Hole Depth Prediction in a Femtosecond Laser Drilling Process Using Deep Learning.

In high-aspect ratio laser drilling, many laser and optical parameters can be controlled, including the high-laser beam fluence and number of drilling process cycles. Measurement of the drilled hole depth is occasionally difficult or time consuming, especially during machining processes. This study aimed to estimate the drilled hole depth in high-aspect ratio laser drilling by using captured two-dimensional (2D) hole images. The measuring conditions included light brightness, light exposure time, and gamma value. In this study, a method for predicting the depth of a machined hole by using a deep learning methodology was devised. Adjusting the laser power and the number of processing cycles for blind hole generation and image analysis yielded optimal conditions. Furthermore, to forecast the form of the machined hole, we identified the best circumstances based on changes in the exposure duration and gamma value of the microscope, which is a 2D image measurement instrument. After extracting the data frame by detecting the contrast data of the hole by using an interferometer, the hole depth was predicted using a deep neural network with a precision of within 5 µm for a hole within 100 µm.

Nanorod and nanoparticle shells in concentration gradient core-shell lithium oxides for rechargeable lithium batteries.

The structure, electrochemistry, and thermal stability of concentration gradient core-shell (CGCS) particles with different shell morphologies were evaluated and compared. We modified the shell morphology from nanoparticles to nanorods, because nanorods can result in a reduced surface area of the shell such that the outer shell would have less contact with the corrosive electrolyte, resulting in improved electrochemical properties. Electron microscopy studies coupled with electron probe X-ray micro-analysis revealed the presence of a concentration gradient shell consisting of nanoparticles and nanorods before and after thermal lithiation at high temperature. Rietveld refinement of the X-ray diffraction data and the chemical analysis results showed no variations of the lattice parameters and chemical compositions of both produced CGCS particles except for the degree of cation mixing (or exchange) in Li and transition metal layers. As anticipated, the dense nanorods present in the shell gave rise to a high tap density (2.5 g cm(-3) ) with a reduced pore volume and surface area. Intimate contact among the nanorods is likely to improve the resulting electric conductivity. As a result, the CGCS Li[Ni0.60 Co0.15 Mn0.25 ]O2 with the nanorod shell retained approximately 85.5% of its initial capacity over 150 cycles in the range of 2.7-4.5 V at 60 °C. The charged electrode consisting of Li0.16 [Ni0.60 Co0.15 Mn0.25 ]O2 CGCS particles with the nanorod shell also displayed a main exothermic reaction at 279.4 °C releasing 751.7 J g(-1) of heat. Due to the presence of the nanorod shell in the CGCS particles, the electrochemical and thermal properties are substantially superior to those of the CGCS particles with the nanoparticle shell.

Progress in High-Capacity Core-Shell Cathode Materials for Rechargeable Lithium Batteries.

High-energy-density rechargeable batteries are needed to fulfill various demands such as self-monitoring analysis and reporting technology (SMART) devices, energy storage systems, and (hybrid) electric vehicles. As a result, high-energy electrode materials enabling a long cycle life and reliable safety need to be developed. To ensure these requirements, new material chemistries can be derived from combinations of at least two compounds in a secondary particle with varying chemical composition and primary particle morphologies having a core-shell structure and spherical cathode-active materials, specifically a nanoparticle core and shell, nanoparticle core and nanorod shell, and nanorod core and shell. To this end, several layer core-shell cathode materials were developed to ensure high capacity, reliability, and safety.