RESUMEN
A three-dimensional topography simulation of deep reactive ion etching (DRIE) is developed based on the narrow band level set method for surface evolution and Monte Carlo method for flux distribution. The advanced level set method is implemented to simulate the time-related movements of etched surface. In the meanwhile, accelerated by ray tracing algorithm, the Monte Carlo method incorporates all dominant physical and chemical mechanisms such as ion-enhanced etching, ballistic transport, ion scattering, and sidewall passivation. The modified models of charged particles and neutral particles are epitomized to determine the contributions of etching rate. The effects such as scalloping effect and lag effect are investigated in simulations and experiments. Besides, the quantitative analyses are conducted to measure the simulation error. Finally, this simulator will be served as an accurate prediction tool for some MEMS fabrications.
RESUMEN
The floral headspace compounds of Chinese Rosa rugosa germplasms that were isolated by an automated headspace sampler with built-in trap, and followed by gas chromatography-mass spectrometry for identification and quantification. Up to 33 volatile compounds were identified from the 23 rose germplasms, including nine alcohols, five esters, three alkanes, 10 terpenes, three aldehydes, two ketones, and one ether. The main floral components identified were 2-phenylethanol, ß-citronellol, ethanol, and n-hexane. 'xizi', 'miaofengshan', 'xiangciguo', and 'tangbai' contained the highest amounts of 2-phenylethanol at 84.66 µg·g⻹, ß-citronellol at 70.98 µg·g⻹, ethanol at 83.87 µg·g⻹, and n-hexane at 18.23 µg·g⻹, respectively. 'Rongchengyesheng', 'tanghong', 'xizi', 'miaofengshan', and 'baizizhi' could be considered good materials for extracting rose oil and breeding new cultivars.