Structure and Two-dimensional Correlation Infrared Spectroscopy Study of a New One-dimensional Chain Compound: (4,4’-Hbpy)_3[NaMo_8O_(26)](4,4’- bpy)_2(H_2O)_4 (bpy = Bipydine)

A novel compound, （4,4＇-Hbpy）3[NaMo8O26]（4,4＇-bpy）2（H2O）4 1 （bpy=bipydine）, was synthesized by the hydrothermal method. Single-crystal X-ray diffraction shows that compound 1 belongs to the monoclinic system, space group C2/m with a=19.1921（5）, b=18.6931（6）, c=9.3821（3） A° β=104.8020（11）°, V=3254.22（17）A°^3 C50H51Mo8N10NaO30, Mr=2062.52, Z=2, F（000）=2016, μ=1.591 mm^-1 and Dc=2.105 g/cm^3. The final R=0.0283 and wR=0.0912 for 3118 observed reflections （I〉20（I））. Compound 1 contains the β-[Mo8O26]^4-anion, sodium ion, 4,4＇-bpy and lattice crystalline water molecules. The β-[MosO26] units link the sodium ion to form a chain structure. The infinitechains of [Na（Mo8O26）]^3- blocks are surrounded by protonized 4,4＇-bpy cations, 4,4＇-bpy and lattice crystalline water molecules. The 2D-IR correlation spectroscopy study indicates that the stretching vibrations of Mo=O occur more preferentially due to the thermal effect. The TGA analysis shows that compound 1 has high thermal stability.

Study on the Hydrogen Bond Interaction Between Soy Protein Isolate and Glycerol Using Two-Dimensional Correlation Fourier-Transform Infrared Spectroscopy

A series of soy protein isolate(SPI)films plasticized by glycerol(Gly)were studied using attenuated total reflectance-Fourier transform infrared spectroscopy(ATR/FTIR).Perturbation-correlation movingwindow two-dimensional(PCMW2D)and two-dimensional correlation(2DCOS)analyses were applied to the amideⅠband and thus the hydrogen bond interaction between SPI and Gly was systematically investigated.When Gly concentrations were in the range 0~35%,the hydrogen bond amongβ-sheets was replaced by the one between SPI chain and Gly molecule,which caused these protein chains being changed toα-helix.However,the transformation ofβ-sheet toα-helix was saturated and both of them tend to change to random coil when Gly concentrations were in the range 35%~60%.

Application of Two-Dimensional Correlation UV-Vis Spectroscopy in Chinese Liquor Moutai Discrimination

Chinese liquor Moutai is the “National alcoholic drink” in China and plays a very important role of social activities in Chinese people’s life. In pursuit of high profits, some illegal counterfeit Moutai liquors have begun to appear in the market. Therefore, it is an urgent need for new techniques to discriminate the genuine and counterfeit Moutai liquor. In this work, the conventional Ultraviolet-Visible (UV-Vis) spectroscopy and two-dimensional correlation UV-Vis spectroscopy are applied to obtain the UV-Vis characteristic of Moutai liquor and counterfeit one, respectively. The experimental results reveal that the conventional UV-Vis spectra of the genuine and counterfeit Moutai liquor are similar. However, the two-dimensional correlation UV-Vis spectra of them are different and this method would be applied to differentiate the counterfeit Moutai liquor from the genuine Moutai liquor. Compared with conventional methods, this novel method has the advantages of easy operation, simple instrumentation and direct recognition, which make it a potential tool in the fields of food safety.

Evolution of Two-Dimensional Correlation Spectroscopy

A number of useful techniques associated with two-dimensional correlation spectroscopy(2DCOS)to improve its performance and utility have been developed in the last 30years.Evolution of these 2DCOS techniques,including some of the very recent developments,is reviewed with examples.Topics include merged or modified asynchronous 2Dcorrelation spectrum,two-dimensional codistribution spectroscopy(2DCDS),Pareto scaling,and null-space projection treatment of spectral dataset.

Docosahexaenoic Acid Ester Degradation Measured by FTIR-ATR with Correlation Spectroscopy

Highly unsaturated fatty acids such as docosahexaenoic acid and linolenic acid are prone to oxidation with a resulting loss of bioactivity and generation of malodorous degradation compounds. Degradation proceeds by formation of the corresponding hydroperoxyl free radical with subsequent oxidative cleavage at the double bond site. FTIR-ATR was used to detect degradation through spectral changes that were correlated to oxidative degradation. The spectrometer was equipped with a heated stage so that a series of spectra could be collected while the sample was exposed to elevated temperatures. The appearance of new bands at 972.8 cm﹣1, 2934 cm﹣1, and 3498 cm﹣1 with the disappearance of bands at 703.6 cm﹣1 and 3013 cm﹣1 were observed after heating and these spectral changes were evaluated by correlation spectroscopy analysis. These results provide a method to quickly detect the oxidative degradation of polyunsaturated fats. This approach is expected to be applied for the quality assessment of feed formulations fortified with omega-3 fatty acids.

Application of Grey-correlated Spectral Region Selection in Analysis of Near-infrared Spectra

The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared（NIR） spectra. In order to compute ＂characteristic＂ spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as ＂characteristic＂ spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.

Generalized two-dimensional correlation near-infrared spectroscopy and principal component analysis of the structures of methanol and ethanol

Liquid state methanol and ethanol under different temperatures have been investigated by FT-NIR(Fourier transform nearinfrared) spectroscopy,generalized two-dimensional(2D) correlation spectroscopy,and PCA(principal component analysis) . First,the FT-NIR spectra were measured over a temperature range of 30-64(or 30-71) °C,and then the 2D correlation spectra were computed.Combining near-infrared spectroscopy,generalized 2D correlation spectroscopy,and references,we analyzed the molecular structures(especially the hydrogen bond) of methanol and ethanol,and performed the NIR band assignments. The PCA method was employed to verify the results of the 2D analysis.This study will be helpful to the understanding of these reagents.

Solvent effects on infrared spectra of 2-methyl-4,5-dimethoxy-3-oxo-2H-pyridizine： Part 1. Single solvent systems

Infrared spectroscopy studies of 2 methyl 4,5 dimethoxy 3 oxo 2H pyridizine (MDOP) in 12 pure organic solvents were undertaken to investigate the solvent solute interactions. The frequencies of the carbonyl (C=O) of MDOP were correlated with solvent properties such as solvent acceptor number (AN) and the linear solvation energy relationships (LSER). These frequencies showed a good correlation with the solvent acceptor number (AN) and the LSER.

Introducing a Novel Approach for Oil-Oil Correlation based on Asphaltene Structure: X-ray Diffraction

Asphaltenes have always been an attractive subject for researchers.However,the application of this fraction of the geochemical field has only been studied in a limited way.In other words,despite many studies on asphaltene structure,the application of asphaltene structures in organic geochemistry has not so far been assessed.Oil-oil correlation is a wellknown concept in geochemical studies and plays a vital role in basin modeling and the reconstruction of the burial history of basin sediments,as well as accurate characterization of the relevant petroleum system.This study aims to propose the Xray diffraction(XRD)technique as a novel method for oil-oil correlation and investigate its reliability and accuracy for different crude oils.To this end,13 crude oil samples from the Iranian sector of the Persian Gulf region,which had previously been correlated by traditional geochemical tools such as biomarker ratios and isotope values,in four distinct genetic groups,were selected and their asphaltene fractions analyzed by two prevalent methods of XRD and Fouriertransform infrared spectroscopy(FTIR).For oil-oil correlation assessment,various cross-plots,as well as principal component analysis(PCA),were conducted,based on the structural parameters of the studied asphaltenes.The results indicate that asphaltene structural parameters can also be used for oil-oil correlation purposes,their results being completely in accord with the previous classifications.The average values of distance between saturated portions(d_(r))and the distance between two aromatic layers(d_(m))of asphaltene molecules belonging to the studied oil samples are 4.69Aand 3.54A,respectively.Furthermore,the average diameter of the aromatic sheets(L_(a)),the height of the clusters(L_(c)),the number of carbons per aromatic unit(C_(au)),the number of aromatic rings per layer(R_(a)),the number of sheets in the cluster(M_(e))and aromaticity(f_(a))values of these asphaltene samples are 10.09A,34.04A,17.42A,3.78A,10.61Aand 0.26A,respectively.The results of XRD parameters indicate that plots of dr vs.d_(m),d_(r) vs.M_(e),d_(r) vs.f_(a),d_(m) vs.L_(c),L_(c) vs.L_(a),and f_(a) vs.L_(a) perform appropriately for distinguishing genetic groups.A comparison between XRD and FTIR results indicated that the XRD method is more accurate for this purpose.In addition,decision tree classification,one of the most efficacious approaches of machine learning,was employed for the geochemical groups of this study for the first time.This tree,which was constructed using XRD data,can distinguish genetic groups accurately and can also determine the characteristics of each geochemical group.In conclusion,the obtaining of structural parameters for asphaltene by the XRD technique is a novel,precise and inexpensive method,which can be deployed as a new approach for oil-oil correlation goals.The findings of this study can help in the prompt determination of genetic groups as a screening method and can also be useful for assessing oil samples affected by secondary processes.

Generalized two-dimensional correlation spectroscopy——Theory and applications in analytical field

Since the theory of generalized two-dimensional (2-D) correlation spectroscopy was proposed, it has been keenly concerned in scientific research and its analytical method has been widely applied in various analytical fields. The mathematical process to construct generalized 2-D correlation spectroscopy and the physical meaning of 2-D correlation spectral map are described, and three examples in the fields of chemical analysis and molecular biology are provided, such as the component analysis of organic solvent, the analysis of biological molecules in the solvent with different pH values and structural analysis of protein. The theory and analytical method of generalized 2-D correlation spectroscopy are also detailedly commented.

Spectral Insights into Microdynamics of Thermoresponsive Polymers from the Perspective of Two-dimensional Correlation Spectroscopy

Generalized two-dimensional correlation spectroscopy （2DCOS） and its derivate technique, perturbation correlation moving window （PCMW）, have found great potential in studying a series of physico-chemical phenomena in stimuli-responsive polymeric systems. By spreading peaks along a second dimension, 2DCOS can significantly enhance spectral resolution and discern the sequence of group dynamics applicable to various external perturbation-induced spectroscopic changes, especially in infrared （IR）, near-infrared （NIR） and Raman spectroscopy. On the basis of 2DCOS synchronous power spectra changing, PCMW proves to be a powerful tool to monitor complicated spectral variations and to find transition points and ranges. This article reviews the recent work of our research group in the application of 2DCOS and PCMW in thermoresponsive polymers, mainly focused on liquid crystalline polymers and lower critical solution temperature （LCST）-type polymers. Details of group motions and chain conformational changes upon temperature perturbation can thus be elucidated at the molecular level, which contribute to the understanding of their phase transition nature.

Recent developments in two-dimensional (2D) correlation spectroscopy

Recent noteworthy developments in the field of two-dimensional（2D） correlation spectroscopy are reviewed.2D correlation spectroscopy has become a very popular tool due to its versatility and relative ease of use.The technique utilizes a spectroscopic or other analytical probe from a number of selections for a broad range of sample systems by employing different types of external perturbations to induce systematic variations in intensities of spectra.Such spectral intensity variations are then converted into2 D spectra by a form of correlation analysis for subsequent interpretation.Many different types of 2D correlation approaches have been proposed.In particular,2D hetero-correlation and multiple perturbation correlation analyses,including orthogonal sample design scheme,are discussed in this review.Additional references to other important developments in the field of 2D correlation spectroscopy,such as projection correlation and codistribution analysis,were also provided.

Two-dimensional correlation spectroscopic analysis on the interaction between humic acids and aluminum coagulant

In this study, two-dimensional correlation spectroscopy integrated with synchronous fluorescence and infrared absorption spectroscopy was employed to investigate the interaction between humic acids and aluminum coagulant at slightly acidic and neutral p H. Higher fluorescence quenching was produced for fulvic-like and humic-like fractions at p H 5. At p H 5, the humic-like fractions originating from the carboxylic acid, carboxyl and polysaccharide compounds were bound to aluminum first, followed by the fulvic-like fractions originating from the carboxyl and polysaccharide compounds. This finding also demonstrated that the activated functional groups of HA were involved in forming the Al-HA complex, which was accompanied by the removal of other groups by co-precipitation.Meanwhile, at p H 7, almost no fluorescence quenching occurred, and surface complexation was observed to occur, in which the activated functional groups were absorbed on the amorphous Al（OH）3. Two-dimensional FT-IR correlation spectroscopy indicated the sequence of HA structural change during coagulation with aluminum, with IR bands affected in the order of COOH〉 COO-〉NH deformation of amide Ⅱ〉 aliphatic hydroxyl C／OH at p H 5, and COO-〉aliphatic hydroxyl C／OH at p H 7. This study provides a promising pathway for analysis and insight into the priority of functional groups in the interaction between organic matters and metal coagulants.

基于DCGAN数据增强的樱桃番茄可溶性固形物含量光谱检测方法

针对樱桃番茄在实际检测中样品数不足的特点,本研究提出一种深度卷积生成对抗网络(deep convolutional generative adversarial network,DCGAN)模型以同时扩充光谱数据及可溶性固形物含量(soluble solids content,SSC)标签数据,并建立一维卷积神经网络回归(one dimensional-convolutional neural networks regression,1D-CNNR)模型以提高模型的预测精度和泛化能力。为了比较,分别建立偏最小二乘回归(partial least squares regression,PLSR)模型和支持向量机回归(support vector regression,SVR)模型。将原始80个样品数据集、1000个样品的DCGAN扩充数据集和1080个样品的合并数据集,分别结合1D-CNNR、SVR及PLSR进行建模与预测。为了进一步验证模型的泛化能力,一批新的总数为40个样品的樱桃番茄数据作为上述3个模型的新测试集。结果显示,使用合并数据集划分所得校正集进行1D-CNNR建模后,模型为最优的SSC回归检测模型。此时1D-CNNR面向合并样品测试集的预测准确率最高,预测相关系数rp=0.9807,均方根误差RMSE_(p)=0.1929;与SVR与PLSR对比,1D-CNNR面向新的40个样品数据集的预测准确率也最高,其rp=0.9638,RMSE_(p)=0.2245。本研究可为有效准确检测樱桃番茄的可溶性固形物含量提供一种新思路。

Two-dimension fluorescence correlation spectroscopy to characterize the binding of organic ligands with zinc in eutrophic lake

Metal binding of organic ligands can definitely affect its environmental behavior in waters,while information on the binding heterogeneity with different organic ligands is still lacked till now.In this study,the binding of zinc with organic matters associated with cyanobacterial blooms,including dissolved organic matters（DOM） and attached organic matters（AOM）,were studied by using fluorescence quenching titration combined with two-dimensional correlation spectroscopy（2D-COS）.Metal-induced fluorescent quenching was obviously observed both for DOM and AOM,indicating the formation of metal-ligand complexes.Compared with the one-dimensional spectra,2D-COS revealed the sequences of metal-ligand interaction with the following orders：276 nm 〉 232 ran for DOM and232 nm 〉 276 nm for AOM.Furthermore,the modified Stern-Volmer model showed that the binding constant（logKM） of 276 nm in DOM was higher than that of 232 nm（4.93 vs.4.51）,while AOM was characterized with a high binding affinity for 232 nm（log KM：4.83）.The ranks of log KM values were consistent with the sequential orders derived from 2D-COS results both for the two samples.Fluorescence quenching titration combined with 2D-COS was an effective method to characterize the metal-ligand interaction.

大米淀粉晶体/非晶体结构耐热性研究

采用中红外(MIR)光谱及二维中红外(2D-MIR)光谱分别开展大米结构及其淀粉晶体/非晶体结构热变性研究。实验发现:大米的红外吸收模式主要包括:νOH-大米、νas CH2-大米、νs CH2-大米、νamide-Ⅰ-大米、νamide-Ⅱ-大米和νC-O-大米。随着测定温度升高(303~393 K),不同产地的大米淀粉晶体/非晶体结构对于热的敏感程度及变化快慢顺序均存在一定的差异性。进一步探究相关机理,认为不同大米淀粉晶体/非晶体结构耐热性存在一定差异性,因而进一步影响其口感。并拓展了MIR光谱及2D-MIR光谱技术在大米结构及其淀粉晶体/非晶体结构热变性的研究范围。

氢氧化钠分子结构原位漫反射一维及二维漫反射中红外光谱研究

通过原位一维漫反射中红外(MIR)光谱开展了氢氧化钠分子结构研究。实验发现,氢氧化钠分子结构主要红外吸收模式包括OH基团伸缩振动模式(νOH-NaOH-_(一维))和OH基团面内摇摆振动模式(ρOH-NaOH-_(一维))。进一步开展了氢氧化钠分子结构的原位二维漫反射MIR光谱研究。采用原位漫反射一维及二维漫反射MIR光谱开展氢氧化钠结构研究,对氯碱工业具有重要意义。

基于校正光谱序列融合的小麦腥黑穗病籽粒分类方法

针对小麦腥黑穗病轻度患病籽粒易与健康籽粒混淆,人工识别难度大的问题,将校正光谱序列融合技术与深度学习模型相结合,实现小麦腥黑穗病籽粒快速、精准分类。以健康、轻度患病、重度患病各300粒小麦籽粒的高光谱数据为样本,通过多元散射校正算法(MSC)和标准正态变换算法(SNV)对原始光谱进行预处理,并利用二维相关光谱法(2D-COS)分析SNV与MSC算法处理后的光谱之间的互补性。使用校正光谱序列融合技术将原始光谱、SNV预处理光谱与MSC预处理光谱三者进行融合得到序列融合光谱,以充分利用不同光谱预处理数据间的互补信息。最终,利用序列融合光谱数据建立基于ResNet 50算法的小麦腥黑病分类模型。试验结果表明,序列融合光谱ResNet 50模型总体准确率最高为93.89%,F1值为93.87%,分类性能优于单一预处理光谱建立的ResNet 50模型。为进一步评估模型分类效果,使用序列融合光谱分别建立偏最小二乘判别分析(PLS-DA)、支持向量机(SVM)以及集成学习算法模型随机森林(RF)与极端梯度提升树(XGBoost)模型,并进行对比,结果显示:SVM、PLS-DA、RF与XGBoost总体准确率分别为81.67%、84.44%、89.44%与90.55%,F1值分别为81.59%、84.04%、89.49%与90.59%,ResNet 50总体准确率与F1值优于传统光谱分析模型。因此,本研究表明校正光谱序列融合技术结合深度学习模型,能够实现对不同患病程度腥黑穗病籽粒的有效分类。

基于反向比例解析的近红外光谱定量模型快速构建方法

为解决光谱漂移问题,该研究设计了一种基于反向比例解析的近红外光谱定量模型方法。以烟叶近红外光谱和烟碱含量为研究对象,将数据划分为训练集和测试集。通过计算训练集光谱与测试集光谱的相关性并按照高低排序,选择前20%的光谱,运用约束规划的方法,计算测试集的拟合系数,得到测试集光谱的估计值。结果显示,使用反向比例解析法建立的模型的平均绝对误差为0.3466,预测标准偏差为0.4252,相关系数为0.7932,优于PLS模型。反向光谱比例解析可以有效解决光谱漂移问题,实现烟草中烟碱含量的准确预测,为烟碱的有效测量提供参考。

基于光谱特征的多重金属离子与DOM结合特性

通过淬灭滴定实验,文章采用同步荧光光谱和傅里叶红外光谱(FTIR)结合二维相关光谱分析,探究Cu^(2+)和Cd^(2+)多重离子与溶解态有机质(DOM)结合特性。研究结果表明,(1)DOM与Cu^(2+)和Cd^(2+)结合稳定常数(lg KM)分别为4.75~5.18和3.71~4.12,Cu^(2+)与DOM的结合能力要强于Cd^(2+)。(2)Cd^(2+)浓度为0和100μmol/L时,DOM点位与Cu^(2+)的结合顺序均为430~500 nm>330~420 nm,且Cd^(2+)存在时Cu^(2+)与DOM的lg KM为4.56~4.95。对比结果表明Cd^(2+)的存在并未影响DOM点位与Cu^(2+)的结合顺序,但减弱了DOM与Cu^(2+)的结合能力。(3)FTIR结果表明,Cd^(2+)浓度为0和100μmol/L时DOM官能团与Cu^(2+)结合顺序依次为酚类C-O>酰胺N-H>酰胺C=O>羧基C=O>芳香族C-H>多糖C-O和酰胺N-H>酰胺C=O>酚类C-O>芳香族C-H>多糖C-O。Cd^(2+)与酚类C-O结合后影响了Cu^(2+)与DOM中酚类C-O和羧基C=O官能团的结合。水环境中多重金属离子共存时的生物有效性和生态风险应受到关注。