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In this work, PEDOT: PSS 1000 was used as hole transporting layer to fabricate high luminescent perovskite light-emitting diodes. Combined with potassium doping strategy, the according perovskite light-emitting diode reaches a high brightness of 40 000 cd/m2.

A large transparent liquid crystal display (LCD) prototype with ultrahigh transmittance and good see-through property is demonstrated in this paper. The transmittance reaches more than 20% by introducing the RGBW pixel arrangement, a thin color filter process, a large aperture ratio design, as well as antireflective polarizer film. The see-through image quality is also greatly improved by suppressing the blurring by using domain reduction pixel design. All these approaches are applicable for large LCD panel products, and we expect broad applications of large transparent LCDs in the near future.

2D perovskites, typically with a standard formula of L2An-1MnX3n+1, have recently attracted significant attention due to their promising optoelectronic properties. Normally, they contain a mono cation (e.g., butylammonium (BA+) or phenylethylammonium (PEA+) for “L” and methylammonium (MA+) or formamidinium (FA+) for “A”). In this work, multiple cation-substitution strategy was used to improve the luminescence and emission efficiency of perovskite thin films. As a result, brightly blue emission with a high photoluminescence quantum yield of 26% was achieved. Finally, the according perovskite light-emitting diodes reached a brightness of 110 cd/m2, and a maximum external quantum efficiency of 0.79%.

Virtual machine (VM) technology plays an important role in modern cluster and cloud computing environments due to its advantages in application isolation, resource partition and load consolidation. Since a large number of VMs usually run simultaneously in these environments, VMs scheduling is key to achieve resources efficiency. Unfortunately, most existing scheduling strategies are complicated, with unacceptable overhead in a large-scale virtualization environment. Further more, they tend to produce biased results without considering the I/O characteristics of VMs and physical machines (PMs). To deal with the issue, this paper proposes a new strategy for scheduling VMs over physical clusters. Taking into consideration the I/O characteristics, the proposed strategy can obtain better scheduling results while with lower overhead. Moreover, a prediction algorithm is suggested, which, when combined with the proposed strategy, can further improve the scheduling results. The proposed strategy and prediction algorithm have been implemented and evaluated with the SPEC CPU 2006 and Netperf benchmarks. The experimental results show that the average completion time of SPEC reduces by about 23%, whereas the standard deviation of Netperf average bandwidth decreases from 10.9 to 4.2.