In this article,a series of high refractive indices(1.50-1.53)thiol phenyl polysiloxane(TPS)were synthesized via hydrolytic sol-gel reaction.The Fourier transform infrared spectra(FT-IR)and nuclear magnetic resonance ...In this article,a series of high refractive indices(1.50-1.53)thiol phenyl polysiloxane(TPS)were synthesized via hydrolytic sol-gel reaction.The Fourier transform infrared spectra(FT-IR)and nuclear magnetic resonance spectra(NMR)results showed that TPS conformed to the predicted structures.Natural terpene linalool was exploited as photocrosslinker to fabricate UV-curing linalool-polysiloxane hybrid films(LPH)with TPS via photoinitiated thiol-ene reaction.LPH rapidly cured under UV irradiation at the intensity of 80 mW/cm^(2) in 30 s,exhibiting good UV-curing properties.The optical transmittance of LPH in the wavelength of 300-800 nm was over 90%,exhibiting good optical transparency.The water contact angle and water vapor permeability results showed that the introduction of phenyl groups enhance the hydrophobicity and water vapor barrier properties of LPH.The results indicated the potential of LPHs in the applications of optical functional coatings.展开更多
Particle swarm optimization(PSO)algorithms have been successfully used for various complex optimization problems.However,balancing the diversity and convergence is still a problem that requires continuous research.The...Particle swarm optimization(PSO)algorithms have been successfully used for various complex optimization problems.However,balancing the diversity and convergence is still a problem that requires continuous research.Therefore,an evolutionary experience-driven particle swarm optimization with dynamic searching(EEDSPSO)is proposed in this paper.For purpose of extracting the effective information during population evolution,an adaptive framework of evolutionary experience is presented.And based on this framework,an experience-based neighborhood topology adjustment(ENT)is used to control the size of the neighborhood range,thereby effectively keeping the diversity of population.Meanwhile,experience-based elite archive mechanism(EEA)adjusts the weights of elite particles in the late evolutionary stage,thus enhancing the convergence of the algorithm.In addition,a Gaussian crisscross learning strategy(GCL)adopts cross-learning method to further balance the diversity and convergence.Finally,extensive experiments use the CEC2013 and CEC2017.The experiment results show that EEDSPSO outperforms current excellent PSO variants.展开更多
基金the financial funding of the Guangdong Province Applied Science and Technology R&D Special Fund Project:Key Technologies for Industrialization of Sulfur-Resistant and High Refractive-Index LED Packaging Silicone Materials(2016B090930010).
文摘In this article,a series of high refractive indices(1.50-1.53)thiol phenyl polysiloxane(TPS)were synthesized via hydrolytic sol-gel reaction.The Fourier transform infrared spectra(FT-IR)and nuclear magnetic resonance spectra(NMR)results showed that TPS conformed to the predicted structures.Natural terpene linalool was exploited as photocrosslinker to fabricate UV-curing linalool-polysiloxane hybrid films(LPH)with TPS via photoinitiated thiol-ene reaction.LPH rapidly cured under UV irradiation at the intensity of 80 mW/cm^(2) in 30 s,exhibiting good UV-curing properties.The optical transmittance of LPH in the wavelength of 300-800 nm was over 90%,exhibiting good optical transparency.The water contact angle and water vapor permeability results showed that the introduction of phenyl groups enhance the hydrophobicity and water vapor barrier properties of LPH.The results indicated the potential of LPHs in the applications of optical functional coatings.
基金This work was supported by the National Natural Science Foundation of China(No.62066019)Jiangxi Provincial Education Department Project(No.GJJ200819)Doctoral Startup Foundation of Jiangxi University of Science and Technology(No.205200100022).
文摘Particle swarm optimization(PSO)algorithms have been successfully used for various complex optimization problems.However,balancing the diversity and convergence is still a problem that requires continuous research.Therefore,an evolutionary experience-driven particle swarm optimization with dynamic searching(EEDSPSO)is proposed in this paper.For purpose of extracting the effective information during population evolution,an adaptive framework of evolutionary experience is presented.And based on this framework,an experience-based neighborhood topology adjustment(ENT)is used to control the size of the neighborhood range,thereby effectively keeping the diversity of population.Meanwhile,experience-based elite archive mechanism(EEA)adjusts the weights of elite particles in the late evolutionary stage,thus enhancing the convergence of the algorithm.In addition,a Gaussian crisscross learning strategy(GCL)adopts cross-learning method to further balance the diversity and convergence.Finally,extensive experiments use the CEC2013 and CEC2017.The experiment results show that EEDSPSO outperforms current excellent PSO variants.
