Gaofang Yin

Hydrothermal synthetic mercaptopropionic acid stabled CdTe quantum dots as fluorescent probes for detection of Ag

Mercaptopropionic acid (MPA) capped CdTe quantum dots (QDs) with particle size 3 nm have been successfully synthesized in aqueous medium by hydrothermal synthesis method. And the effects of different metal ions on MPA capped CdTe QDs fluorescence were studied using fluorescence spectrometry. The results demonstrated that at the same concentration level, Ag(+) could strongly quench CdTe QDs fluorescence, and the other metal ions had little effect on CdTe QDs fluorescence except Cu(2+). On the basis of this fact, a rapid, simple, highly sensitive and selective method based on fluorescence quenching principle for Ag(+) detection in aqueous solution was proposed. Under optimal conditions, the quenched fluorescence intensity (F(0)-F) increased linearly with the concentration of Ag(+) ranging from 4 × 10(-7) to 32 × 10(-7)mol L(-1). The limit of detection for Ag(+) was 4.106 × 10(-8)mol L(-1). The obtained plot of F(0)/F versus [Ag(+)] was an upward curvature, concave towards the y-axis, rather than a straight line. The modified form of the Stern-Volmer equation was third order in Ag(+) concentration. According to the modified Stern-Volmer equation, it can be inferred that dynamic quenching and static quenching simultaneously occurred when Ag(+) interacted with MPA capped CdTe QDs. At the same time other factors might also influence the quenching process. Based on this study, hydrothermal synthesized MPA capped CdTe QDs with particle size 3 nm may be used as a novel fluorescence probe to quantificationally and selectively detect Ag(+).

A novel initialization method for nonnegative matrix factorization and its application in component recognition with three-dimensional fluorescence spectra

Nonnegative matrix factorization has been widely used in many areas and has been applied for component recognition with three dimensional fluorescence spectra recently. However, nonnegative matrix factorization is a nonconvex programming in the iteration process, thus the solution is dependent on the initial values and consequently not unique. Up to now, an effective global convergent algorithm is still absent. In this work, we propose an initialization scheme based on independent component analysis. Compared with other initialization schemes, the optimal solution of nonnegative matrix factorization based on independent component analysis is much better and it is demonstrated by typical experiments of component recognition with three-dimensional fluorescence spectra.

Component recognition with three-dimensional fluorescence spectra based on non-negative matrix factorization

Non‐negative matrix factorization (NMF) is a widely used approach in signal processing. In this work, we apply it to the component recognition of mixtures with multicomponent three‐dimensional fluorescence spectra. Compared with the popular PARAFAC for component recognition, NMF has the following advantages: on one hand, the decomposed spectra are three dimensional, and thus, more information can be obtained, which is beneficial for component recognition; on the other hand, the decomposed spectra are non‐negative and thus have a certain physical significance. More importantly, we propose a type of integrated similarity indices for the three‐dimensional fluorescence spectra, which, by construction, is good at component recognition from overlapping fluorescence spectra. Experiment results demonstrate that NMF combined with integrated similarity index provides an effective method for component recognition of multicomponent three‐dimensional overlapping fluorescence spectra. Copyright

Integrated similarity indices for component recognition in mixtures with three-dimensional fluorescence spectra.

Component recognition is a very important issue in the analysis of mixed three-dimensional fluorescence spectra and it can be realized by calculating the similarity index between the reference spectra and the computed spectra from the trilinear decomposition of the three-dimensional data arrays. However, the most popular similarity index available in the literature for processing three-dimensional fluorescence spectra takes advantage of only part of the information from the trilinear decomposition. It works well when there are clear differences between the component spectra, but it may fail when the spectra are severely overlapped. In order to overcome the shortcomings and to adapt to the rapid development of online monitoring, we propose a type of integrated similarity index (ISI) that is particularly superior for component recognition in mixtures with severely overlapped spectra. The ISI makes full use of as much information of the three-dimensional fluorescence spectra as possible, namely, of both the waveform and the characteristic peak wavelength, as well as both the emission spectra and the excitation spectra. With the ISI, the recognition process can be accomplished automatically and more accurately in extreme cases than the traditionally defined similarity indices that are based on only one specific feature. The feasibility of the ISI is demonstrated by experiments with mixtures of phenol, cresol, and thymol.

Mercaptopropionic acid-capped Mn-doped ZnS quantum dots as a probe for selective room-temperature phosphorescence detection of Pb2+ in water

In this study, highly water-soluble Mn-doped ZnS quantum dots (QDs) capped by 3-mercaptopropionic acid (MPA) were successfully synthesized by three different synthetic methods. By comparison, QDs prepared by hydrothermal synthesis method at 100 °C heating for 2 h had the best phosphorescence emission properties. Room-temperature phosphorescence (RTP) could be remarkably and selectively quenched by Pb2+ in a pH 3.8 NaAc–HAc buffer solution. Based on the abovementioned finding, a simple, sensitive, and selective phosphorescence method for rapid detection of Pb2+ was successfully developed using MPA-capped Mn-doped ZnS QDs as a probe. Under the optimized conditions, the RTP intensity ratio of P0/P had a good linear relationship with Pb2+ concentration in the concentration ranges of 4 × 10−8–90 × 10−8 mol L−1 and 90 × 10−8–600 × 10−8 mol L−1 with the correlation coefficients of 0.9967 and 0.9970, which well followed the Stern–Volmer quenching equation, and the Stern–Volmer quenching constants were 8.41 × 105 L mol−1 and 3.452 × 106 L mol−1, respectively. The detection limit was 3.69 × 10−8 mol L−1, and the relative standard deviation for 11 repeated detections of 60 × 10−8 mol L−1 Pb2+ was 2.8%. According to the analysis of the Stern–Volmer quenching equation, UV-Vis absorption spectra, decay curves of phosphorescence emission, and phosphorescence lifetime, the quenching mechanism may imply that energy transfer and charge transfer in the interaction of MPA-capped Mn-doped ZnS QDs at the excited state with Pb2+ made QDs lose excitation energy. This resulted in phosphorescence of QDs causing dynamic quenching. The proposed method was successfully applied to detect Pb2+ in real water samples with satisfactory results, and the recoveries ranged from 93% to 109.3%. The developed method was simple, rapid, and specific and could effectively avoid fluorescence interference of the system, which opened up a promising prospect for the sensitive, convenient, and fast sensing and monitoring of small molecule pollutants in water based on phosphorescence sensors.

Quantifying PAHs in water by three-way fluorescence spectra and second-order calibration methods

It is still difficult to determine the concentrations of polycyclic aromatic hydrocarbons accurately in natural water by fluorescence technique because of their low solubility, different fluorescent intensity, and the complex interferents from water environments. In this work, three-way fluorescence spectra combined with three methods including three-way parallel factor analysis, multi-way partial least square with residual bilinearization and unfolded partial least square with residual bilinearization were used to predict the concentrations of polycyclic aromatic hydrocarbons at the μg L-1 level in reservoir and river water, respectively. The prediction abilities of these methods on different analytes were evaluated by validation sets. The results demonstrate that unfolded partial least square with residual bilinearization yields the optimal results with relative error less than or equal to 6% for phenanthrene, pyrene, anthracene and fluorene, and 35% for acenaphthene and fluoranthene in different water backgrounds.

Discrimination of three dimensional fluorescence spectra based on wavelet analysis and independent component analysis.

Fluorescence spectroscopy is a rapid and non-destructive method for monitoring water quality. In this work, wavelet analysis, together with independent component analysis (ICA), was applied for component recognition of seriously overlapped, multi-component, three dimensional fluorescence spectra. Wavelet analysis extracts the features of the spectra and amplifies differences among phenolic homologs. ICA analysis in blind signal separation was used to separate single component before multiple linear regression (MLR). The proposed method increases the correct classification rate and enriches the spectra library. As such, it is a useful alternative to traditional techniques in component recognition.

Underdetermined blind separation of three-way fluorescence spectra of PAHs in water

In this work, underdetermined blind decomposition method is developed to recognize individual components from the three-way fluorescent spectra of their mixtures by using sparse component analysis (SCA). The mixing matrix is estimated from the mixtures using fuzzy data clustering algorithm together with the scatters corresponding to local energy maximum value in the time-frequency domain, and the spectra of object components are recovered by pseudo inverse technique. As an example, using this method three and four pure components spectra can be blindly extracted from two samples of their mixture, with similarities between resolved and reference spectra all above 0.80. This work opens a new and effective path to realize monitoring PAHs in water by three-way fluorescence spectroscopy technique.

Characterization of coal oil using three-dimensional excitation and emission matrix fluorescence spectroscopy

Three-dimensional (3D) excitation-emission matrix (EEM) fluorescence spectroscopy is applied to characterize the coal oil. The results show that the 3D fluorescence spectra of coal oil in aqueous solution mainly have one broad peak. This peak is identified at the excitation/emission wavelengths of 270/290 nm. The relation between the fluorescence intensity and the concentration of coal oil is also studied. When the concentration lies between 2-2000 ppm, the relation between the fluorescence intensity and the concentration of coal oil is well linear. The nature of solvents significantly affects the EEM fluorescence of coal oil.

Measurement of Phytoplankton Photosynthesis under Different Habitats Using Variable Pulse Light Induced Fluorescence

The technique based on variable pulse light induced fluorescence was employed to measure the photosynthesis of phytoplankton under different nutrient, light, temperature conditions and growing periods. The validity of this technique was conformed.