1. Kinetic Monte Carlo simulation of random deposition and scaling behavior with respect to the germination length
- Author
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Linda Aissani, Grégoire Sorba, Abdenour Saoudi, Francisco Chinesta, Universite Abbes Laghrour [Khenchela], École Supérieure des Techniques Aéronautiques et de Construction Automobile (ESTACA), Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM), and ESI Group (ESI Group)
- Subjects
Surface (mathematics) ,Work (thermodynamics) ,Materials science ,Quantitative Biology::Tissues and Organs ,02 engineering and technology ,Surface finish ,Random deposition ,Sciences de l'ingénieur ,01 natural sciences ,Quantitative Biology::Cell Behavior ,[SPI]Engineering Sciences [physics] ,germination length ,0103 physical sciences ,Deposition (phase transition) ,General Materials Science ,Statistical physics ,Kinetic Monte Carlo ,Scaling ,roughness ,010302 applied physics ,Numerical Analysis ,growth scaling ,021001 nanoscience & nanotechnology ,Computer Science Applications ,Mechanics of Materials ,Germination ,Modeling and Simulation ,0210 nano-technology - Abstract
International audience; This work aims at analyzing the scaling behavior and develop correlations during surface growing for different germination lengths. The surface growing by random deposition is simulated using a kinetic Monte Carlo approach, by considering different germination lengths. Different surface descriptors are extracted, among them the roughness and the correlation. The former allows extracting the scaling behavior, while the latter proves the existence of correlations independent of the system size but dependent on the germination length. Moreover, as in the case of random deposition with a null germination length, the growing roughness never saturates.
- Published
- 2021
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