A cost effectively method to fabricate nanopores in silicon by only using the conventional wet-etching technique is developed in this research. The main concept of the proposed method is a two-step etching process, including a premier double-sided wet etching and a succeeding track-etching. A special fixture is designed to hold the pre-etched silicon wafer inside it such that the track-etching can be effectively carried out. An electrochemical system is employed to detect and record the ion diffusion current once the pre-etched cavities are etched into a through nanopore. Experimental results indicate that the proposed method can cost effectively fabricate nanopores in silicon.
We demonstrate a simple scheme to achieve Fano-like resonance by coupling a microsphere resonator with a fiber Mach-Zehnder interferometer (FMZI), which includes a tapered microfiber in one pathway to evanescently couple with the microsphere. In this system, Fano-like asymmetric lineshapes could be converted into different types by introducing an extra phase shift in the FMZI. In addition, the sharpness of the Fano-like lineshapes could be controlled by changing the coupling strength between the microsphere and the microfiber. This Fano-like resonance with advantages of fiber integration, tunable lineshape, and ease of operation may have great potential in optical signal processing and sensing.
Process control is one of the key methods to improve manufacturing quality. This research proposes a neural network based run-to-run process control scheme that is adaptive to the time-varying environment. Two multilayer feedforward neural networks are implemented to conduct the process control and system identification duties. The controller neural network equips the control system with more capability in handling complicated nonlinear processes. With the system information provided by this neural network, batch polishing time (T) an additional control variable, can be implemented along with the commonly used down force (p) and relative speed between the plashing pad and the plashed wafer (v). Computer simulations and experiments on copper chemical mechanical polishing processes illustrate that in drafting suppression and environmental changing adaptation that the proposed neural network based run-to-run controller (NNRTRC) performs better than the double exponentially weighted moving average (d-EWMA) approach. It is also suggested that the proposed approach can be further implemented as both an end-point detector and a pad-conditioning sensor
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