High efficiency and high transmission asymmetric polarization converter with chiral metasurface in visible and near-infrared region

Polarization manipulation of light is of great importance because it could promote development of wireless communications,biosensing,and polarization imaging.In order to use natural light more efficiently,it is highly demanded to design and fabricate high performance asymmetric polarization converters which could covert the natural light to one particular linearly polarized light with high efficiency.Traditionally,polarizers could be achieved by controllers with crystals and polymers exhibiting birefringence.However,the polarizers are bulky in size and the theoretical conversion efficiency of the polarizers is limited to 0.5 with unpolarized light incidence.In this paper,we propose a polarization converter which could preserve high transmission for one linearly polarized light and convert the orthogonal linearly polarized light to its cross-polarized with high transmittance based on a multi-layer chiral metasurface.Theoretical results show that normally incident y-polarized light preserves high transmittance for the wavelength range from 685 nm to 800 nm while the orthogonal normally incident x-polarized light is efficiently converted to the y-polarized light with high transmittance from 725 nm to 748 nm.Accordingly,for unpolarized light incidence,transmittance larger than 0.5 has been successfully achieved in a broadband wavelength range from 712 nm to 773 nm with a maximum transmittance of 0.58 at 732 nm.

Photoprotective Ability of Sunscreens against Ultraviolet, Visible Light and Near-Infrared Radiation

Despite the widespread prevalence of daily sunscreen usage, solar-induced skin damage continues to occur. We have previously reported that solar visible light and near-infrared, in addition to ultraviolet radiation, perform as aging factors and induce deleterious effects such as photoaging, vasodilation, muscle thinning, skin ptosis, photoimmunosupression and photocarcinogenesis. Despite this, most commonly used sunscreens only block ultraviolet radiation. To evaluate the complete solar-spectrum blocking ability of sunscreens produced by internationally well-known companies, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer utilizes a unique, single monochromatic design covering a wavelength range of 240 to 2600 nm. Sunscreens (thickness, 0.1 mm, SPF50+, PA+++ or ++++) from internationally well-known companies blocked 78.8% - 99.9% of ultraviolet, 33.4% - 99.6% of visible light, and 27.0% - 76.4% of near-infrared. It can be concluded that while most commercially available sunscreens filter ultraviolet radiation, they are not effective at blocking visible light and near-infrared radiation. The results of this study imply that sunscreens that provide comprehensive photoprotection from ultraviolet through to near-infrared should be considered to prevent skin photodamage.

Novel Low Viscosity Zinc Oxide, Iron Oxides and Erioglaucine Sunscreen Potential to Protect from Ultraviolet, Visible Light and Near-Infrared Radiation

Despite the widespread recommendation and use of sunscreens and ultraviolet blocking materials, solar-induced skin damage and photoageing continues to pose a problem to human health worldwide. We have previously reported that solar visible light and near-infrared also contribute to skin damage and photo ageing. Most commonly recommended sunscreens are only effective throughout the UV spectrum, offering no protection from visible light and near-infrared. A possible solution could be to augment sunscreens with metal oxides which block visible light and near-infrared radiation. To evaluate the enhanced solar-spectrum blocking ability of novel low viscosity sunscreen containing zinc and iron oxides, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer deploys a unique, single monochromatic design to detect wavelength penetration in the range of 240 to 2600 nm. The Sunscreen base without zinc oxide and iron oxides (control) blocked over 80% of ultraviolet-C and ultraviolet-B but did not block ultraviolet-A, visible light, or near-infrared. The novel low viscosity zinc oxide sample blocked almost over 90% ultraviolet, but did not block visible light and near-infrared sufficiently. However, the samples with the novel low viscosity zinc oxide, iron oxides and erioglaucine blocked almost over 90% of ultraviolet, visible light and near-infrared. It can be concluded that this novel combination of low viscosity zinc oxide, iron oxides and erioglaucine is effective at blocking ultraviolet, visible light and near-infrared radiation. The results of this study imply that sunscreens that provide comprehensive photoprotection from ultraviolet through to near-infrared should be adopted to prevent skin photodamage.

Photoprotective Ability of Colored Iron Oxides in Tinted Sunscreens against Ultraviolet, Visible Light and Near-Infrared Radiation

Solar-induced skin damage continues to pose a problem to human health worldwide, despite the widespread recommendation and use of sunscreens. We have previously reported that solar visible light and near-infrared also contribute to skin damage and photoageing. Most commonly recommended sunscreens are only effective throughout the UV spectrum, offering no protection from visible light and near-infrared. To evaluate the enhanced solar-spectrum blocking ability of iron oxides, a double-beam spectrophotometer was used to optically measure the transmission spectra. The spectrophotometer deploys a unique, single monochromatic design to detect wavelength penetration in the range of 240 to 2600 nm. The sample without iron oxide (control) blocked over 80% of ultraviolet-C and ultraviolet-B but did not block ultraviolet-A, visible light, or near-infrared wavelengths. The samples with yellow, and red iron oxide blocked over 90% ultraviolet, but did not block visible light and near-infrared effectively. The sample with black iron oxide blocked visible light, and near-infrared effectively compared with other samples with yellow, blue, and red iron oxide. The sample with red and black iron oxides, and the sample with yellow, blue, red, and black iron oxides blocked ultraviolet through to near-infrared. It can be concluded that dark colored iron oxide combinations are effective at blocking from ultraviolet through to visible light and near-infrared radiation. The results of this study may also suggest that biological colour of human skin and subcutaneous tissues are conserved for comprehensive photoprotection.

Visible and Near-Infrared Spectroscopy with Multi-Parameters Optimization of Savitzky-Golay Smoothing Applied to Rapid Analysis of Soil Cr Content of Pearl River Delta

Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters d, p, m and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEPV), relative root mean square error (R-SEPV) and correlation coefficients (RP, V) of prediction were 11.66 mg·kg-1, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.

Biological Defenses against Ultra-Violet, Visible Light, and Near-Infrared Exposure

Objective: Humans are increasingly exposed to artificial light and electromagnetic wave radiation, in addition to solar radiation. Many studies have shown the biological effects of ultra-violet and near-infrared exposure, but few have extensively investigated the innate biological defenses within human tissues against visible light and near-infrared exposure. Herein, we investigated spectral properties of endogenous human biological defenses against ultra-violet to near-infrared. Methods: A double-beam spectrophotometer (190 - 2700 nm) was used to measure the transmission spectra of a saline solution used to imitate perspiration, and oil to imitate sebum, as well as human skin, blood, adipose tissue, and muscle. Results: Saline (thickness, 0.5 mm) blocked 27.5% - 98.6% of ultra-violet, 13.2% - 34.3% of visible light, and 10.7% - 99.8% of near-infrared. Oil (thickness, 0.5 mm) blocked 50.5% - 100% of ultra-violet, 28.7% - 54.8% of visible light, and 19.0% - 98.3% of near-infrared. Blood thicknesses of 0.05 and 0.5 mm blocked over 97.8%, 100% of ultra-violet, over 94.6%, 99.7% of visible light, and over 75.8%, 99.4% of near-infrared, respectively. Skin thicknesses of 0.25 and 0.5 mm blocked over 99.4%, 100% of ultra-violet and over 94.3%, 99.7% of visible light, and over 74.7%, 93.5% of near-infrared, respectively. Adipose tissue thickness of 0.25 and0.5 mm blocked over 98.3%, 100% of ultra-violet, over 94.7%, 99.7% of visible light, and over 88.1%, 98.6% of near-infrared, respectively. Muscle thickness of 0.25 and0.5 mm blocked over 95.4%, 99.8% of ultra-violet, over 93.1%, 99.5% of visible light, and over 86.9%, 98.3% of near-infrared, respectively. Conclusions: Humans possess endogenous biological protection against ultra-violet, visible light and near-infrared exposure on multiple levels, including through perspiration, sebum, blood, skin, adipose tissue, and muscle. Since solar and artificial radiation affects human tissues, biological defenses made of biological materials may be induced to protect subcutaneous tissues against these wavelengths.

The near-infrared spectra and distribution of excited states of electrodeless discharge rubidium vapour lamps

The population ratio between the excited states of rubidium in the electrodeless discharge rubidium vapour lamp is calculated according to the near-infrared spectra in the region of 780-1550 nm. By using a 1529 nm laser, we measure the density of natural rubidium atoms at the 5P3/2 level. The populations of different excited states are then clarified.

UV–visible spectral characterization and density functional theory simulation analysis on laser-induced crystallization of amorphous silicon thin films

The effect of laser energy density on the crystallization of hydrogenated intrinsic amorphous silicon （a-Si：H） thin films was studied both theoretically and experimentally. The thin films were irritated by a frequency-doubled （λ= 532 nm） Nd：YAG pulsed nanosecond laser. An effective density functional theory model was built to reveal the variation of bandgap energy influenced by thermal stress after laser irradiation. Experimental results establish correlation between the thermal stress and the shift of transverse optical peak in Raman spectroscopy and suggest that the relatively greater shift of the transverse optical （TO） peak can produce higher stress. The highest crystalline fraction （84.5%） is obtained in the optimized laser energy density （1000 mJ/cm2） with a considerable stress release. The absorption edge energy measured by the UV- visible spectra is in fairly good agreement with the bandgap energy in the density functional theory （DFT） simulation.

Effect of head model on Monte Carlo modeling of spatial sensitivity distribution for functional near-infrared spectroscopy

Modeling Light propagation within human head to deduce spatial sensitivity distribution(SSD)is important for Near-infrared spectroscopy(NIRS)/imaging(NIRI)and diffuse correlation tomography.Lots of head models have been used on this issue,including layered head model,artificial simplified head model,MRI slices described head model,and visible human head model.Hereinto,visible Chinese human(VCH)head model is considered to be a most faithful presentation of anatomical structure,and has been highlighted to be employed in modeling light propagation.However,it is not practical for all researchers to use VCH head models and actually increasing number of people are using magnet resonance imaging(MRI)head models.Here,all the above head models were simulated and compared,and we focused on the effect of using di®erent head models on predictions of SSD.Our results were in line with the previous reports on the effect of cerebral cortex folding geometry.Moreover,the in fluence on SSD increases with thefidelity of head models.And surprisingly,the SSD percentages in scalp and gray matter(region of interest)in MRI head model were found to be 80%and 125%higher than in VCH head model.MRI head models induced nonignorable discrepancy in SSD estimation when compared with VCH head model.This study,as we believe,is the first to focus on comparison among full serials of head model on estimating SSD,and provided quantitative evidence for MRI head model users to calibrate their SSD estimation.

Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

Hyperspectral imaging is gaining a significant role in agricultural remote sensing applications.Its data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third dimension.The classification accuracy of hyperspectral images(HSI)increases significantly by employing both spatial and spectral features.For this work,the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral bands.The dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each pixel.The data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation system.In this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in conjunction.The preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired HSI.In the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral information.The resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational cost.The support vector machines classifier was employed for multiclass classification of target crops using PCA-EPF.The classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa factor.The proposed scheme achieved greater than 90%results for all the performance evaluation metrics.The PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR range.The proposed scheme is well-suited for practical applications of crops and landfill estimations using agricultural remote sensing methods.

Application of Visible/Near-Infrared Spectra in Modeling of Soil Total Phosphorus

Overabundance of phosphorus (P) in soils and water is of great concern and has received much attention in Florida, USA. Therefore, it is essential to analyze and predict the distribution of P in soils across large areas. This study was undertaken to model the variation of soil total phosphorus (TP) in Florida. A total of 448 soil samples were collected from different soil types. Soil samples were analyzed by chemical reference method and scanned in the visible/near-infrared (VNIR) region of 350-2 500 nm. Partial least squares regression (PLSR) calibration model was developed between chemical reference values and VNIR values. The coefficient of determination (R2) and the root mean squares error (RMSE) of calibration and validation sets, and the residual prediction deviation (RPD) were used to evaluate the models. The R2in calibration and validation for log-transformed TP (log TP) were 0.69 and 0.65, respectively, indicating that VNIR calibration obtained in this study accounted for at least 65% of the variance in log TP using only VNIR spectra, and the high RPD of 2.82 obtained suggested that the spectral model derived in this study was suitable and robust to predict TP in a wide range of soil types, being representative of Florida soil conditions.

Modeling for mung bean variety classification using visible and near-infrared hyperspectral imaging

This study was carried out to investigate the feasibility of using visible and near infrared hyperspectral imaging for the variety classification of mung beans.Raw hyperspectral images of mung beans were acquired in the wavelengths of 380-1023 nm,and all images were calibrated by the white and dark reference images.The spectral reflectance values were extracted from the region of interest(ROI)of each calibrated hyperspectral image,and then they were treated as the independent variables.The dependent variables of four varieties of mung beans were set as 1,2,3 and 4,respectively.The extreme learning machine(ELM)model was established using full spectral wavelengths for classification.Modified gram-schmidt(MGS)method was used to identify effective wavelengths.Based on the selected wavelengths,the ELM and linear discriminant analysis(LDA)models were built.All models performed excellently with the correct classification rates(CCRs)covering 99.17%-99.58% in the training sets and 99.17%-100%in the testing sets.Fifteen wavelengths(432 nm,455 nm,468 nm,560 nm,705 nm,736 nm,760 nm,841 nm,861 nm,921 nm,930 nm,937 nm,938 nm,959 nm and 965 nm)were recommended by MGS.The results demonstrated that hyperspectral imaging could be used as a non-destructive method to classify mung bean varieties,and MGS was an effective wavelength selection method.

基于可见光谱特征波长提取和分类算法的柑橘黄龙病快检研究

柑橘黄龙病(HLB)是由亚洲韧皮杆菌引起的一种严重病害,目前无法根治。其防控具有重要意义和经济价值。当前利用健康和患病叶片的光谱差异对其进行诊断显示了良好的应用前景。因患病叶片在叶绿素反射区及O—H伸缩振动区的可见光谱与健康叶片存在显著差异,而可见光谱检测在采集和数据处理方面具有成本低、简便的优势,研究可见光谱的黄龙病快速检测方法具有可行性和重要意义。为了减少光谱数据冗余和计算量,实现精准的黄龙病的早期鉴别以及降低黄龙病相似病症的误诊率,采集了黄龙病患病地区共160个叶片样本。经qPCR测定分别将其分类标定为健康、轻度疾病、重度疾病和缺镁症四类。根据叶片样本在可见光波段450~800 nm的反射光谱特征,通过S-G平滑以及降采样等预处理光谱数据后,为了优选出尽可能囊括光谱特征信息的特征波长,分别使用遗传算法(GA)、连续投影算法(SPA)以及竞争自适应重加权采样法(CARS)对采集到的可见光谱数据进行特征波长提取和降维优选出特征波长,进一步降低模型复杂度,提高预测精度。综合泛化能力及检测速度的考量,在定性判别分析模型的选择中采用训练速度快,分析准确率高的最小二乘支持向量机(LS-SVM)以及随机森林(RF)对两种变量筛选算法降维后的数据进行分类判别。通过对不同的模型的验证优选,筛选出最佳的快检方案。对比发现,在建立的模型中,SPA-RF模型与其他模型比较,对于训练集和测试集的判别准确率分别达到了100%和97.5%。结果表明,连续投影算法以及随机森林的组合分类模型可以很好地实现黄龙病早期的病理鉴别,同时也能够很好地识别出黄龙病病叶与其他相似病症的差异,为柑橘黄龙病快速检测及防治提供了一种方法依据。

基于沙柳冠层可见-近红外光谱的热值预测

热值是灌木生物质能源利用的重要燃烧性能参数之一。针对传统实验室检测方法破坏性大、费时费力、无法实现大量样本的快速检测问题,探讨了沙柳冠层可见-近红外光谱(Vis-NIR)结合不同化学计量学方法预测沙柳热值的精度差异。采用标准正态变量变换(SNV)、归一化数据(normalize)、标准正态变量变换+归一化数据和第二代小波变换即提升小波变换(LWT)对冠层光谱进行预处理,采用偏最小二乘法(PLS)和卷积神经网络(CNN)构建了沙柳热值可见-近红外模型。同时,对比分析了鲸鱼优化算法(WOA)、麻雀搜索算法(SSA)和灰狼优化算法(GWO)对CNN模型参数的优化效果。结果表明:当采用db4小波进行5层分解后,其对沙柳冠层可见-近红外光谱的去躁效果最好,基于LWT-WOA-CNN法构建的沙柳热值可见-近红外模型的预测精度最优,校正模型的决定系数(R2)、均方根误差(RMSE)和相对分析误差(RPD)分别为0.852,0.103和2.599,RPD值较原始的PLS和CNN模型分别提高19.11%和76.80%。该研究可为沙柳生物质能源的高效、精细化利用提供技术支撑。

基于紫外-可见和近红外光谱技术的葡萄酒产地鉴别

该研究将紫外-可见光谱、近红外光谱技术与化学计量学方法相结合,建立一种快速、准确鉴别干红葡萄酒产地的方法。采集3个不同产地(怀涿盆地、宁夏贺兰山东麓和渤海湾)的108个赤霞珠干红葡萄酒样品的紫外-可见和近红外光谱信息。首先,对比采用标准正态变量变换(standard normal variable,SNV)、一阶导数(first derivative,FD)、二阶导数(second derivative,SD)及不同方法组合对两种光谱数据进行预处理,分别建立随机森林(random forest,RF)、K-最邻近法(K-nearest neighbor,KNN)和最小二乘支持向量机(least squares support vector machine,LS-SVM)判别模型,通过比较建模结果得到最优的预处理-建模方法组合;然后,基于最优判别模型,采用竞争性自适应重加权采样(competitive adaptive reweighted sampling,CARS)算法和无信息变量消除(uninformative variable elimination,UVE)法对光谱数据进行特征波段提取并建立判别模型。结果表明,基于紫外-可见光谱建立的SNV+FD-UVE-LSSVM模型的校正集和验证集的识别率分别达到97.53%和96.30%,基于近红外光谱建立的FD-CARS-KNN模型的校正集和验证集的识别率分别达到98.76%和96.30%。该结果证实将紫外-可见光谱、近红外光谱技术与机器学习相结合,有望成为一种简单、快速和低成本的工具,用于鉴别中国干红葡萄酒的地理来源。

Eye on the Sky: A UAP Research and Field Study off New York’s Long Island Coast

A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.

Band structure engineered tunneling heterostructures for high-performance visible and near-infrared photodetection

Tunneling heterostructures are emerging as a versatile architecture for photodetection due to their advanced optical sensitivity,tailorable detection band,and wellbalanced photoelectric performances.However,the existing tunneling heterostructures are mainly operated in the visible wavelengths and have been rarely investigated for the nearinfrared detection.Herein,we report the design and realization of a novel broken-gap tunneling heterostructure by combining WSe2 and Bi2Se3,which is able to realize the simultaneous visible and near-infrared detection because of the complementary bandgaps of WSe2 and Bi2Se3(1.46 and 0.3 e V respectively).Thanks to the realigned band structure,the heterostructure shows an ultralow dark current below picoampere and a high tunneling-dominated photocurrent.The photodetector based on our tunneling heterostructure exhibits a superior specific detectivity of 7.9×1012Jones for a visible incident of 532 nm and 2.2×1010Jones for a 1456 nm nearinfrared illumination.Our study demonstrates a new band structure engineering avenue for the construction of van der Waals tunneling heterostructures for high-performance wide band photodetection.

Lanthanide complexes-functionalized ordered mesoporous TiO_2:Multicolor emission(visible and near-infrared luminescence) based on visible-light sensitization

Recently,much attention has been paid to the lanthanide luminescent materials based on the visiblelight sensitization for their potential applications in the fields of bio-imaging and optical devices.In this work,the lanthanide complexes have been covalently bonded to the ordered mesoporous titania（OMT） matrix,and the resulting titania-based hybrid ordered mesoporous materials（named as LnDBOMT,Ln = Eu,Sm,Yb,Nd） were characterized by using Fourier-transform infrared（FT-IR） spectroscopy,small-angle X-ray powder diffraction（SAXD）,N2 adsorption-desorption isotherms,transmission electron microscopy（TEM）,fluorescence spectroscopy,and thermogravimetric analysis.Generally,exciting with visible light is advantageous over UV excitation.Of importance here is that,under excitation with visible light,the LnDB-OMT all show characteristic visible（Eu3＋,Sm3＋） as well as nearinfrared（Sm3＋,Yb3＋,Nd3＋） luminescence of the corresponding Ln3＋ ions（multicolor emission covered from 500 to 1400 nm spectral region）,which is attributed to the energy transfer from the ligands to the Ln3＋ ions via an antenna effect.

Visible and near-infrared light activated azo dyes

The photoisomerization properties of azo derivatives have been widely used in the fields of materials and biology.One serious restriction to the development of functional azo-based materials is the necessity to trigger switching by UV light,which damage the corresponding surfaces and penetrate only partially through the matter.Therefore,developing the visible and near-infrared light activated azo switches can solve this problem.This review provides a summary of molecular design strategies for driving the isomerization of azo derivatives with visible light and near-infrared light:(1) smart design directly excited by visible light,(2) the addition of upconversion nanoparticles,(3) the employment of twophoton absorption,(4) indirect excitation in combination with metal sensitizer.