CMOS imagers are commonly employing pinned photodiode pixels and true correlated double sampling to eliminate kTC noise and achieve low noise performance. Low noise performance also depends on optimisation of the readout circuitry. This paper investigates the effect of the pixel source follower transistor on the overall noise performance through several characterization methods. The characterization methods are described, and experimental results are detailed. It is shown that the source follower noise can be the limiting factor of the image sensor and requires optimisation.
KEYWORDS: Resistors, Resistance, 3D modeling, Field effect transistors, Semiconductors, Process control, 3D imaging standards, Modulation, Manufacturing, Analog electronics
Sheet resistance measurements are often used as process control monitors and are a key part of resistor measurements for SPICE models. These are normally Ohmic in nature. However it can be seen that buried layer resistors are strongly affected by the applied bias conditions in a similar mode to JFET operation. Two standard resistor structures have been studied to investigate this effect: the bar resistor and the van der Pauw, 2D and 3D-device simulation have been used to model the self-modulation and to produce recommendations for optimized routine measurement.
Technology CAD (TCAD) is a commonly used tool in process development and analysis. The task of creating the process in the required format for the TCAD deck is non-trivial and often prone to error due to the detailed nature of the furnace processing. Ensuring that the simulation deck is matched to the actual furnace process is also a key area. There is a difference between what is programmed into the furnace and what the wafers actually see. This work presents a method of automatic download of the actual furnace parameters to a format directly readable by the process simulator SUPREM, and examines the consequences of the furnace variability inherent in batch processing. The three furnace zones can be seen to interact and product best-worst case simulations to aid in the prediction of manufacturability.
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