Study particle emission in vacuum from film deposits
Joseph S. Logan, James J. McGill
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Digitisation offers significant opportunities for the formulated product industry to transform the way it works. Recent developments in the fields of artificial intelligence, machine learning, robotics and high performance computing present disruptive and transformative methods to accelerate the R&D process. These methods include physics-based chemical simulation, data driven models and hybrid approaches, each of which has been shown to provide new physical and chemical insights that can augment experimental R&D. However, successfully exploiting these technologies in R&D organisations at scale is challenging due to the high level of domain specialisation required and the need for novel models for the formulation domain. In this paper we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. These demonstrators focus on computational modelling methods. In particular we discuss how we tackled the issue of domain specialisation and the challenges we encountered in creating accurate models for formulation problems. © 2020 Society of Chemical Industry.
Joseph S. Logan, James J. McGill
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
S.M. Rossnagel, Michael A. Russak, et al.
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Ijeoma Nnebe, Claudius Feger, et al.
MRS Fall Meeting 2006
H.R. Brown
International Conference on the Role of Interfaces in Advanced Materials Design, Processing and Performance 1993