We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the Gaussian approximation potential framework, fitted to a database of first-principles density functional theory calculations. We investigate the performance of a sequence of models based on databases of increasing coverage in configuration space and showcase our strategy of choosing representative small unit cells to train models that predict properties observable only using thousands of atoms. The most comprehensive model is then used to calculate properties of the screw dislocation, including its structure, the Peierls barrier and the energetics of the vacancy-dislocation interaction. All software and raw data are available at www.libatoms....
International audienceCalculations of dislocation-defect interactions are essential to model metalli...
Understanding and improving the mechanical properties of tungsten is a critical task for the materia...
Data-driven, or machine learning (ML), approaches have become viable alternatives to semiempirical m...
We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the...
We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the...
An accurate description of atomic interactions, such as that provided by first principles quantum me...
We present a bond-order potential (BOP) for the bcc transition metal tungsten. The bond-order potent...
We present a bond-order potential (BOP) for the bcc transition metal tungsten. The bond-order potent...
The results of atomistic simulations of migration and formation energies of mono- and di-vacancies i...
Texto completo: acesso restrito. p. 191–197The results of atomistic simulations of migration and for...
We systematically investigate the interaction between a monovacancy and various lattice dislocations...
Mechanical properties of polycrystalline materials are greatly influenced by the motion of dislocati...
Tungsten and tungsten-based alloys are the primary candidate materials for plasma facing components ...
The thermodynamic properties of intrinsic and extrinsic (Ti, V, Zr, Nb, Hf, Ta, Re) defects in tungs...
The plastic flow behavior of bcc transition metals up to moderate temperatures is dominated by the t...
International audienceCalculations of dislocation-defect interactions are essential to model metalli...
Understanding and improving the mechanical properties of tungsten is a critical task for the materia...
Data-driven, or machine learning (ML), approaches have become viable alternatives to semiempirical m...
We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the...
We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the...
An accurate description of atomic interactions, such as that provided by first principles quantum me...
We present a bond-order potential (BOP) for the bcc transition metal tungsten. The bond-order potent...
We present a bond-order potential (BOP) for the bcc transition metal tungsten. The bond-order potent...
The results of atomistic simulations of migration and formation energies of mono- and di-vacancies i...
Texto completo: acesso restrito. p. 191–197The results of atomistic simulations of migration and for...
We systematically investigate the interaction between a monovacancy and various lattice dislocations...
Mechanical properties of polycrystalline materials are greatly influenced by the motion of dislocati...
Tungsten and tungsten-based alloys are the primary candidate materials for plasma facing components ...
The thermodynamic properties of intrinsic and extrinsic (Ti, V, Zr, Nb, Hf, Ta, Re) defects in tungs...
The plastic flow behavior of bcc transition metals up to moderate temperatures is dominated by the t...
International audienceCalculations of dislocation-defect interactions are essential to model metalli...
Understanding and improving the mechanical properties of tungsten is a critical task for the materia...
Data-driven, or machine learning (ML), approaches have become viable alternatives to semiempirical m...