Abstract: A method of forming a semiconductor device includes forming a first conductive feature on a bottom surface of an opening through a dielectric layer. The forming the first conductive feature leaves seeds on sidewalls of the opening. A treatment process is performed on the seeds to form treated seeds. The treated seeds are removed with a cleaning process. The cleaning process may include a rinse with deionized water. A second conductive feature is formed to fill the opening.

Abstract: An optical element driving mechanism includes a movable assembly, a fixed assembly, and a driving assembly. The movable assembly is configured to be connected to an optical element. The movable assembly is movable relative to the fixed assembly. The driving assembly is configured to drive the movable assembly to move relative to the fixed assembly in a range of motion. The optical element driving mechanism further includes a positioning assembly configured to position the movable assembly at a predetermined position relative to the fixed assembly when the driving assembly is not operating.

Abstract: The present disclosure provides a method of forming a semiconductor device including an nFET structure and a pFET structure where each of the nFET and pFET structures include a semiconductor substrate and a gate trench. The method includes depositing an interfacial layer in each gate trench, depositing a first ferroelectric layer over the interfacial layer, removing the first ferroelectric layer from the nFET structure, depositing a metal oxide layer in each gate trench, depositing a second ferroelectric layer over the metal oxide layer, removing the second ferroelectric layer from the pFET structure, and depositing a gate electrode in each gate trench.

Abstract: Simulating particle beam interactions includes identifying a set of n functions F1, F2, . . . , Fn corresponding to a plurality of different physical aspects of a particle beam, performing simulations of each Fi using a full physics model, selecting for each Fi a distribution function fi that models relevant behavior and reducing computation of the full physics model for each Fi by replacing Fi with a distribution function fi. The computation reduction includes comparing a set of simulations wherein each fi replaces its respective Fi to determine if relevant behavior is accurately modeled and selecting one of fi or Fi for each n, for a Monte Carlo simulation based on a runtime and accuracy criteria.

Abstract: Simulating particle beam interactions includes identifying a set of n functions F1, F2, . . . , Fn corresponding to a plurality of different physical aspects of a particle beam, performing simulations of each Fi using a full physics model, selecting for each Fi a distribution function fi that models relevant behavior and reducing computation of the full physics model for each Fi by replacing Fi with a distribution function fi. The computation reduction includes comparing a set of simulations wherein each fi replaces its respective Fi to determine if relevant behavior is accurately modeled and selecting one of fi or Fi for each n, for a Monte Carlo simulation based on a runtime and accuracy criteria.