Year: 2026
Type: article
Abstract: This work presents a novel and general multiscale computational methodology for modeling the focused electron beam–induced deposition (FEBID) process. The approach is based on stochastic dynamics implemented using the MBN Explorer and MBN Studio software packages and provides a probabilistic description of the complex sequence of physical and chemical processes that govern FEBID, including precursor adsorption, diffusion, dissociation, and desorption. The developed framework enables simulations under experimentally realistic spatial and temporal conditions while retaining molecular-level resolution. An exemplary set of model parameters has been derived from atomistic simulations to demonstrate the methodology’s capabilities; however, the primary goal of this work is not parameter optimization, but rather the establishment of a general and transferable modeling framework applicable to a broad range of precursors, substrates, and irradiation conditions. As a representative case, the FEBID of W(CO) 6 precursors on a hydroxylated SiO 2 –H substrate is investigated, showing how the method reproduces key experimental trends and reveals the microscopic mechanisms of deposit formation. The developed multiscale approach provides a robust foundation for predictive simulations of irradiation-driven fabrication processes and their applications in 3D nanoprinting and nanoscale materials engineering.
Source: Frontiers in Physics
Institutions: Carl von Ossietzky Universität Oldenburg, MBN Research Center
Language: English
Subfield: Surfaces, Coatings and Films
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,077
Awards: G1803172066, G3041538400, G3345895242, G3477743816, G3735802008, SFB 1372: Magnetrezeption und Navigation in Vertebraten: von der Biophysik zu Gehirn und Verhalten, G4780484384, G495415785, Irradiation driven nanofabrication: computational modelling versus experiment, G5986239459, TRR 386: HYP*MOL – Hyperpolarisation in molekularen Systemen, G7286304022, G8367957132
OpenAlex ID: W7223283104
