Recently, the pursuit of high photoluminescence quantum yields (PLQYs) for blue emission in perovskite nanocrystals (NCs) has attracted increased attention because the QY of blue NCs lags behind those of green and red ones severely, which is fatal for three-primary-color displays. Here, we propose an in situ PbBr 6 4− octahedra passivation strategy to achieve a 96% absolute QY for the ultrapure (line width = 12 nm) blue emission from CsPbBr 3 nanoplatelets (NPLs), and both values rank first among perovskite NCs with blue emission. From the aspect of constructing intact PbBr 6 4− octahedra, additional Br − was introduced to drive the ionic equilibrium to form intact Pb−Br octahedra. The reduced Br vacancy and inhibited nonradiative recombination processes are well proved by reduced Urbach energy, increased Pb−Br bonds, and slower transient absorption delay. Blue light-emitting diodes (LEDs) using NPLs were fabricated, and a high external quantum efficiency (EQE) of 0.124% with an emission line width of ∼12 nm was realized. This work will provide good references to break the "blue-wall" in perovskite NCs.

Fluorescent type nuclear battery consisting of scintillator and photovoltaic device enables semipermanent power source for devices working under harsh circumstances without instant energy supply. In spite of the progress of device structure design, the development of scintillators is far behind. Here, a Cs3Cu2I5: Mn scintillator showing a high light yield of ~67000 ph MeV−1 at 564 nm is presented. Doping and intrinsic features endow Cs3Cu2I5: Mn with robust thermal stability and irradiation hardness that 71% or >95% of the initial radioluminescence intensity can be maintained in an ultra-broad temperature range of 77 K-433 K or after a total irradiation dose of 2590 Gy, respectively. These superiorities allow the fabrication of efficient and stable nuclear batteries, which show an output improvement of 237% respect to the photovoltaic device without scintillator. Luminescence mechanisms including self-trapped exciton, energy transfer, and impact excitation are proposed for the anomalous dramatic radioluminescence improvement. This work will open a window for the fields of nuclear battery and radiography.

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Face restoration is important in face image processing, and has been widely studied in recent years. However, previous works often fail to generate plausible high quality (HQ) results for real-world low quality (LQ) face images. In this paper, we propose a new progressive semantic-aware style transformation framework, named PSFR-GAN, for face restoration. Specifically, instead of using an encoder-decoder framework as previous methods, we formulate the restoration of LQ face images as a multi-scale progressive restoration procedure through semantic-aware style transformation. Given a pair of LQ face image and its corresponding parsing map, we first generate a multi-scale pyramid of the inputs, and then progressively modulate different scale features from coarse-to-fine in a semantic-aware style transfer way. Compared with previous networks, the proposed PSFR-GAN makes full use of the semantic (parsing maps) and pixel (LQ images) space information from different scales of input pairs. In addition, we further introduce a semantic aware style loss which calculates the feature style loss for each semantic region individually to improve the details of face textures. Finally, we pretrain a face parsing network which can generate decent parsing maps from real-world LQ face images. Experiment results show that our model trained with synthetic data can not only produce more realistic high-resolution results for synthetic LQ inputs and but also generalize better to natural LQ face images compared with state-of-the-art methods. Codes are available at https://github.com/chaofengc/PSFRGAN.