Scattering dynamics of rarefied gases: A hybrid atomistic/machine learning approach

Research output: Thesis › Phd Thesis 1 (Research TU/e / Graduation TU/e)

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Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Mechanical Engineering
Supervisors/Advisors	Smeulders, David M.J., Promotor Frijns, Arjan J.H., Copromotor Gaastra-Nedea, Silvia V., Copromotor
Award date	6 Apr 2023
Place of Publication	Eindhoven
Publisher	Eindhoven University of Technology
Print ISBNs	978-90-386-5699-1
Publication status	Published - 6 Apr 2023

Proefschrift.

Access to Document

@phdthesis{1c8216f942334bcba34aca4145ae52c0,

title = "Scattering dynamics of rarefied gases: A hybrid atomistic/machine learning approach",

author = "\{Mohammad Nejad\}, Shahin",

note = "Proefschrift.",

year = "2023",

month = apr,

day = "6",

language = "English",

isbn = "978-90-386-5699-1",

publisher = "Eindhoven University of Technology",

type = "Phd Thesis 1 (Research TU/e / Graduation TU/e)",

school = "Mechanical Engineering",

}