Despite being recognized as a promising technique for treating high salinity water, membrane distillation (MD) has been plagued by the scaling of sparingly soluble salts. The growth of crystals can not only create additional resistance to evaporating water at the feed-membrane interface, but also alter the hydrophobic network to bridge the feed and distillate (i.e., result in the phenomenon of wetting). When recognizing the uncertain behaviors of calcium sulfate (CaSO 4 ) scaling in MD, this study was motivated to ascertain whether the crystal-membrane interactions could be dependent on the variation in crystalline morphology. In particular, optical coherence tomography (OCT) was employed to characterize the scaling-induced wetting via a direct-observation-through-the-membrane (DOTM) mode, which mitigated the effects of developing an external scaling layer on resolving the crystal-membrane interactions. The improved in-situ characterization suggests that the crystalline morphology of CaSO 4 could be effectively regulated by varying the stoichiometry of crystallizing ions; the richness of calcium in the aqueous environment for crystallization would be in favor of weakening the crystal-membrane interactions. The stoichiometry-dependent growth of CaSO 4 crystals can be exploited to develop an effective strategy for preventing the hydrophobic network from being wetted or irreversibly damaged.
Li Bowen,Zhang Yipeng,Wang Jiashuai,Jia Zezhao,Shi Chengqian,Ma Yanqing,Ma Lei
The double-electrolyte etching method is a simple and effective way to fabricate ultra-sharp scanning tunnel microscopy (STM) tungsten tips. However, it is still challenging for this method to get ultra-sharp tungsten tips with high yield. In this work, significant enhancing of the yield is presented through optimized etching parameters as follows: temperature of 26 °C, applied voltage 7.5 V, electrolyte concentration 4 mol L −1 and length below the liquid lamellae of 2 mm. Under these conditions, the smallest tip radius is around 8 nm and the yield (radius < 10 nm) is 63.5%. These tips are capable of producing high-quality atomic resolution STM images, as demonstrated by testing on Si (111) and highly oriented pyrolytic graphite (HOPG) samples at room temperature. Furthermore, in order to find the relationship between the tip features and experimental etching parameters, an artificial neural network (ANN) model is built by machine learning. Garson’s algorithm is used to analyze the relative importance of each experimental parameter on tip features. The tip features can be estimated by this model with a correlation factor R over 0.85 indicating great predictive performance . Importance analysis indicates that the length of the tungsten wire below the liquid lamellae is the most important parameter to obtain high-quality STM tungsten tips in the double-electrolyte etching method. This result provides a clear direction for rapidly selecting optimized tip fabrication parameters in the future.
危险品化学品经营许可证（带存储）