In situ infrared, Raman and X-ray spectroscopy for the mechanistic understanding of hydrogen evolution reaction

Hydrogen production by water reduction reactions has received considerable attention because hydrogen is considered a clean-energy carrier,key for a sustainable energy future.Computational methods have been widely used to study the reaction mechanism of the hydrogen evolution reaction(HER),but the calculation results need to be supported by experimental results and direct evidence to confirm the mechanistic insights.In this review,we discuss the fundamental principles of the in situ spectroscopic strategy and a theoretical model for a mechanistic understanding of the HER.In addition,we investigate recent studies by in situ Fourier transform infrared(FTIR),Raman spectroscopy,and X-ray absorption spectroscopy(XAS) and cover new findings that occur at the catalyst-electrolyte interface during HER.These spectroscopic strategies provide practical ways to elucidate catalyst phase,reaction intermediate,catalyst-electrolyte interface,intermediate binding energy,metal valency state,and coordination environment during HER.

Application of near-infrared spectroscopy for fast germplasm analysis and classification in multi-environment using intact-seed peanut(Arachis hypogaea L.)

Peanut is a worldwide oilseed crop and the need to assess germplasm in a non-destructive manner is important for seed nutritional breeding.In this study,Near Infrared Spectroscopy(NIRS)was applied to rapidly assess germplasm variability from whole seed of 699 samples,field-collected and assembled in four genetic and environmentbased sets:one set of 300 varieties of a core-collection and three sets of 133 genotypes of an interspecific population,evaluated in three environments in a large spatial scale of two countries,Mbalmayo and Bafia in Cameroon and Nioro in Senegal,under rainfed conditions.NIR elemental spectra were gathered on six subsets of seeds of each sample,after three rotation scans,with a spectral resolution of 16 cm-1over the spectral range of867 nm to 2530 nm.Spectra were then processed by principal component analysis(PCA)coupled with Partial least squares-discriminant analysis(PLS-DA).As results,a huge variability was found between varieties and genotypes for all NIR wavelength within and between environments.The magnitude of genetic variation was particularly observed at 11 relevant wavelengths such as 1723 nm,usually related to oil content and fatty acid composition.PCA yielded the most chemical attributes in three significant PCs(i.e.,eigenvalues>10),which together captured 93%of the total variation,revealing genetic and environment structure of varieties and genotypes into four clusters,corresponding to the four samples sets.The pattern of genetic variability of the interspecific population covers,remarkably half of spectrum of the core-collection,turning out to be the largest.Interestingly,a PLS-DA model was developed and a strong accuracy of 99.6%was achieved for the four sets,aiming to classify each seed sample according to environment origin.The confusion matrix achieved for the two sets of Bafia and Nioro showed 100%of instances classified correctly with 100%at both sensitivity and specificity,confirming that their seed quality was different from each other and all other samples.Overall,NIRS chemometrics is useful to assess and distinguish seeds from different environments and highlights the value of the interspecific population and core-collection,as a source of nutritional diversity,to support the breeding efforts.

Near Infrared Spectroscopy (NIRS) Model-Based Prediction for Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp) is a multi-purpose legume with high quality protein for human consumption and livestock. The objective of this work was to develop near-infrared spectroscopy (NIRS) prediction models to estimate protein content in cowpea. A total of 116 cowpea breeding lines with a wide range of protein contents (19.28 % to 32.04%) were selected to build the model using whole seed and ground seed samples. Partial least-squares discriminant analysis (PLS-DA) regression technique with different pre-treatments (derivatives, standard normal variate, and multiplicative scatter correction) were carried out to develop the protein prediction model. Results showed: 1) spectral plots of both the whole seed and ground seed showed higher spectral scatter at higher wavelengths (>1450 nm), 2) data pre-processing affects prediction accuracy for bot whole seed and ground seed samples, 3) prediction using ground seed samples (0.64 R2 0.85) is better than the whole seed (0.33 R2 0.78), and 4) the data pre-processing second derivative with standard normal variate has the best prediction (R2_whole seed = 0.78, R2_ground seed = 0.85). The results will be of interest in cowpea breeding programs aimed at improving total seed protein content.

The Study of Using Near-infrared Diffuse Reflectance Spectroscopy Rapid Identify Wheat Drought Resistance-Ⅱ

[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards （GB/T 21127-2007）, and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination （RSQ） and cross-validation coefficient of determination （1-VR） were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.

Photochemical Reaction of Benzoin Caged Compound： Time-Resolved Fourier Transform Infrared Spectroscopy Study

The benzoin group caged compound has received strong interests due to its excellent photo- deprotection properties and wide use in chemical and biological studies. We used timeresolved infrared spectroscopy to investigate the photochemical reaction of the benzoin caged compound, o-（2-methylbenzoyl）-DL-benzoin under 266 nm laser irradiation. Taking advantage of the specific vibrational marker bands and the IR discerning capability, we have detected and identified the uncaging product 2-methylbenzoic acid, and two intermediate radicals of benzoyl and 2-methylbenzoate benzyl in the transient infrared spectra. Our results provide spectral evidence to support the homolytic cleavage reaction of C-C=O bond in competition with the deprotection reaction. Moreover, the product yields of 2-methylbenzoic acid and benzoyl radical were observed to be affected by solvents and a largely water contalning solvent can be in favor of the deprotection reaction.

Application of Wavelet Transform in the Prediction of Navel Orange Vitamin C Content by Near-Infrared Spectroscopy

This study was to search for an approach for rapid measurement of orange vitamin C （Vc） content. By using different decomposing levels of Daubechies 3 wavelet transform, the near-infrared spectra signals obtained from intact fruits of 100 navel orange samples were denoised, and the results of the predicted Vc contents for the corresponding samples determined by the reconstructed spectra after denoising were validated by means of PLS-CV （partial least squared-cross validation）. It was shown that the prediction effects verified by PLS-CV analysis varied when different wavelet transform decomposing levels were employed. At the wavelet decomposing level 4, the best prediction effect was obtained, with the correlation coefficient R between the prediction and true values being 0.9574 and the expected variance RMSECV being as low as 3.9 mg 100 g^-1. Furthermore, the 11 different approaches for the pretreatment of the near-infrared spectrum were compared. It was found that the calibration model established by PLS using spectra pretreated by wavelet transform denoising provided the best prediction for Vc content, exhibiting the highest correlation between the prediction and true values by cross validation. In conclusion, the near infrared spectral model denoised by means of wavelet transform can be used for accurate, rapid, and nondestructive quantitative analysis on navel orange Vc content.

Supercritical water syntheses of transition metal-doped CeO_2 nano-catalysts for selective catalytic reduction of NO by CO:An in situ diffuse reflectance Fourier transform infrared spectroscopy study

In the present study,we synthesized CeO2 catalysts doped with various transition metals(M=Co,Fe,or Cu)using a supercritical water hydrothermal route,which led to the incorporation of the metal ions in the CeO2 lattice,forming solid solutions.The catalysts were then used for the selective catalytic reduction(SCR)of NO by CO.The Cu‐doped catalyst exhibited the highest SCR activity;it had a T50(i.e.,50%NO conversion)of only 83°C and a T90(i.e.,90%NO conversion)of 126°C.Such an activity was also higher than in many state‐of‐the‐art catalysts.In situ diffuse reflectance Fourier transform infrared spectroscopy suggested that the MOx‐CeO2 catalysts(M=Co and Fe)mainly followed an Eley‐Rideal reaction mechanism for CO‐SCR.In contrast,a Langmuir‐Hinshelwood SCR reaction mechanism occurred in CuO‐CeO2 owing to the presence of Cu+species,which ensured effective adsorption of CO.This explains why CuO‐CeO2 exhibited the highest activity with regard to the SCR of NO by CO.

Rapid Non-destructive Detection for Molds Colony of Paddy Rice Based on Near Infrared Spectroscopy

Near infrared spectrometer technology under a wavelength range of 918-1045 nm was used to rapidly detect paddy rice that was stored at 5℃, 15℃ and 25℃. A total of 121 paddy rice samples were collected from artificial infection with moulds to build the calibration models to calculate the total number colony of moulds based on the principal component regression method and multiple linear regression method. The results of statistical analysis indicated that multiple linear regression method was applicable to the detection of the total number colony of moulds. The correlation of calibration data set was 0.943. The correlation of prediction data set was 0.897. Therefore, the result showed that near infrared spectroscopy could be a useful instrumental method for determining the total number colony of moulds in paddy rice. The near infrared spectroscopy methodology could be applied for monitoring mould contamination in postharvest paddy rice during storage and might become a powerful tool for monitoring the safety of the grain.

High-resolution Infrared Spectroscopy of ^15N2^16O in 1650-3450 cm-1

High-resolution ro-vibrational spectroscopy of ^15N2^16O in 1650-3450 cm-1 region is studied using highly enriched isotopologue sample. The positions of more than 7300 lines of ^15N2^16O isotopologue were measured with a typical accuracy of 5.0×10-4 cm-1. The transitions were rovibrationally assigned on the basis of the global effective Hamiltonian model. The band by band analysis allowed for the determination of the rovibrational parameters of a total of 73 bands. 29 of them are newly reported and more rotational transitions have been observed for the others. The maximum deviation of the preidictions of the effective Hamiltonian model is up to 0.70 cm-1 for the ^15N2^16O species.

Acupuncture enhances brain function in patients with mild cognitive impairment: evidence from a functional-near infrared spectroscopy study

Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.

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.

A simple,sensitive and non-destructive technique for characterizing bovine dental enamel erosion:attenuated total reflection Fourier transform infrared spectroscopy

Although many techniques are available to assess enamel erosion in vitro, a simple, non-destructive method with sufficient sensitivity for quantifying dental erosion is required. This study characterized the bovine dental enamel erosion induced by various acidic beverages in vitro using attenuated total reflection Fourier transform infrared （ATR-FTIR） spectroscopy. Deionized water （control） and 10 acidic beverages were selected to study erosion, and the pH and neutralizable acidity were measured. Bovine anterior teeth （110） were polished with up to 1 200-grit silicon carbide paper to produce flat enamel surfaces, which were then immersed in 20 mL of the beverages for 30 min at 37 ℃. The degree of erosion was evaluated using ATR-FTIR spectroscopy and Vickers＇ microhardness measurements. The spectra obtained were interpreted in two ways that focused on the ~1, ~3 phosphate contour： the ratio of the height amplitude of ~3 P04 to that of/11 P04 （Method 1） and the shift of the v3 P04 peak to a higher wavenumber （Method 2）. The percentage changes in microhardness after the erosion treatments were primarily affected by the pH of the immersion media. Regression analyses revealed highly significant correlations between the surface hardness change and the degree of erosion, as detected by ATR-FTIR spectroscopy （P〈0.001）. Method 1 was the most sensitive to these changes, followed by surface hardness change measurements and Method 2. This study suggests that ATR- FTIR spectroscopy is potentially advantageous over the microhardness test as a simple, non-destructive, sensitive technique for the quantification of enamel erosion.

Synchrotron-based infrared microspectroscopy under high pressure:An introduction

Synchrotron sources with high photon flux,small source size,and broad energy range have revolutionized ultrafine characterization of condensed matter.With the addition of the pressure dimension realized by the use of diamond anvil cells,enormous progress has been achieved throughout high-pressure science.This is particularly so for synchrotron-based infrared microspectroscopy(SIRMS)with its very high signal-tonoise ratio,high spatial resolution,and extended measurement conditions.SIRMS has high sensitivity,providing a platform for the investigations of the very small amounts of material that need to be used in high-pressure research.This review summarizes developments in SIRMS,focusing on instrumentation and high-pressure measurements.Applications to measurements of infrared reflectance and absorption are presented,illustrating how SIRMS results play a crucial role in advancing understanding of the crystalline phase transitions,electronic transitions,metallization,lattice dynamics,superconductivity,and novel functional behavior.New insights into spectroscopic properties,together with some cutting edge issues and open problems,are also briefly discussed.

Polarization Dependent Time-Resolved Infrared Spectroscopy and Its Applications

Polarization dependent time-resolved infrared （TRIR） spectroscopy has proven to be a useful technique to study the structural dynamics in a photochemical process. The angular information of transient species is obtainable in this measurement, which makes it a valuable technique for the investigation of electron distribution, molecular structure, and conformational dynamics. In this review, we briefly introduce the principles and applications of polarization dependent TRIR spectroscopy. We mainly focused on the following topics： （i） an overview of TRIR spectroscopy, （ii） principles of TRIR spectroscopy and its advantages compared to the other ultrafast techniques, （iii） examples that use polarization dependent TRIR spectroscopy to probe a variety of cheinical and dynamical phenomena including protein conformational dynamics, excited state electron localization, and photoisomerization, （iv） the limitations and prospects of TRIR spectroscopy.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Brand Identification of Wine

High-end wine brand is made through the use of high-quality grape variety and yeast strain, and through a unique process. Not only is it rich in nutrients, but also it has a unique taste and a fragrant scent. Brand identification of wine is difficult and complex because of high similarity. In this paper, visible and near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was used to explore the feasibility of wine brand identification. Chilean Aoyo wine (2016 vintage) was selected as the identification brand (negative, 100 samples), and various other brands of wine were used as interference brands (positive, 373 samples). Samples of each type were randomly divided into the calibration, prediction and validation sets. For comparison, the PLS-DA models were established in three independent and two complex wavebands of visible (400 - 780 nm), short-NIR (780 - 1100 nm), long-NIR (1100 - 2498 nm), whole NIR (780 - 2498 nm) and whole scanning (400 - 2498 nm). In independent validation, the five models all achieved good discriminant effects. Among them, the visible region model achieved the best effect. The recognition-accuracy rates in validation of negative, positive and total samples achieved 100%, 95.6% and 97.5%, respectively. The results indicated the feasibility of wine brand identification with Vis-NIR spectroscopy.

Deep belief network-based drug identification using near infrared spectroscopy

Near infrared spectroscopy(NIRS)analysis technology,combined with chemometrics,can be effectively used in quick and nondestructive analysis of quality and category.In this paper,an effective drug identification method by using deep belief network(DBN)with dropout mecha-nism(dropout-DBN)to model NIRS is introduced,in which dropout is employed to overcome the overfitting problem coming from the small sample.This paper tests proposed method under datasets of different sizes with the example of near infrared diffuse refectance spectroscopy of erythromycin ethylsuccinate drugs and other drugs,aluminum and nonaluminum packaged.Meanwhile,it gives experiments to compare the proposed method's performance with back propagation(BP)neural network,support vector machines(SVMs)and sparse denoising auto-encoder(SDAE).The results show that for both binary classification and multi-classification,dropout mechanism can improve the classification accuracy,and dropout-DBN can achieve best classification accuracy in almost all cases.SDAE is similar to dropout-DBN in the aspects of classification accuracy and algorithm stability,which are higher than that of BP neural network and SVM methods.In terms of training time,dropout-DBN model is superior to SDAE model,but inferior to BP neural network and SVM methods.Therefore,dropout-DBN can be used as a modeling tool with effective binary and multi-class classification performance on a spectrum sample set of small size.

The evolving role of Fourier-transform midinfrared spectroscopy in genetic improvement of dairy cattle

Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm collection and processing of samples that assess yield and fat levels in milk,to large-scale processing of samples through centralised laboratories,with the scope extended to include quantification of other traits.Fourier-transform midinfrared(FT-MIR)spectroscopy has had a significant role in the transformation of milk composition phenotyping,with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally.Increasingly,there is interest in analysing the individual FT-MIR wavenumbers,and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs.This includes traits related to the nutritional value of milk,the processability of milk into products such as cheese,and traits relevant to animal health and the environment.The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits,and the genetic correlations between the FT-MIR predicted and actual trait values.Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis.The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes.Additionally,there are other molecular phenotypes such as those related to the metabolome,chromatin accessibility,and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest.Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets,and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

Near-infrared spectroscopy in adult cardiac surgery： between conflicting results and unexpected uses

Neurological complications after cardiac surgery, rang- ing from permanent stroke to transient dysfunction, repre- sent a key issue in the management of geriatric patients. Many patients aged 70 or more have history of neurological dysfunctions, which increases the risk of complications and sequelae, Severe neurologic diseases, such as strokes, occur in up to 6% of patients undergoing cardiac surgery. Therefore, in the setting of fragile patients, prevention is more important than treatment. There are several intraop- erative mechanisms of neurological injury, such as embo- lism, inflammation, intraoperative anemia,

Study on Detection of Pesticide Residues on Winter Jujube Surface by Near-infrared Spectroscopy Combined with PLS and SPA

With fresh winter jujube from the southern region of Xinjiang as the object of study, the method for detecting pesticide residues on winter jujube surface by near-infrared spectroscopy （NIR） combined with successive projections algorithm （SPA） and partial least squares （PLS） was investigated. The absorbance information of winter jujube sample surface was obtained through NIR technology, for the building of a full-wave band PLS model of fresh winter jujube sample sprayed with different concentrations of pesticide （taking chlorpyrifos as an example） as well as an SPA-PLS model which was built with the characteristic wavelengths extracted with SPA as the input variables for PLS, and the prediction precision of the two kinds of models was compared. The model built with the five characteristic waveslengths extected by SPA method only used the variables 0.32% of all the variables in the full wave band, but its accuracy and precision were better than the model built with the full wave band. It is feasible to build a model for different concentrations of chlorpyrifos on fresh winter jujube surfarce by NIR technology combined with SPA and PLS, and SPA method could simplify the complexity of the model and improve the precision and stablity of the model.

Applications of in-situ wide spectral range infrared absorption spectroscopy for CO oxidation over Pd/SiO_(2) and Cu/SiO_(2) catalysts

Infrared(IR)absorption spectroscopy has been widely used for dynamic characterization of catalysts and mechanism of catalytic reactions.However,due to the strong infrared absorption of heterogeneous catalysts(mainly oxides,or supported metal and metal oxides,etc.)below 1200 cm^(-1),and the intensity of regular infrared light source rapidly decays at low-wavenumber range,most in-situ infrared spectroscopy studies are limited to the detection of surface adsorbates in the range of 4000-900 cm^(-1).The change of catalytically active component itself(M-O,M-M bond,etc.,1200-50 cm^(-1))during the reaction is hard to be tracked under reaction conditions by in-situ IR.In this work,a home-made in-situ IR reactor was designed and a sample preparing method was developed.With such progresses,the changes of reactants,products,surface adsorbates,and catalysts themselves can be measured under the same reaction conditions with a spectral range of 4000-400 cm^(-1),providing a new opportunity for in-situ characterization of heterogeneous catalysis.CO oxidation on Pd/SiO_(2) and Cu/SiO_(2) catalysts were taken as examples,since both the two catalytic systems were extensively used commercially,and moreover reduction and oxidation of palladium and copper occur during the examined reaction conditions.The characteristic bands of Pd^(2+)-O(670,608 cm^(-1)),Cu^(+)-O(635 cm^(-1))and Cu^(2+)-O(595,535 cm^(-1))were observed by IR,and the changes during CO oxidation reaction were successfully monitored by IR.The oxidation/reduction of palladium and copper were also confirmed by ex-situ XPS.Moreover,Pd^(0) in Pd/SiO_(2) and Cu^(+)in Cu/SiO_(2) were found as the thermal dynamically stable phases under the examined conditions for CO oxidation.