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The combinative effects of thermal annealing and additive processes on the performance of all-polymer bulk heterojunction (BHJ) solar cells with composites of different donor polymers (PTQ1, P3HT, PTB7-Th) and poly[1,8bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2,2′-bithiophene)P(NDI2OD-T2) [PolyeraActivInk N2200] were investigated. We found that devices treated with both processes show significant improved performance compared with those treated with either process alone. To reveal the mechanism of this enhancement in device performance, the optical and electrical properties of all-polymer blends were carefully investigated in the PTQ1/N2200 system. The synergetic effect of both processes can largely enhance the polymer aggregation, especially for N2200, leading to improved absorbance, improved charge mobility, and thus higher device performance. In addition, the device efficiency can be further enhanced by postannealing which can improve the interface between the active layer and Al cathode, as revealed by atomic force microscopy investigations. Moreover, the approaches reported here provide a simple and versatile method to optimize all-polymer solar cells and may help pave the route for this emerging system to overtake the state-of-the-art polymer/fullerene solar cells.

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An automated corrosion monitor, named the Internet of Things atmospheric corrosion monitor (IoT ACM) has been developed. IoT ACM is based on electrical resistance sensor and enables accurate and continuous measurement of corrosion data of metallic materials. The objective of this research is to study the characteristics of atmospheric corrosion by analyzing the acquired corrosion data from IoT ACM. Employing data processing and data analysis methods to research the acquired corrosion data of steel, the atmospheric corrosion characteristics implied in the corrosion data can be discovered. Comparing the experiment results with the phenomenon of previous laboratory experiment and conclusions of previously published reports, the research results are tested and verified. The experiment results show that the change regulation of atmospheric corrosion data in the actual environment is reasonable and normal. The variation of corrosion depth is obviously influenced by relative humidity, temperature and part of air pollutants. It can be concluded that IoT ACM can be well applied to the conditions of atmospheric corrosion monitoring of metallic materials and the study of atmospheric corrosion by applying IoT ACM is effective and instructive under an actual atmospheric environment.