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.

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%.

Infrared Spectroscopy-Based Chemometric Analysis for Lard Differentiation in Meat Samples

One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness.The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary,for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis.Fourier Transform Infrared Spectroscopy(FTIR)is used in this work to identify lard adulteration in cow,lamb,and chicken samples.A simplified extraction method was implied to obtain the lipids from pure and adulterated meat.Adulterated samples were obtained by mixing lard with chicken,lamb,and beef with different concentrations(10%–50%v/v).Principal component analysis(PCA)and partial least square(PLS)were used to develop a calibration model at 800–3500 cm^(−1).Three-dimension PCA was successfully used by dividing the spectrum in three regions to classify lard meat adulteration in chicken,lamb,and beef samples.The corresponding FTIR peaks for the lard have been observed at 1159.6,1743.4,2853.1,and 2922.5 cm−1,which differentiate chicken,lamb,and beef samples.The wavenumbers offer the highest determination coefficient R2 value of 0.846 and lowest root mean square error of calibration(RMSEC)and root mean square error prediction(RMSEP)with an accuracy of 84.6%.Even the tiniest fat adulteration up to 10%can be reliably discovered using this methodology.

Process Characterization of the Transesterification of Rapeseed Oil to Biodiesel Using Design of Experiments and Infrared Spectroscopy

For optimization of production processes and product quality,often knowledge of the factors influencing the process outcome is compulsory.Thus,process analytical technology(PAT)that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality.The present study aims at characterizing a well-known industrial process,the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters(FAME)for usage as biodiesel in a continuous micro reactor set-up.To this end,a design of experiment approach is applied,where the effects of two process factors,the molar ratio and the total flow rate of the reactants,are investigated.The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield.The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression.The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis.A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination(R^(2))of 0.9608.Thus,we applied a PAT approach to generate further insight into this established industrial process.

Room-temperature infrared photodetectors with hybrid structure based on two-dimensional materials

Two-dimensional(2D) materials, such as graphene, transition metal dichalcogenides(TMDs), black phosphorus(BP),and related derivatives, have attracted great attention due to their advantages of flexibility, strong light–matter interaction,broadband absorption, and high carrier mobility, and have become a powerful contender for next-generation infrared photodetectors. However, since the thickness of 2D materials is on the order of nanometers, the absorption of 2D materials is very weak, which limits the detection performance of 2D materials-based infrared photodetectors. In order to solve this problem, scientific researchers have tried to use optimized device structures to combine with 2D materials for improving the performance of infrared photodetectors. In this review, we review the progress of room-temperature infrared photodetectors with hybrid structure based on 2D materials in recent years, focusing mainly on 2D–nD(n = 0, 1, 2) heterostructures, the integration between 2D materials and on-chip or plasmonic structure. Finally, we summarize the current challenges and point out the future development direction.

Analysis of Protein Content in Panicum miliaceum L. Using Near Infrared Transmittance Spectroscopy

[Objective] To explore a method for the rapid determination of protein con- tent in grains of Panicum miliaceum L. [Method] The near infrared transmittance spec- troscopy （NITS） was used to build the mathematical models for the quantitative analy- sis of protein content in the grains. Four combinations of treatment that first derivative and second derivative were respectively combined with partial least squares （PLS） and modified partial least squares （MPLS） were set to compare their effects on the original transmission spectrum. [Result] The predicting effects of the 4 combinations were similar. The optimal combination was first derivative with MPLS, in which the average determination coefficient of validation （RSQ） was 0.880 6, correlation coeffi- cient of cross validation （1-VR） was 0.857 0, standard error of calibration （SEC） was 0.342 4, standard error of cross validation （SECV） was 0.375 1, and the standard er- ror of prediction （SEP） was 0.454. [Conclusion] The constructed NITS model is a rapid way for the determination of protein content in grains of P. miliaceum.

Determination of Melamine by Infrared Spectroscopy Based on Nonlinear Modeling

[Objective] The aim was to develop a nonlinear model of quantitative analysis of melamine content by infrared spectroscopy and provide theoretical basis for the nondestructive detection of melamine. [Method] According to dynamics,mathematical modeling and optimization theory,linear and nonlinear models were respectively set up by taking an absorption peak of 1 550 cm-1 as characteristic absorption peak. [Result] The correlation coefficient of nonlinear model was 0.922 7 and the recovery was 96%,which showed that the nonlinear model was more accurate than linearity model with correlation coefficient of 0.904 9 and recovery of 557%. [Conclusion] It is feasible to determine melamine content by using the nonlinear model quantitatively.

Study on Methanol Oxidation at Pt and PtRu Electrodes by Combining in situ Infrared Spectroscopy and Differential Electrochemical Mass Spectrometry

Methanol oxidation reaction （MOR） at Pt and Pt electrode surface deposited with various amounts of Ru （denoted as PtxRuy, nominal coverage y is 0.17, 0.27, and 0.44 ML） in 0.1 mol/L HClO4＋0.5 mol/L MeOH has been studied under potentiostatic conditions by in situ FTIR spectroscopy in attenuated-total-reflection con guration and di erential electro-chemical mass spectrometry under controlled flow conditions. Results reveal that （i） CO is the only methanol-related adsorbate observed by IR spectroscopy at all the Pt and PtRu electrodes examined at potentials from 0.3 V to 0.6 V （vs. RHE）; （ii） at Pt0.56Ru0.44, two IR bands, one from CO adsorbed at Ru islands and the other from COL at Pt substrate are detected, while at other electrodes, only a single band for COL adsorbed at Pt is observed; （iii） MOR activity decreases in the order of Pt0.73Ru0.27〉Pt0.56Ru0.44〉Pt0.83Ru0.17〉Pt; （iv） at 0.5 V, MOR at Pt0.73Ru0.27 reaches a current e ciency of 50% for CO2 production, the turn-over frequency from CH3OH to CO2 is ca. 0.1 molecule/（site sec）. Suggestions for further improving of PtRu catalysts for MOR are provided.

Experimental Consideration of Two-Dimensional Fourier Transform Spectroscopy

Two-dimensional Fourier transform(2D FT) spectroscopy is an important technology that developed in recent decades and has many advantages over other ultrafast spectroscopy methods. Although 2D FT spectroscopy provides great opportunities for studying various complex systems, the experimental implementation and theoretical description of 2D FT spectroscopy measurement still face many challenges, which limits their wide application.Recently, the 2D FT spectroscopy reaches maturity due to many new developments which greatly reduces the technical barrier in the experimental implementation of the 2D FT spectrometer. There have been several different approaches developed for the optical design of the 2D FT spectrometer, each with its own advantages and limitations. Thus, a procedure to help an experimentalist to build a 2D FT spectroscopy experimental apparatus is needed.This tutorial review is intending to provide an accessible introduction for a beginner to build a 2D FT spectrometer.

Detection of Broad Bean Diseases by Fourier Transform Infrared Spectroscopy Combined with Curve Fitting

Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made up of the vibrational absorption bands of protein,lipid and polysaccharide.There were minor differences in-cluding the spectral peak position, peak shape and the absorption intensity in the range of 1 800-1 300 cm-1. There were obvious differences among their second derivative spectra in the range of 1 800-1 300 cm-1. After the procedure of the Fourier self-deconvolution and curve fitting of health bean leaves and broad bean diseased leaves in the range of 1 700-1 500 cm-1, three sub-peaks were obtained at 1 550 cm-1 （protein amide Ⅱ band）, 1 605 cm-1 （lignin） and 1 650 cm-1 （protein amide I band）.The ratios of relative areas of the bands of amide Ⅱ, lignin, and amide I were 38.86%, 28.68% and 32.47% in the spectra of healthy leaves, respec-tively. It was distinguished from the diseased leaves （chocolate spot leaf： 15.42%, 42.98% and 41.61%, ring spot leaf：32.39%, 35.63% and 31.98%, rust leaf： 13.97%, 46.40% and 39.65%, yel owing leaf curl disease leaf： 24.01%,36.55% and 39.44%）. For sub-peak area ratios （A1 563/A1 605, A1 650/A1 605 and A1 563/A1 654）, those of four kinds of diseased leaves were smal er than that of healthy leaves, and there were also differences among four kinds of diseased leaves. The results proved that FTIR combining with curve fitting might be a potential y useful tool for detecting different kinds of broad bean diseases.

Two-dimensional ATR-FTIR Spectroscopic Study on the Water Diffusion Behavior in Polyimide/Silica Nanocomposite

To consider the reliability and performance of electronic devices based on polyimide derivatives, dynamic water sorption and diffusion behavior in a polyimide derivative： poly（4＇4 oxydiphenylene pyromellitimide） （PMDA-ODA）/silica nanocomposite was investigated by two-dimensional ATR-FTIR spectroscopy, by which three states of water molecules owning different H-bonding strength were distinguished. The amounts and strength of H-bonding also played a significant role in determining the diffusion rate of the different states of water molecules. The type of aggregated water molecules which also formed H-bonding with silicic acid （residues） or polyimide system was the last one diffusing to the polymer side in contact with the ATR crystal element because the polymeric matrix blocked their diffusion to a great extent. The diffusion coefficient was also estimated to gain the information of the dynamic diffusion behavior.

Rapid Detection on Quinoa Fiber Based on Near Infrared Spectroscopy

[Objective] To explore a rapid determination method for fiber content in grains of quinoa. [Method] Near infrared spectra of 100 quinoa samples were collected. The predicted models for quantitative analysis of fiber contents in the grains were built using near infrared transmittance spectroscopy （NITS）. [Result] In the wavelength range of 10 000-4 000 cm-1, the near infrared quantitative model of quinoa crude fiber was set up via first derivative ＋ vector normalization preprocessing and combining with the data from chemical methods. The calibration and prediction effect were best, and then the cross validation determination coefficient （FFcv） and external validation determination coefficient （FFval） of fiber by near in- frared quantitative model were 0.884 8 and 0.876 1, respectively. [Conclusion] the model of NITS about complete grains quinoa fiber can be available for fast detecting quinoa fiber content.

Advancing Hierarchical Equations of Motion for Efficient Evaluation of Coherent Two-dimensional Spectroscopy

To advance hierarchical equations of motion as a standard theory for quantum dissipative dynamics, we put forward a mixed Heisenberg-SchrSdinger scheme with block-matrix implementation on efficient evaluation of nonlinear optical response function. The new approach is also integrated with optimized hierarchical theory and numerical filtering algorithm. Different configurations of coherent two-dimensional spectroscopy of model excitonic dimer systems are investigated, with focusing on the effects of intermolecular transfer coupling and bi-exciton interaction.

Recognition of wood surface defects with near infrared spectroscopy and machine vision

To improve the accuracy in recognizing defects on wood surfaces,a method fusing near infrared spectroscopy(NIR)and machine vision was examined.Larix gmelinii was selected as the raw material,and the experiments focused on the ability of the model to sort defects into four types:live knots,dead knots,pinholes,and cracks.Sample images were taken using an industrial camera,and a morphological algorithm was applied to locate the position of the defects.A portable near infrared spectrometer(900–1800 nm)collected the spectra of these positions.In addition,principal component analysis was utilized on these variables from spectral information and principal component vectors were extracted as the inputs of the model.The results show that a back propagation neural network model exhibited better discrimination accuracy of 92.7%for the training set and 92.0%for the test set.The research reveals that the NIR fusing machine vision is a feasible tool for detecting defects on board surfaces.

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.

Infrared Spectroscopic Study of Fistular Onion (Allium fistulosum) and Garlic (Allium sativum) Rust Leaves

[ Objective] Fourier transform infrared spectroscopy was used to study fistular onion （Alliumfistulosum） and garlic （Allium sativum） rust leaves, so as to explore the application potential of mid-infrared spectroscopy in the diagnosis of crop disease. [ Method] The normal green leaves and rust leaves of fistular onion and garlic were tested using fourier transform infrared spectroscopy, and their spectral differences were analyzed. [ Result] The infrared spectra of green leaves of fistular onion and garlic are mainly composed of the vibrational bands of polysaccharides, protein and ester. Normal and rust leaves exhibited differences in the fin- gerprint interval of 1 800 -900 cm-1 , in which the band at 1 640 cm-1 in the spectrum of flstular onion rust leaf became stronger, and the band at 1 103 cm-1 was not obvious compared with the spectrum of normal leaf. The absorbance ratios A1640/A1063, A1640/A1736, A1640/A2924, and A1063/A2924 of onion rust leaf were larger than the corresponding ratios A1638/A1 059, A1738/A1 38, A2921/A1638, and A2 92l/A1059 in the spectrum of normal leaf. The band of polysaccharides at 1 056 cm-1 in the spectrmn of garlic normal leaf was the strongest in fingerprint area, while the band at 1 634 cm-1 in the spectrum of garlic rust leaf was the strongest in that are- a. The absorbance ratios A1634/A1069 , A1634/A1099 , A1409/A2923 , and A1634/A737 of garlic rust leaf were larger than the corresponding ratios A1627/A1056 , A1623/A1104 , A1411/A2920 and A1627/A1740 of normal leaves. While the ratios A1634/A2923, A1059/A2923, and A1737/A2923 of garlic rust leaf were less than the corresponding values of A1627/A2920, A1056/A2920, and A1 740/A2920 of normal leaf. [ Conclusion] Rust leaf and normal leaf could be distinguished according to the differences in infrared spectra, and infrared spectroscopy could be developed as the detection method for crop diseases.

Structural and Infrared Spectroscopic Study on Solvation of Acetylene by Protonated Water Molecules

The effect of solvation on the conformation of acetylene has been studied by adding one water molecule at a time. Quantum chemical calculations of the n＋ （C2H2）（H2O）n （n=1-5） clusters indicate that the H2O molecules prefer to form the OH...Tr interaction rather than the CH...O interaction. This solvation motif is different from that of neutral （C2H2）（H2O）n （n=1-4） clusters, in which the H2O molecules prefer to form the CH...O and OH...C Hbonds. For the H＋（C2H2）（H2O）n cationic clusters, the first solvation shell consists of one ring structure with two OH...Tr H-bonds and three water molecules, which is completed at n=4. Simulated infrared spectra reveal that vibrational frequencies of OH... H-bonded O-H stretching afford a sensitive probe for exploring the solvation of acetylene by protonated water molecules. Infrared spectra of the H＋ （C2H2）（H2O）n （n=1-5） clusters could be readily measured by the infrared photodissociation technique and thus provide useful information for the understanding of solvation processes.