In this work, we developed silver nanowires and a silicon based Schottky junction and demonstrated ultrafast broadband photosensing behavior. The current device had a response speed that was ultrafast, with a rising time of 36 μs and a falling time of 382 μs, and it had a high level of repeatability across a broad spectrum of wavelengths (λ = 365 to 940 nm). Furthermore, it exhibited excellent responsivity of 60 mA/W and a significant detectivity of 3.5 × 1012 Jones at a λ = 940 nm with an intensity of 0.2 mW cm2 under zero bias operating voltage, which reflects a boost of 50%, by using the AC PV effect. This excellent broadband performance was caused by the photon-induced alternative photocurrent effect, which changed the way the optoelectronics work. This innovative approach will open a second door to the potential design of a broadband ultrafast device for use in cutting-edge optoelectronics.
The lattice oxygen mechanism (LOM) is considered one of the promising approaches to overcome the sluggish oxygen evolution reaction (OER), bypassing -OOH* coordination with a high energetic barrier. Activated lattice oxygen can participate in the OER as a reactant and enables O*-O* coupling for direct O2 formation. However, such reaction kinetics inevitably include the generation of oxygen vacancies, which leads to structural degradation, and eventually shortens the lifetime of catalysts. Here, we demonstrate that Se incorporation significantly enhances OER performance and the stability of NiFe (oxy)hydroxide (NiFe) which follows the LOM pathway. In Se introduced NiFe (NiFeSe), Se forms not only metal-Se bonding but also Se-oxygen bonding by replacing oxygen sites and metal sites, respectively. As a result, transition metals show reduced valence states while oxygen shows less reduced valence states (O-/O2 2-) which is a clear evidence of lattice oxygen activation. By virtue of its electronic structure modulation, NiFeSe shows enhanced OER activity and long-term stability with robust active lattice oxygen compared to NiFe.
In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 256 pixels (high resolution: HR) from TEM measurements and 32 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO4 nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.
In this study, an Co/Fe coated porcelain using a cobalt and ferrous sulfate was sintered at 1,250 oC. The specimens were investigated by HR-XRD, FE-SEM (EDS), Dilatometer, and UV-vis spectrophotometer. The surface of the porcelain was uniformly fused with the pigment, and white ware and celadon body specimens were densely fused to a certain thickness from the surface. Other new compounds were produced by the chemical reaction of cobalt/ferrous sulfate with the porcelain body during the sintering process. These compounds were identified as cobalt ferrite spinel phases for white ware and white mixed ware, and an andradite phase for the celadon body, and the amorphous phase, respectively. As for the color of the specimens coated with cobalt and ferrous mixed pigments, it was found that the L* value was greatly affected by the white ware, and the a* and b* values were significantly changed in the celadon body. The L* values of the specimens fired with pure white ware, celadon body, and white mix ware were 72.1, 60.92, 82.34, respectively. The C7F3 pigment coated porcelain fired at 1,250 oC had L* values of 39.91, 50.17, and 40.53 for the white ware, celadon body, and white mixed ware, respectively; with a* values of -1.07, -2.04, and -0.19, and at b* values of 0.46 and 6.01, it was found to be 4.03. As a new cobalt ferrite spinel phase was formed, it seemed to have had a great influence on the color change of the ceramic surface.