The trivalent ytterbium(Yb^(3+))ion has been extensively used as an emitter in short-wave infrared(SWIR)lasers,a sensitizer to activate other lanthanide ions for up-conversion luminescence,and a spectral converter in ...The trivalent ytterbium(Yb^(3+))ion has been extensively used as an emitter in short-wave infrared(SWIR)lasers,a sensitizer to activate other lanthanide ions for up-conversion luminescence,and a spectral converter in Ln^(3+)-Yb^(3+)doubly doped quantum cutting phosphors.Here we report a new function of the Yb^(3+)ion—as an efficient emitting center for SWIR persistent luminescence.We have developed the first real SWIR persistent phosphor,MgGeO3:Yb^(3+),which exhibits very-long persistent luminescence at around 1000 nm for longer than 100 h.The MgGeO3:Yb^(3+)phosphor is spectrally transparent to visible/near-infrared light(~400–900 nm)and is a promising ultraviolet-to-SWIR spectral convertor.The MgGeO3:Yb^(3+)phosphor also exhibits a photostimulated persistent luminescence capability,where the SWIR persistent emission in an ultraviolet-light pre-irradiated sample can be rejuvenated by low-energy light(white or red light)stimulation.The MgGeO3:Yb^(3+)phosphor is expected to have promising applications in biomedical imaging,night-vision surveillance and photovoltaics.展开更多
A novel portable analyzer for raw milk quality control during the material purchase at dairy plants was developed, by which the percentages（mass fraction） of main components including total protein, fat, and lactose...A novel portable analyzer for raw milk quality control during the material purchase at dairy plants was developed, by which the percentages（mass fraction） of main components including total protein, fat, and lactose of an unhomogenized milk sample could be determinated in 1 min with the help of non-dispersive short-wave near-infrared （NDSWNIR） spectrometry in a wavelength range from 600 nm to 1100 nm and multivariate calibration. The analyzer was designed with a single-beam optical system, which comprised a temperature control module, a multi-channel narrow-band light source（16 wavelengths）, a glass absorption cell with 15 mm sample thickness, a silicon photodiode detector, several compound lenses and a recorder module. A total of 80 raw milk samples were collected at a dairy farm twice a month for 4 months. The samples were scanned with a common UV-Vis-NIR spectrometer and analyzed according to China GB standard methods. The uninformative variables elimination（UVE） method was carried out on the spectrum data and the percentages of main components of all the samples to choose the peak emitting wavelength of each channel of the light source. Another 90 raw milk samples were collected from the same dairy farm thrice a month for 3 months. The samples were analyzed according to China GB standard methods and with the proposed analyzer. The percentages of the main components and the NDSWNIR absorption data of the samples were used for the construction and validation of the multivariate calibration model with partial least squares（PLS） method. The root-mean-square errors of prediction（RMSEP） of total protein, fat and lactose were 0.201, 0.172 and 0.247 and the coefficients of correlation（R） were 0.932, 0.981 and 0.933, respectively.展开更多
In this article, unique spectral features of short-wave infrared band of 1 μm–3 μm, and various applications related to the photodetectors and focal plane arrays in this band, are introduced briefly. In addition, t...In this article, unique spectral features of short-wave infrared band of 1 μm–3 μm, and various applications related to the photodetectors and focal plane arrays in this band, are introduced briefly. In addition, the different material systems for the devices in this band are outlined. Based on the background, the development of lattice-matched and wavelengthextended InGaAs photodetectors and focal plane arrays, including our continuous efforts in this field, are reviewed. These devices are concentrated on the applications in spectral sensing and imaging, exclusive of optical fiber communication.展开更多
To explore new operational forecasting methods of waves,a forecasting model for wave heights at three stations in the Bohai Sea has been developed.This model is based on long short-term memory(LSTM)neural network with...To explore new operational forecasting methods of waves,a forecasting model for wave heights at three stations in the Bohai Sea has been developed.This model is based on long short-term memory(LSTM)neural network with sea surface wind and wave heights as training samples.The prediction performance of the model is evaluated,and the error analysis shows that when using the same set of numerically predicted sea surface wind as input,the prediction error produced by the proposed LSTM model at Sta.N01 is 20%,18%and 23%lower than the conventional numerical wave models in terms of the total root mean square error(RMSE),scatter index(SI)and mean absolute error(MAE),respectively.Particularly,for significant wave height in the range of 3–5 m,the prediction accuracy of the LSTM model is improved the most remarkably,with RMSE,SI and MAE all decreasing by 24%.It is also evident that the numbers of hidden neurons,the numbers of buoys used and the time length of training samples all have impact on the prediction accuracy.However,the prediction does not necessary improve with the increase of number of hidden neurons or number of buoys used.The experiment trained by data with the longest time length is found to perform the best overall compared to other experiments with a shorter time length for training.Overall,long short-term memory neural network was proved to be a very promising method for future development and applications in wave forecasting.展开更多
基金support from the National Science Foundation(CAREER DMR-0955908,DMR-1403929)support from the National Natural Science Foundation of China(no.81171463)support from the China Scholarship Council.
文摘The trivalent ytterbium(Yb^(3+))ion has been extensively used as an emitter in short-wave infrared(SWIR)lasers,a sensitizer to activate other lanthanide ions for up-conversion luminescence,and a spectral converter in Ln^(3+)-Yb^(3+)doubly doped quantum cutting phosphors.Here we report a new function of the Yb^(3+)ion—as an efficient emitting center for SWIR persistent luminescence.We have developed the first real SWIR persistent phosphor,MgGeO3:Yb^(3+),which exhibits very-long persistent luminescence at around 1000 nm for longer than 100 h.The MgGeO3:Yb^(3+)phosphor is spectrally transparent to visible/near-infrared light(~400–900 nm)and is a promising ultraviolet-to-SWIR spectral convertor.The MgGeO3:Yb^(3+)phosphor also exhibits a photostimulated persistent luminescence capability,where the SWIR persistent emission in an ultraviolet-light pre-irradiated sample can be rejuvenated by low-energy light(white or red light)stimulation.The MgGeO3:Yb^(3+)phosphor is expected to have promising applications in biomedical imaging,night-vision surveillance and photovoltaics.
文摘A novel portable analyzer for raw milk quality control during the material purchase at dairy plants was developed, by which the percentages（mass fraction） of main components including total protein, fat, and lactose of an unhomogenized milk sample could be determinated in 1 min with the help of non-dispersive short-wave near-infrared （NDSWNIR） spectrometry in a wavelength range from 600 nm to 1100 nm and multivariate calibration. The analyzer was designed with a single-beam optical system, which comprised a temperature control module, a multi-channel narrow-band light source（16 wavelengths）, a glass absorption cell with 15 mm sample thickness, a silicon photodiode detector, several compound lenses and a recorder module. A total of 80 raw milk samples were collected at a dairy farm twice a month for 4 months. The samples were scanned with a common UV-Vis-NIR spectrometer and analyzed according to China GB standard methods. The uninformative variables elimination（UVE） method was carried out on the spectrum data and the percentages of main components of all the samples to choose the peak emitting wavelength of each channel of the light source. Another 90 raw milk samples were collected from the same dairy farm thrice a month for 3 months. The samples were analyzed according to China GB standard methods and with the proposed analyzer. The percentages of the main components and the NDSWNIR absorption data of the samples were used for the construction and validation of the multivariate calibration model with partial least squares（PLS） method. The root-mean-square errors of prediction（RMSEP） of total protein, fat and lactose were 0.201, 0.172 and 0.247 and the coefficients of correlation（R） were 0.932, 0.981 and 0.933, respectively.
基金Project supported by the National Key Research and Development Program of China(Grant No.2016YFB0402400)the National Natural Science Foundation of China(Grant Nos.61675225,61605232,and 61775228)the Shanghai Rising-Star Program,China(Grant No.17QA1404900)
文摘In this article, unique spectral features of short-wave infrared band of 1 μm–3 μm, and various applications related to the photodetectors and focal plane arrays in this band, are introduced briefly. In addition, the different material systems for the devices in this band are outlined. Based on the background, the development of lattice-matched and wavelengthextended InGaAs photodetectors and focal plane arrays, including our continuous efforts in this field, are reviewed. These devices are concentrated on the applications in spectral sensing and imaging, exclusive of optical fiber communication.
基金The National Key R&D Program of China under contract No.2016YFC1402103
文摘To explore new operational forecasting methods of waves,a forecasting model for wave heights at three stations in the Bohai Sea has been developed.This model is based on long short-term memory(LSTM)neural network with sea surface wind and wave heights as training samples.The prediction performance of the model is evaluated,and the error analysis shows that when using the same set of numerically predicted sea surface wind as input,the prediction error produced by the proposed LSTM model at Sta.N01 is 20%,18%and 23%lower than the conventional numerical wave models in terms of the total root mean square error(RMSE),scatter index(SI)and mean absolute error(MAE),respectively.Particularly,for significant wave height in the range of 3–5 m,the prediction accuracy of the LSTM model is improved the most remarkably,with RMSE,SI and MAE all decreasing by 24%.It is also evident that the numbers of hidden neurons,the numbers of buoys used and the time length of training samples all have impact on the prediction accuracy.However,the prediction does not necessary improve with the increase of number of hidden neurons or number of buoys used.The experiment trained by data with the longest time length is found to perform the best overall compared to other experiments with a shorter time length for training.Overall,long short-term memory neural network was proved to be a very promising method for future development and applications in wave forecasting.
