Polymer-stabilized cholesteric liquid crystals (PSCLCs) with a double-handed circularly polarized reflection band are fabricated by a wash-out/refill method. By removing the low molar weight LCs from the original PSCLC film, desirable liquid crystals (LCs) can be infiltrated into a prefabricated polymer network. The results showed that the memory of the polymer network controls the resulting material properties. The concentration of the prefabricated polymer network also plays a relevant role in the formation of a singlelayer cholesteric LC (Ch-LC) structure that has a clear-cut double-handed circularly polarized reflection band. A light-scattering phenomenon occurring in the system alters the reflection properties of Ch-LCs, which is due to the weak anchoring effect of the network when PSCLC film contains a low network concentration. Both kinds of circularly polarized reflection become more obvious with increase in the network concentration, followed by the strong anchoring effect of the network. The technique developed in this study has great applications in industries that require solid optical functional films and coatings.

A series of triphenylene-based discotic dimers have been synthesized, each of the triphenylene nuclei bears five b-OC 4 H 9 substituents, which are linked through the remaining b-positions by a flexible O(CH 2 ) n O polymethylene chain (n ¼ 2-12). Their chemical structures were confirmed by proton nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, high-resolution mass spectrometry and elemental analysis. The mesomorphic properties of these compounds were investigated by differential scanning calorimetry, polarizing optical microscopy and X-ray diffraction. It was found that these dimers for which n > 4 formed a highly ordered columnar plastic phase and some of them (n ¼ 6, 7, 10, 11, and 12) exhibited multiple mesophases. This is the first time that the rectangular columnar plastic phase was defined by us as a novel liquid crystal phase of compound 4d (n ¼ 5). The introduction of a single interconnecting chain between adjacent molecules does not significantly perturb the formation of a columnar plastic phase but enriches the mesophases of discotic molecules and hinders the crystallization; the mesophases of 4e-k (n ¼ 6-12) can be supercooled into a glass state in which the self-assembly columnar structures are retained.

The fabrication of organic semiconductor thin films by printing technologies is expected to enable the low-cost production of devices such as flexible display drivers, RF-ID tags, and various chemical/biological sensors. However, large-scale high-speed fabrication of uniform semiconductor thin films with adequate electrical properties for these devices remains a big challenge. Herein, we demonstrate an ultrafast and scalable fabrication of uniform polycrystalline thin films with 100% surface coverage using liquid crystalline semiconductors such as 2-phenyl-7-decyl[1]­benzothieno­[3,2-b]­[1]­benzothiophene (Ph-BTBT-10) and 2.7-dioctyl[1]­benzothieno­[3,2-b]­[1]­benzothiophene (C8-BTBT-C8), at a rate of 3 orders of magnitude higher than before, i.e., 40 mm/s (2.4 m/min) or more by dip-coating in the drainage regime. Organic transistors fabricated with polycrystalline thin films of Ph-BTBT-10 show average mobilities of 4.13 ± 0.75 cm2/(V s) in the bottom-gate–bottom-contact configuration and 10.90 ± 2.40 cm2/(V s) in the bottom-gate–top-contact configuration comparable to those of the devices prepared with single-crystalline thin films. More importantly, these films almost maintain the FET performance when the substrate size is extended up to 4 square inch. The present findings are available for other liquid crystalline semiconductors and bring us one step closer to the realization of printed electronics.

Accurate and timely crop yield estimation is critical for food security and sustainable development. The rapid development of unmanned aerial vehicles (UAVs) offers a new approach to acquire high spatio-temporal resolution imagery of farmland at a low cost. In order to realize the full potential of UAV platform and sensor, machine learning has been introduced to estimate crop yield, but the shortages of field measurements have troubled researchers. In this study, the CW-RF model, a new wheat yield estimation model suitable for the North China Plain, was established using random forest, and the crop growth model (the CERES-Wheat model) was chosen to simulate abundant training samples for random forest at field plot scale. According to CERES-Wheat model simulation, the leaf area index (LAI) and leaf nitrogen content (LNC) at the wheat jointing and heading stages were selected as the most sensitive parameters, and were retrieved from UAV hyperspectral imagery using the directional second derivative (DSD) and angular insensitivity vegetation index (AIVI) methods respectively. Then the retrieved LAI and LNC results were input into the CW-RF model to estimate winter wheat yield. The field validation in Luohe, Henan showed that the root mean squared error (RMSE) of the retrieved LAI and LNC were 6.27% and 12.17% at jointing stages, 9.21% and 13.64% at heading stages, respectively. The RMSE of estimated yield was 1,008.08 kg/ha, and the mean absolute percent error (MAPE) of estimated yield was 9.36%, demonstrating the available of the CW-RF model in wheat yield estimation at field plot scale. Apart from Luohe, validations in some other fields (e.g. Xiaotangshan, Beijing), prove the wide applicability of the CW-RF model. In addition, the UAV hyperspectral data were found to significantly improve the retrieval accuracy, and further improve CW-RF model estimation accuracy. In conclusion, this study showed that the CERES-Wheat model simulation can be important data source for machine learning-based wheat yield estimation model at field plot scale, and the hyperspectral sensor mounted on a UAV is a feasible remote sensing data acquisition mode for winter wheat growth monitoring and yield estimation.Index Terms-wheat yield estimation, the CERES-Wheat model, random forest, unmanned aerial vehicle (UAV), hyperspectral remote sensing