Polymer assisted colloidal nanocrystal framework synthesis: sol-gel approach

The porous colloidal nanocrystal framework material was synthesized by sol-gel assembly followed by a self-propagation procedure. The characteristics of the synthesized nanocrystal were confirmed by advanced instruments. From the DTG analysis, the poly (vinyl alcohol) was completely degraded at 400 °C. The XRD pattern and TEM image confirmed the nanoscale crystallite size of the material. BET and SEM analysis showed the mesoporous type pore size distribution. The predictable compositional analysis was confirmed from EDX, SAED, and XPS compositional analysis. Using the HSAB theory and HRTEM image analysis the formation of local heterojunction between metal oxides was approved.

Super-Resolution Based on Generative Adversarial Network for HRTEM Images

As an important tool to study the microstructure and properties of materials, High Resolution Transmission Electron Microscope (HRTEM) images can obtain the lattice fringe image (reflecting the crystal plane spacing information), structure image and individual atom image (which reflects the configuration of atoms or atomic groups in crystal structure). Despite the rapid development of HTTEM devices, HRTEM images still have limited achievable resolution for human visual system. With the rapid development of deep learning technology in recent years, researchers are actively exploring the Super-resolution (SR) model based on deep learning, and the model has reached the current best level in various SR benchmarks. Using SR to reconstruct high-resolution HRTEM image is helpful to the material science research. However, there is one core issue that has not been resolved: most of these super-resolution methods require the training data to exist in pairs. In actual scenarios, especially for HRTEM images, there are no corresponding HR images. To reconstruct high quality HRTEM image, a novel Super-Resolution architecture for HRTEM images is proposed in this paper. Borrowing the idea from Dual Regression Networks (DRN), we introduce an additional dual regression structure to ESRGAN, by training the model with unpaired HRTEM images and paired nature images. Results of extensive benchmark experiments demonstrate that the proposed method achieves better performance than the most resent SISR methods with both quantitative and visual results.

HRTEM image-stitching for measurement of distances

Very accurate measurement of distances in the order of several µm is demonstrated on a single crystal Si sample by counting the lattice fringes on stitched high resolution TEM/STEM images. Stitching of TEM images commonly relies on correspondence points found in the image, however, the nearly perfect periodic nature of a lattice image renders such a procedure very unreliable. To overcome this difficulty artificial correspondence points are created on the sample using the electron beam. An accuracy better than 1% can be reached while measuring distances in the order of 1 µm. A detailed description of the process is provided, and its usability for accurately measuring large distances is discussed in detail.

Enhanced photocatalytic properties of TiO2 nanosheets@2D layered black phosphorus composite with high stability under hydro-oxygen environment

Typical HRTEM image of the TiO2 nanosheets@BP composite and photocatalytic performance of the BP nanosheets, TiO2 nanosheets and TiO2 nanosheets@BP composite under visible-light irradiation (λ > 420 nm).

Tailoring 2D MoS2 heterointerfaces for promising oxygen reduction reaction electrocatalysis

A schematic representation of the ORR on Ni3S2/MoS2 nanosheets and HRTEM image of their heterointerfaces.