model

M. Chiapetto; Luca Messina; C.S. Becquart; Pär Olsson; Lorenzo Malerba

Physica Status Solidi (a) | 2016

An object kinetic Monte Carlo model for the microstructure evolution of neutron-irradiated reactor pressure vessel steels

Luca Messina; M. Chiapetto; Pär Olsson; C.S. Becquart; Lorenzo Malerba

Physical Review B | 2017

Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations

Luca Messina; Nicolas Castin; Christophe Domain; Pär Olsson

Physical Review B | 2017

Improved atomistic Monte Carlo models based on ab-initio -trained neural networks: Application to FeCu and FeCr alloys

N. Castin; Luca Messina; C. Domain; R.C. Pasianot; Pär Olsson

arXiv: Computational Physics | 2018

Smart energy models for atomistic simulations using a DFT-driven multifidelity approach.

Luca Messina; Alessio Quaglino; Alexandra Goryaeva; Mihai-Cosmin Marinica; Christophe Domain; Nicolas Castin; Giovanni Bonny; Rolf Krause

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Collaboration

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Pär Olsson

Malmö University

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Lorenzo Malerba

Université libre de Bruxelles

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Nils Sandberg

Royal Institute of Technology

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Zhongwen Chang

Royal Institute of Technology

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C. Domain

Électricité de France

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Maylise Nastar

Massachusetts Institute of Technology

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Christophe Domain

university of lille

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R.C. Pasianot

National Scientific and Technical Research Council

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Nicolas Castin

Université libre de Bruxelles

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Mattias Thuvander

Chalmers University of Technology

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