In nanoparticle sizing using the ultrafast image-based dynamic light scattering (UIDLS)method,larger impurities and dark noise from the complementary metal-oxide-semiconductor (CMOS)detector affect measurement accurac...In nanoparticle sizing using the ultrafast image-based dynamic light scattering (UIDLS)method,larger impurities and dark noise from the complementary metal-oxide-semiconductor (CMOS)detector affect measurement accuracy.To solve this problem,a two-dimensional self-adapting fast Fourier transform (2D-SAFFT)algorithm is proposed for UIDLS.Dynamic light scattering images of nanoparticles are processed using 2D fast Fourier transforms,and a high-frequency threshold and a low-frequency threshold are then set using the self-adapting algorithm to eliminate the effects of the dark noise of the CMOS detector and the impurities.The signals caused by the dark noise of the CMOS detector and the impurities are cut off using the high-frequency threshold and the low-frequency threshold.The signals without the high- and low-frequency components are then processed again using an inverse Fourier transform to obtain new images without the dark noise and impurities signals.The mean diameters of the measured nanoparticles can be obtained from images obtained using UIDLS.Five standard latex nanoparticles (46,100, 203,508,994nm)and commercial nanoparticles (antimony-doped tin oxide,indium tin oxide,TWEEN- 80,nano-Fe,and nano-Al2O3)were measured using this new method.Results show that 2D-SAFFT can effectively eliminate the effects of dark noise from the CMOS detector and the impurities.展开更多
Starting from the extended nonlinear Schrodinger equation in which the self-steepening effect is included, the evolution and the splitting processes of continuous optical wave whose amplitude is perturbed into time re...Starting from the extended nonlinear Schrodinger equation in which the self-steepening effect is included, the evolution and the splitting processes of continuous optical wave whose amplitude is perturbed into time related ultra-short optical pulse trains in an optical fibre are numerically simulated by adopting the split-step Fourier algorithm. The results show that the self-steepening effect can cause the characteristic of the pulse trains to vary with time, which is different from the self-steepening-free case where the generated pulse trains consist of single pulses which are identical in width, intensity, and interval, namely when pulses move a certain distance, they turn into the pulse trains within a certain time range. Moreover, each single pulse may split into several sub-pulses. And as time goes on, the number of the sub-pulses will decrease gradually and the pulse width and the pulse intensity will change too. With the increase of the self-steepening parameter, the distance needed to generate time-dependent pulse trains will shorten. In addition, for a large self-steepening parameter and at the distance where more sub-pulses appear, the corresponding frequency spectra of pulse trains are also wider.展开更多
基金National Natural Science Foundation of China (Grant No.51573093).
文摘In nanoparticle sizing using the ultrafast image-based dynamic light scattering (UIDLS)method,larger impurities and dark noise from the complementary metal-oxide-semiconductor (CMOS)detector affect measurement accuracy.To solve this problem,a two-dimensional self-adapting fast Fourier transform (2D-SAFFT)algorithm is proposed for UIDLS.Dynamic light scattering images of nanoparticles are processed using 2D fast Fourier transforms,and a high-frequency threshold and a low-frequency threshold are then set using the self-adapting algorithm to eliminate the effects of the dark noise of the CMOS detector and the impurities.The signals caused by the dark noise of the CMOS detector and the impurities are cut off using the high-frequency threshold and the low-frequency threshold.The signals without the high- and low-frequency components are then processed again using an inverse Fourier transform to obtain new images without the dark noise and impurities signals.The mean diameters of the measured nanoparticles can be obtained from images obtained using UIDLS.Five standard latex nanoparticles (46,100, 203,508,994nm)and commercial nanoparticles (antimony-doped tin oxide,indium tin oxide,TWEEN- 80,nano-Fe,and nano-Al2O3)were measured using this new method.Results show that 2D-SAFFT can effectively eliminate the effects of dark noise from the CMOS detector and the impurities.
基金supported by Key Program of Natural Science Foundation of Educational Commission of Sichuan Province, China (GrantNo 2006A124)the Fundamental Application Research Project of the Department of Science and Technology of Sichuan Province,China (Grant No 05JY029-084)the Foundation of Science and Technology Development of Chengdu University of Information Technology, China (Grant No KYTZ20060604)
文摘Starting from the extended nonlinear Schrodinger equation in which the self-steepening effect is included, the evolution and the splitting processes of continuous optical wave whose amplitude is perturbed into time related ultra-short optical pulse trains in an optical fibre are numerically simulated by adopting the split-step Fourier algorithm. The results show that the self-steepening effect can cause the characteristic of the pulse trains to vary with time, which is different from the self-steepening-free case where the generated pulse trains consist of single pulses which are identical in width, intensity, and interval, namely when pulses move a certain distance, they turn into the pulse trains within a certain time range. Moreover, each single pulse may split into several sub-pulses. And as time goes on, the number of the sub-pulses will decrease gradually and the pulse width and the pulse intensity will change too. With the increase of the self-steepening parameter, the distance needed to generate time-dependent pulse trains will shorten. In addition, for a large self-steepening parameter and at the distance where more sub-pulses appear, the corresponding frequency spectra of pulse trains are also wider.
