Mass production of quartz high-speed chemical etching applied to AT-cut wafers

Watanabe, Takeshi

doi:10.1109/freq.2001.956251

Cited by 4 publications

(2 citation statements)

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“…A lower equivalent resistance requires that the surface quality of the quartz wafer be increasingly higher. The main methods used to improve the surface quality of quartz wafers include lowering the etching temperature and adding surfactants to the etching solution [8][9][10][11][12]. However, there is little research on the effect of organic solution etching on the surface morphology and electrical properties of quartz wafers in wet etching.…”

Section: Introductionmentioning

confidence: 99%

Wet Etching of Quartz Using a Solution Based on Organic Solvents and Anhydrous Hydrofluoric Acid

et al. 2022

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The quartz-crystal resonator is the core device for frequency control in modern communication systems and network technology. At present, in modern resonator blanks manufacturing, BOE solution is usually used as the etching solution, but its etching rate is relatively volatile, and the surface morphology of the blanks is prone to defects after etching, which brings certain difficulties to the deep-etching process of the wafer. To solve the above challenges, this paper systematically compares a BOE solution and anhydrous etching solution in terms of etching rate, surface morphology, and electrical properties of the blanks after etching. Seven groups of blanks were etched using different etching solutions with different etching conditions to verify their effect on the surface morphology and electrical properties of quartz blanks. The experimental results suggest that the application of anhydrous etching solution has achieved better surface morphology and electrical properties and can be more suitable for application in batch manufacturing. In general, when using anhydrous etching solution, it is possible to reduce surface roughness by up to 70% and equivalent resistance by 32%, and the etch rate is almost 10 times lower than BOE solution under the same temperature, which is more conducive to the rate control of wafers in the etching process.

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Section: Introductionmentioning

confidence: 99%

Wet Etching of Quartz Using a Solution Based on Organic Solvents and Anhydrous Hydrofluoric Acid

et al. 2022

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“…In terms of the etching process, chemical etching is among the most commonly used method compared to other advanced machining methods (laser beam machining, elec-tron discharge machining and etch). Watanabe [35] obtained a linear relationship between etching rate and temperature while comparing wet etching and mechaniccal machining. Williams et al [36] stated that not all materials were etched in all etchants due to time limitations.…”

Section: Introductionmentioning

confidence: 99%

Predictive Modelling of Etching Process of Machinable Glass Ceramics, Boron Nitride, and Silicon Carbide

Ting

Abou-El-Hossein

Chua

2011

MSA

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The present paper discusses the development of the first and second order model for predicting the chemical etching variables, namely, etching rate, surface roughness and accuracy of advanced ceramics. The first and second order etching rate, surface roughness and accuracy equations were developed using the Response Surface Method (RSM). The etching variables included etching temperature, etching duration, solution and solution concentration. The predictive models’ analyses were supported with the aid of the statistical software package – Design Expert (DE 7). The effects of the individual etching variables and interaction between these variables were also investigated. The study showed that predictive models successfully predicted the etching rate, surface roughness and accuracy readings recorded experimentally with 95% confident interval. The results obtained from the predictive models were also compared with Multilayer Perceptron Artificial Neural Network (ANN). Chemical Etching variables predictive by ANN were in good agreement with those with those obtained by RSM. This observation indicated the potential of ANN in predicting chemical etching variables thus eliminating the need for exhaustive chemical etching in optimization

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