Abstract: A method of determining wafer curvature in real-time is presented. The method includes establishing a first temperature profile for a hotplate surface, where the hotplate surface is divided into a plurality of temperature control zones. The method further includes positioning a wafer at a first height above the hotplate surface and determining a second temperature profile for the hotplate surface. The wafer curvature is then determined by using the second temperature profile. Also, a dynamic model of a processing system is presented and wafer curvature can be incorporated into the dynamic model.

Abstract: Methods for adaptive real time control of a system for thermal processing substrates, such as semiconductor wafers and display panels. Generally, the method includes creating a dynamic model of the thermal processing system, incorporating wafer bow in the dynamic model, coupling a diffusion-amplification model into the dynamic thermal model, creating a multivariable controller, parameterizing the nominal setpoints, creating a process sensitivity matrix, creating intelligent setpoints using an efficient optimization method and process data, and establishing recipes that select appropriate models and setpoints during run-time.

Abstract: An adaptive real time thermal processing system is presented that includes a multivariable controller. The method includes creating a dynamic model of the MLD processing system and incorporating virtual sensors in the dynamic model. The method includes using process recipes comprising intelligent set points, dynamic models, and/or virtual sensors.

Abstract: An adaptive real time thermal processing system is presented that includes a multivariable controller. The method includes creating a dynamic model of the MLD processing system and incorporating virtual sensors in the dynamic model. The method includes using process recipes comprising intelligent set points, dynamic models, and/or virtual sensors.

Abstract: An adaptive real time thermal processing system is presented that includes a multivariable controller. Generally, the method includes creating a dynamic model of the thermal processing system; incorporating reticle/mask curvature in the dynamic model; coupling a diffusion-amplification model into the dynamic thermal model; creating a multivariable controller; parameterizing the nominal setpoints into a vector of intelligent setpoints; creating a process sensitivity matrix; creating intelligent setpoints using an efficient optimization method and process data; and establishing recipes that select appropriate models and setpoints during run-time.

Abstract: A method for using a silicon germanium (SiGe) surface layer to integrate a high-k dielectric layer into a semiconductor device. The method forms a SiGe surface layer on a substrate and deposits a high-k dielectric layer on the SiGe surface layer. An oxide layer, located between the high-k dielectric layer and an unreacted portion of the SiGe surface layer, is formed during one or both of deposition of the high-k dielectric layer and an annealing process after deposition of the high-k dielectric layer. The method further includes forming an electrode layer on the high-k dielectric layer.

Abstract: An adaptive real time thermal processing system is presented that includes a multivariable controller. Generally, the method includes creating a dynamic model of the thermal processing system; incorporating reticle/mask curvature in the dynamic model; coupling a diffusion-amplification model into the dynamic thermal model; creating a multivariable controller; parameterizing the nominal setpoints into a vector of intelligent setpoints; creating a process sensitivity matrix; creating intelligent setpoints using an efficient optimization method and process data; and establishing recipes that select appropriate models and setpoints during run-time.

Abstract: Methods for adaptive real time control of a system for thermal processing substrates, such as semiconductor wafers and display panels. Generally, the method includes creating a dynamic model of the thermal processing system, incorporating wafer bow in the dynamic model, coupling a diffusion-amplification model into the dynamic thermal model, creating a multivariable controller, parameterizing the nominal setpoints, creating a process sensitivity matrix, creating intelligent setpoints using an efficient optimization method and process data, and establishing recipes that select appropriate models and setpoints during run-time.