Performance Forecast of Solar Spectrum Selective Absorbing Coating Based on RBF Neural Network

Abstract:

The paper researches on the coating performance prepared by sputtering stainless steel particles to Cu substrate, analyzes the effect of the six magnetron sputtering process parameters on absorption rate, such as Ar pressure, oxygen flow, sputtering vacuum degree, sputtering time, target voltage and target current with the artificial neural network technology, and forecasts the performance of the coating prepared by specific process parameters. The results show that during the process of magnetron sputtering when Ar pressure is within the range of 0.2 ~ 0.5 Pa, the oxygen flow is within the range of 0 ~ 20 sccm, and the target current is within the range of 380~ 430 A, the higher the sputtering vacuum degree and the target voltage, the superior the performance of the coating can be obtained. It is also found that the sputtering time has little effect on the coating performance, in the actual preparation process, on the condition that the performance can be guaranteed, the sputtering time should be as short as possible.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 577-580
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.577
• Online since: September 2013
• Authors: Han Wu Liu, Shao Bo Ping, Feng Zhang, Xin Long Zhang
• Keywords: Magnetron Sputtering, Medium-High Temperature Coating, Performance Forecast, RBF Neural Network, Selective Absorbing Spectrum

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