Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jyri Kimari"'
Autor:
Jyri Kimari, Ville Jansson, Simon Vigonski, Ekaterina Baibuz, Roberto Domingos, Vahur Zadin, Flyura Djurabekova
Publikováno v:
Data in Brief, Vol 32, Iss , Pp 106094- (2020)
Kinetic Monte Carlo (KMC) is an efficient method for studying diffusion. A limiting factor to the accuracy of KMC is the number of different migration events allowed in the simulation. Each event requires its own migration energy barrier. The calcula
Externí odkaz:
https://doaj.org/article/8eb247bd0f604d17815a0574e8f2b438
Publikováno v:
Journal of Physics D
Under strong electric fields, an arc of strong current flowing through plasma can link two metal surfaces even in ultra high vacuum. Despite decades of research, the chain of events leading to vacuum arc breakdowns is hitherto unknown. Previously we
Many applications, especially in physics and other sciences, call for easily interpretable and robust machine learning techniques. We propose a fully gradient-based technique for training radial basis function networks with an efficient and scalable
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd616e8f011915cf58267af1f1606584
http://hdl.handle.net/10138/324975
http://hdl.handle.net/10138/324975
Autor:
Vahur Zadin, Simon Vigonski, Jyri Kimari, Flyura Djurabekova, Ville Jansson, Ekaterina Baibuz, Roberto P. Domingos
Kinetic Monte Carlo (KMC) is a powerful method for simulation of diffusion processes in various systems. The accuracy of the method, however, relies on the extent of details used for the parameterization of the model. Migration barriers are often use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59850d7116b1aa10b6a6beab5ec5fb03
http://hdl.handle.net/10138/318844
http://hdl.handle.net/10138/318844