Surface preparation by mechanical polishing of the 1.3-GHz mono-cell copper cavity substrate prior chemical etching for niobium coating

2020
Surface quality of the substrate is widely acknowledged to be essential for the niobium thin film deposition. Much effort has thus been spent to improve the surface roughness by using various chemical etching techniques. However, surface preparation before the chemical etching also plays a part in obtaining a satisfactory substrate, but has rarely been studied before. This paper aims to define a specification for the pre-polished copper substrate prior chemical etching and searches for suitable alternative non-chemical grinding methods for the copper cavity. Copper samples were mechanically pre-polished at first by using flap sanding wheels of different grits and then chemically etched by using the well-established SUBU solutions. Surface roughness, as a figure of merit, was measured and compared before and after SUBU. Optimum practice for pre-polishing may therefore be determined. The mechanical grinding was subsequently applied on the 1.3-GHz mono-cell copper cavity. Meantime, the previously reported centrifugal barrel polishing method was also applied with new abrasive materials and modified schemes. A comprehensive study of etching rate, surface roughness and morphologies was conducted. The specification for surface roughness prior SUBU was determined. Due to a complex geometry and curved surfaces possessed by the 1.3-GHz copper cavity, the traditional mechanical grinding was proved to be not ideal. Satisfactory surface quality was obtained by using the alternative centrifugal barrel polishing on the cavity. The proposed new scheme and new abrasive materials were demonstrated to be effective, and a mirror-like surface was achieved on the copper cavity. The traditional mechanical grinding can therefore be replaced. This constitutes a dedicated study on pre-polishing of the 1.3-GHz copper cavity substrate prior chemical etching for niobium sputtering.
    • Correction
    • Source
    • Cite
    • Save
    10
    References
    0
    Citations
    NaN
    KQI
    []
    Baidu
    map