Quantum Yield Optimization Of Phosphors Based On Meta Heuristic Algorithms

The quantum yield of phosphors refers to the utilization of photons.Researchers usually use the intensity ratio of emitted light to excited light to describe quantum yield.Eu³⁺doped phosphors and Ce/Tb codoped phosphors synthesized in this article have stable physical and chemical properties and narrow emission bands,so they have a very wide range of application scenarios.The phosphors can be used as dual-modal imaging agent.For example,in the field of molecular imaging,the phosphors are used for visualization of tissues,organs and lesions.In the field of CT imaging,phosphors are used as CT agent.In this thesis,this research combined the synthesis of phosphors with the meta-heuristics algorithm,optimized the quantum yield of phosphors by meta-heuristics algorithm and expanded the application scenarios of phosphors.The main contributions of our work are as following:1.This research used the genetic algorithm to optimize the Eu³⁺doped phosphor,used the MATLAB to realize the process of genetic algorithms and applied the hydrothermal co-precipitation method to synthesize Eu³⁺doped phosphors.The combination of genetic algorithm and phosphor synthesis process was realized by decimal coding.This research tested the cytotoxicity of phosphors,studied the optical imaging and CT imaging of phosphors,and applied the rare earth phosphors to fingerprint identification.There are some characteristics of the co-precipitation method.First,the experimental period is short,and the sample could be synthesized in short time.Second,the synthesized phosphors have the advantages of uniform distribution and small particle size.Third,the process and conditions of reactions are easy to control,and the products are stable.Based on the above characteristics,co-precipitation method is suitable for the optimization of phosphor synthesis.2.This research used multiple algorithms to optimize Ce/Tb co-doped phosphors,realized the process of particle swarm optimization and simulated annealing algorithm,adjusted the parameters of genetic algorithm,combined the algorithm with the process of Ce-Tb co-doped phosphors.By comparing the optimization results of different algorithms,this research explored the characteristics of different algorithms for optimization of phosphors and got the following conclusions.Firstly,the genetic algorithm has high searching speed.The optimal generation of phosphors occurred in the third generation,which indicates that this algorithm is suitable for rapid optimization.Secondly,the particle swarm optimization algorithm is stable.With the increase of iteration times,the optimization effect of phosphors was better.This algorithm is suitable for searching high performance phosphors at more iterations.Thirdly,the simulated annealing algorithm had no obvious effect on the luminescent powder,which shows that the classical simulated annealing algorithm is not suitable for the optimization of phosphors.3.This research improved the simulated annealing algorithm,and the improved algorithm was applied to optimize the Ce-Tb co-doped phosphors.For the poor optimization effect of simulated annealing algorithm,this research analyzed and improved it.This research found that the encoding method of simulated annealing algorithm was too simple to apply to the optimization of phosphors,so this research used the global coding information to improve new coding generation way.The improved algorithm was significantly better than the original simulated annealing algorithm.by analyzing the samples,this reaserch obtained the relationship between the luminescence intensity and the concentration of Ce/Tb.The sample of phosphors and TPE have a shared excitation region in 250-300 nm.Phosphors have good thermal stability but TPE have poor thermal stability.Based on the above characteristics,this research constructed a special improved QR code.