ABSTRACT
Improved nitrogen transport is crucial for enhancing the growth rate of GaN crystals using the Na-flux method. This study investigates the nitrogen transport mechanism during the growth of GaN crystals by the Na-flux method using a combination of numerical simulations and experiments. The results indicate that the temperature field affects the effect of nitrogen transfer, and we propose a novel bottom ring heating approach to optimize the temperature field and enhance nitrogen transfer during the growth of GaN crystals. The simulation results demonstrate that optimizing the temperature field improves nitrogen transfer by causing convection within the melt to float up from the crucible wall and sink at the crucible center. This enhancement improves the nitrogen transfer from the gas-liquid interface to the GaN crystal growth surface, thereby accelerating the growth rate of GaN crystals. Additionally, the simulation results indicate that the optimized temperature field substantially reduces polycrystalline generation at the crucible wall. These findings are also a realistic guide to the growth of other crystals in the liquid phase method.
ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a pandemic infectious disease and become a serious public health crisis. As the COVID-19 pandemic continues to spread, it is of vital importance to detect COVID-19 clusters to better distribute resources and optimizing measures. This study helps the surveillance of the COVID-19 pandemic and discovers major space-time clusters of reported cases in European countries. Prospective space-time scan statistics are particularly valuable because it has detected active and emerging COVID-19 clusters. It can prompt public health decision makers when and where to improve targeted interventions, testing locations, and necessary isolation measures, and the allocation of medical resources to reduce further spread. METHODS: Using the daily case data of various countries provided by the European Centers for Disease Control and Prevention, we used SaTScan™ 9.6 to conduct a prospective space-time scan statistics analysis. We detected statistically significant space-time clusters of COVID-19 at the European country level between March 1st to October 2nd, 2020 and March 1st to October 2nd, 2021. Using ArcGIS to draw the spatial distribution map of COVID-19 in Europe, showing the emerging clusters that appeared at the end of our study period detected by Poisson prospective space-time scan statistics. RESULTS: The results show that among the 49 countries studied, the regions with the largest number of reported cases of COVID-19 are Western Europe, Central Europe, and Eastern Europe. Among the 49 countries studied, the country with the largest cumulative number of reported cases is the United Kingdom, followed by Russia, Turkey, France, and Spain. The country (or region) with the lowest cumulative number of reported cases is the Faroe Islands. We discovered 9 emerging clusters, including 21 risky countries. CONCLUSION: This result can provide timely information to national public health decision makers. For example, a country needs to improve the allocation of medical resources and epidemic detection points, or a country needs to strengthen entry and exit testing, or a country needs to strengthen the implementation of protective isolation measures. As the data is updated daily, new data can be re-analyzed to achieve real-time monitoring of COVID-19 in Europe. This study uses Poisson prospective space-time scan statistics to monitor COVID-19 in Europe.
