We elucidate the catalytic graphitization mechanism using in situ analytical approaches. Catalytic graphitization is achieved through a Ni–P electroless plating process at a relatively low temperature of 1600 °C, which allows for a high crystallinity of coke. We also employ an ultrasonic treatment during the Ni–P electroless plating stage to effectively form metal layers on the surface. The impact of the ultrasonic treatment on the Ni–P electroless plating is confirmed by field emission scanning electron microscopy images of the cross-section and an elemental composition analysis using energy dispersive X-ray spectroscopy mapping. Structural analysis of the graphitized cokes via X-ray diffraction (XRD) and Raman spectroscopy shows that Ni–P electroless plating significantly accelerates the graphitization process. Furthermore, we illuminate the graphitization behavior through in situ transmission electron microscopy and XRD analysis. Nickel layers on the coke surface facilitate graphite formation by encouraging the dissolution and precipitation of amorphous carbons, thus resulting in efficient graphitization at a relatively low temperature.

Multimetallic catalysts have demonstrated their high potential for the controlled synthesis of carbon nanotubes (CNTs), but their development requires a more complicated optimization than that of monometallic catalysts. Here, we employed Bayesian optimization (BO) to optimize the preparation of Co-Mo/Al₂O₃ catalyst using wet impregnation, with the goal of maximizing carbon yield in the chemical vapor deposition (CVD) synthesis of CNTs. In the catalyst preparation process, we selected four parameters to optimize: the weight percentage of metal, the ratio of Co to Mo in the catalyst, the drying temperature, and the calcination temperature. We ran two parallel BO processes to compare the performance of two types of acquisitions: expected improvement (EI), which does not consider noise, and one-shot knowledge gradient (OKG), which takes noise into account. As a result, both acquisition functions successfully optimized the carbon yield with similar performance. The result suggests that the use of EI, which has a lower computational load, is acceptable if the system has sufficient robustness. The investigation of the contour plots showed that the addition of Mo has a negative effect on carbon yield.

We have developed a periodical self-assembled method of patterning the sapphire substrate with silica nanospheres for light-emitting diode (LED) applications. Using this method, silica nanospheres were directed to self-assemble in a periodic fashion on a wet-etched patterned sapphire substrate (WPSS). Moreover, we fabricated an InGaN/GaN-based LED on the silica-nanosphere-assembled WPSS. The light output power of the resultant LED was about 2.23 and 1.7 times higher than that of the LEDs grown on planar sapphire and WPSS, respectively. Moreover, the light extraction efficiency of the silica-nanosphere-assembled WPSS LED was 37% higher than that of conventional LED.

We introduce a low temperature process for coating InGaN/GaN light-emitting diodes (LEDs) with h-BN as a passivation layer. The effect of h-BN on device performance and reliability is investigated. At −5 V, the leakage current of the h-BN passivated LED was −1.15 × 10⁻⁹ A, which was one order lower than the reference LED’s leakage current of −1.09 × 10⁻⁸ A. The h-BN layer minimizes the leakage current characteristics and operating temperature by acting as a passivation and heat dispersion layer. With a reduced working temperature of 33 from 45 °C, the LED lifetime was extended 2.5 times following h-BN passivation. According to our findings, h-BN passivation significantly improves LED reliability.