Papers by Keyword: Photolithography Process

Abstract: This paper illustrate a facile route to fabricate and develop zinc oxide microwire which acts as transducer for biosensor application. Pattern transfer process is conducted on the wafer substrate by using conventional photolithography process to form IDE electrode. The substrate is coated with positive photo-resist (PR) and exposed for UV light for 10 seconds. After development, the unexposed area is etched by using hydrochloric acid, HCI. In this study, zinc oxide material have become a remarkable choice for bio-sensing development due to large band gap and tailor for bio-molecular application. Zinc oxide solution was prepared through chemical route, that is by using sol-gel method. The coated ZnO films were annealed in furnace at 500°C for 2 hours. ZnO seed solution undergoes hydrothermal growth to synthesize ZnO microwires. ithThe substrate used for this study is p-type silicon wafer which is oxidized. SiO₂ layer is used because it acts as an insulator which is very essential for an electronic device to avoid electrical leakage and improve electron mobility. Further investigation of morphological and electrical characterization is conducted through SEM and I-V test .Average size diameter of Zno microwire is 0.45μm and exhibit 900μA of current at 5V.

Abstract: This paper focuses on a scheduling problem in photolithography process of semiconductor manufacturing. The photolithography equipment can be divided into three main parts, that is, scanner, spinner, and developer. Generally, in like manner to the other processes, the identical product types are processed at the same time in photolithography process since a certain amount of recipe change time is required whenever product type is changed. So, in this research, we consider multi-product production case with different processing times and flow recipes, and then attempt to reduce total processing time in photolithography process. From this research, we show that the total processing time can be minimized if we give a variety of input orders of lots and wafers.

Abstract: Photolithography is usually the bottleneck process with the most expensive equipment in a semiconductor wafer fabrication system. To improve the performances of the photolithography area with dynamic combination rules, a method of Kohonen neural network (KNN)–based performance improvements is proposed. First, a dynamic scheduling framework based on a KNN model and scheduling rules is proposed. A KNN-based sample learning algorithm for improving the performances is presented. Finally, to demonstrate the validity and feasibility of the proposed method, data from a real wafer fabrication system are used to simulate the proposed method. Results of simulation experiments indicate that the proposed method can be used to improve a complex wafer photolithography performance.