Sub-photon accuracy noise reduction of a single shot coherent diffraction pattern with an atomic model trained autoencoder

Single-shot imaging with femtosecond X-ray lasers is a powerful measurement technique that can achieve both high spatial and temporal resolution. However, its accuracy has been severely limited by the difficulty of applying conventional noise-reduction processing. This study uses deep learning to validate noise reduction techniques, with autoencoders serving as the learning model. Focusing on the diffraction patterns of nanoparticles, we simulated a large dataset treating the nanoparticles as composed of many independent atoms. Three neural network architectures are investigated: neural network, convolutional neural network and U-net, with U-net showing superior performance in noise reduction and subphoton reproduction. We also extended our models to apply to diffraction patterns of particle shapes different from those in the simulated data. We then applied the U-net model to a coherent diffractive imaging study, wherein a nanoparticle in a microfluidic device is exposed to a single X-ray free-electron laser pulse. After noise reduction, the reconstructed nanoparticle image improved significantly even though the nanoparticle shape was different from the training data, highlighting the importance of transfer learning.

In situ fabrication of silver-based nanostructures using electron beam

The electron beam was employed to in situ fabricate the Ag-based nanostructures with controllable microstructure and composition.

Simple and scalable growth of AgCl nanorods by plasma-assisted strain relaxation on flexible polymer substrates

Implementing nanostructures on plastic film is indispensable for highly efficient flexible optoelectronic devices. However, due to the thermal and chemical fragility of plastic, nanostructuring approaches are limited to indirect transfer with low throughput. Here, we fabricate single-crystal AgCl nanorods by using a Cl₂ plasma on Ag-coated polyimide. Cl radicals react with Ag to form AgCl nanorods. The AgCl is subjected to compressive strain at its interface with the Ag film because of the larger lattice constant of AgCl compared to Ag. To minimize strain energy, the AgCl nanorods grow in the [200] direction. The epitaxial relationship between AgCl (200) and Ag (111) induces a strain, which leads to a strain gradient at the periphery of AgCl nanorods. The gradient causes a strain-induced diffusion of Ag atoms to accelerate the nanorod growth. Nanorods grown for 45 s exhibit superior haze up to 100% and luminance of optical device increased by up to 33%.

3D AgCl microstructures selectively fabricated via Cl−-induced precipitation from [Ag(NH3)2]+

Herein various AgCl microstructures including octapods, octapods with fishbone pods, hexapods, hexapods with 4-blade arrowhead pods, concave octahedra, and octahedra are selectively precipitated from a [Ag(NH₃)₂]⁺ solution by addition of Cl⁻.