A preliminary study of soft cheese degradation in different packaging conditions by 1H-NMR

This preliminary work deals with the influence of packaging on the degradation of an Italian soft cheese studied by NMR. The NMR profiles of aqueous cheese extracts were acquired as a function of time during storage of cheese inside and outside the original package. From the NMR spectra 15 metabolites are quantified and used in a kinetic degradation model and in a multivariate algorithm in order to evaluate the changes in the metabolic composition of cheese stored under different conditions.     

FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Transmission and transflection infrared microscopy of biological cells and tissue suffer from significant baseline distortions due to scattering effects, predominantly resonant Mie scattering (RMieS). This scattering can also distort peak shapes and apparent peak positions making interpretation difficult and often unreliable. A correction algorithm, the resonant Mie scattering extended multiplicative signal correction (RMieS-EMSC), has been developed that can be used to remove these distortions. The correction algorithm has two key user defined parameters that influence the accuracy of the correction. The first is the number of iterations used to obtain the best outcome. The second is the choice of the initial reference spectrum required for the fitting procedure. The choice of these parameters influences computational time. This is not a major concern when correcting individual spectra or small data sets of a few hundred spectra but becomes much more significant when correcting spectra from infrared images obtained using large focal plane array detectors which may contain tens of thousands of spectra. In this paper we show that, classification of images from tissue can be achieved easily with a few (<10) iterations but a reliable interpretation of the biochemical differences between classes could require more iterations. Regarding the choice of reference spectrum, it is apparent that the more similar it is to the pure absorption spectrum of the sample, the fewer iterations required to obtain an accurate corrected spectrum. Importantly however, we show that using three different non-ideal reference spectra, the same unique correction solution can be obtained.     

A robust,general automatic phase correction algorithm for high‐resolution NMR data

The trends towards rapid NMR data acquisition, automated NMR spectrum analysis, and data processing and analysis by more naïve users combine to place a higher burden on data processing software to automatically process these data. Downstream data analysis is compromised by poor processing, and the automated processing algorithms must therefore be robust and accurate. We describe a new algorithm for automatic phase correction of frequency‐domain, high‐resolution NMR spectra. We show this to be reliable for data derived from a wide variety of typical NMR usages. We therefore conclude that the method will have wide‐spread applicability and a positive impact on automated spectral processing and analysis. Copyright © 2017 John Wiley & Sons, Ltd.     

AlON尖晶石微结构的固体NMR研究

γ-Al₂O₃为低温型晶体,是尖晶石型结构,n(O)∶n(Al³⁺)为1∶2,在氧化气氛下升温至950～1000℃时,则向α-Al₂O₃转变.α-Al₂O₃中氧原子呈六方密堆积,Al³⁺离子仅占据氧八面体空隙.     

Efficient removal of unwanted signals in NMR spectra using the filter diagonalization method

It is often desirable to selectively remove corrupting or uninteresting signals from complex NMR spectra without disturbing overlapping or nearby signals. For biofluids in particular, removal of solvent and urea signals is important for retaining quantitative accuracy in NMR‐based metabonomics. This article presents a novel algorithm for efficient filtering of unwanted signals using the filter diagonalization method (FDM). Unwanted signals are modeled in the time domain using FDM. This modeled signal is subtracted from the original free induction decay. The resulting corrected signal is then processed using established workflow. The algorithm is found to be reliable and fast. By eliminating large, broad, uninteresting signals, many spectra can be subjected to fully automated absolute value processing, allowing objective preparation of spectra for pattern recognition analysis. Copyright © 2009 John Wiley & Sons, Ltd.     

Proof of principle of a generalized fuzzy Hough transform approach to peak alignment of one-dimensional <Superscript>1</Superscript>H NMR data

In metabolic profiling, multivariate data analysis techniques are used to interpret one-dimensional (1D) ¹H NMR data. Multivariate data analysis techniques require that peaks are characterised by the same variables in every spectrum. This location constraint is essential for correct comparison of the intensities of several NMR spectra. However, variations in physicochemical factors can cause the locations of the peaks to shift. The location prerequisite may thus not be met, and so, to solve this problem, alignment methods have been developed. However, current state-of-the-art algorithms for data alignment cannot resolve the inherent problems encountered when analysing NMR data of biological origin, because they are unable to align peaks when the spatial order of the peaks changes—a commonly occurring phenomenon. In this paper a new algorithm is proposed, based on the Hough transform operating on an image representation of the NMR dataset that is capable of correctly aligning peaks when existing methods fail. The proposed algorithm was compared with current state-of-the-art algorithms operating on a selected plasma dataset to demonstrate its potential. A urine dataset was also processed using the algorithm as a further demonstration. The method is capable of successfully aligning the plasma data but further development is needed to address more challenging applications, for example urine data. Figure Traces of NMR peaks visualizing the Generalized Fuzzy Hough Transform (GFHT) method for elucidating peak correspondence between samples. The spectra are sorted according to one shift sensitive peak and reveals that other peaks exhibit a similar shift pattern. This pattern(s) can now be searched for using the GFHT. The red and black spectra in the figure are the most shifting spectra (top and bottom), by following the GFHT traces peak correspondence is easily established although peaks change spatial location Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Automatic phase correction of 2D NMR spectra by a whitening method

A new method for the automatic phase correction of multidimensional NMR spectra is described. It is based on the whitening concept formulated as the ‘maximization of the number of white pixels into a bitmap that corresponds to the spectrum’. This process of maximization can be factorized along the individual axes of the spectrum and this property makes the method robust and fast. It employs a statistic measure based on a large number of spectral data points and, for this reason, is very tolerant to low signal‐to‐noise ratio (SNR) and local artifacts. The algorithm can efficiently phase either homonuclear or heteronuclear experiments and, unlike other previous methods, it can also process automatically spectra containing positive or negative peaks so that it is not necessary to deal with individual or special cases Copyright © 2009 John Wiley & Sons, Ltd.     

Beam search for peak alignment of NMR signals

Recent work by Forshed et al. [Anal. Chim. Acta 487 (2003) 189] resulted in an important tool for aligning two NMR spectra. The recognition that the problem posed by Forshed et al. is separable results in fast heuristics that give results that are at least as good as the in an order of magnitude less time. A beam search algorithm is described along with experiments using two different NMR spectrometers and sets of subjects.     

Critical comments on accuracy of quantitative determination of natural humic matter by solid state (13)C NMR spectroscopy

Structural information of natural organic matter (NOM) at the molecular level is very essential in understanding their nature and reactivity. Nuclear magnetic resonance (NMR) is an excellent tool for estimating the gross chemical composition of the very complex humic matter (HM). A well-known fact is that the solid state ¹³C NMR spectral analysis is very parameter-sensitive especially in the study of the heterogenous HM (e.g. baseline corrections, different pulse techniques and spinning rates of the rotor vs. different disruptive sidebands in the spectra). This being the case, it has been emphasized the importance of qualitative and quantitative analyses for generating as real spectra as possible by means of different pulse and polarization techniques, sampling spinning rates as well as certain correction factors. In the present study a practical accuracy for quantitative determination of NOM type material by solid state ¹³C NMR spectroscopy was assessed using a known HM sample. Different magnetic-field strengths, sampling spinning rates, single and ramped amplitude cross polarization techniques and TOSS pulse sequence were applied for obtaining a more reliable insight into the disruptive effect of the chemical shift anisotropy (CSA), especially the most disturbing first order spinning side bands (SSB). The results demonstrated that the SSB problem is not so significant as sometimes stated, at least in the context of HM samples and in the light of the overall reproducibility and uncertainty connected with the sample itself.     

Direct orthogonal signal correction as data pretreatment in the classification of clinical lots of creams from near infrared spectroscopy data

Direct orthogonal signal correction (DOSC) is applied to correct for major variance sources such as temperature effects, time influences and instrumental differences in near infrared (NIR) data. The samples analysed are creams containing different concentrations of an active drug. The final aim is to classify the samples according to their concentration of active compound. Having performed DOSC on the data, it is not necessary anymore to apply sophisticated chemometric techniques to correct for temperature or time effects and to attribute the samples to their respective concentration classes. Moreover, the application of DOSC on the NIR spectra recorded on two different instruments shows that this method can be considered as a valuable alternative for the standardisation in classification applications. Since the applied algorithm tends to overfit, in a second part of this paper, a comparison is made with an algorithm designed by Westerhuis, which should overcome this problem. Although the calibration set results show that the overfitting has been partially corrected for by the latter algorithm, the test set results did not improve significantly.     

Partial‐Homogeneity‐Based Two‐Dimensional High‐Resolution Nuclear Magnetic Resonance Spectroscopy under Inhomogeneous Magnetic Fields

High‐resolution multidimensional nuclear magnetic resonance (NMR) spectroscopy serves as an irreplaceable and versatile tool in various chemical investigations. In this study, a method based on the concept of partial homogeneity is developed to offer two‐dimensional (2D) high‐resolution NMR spectra under inhomogeneous fields. Oscillating gradients are exerted to encode the high‐resolution information, and a field‐inhomogeneity correction algorithm based on pattern recognition is designed to recover high‐resolution spectra. Under fields where inhomogeneity primarily distributes along a single orientation, the proposed method will improve performances of 2D NMR spectroscopy without increasing the experimental duration or significant loss in sensitivity, and thus may open important perspectives for studies of inhomogeneous chemical systems.     

Automated structure verification based on 1H NMR prediction

A unique opportunity exists when an experimental NMR spectrum is obtained for which a specific chemical structure is anticipated. A process of Verification--the confirmation of a postulated structure--is now possible, as opposed to Elucidation-the de novo determination of a structure. A method for automated structure verification is suggested, which compares the chemical shifts, intensities and multiplicities of signals in an experimental 1H NMR spectrum with those from a predicted spectrum for the proposed structure. A match factor (MF) is produced and used to classify the spectrum-structure match into one of three categories, correct, ambiguous, or incorrect. The verification result is also augmented by the spectrum assignment obtained as part of the verification process. This method was tested on a set of synthetic spectra and several sets of experimental spectra, all of which were automatically prepared from raw data. Taking into account even the most problematic structures, with many labile protons present and poor prediction accuracy, 50% of all spectra can still be automatically verified without any false positives or negatives. In a blind test on a typical set of data, it is shown that fewer than 31% of the structures would need manual evaluation. This means that a system is possible whereby 69% of the spectra are prepared and evaluated automatically, and never need to be seen or evaluated by a human.     

Factor analysis of 27Al MAS NMR spectra for identifying nanocrystalline phases in amorphous geopolymers

Nanostructured materials offer enhanced physicochemical properties because of the large interfacial area. Typically, geopolymers with specifically synthesized nanosized zeolites are a promising material for the sorption of pollutants. The structural characterization of these aluminosilicates, however, continues to be a challenge. To circumvent complications resulting from the amorphous character of the aluminosilicate matrix and from the low concentrations of nanosized crystallites, we have proposed a procedure based on factor analysis of ²⁷Al MAS NMR spectra. The capability of the proposed method was tested on geopolymers that exhibited various tendencies to crystallize (i) completely amorphous systems, (ii) X‐ray amorphous systems with nanocrystalline phases, and (iii) highly crystalline systems. Although the recorded ²⁷Al MAS NMR spectra did not show visible differences between the amorphous systems (i) and the geopolymers with the nanocrystalline phase (ii), the applied factor analysis unambiguously distinguished these materials. The samples were separated into the well‐defined clusters, and the systems with the evolving crystalline phase were identified even before any crystalline fraction was detected by X‐ray powder diffraction. Reliability of the proposed procedure was verified by comparing it with ²⁹Si MAS NMR spectra. Factor analysis of ²⁷Al MAS NMR spectra thus has the ability to reveal spectroscopic features corresponding to the nanocrystalline phases. Because the measurement time of ²⁷Al MAS NMR spectra is significantly shorter than that of ²⁹Si MAS NMR data, the proposed procedure is particularly suitable for the analysis of large sets of specifically synthesized geopolymers in which the formation of the limited fractions of nanocrystalline phases is desired. Copyright © 2013 John Wiley & Sons, Ltd.     

Precise Molecular Weight Determination and Structure Characterization of End-functionalized Polymers: An NMR Approach via Combination of One-dimensional and Two-dimensional Techniques

We present here the application of one-dimensional and two-dimensional NMR techniques to characterize the structure of methoxyl end-functionalized polystyrenes (PS).The peaks in 1H-NMR spectra corresponding to main-chain,side-chain and chain-end groups are assigned by 1H-1H gCOSY,1H-13C gHSQC and gHMBC spectra.For the first time,the spin-lattice relaxation time (T1) of protons of the chain-ends is revealed to be affected more by polymer molecular weight (MW) than by the protons of the main-chains and the side-chains (almost independent from MW).As a result,a much higher delay time (d1) for chain-ends (d1 ＞ 20T1) is needed for quantitative NMR measurement when using end-group estimation method to obtain the MW of PS,which is in accordance with the value estimated by GPC.An improved method for the polymer MW determination is established,by combination of different NMR techniques to distinguish the peaks,and a large dl setting to achieve quantitative NMR analysis.     

Assessing 2D electrophoretic mobility spectroscopy (2D MOSY) for analytical applications

Electrophoretic displacement of charged entity phase modulates the spectrum acquired in electrophoretic NMR experiments, and this modulation can be presented via 2D FT as 2D mobility spectroscopy (MOSY) spectra. We compare in various mixed solutions the chemical selectivity provided by 2D MOSY spectra with that provided by 2D diffusion‐ordered spectroscopy (DOSY) spectra and demonstrate, under the conditions explored, a superior performance of the former method. 2D MOSY compares also favourably with closely related LC‐NMR methods. The shape of 2D MOSY spectra in complex mixtures is strongly modulated by the pH of the sample, a feature that has potential for areas such as in drug discovery and metabolomics. Copyright © 2016 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.     

High-resolution magic-angle spinning NMR for the identification of reaction products directly from thin-layer chromatography spots

We have investigated the prospect of identifying organic reaction products directly from separated thin-layer chromatography (TLC) spots with high-resolution magic-angle spinning (HRMAS) NMR. The concept is to use the TLC spots for NMR analysis so that spectra can be obtained before the reaction is worked up, but without having to elute the product from the TLC stationary phase. Thus, the separated spot is scraped from the plate, transferred to an HRMAS sample rotor, and suspended with a deuterated solvent. Herein, we describe the effects of having the stationary phase present during NMR acquisition. Using a Varian 4 mm gHX Nanoprobe and rotenone as a test compound, we found that the presence of the stationary phase during NMR acquisition resulted in (i) a large, broad 'background' signal near 4.6 ppm and (ii) a decrease in the signal-to-noise ratio due to the adsorption of the product molecules to the adsorbent. However, both effects could be adequately and conveniently eliminated. The background signal was removed by using either a CPMG pulse sequence or chemical exchange. The adsorption was avoided by using a more polar solvent system. Finally, we found that spectra with good signal-to-noise ratio and resolution could be acquired in a matter of minutes even for cases of limited product concentration. Therefore, we believe the technique has value and provides the organic chemist with another option to obtain NMR data critical for structural elucidation or verification.     

Pure Isotropic Proton NMR Spectra in Solids using Deep Learning

The resolution of proton solid-state NMR spectra is usually limited by broadening arising from dipolar interactions between spins. Magic-angle spinning alleviates this broadening by inducing coherent averaging. However, even the highest spinning rates experimentally accessible today are not able to completely remove dipolar interactions. Here, we introduce a deep learning approach to determine pure isotropic proton spectra from a two-dimensional set of magic-angle spinning spectra acquired at different spinning rates. Applying the model to 8 organic solids yields high-resolution ¹H solid-state NMR spectra with isotropic linewidths in the 50–400 Hz range.     

High-resolution NMR spectra of n-alkanes penetrating into carbon fibers and of protons in carbon fibers

We present a simple NMR method for microscopically exploring the local environment in carbon fibers. The method utilizes n-alkanes as probe molecules, where the n-alkanes penetrate carbon fibers of interest. The high-resolution (1)H NMR spectra for a mixture of a carbon fiber and n-alkanes acquired by this method show a shift of the resonance line, which is due to the local structure of the fiber. The utility of this method is discussed on the basis of the (1)H NMR spectra obtained. In addition, the (1)H distribution and the local motion in the structure of the carbon fiber are revealed in view of the (1)H NMR spectra.     

Study on Nuclear Magnetic Resonance Logging T2 Spectrum Shape Correction of Sandstone Reservoirs in Oil-Based Mud Wells

The oil-based mud filtrate will invade the formation under the overbalanced pressure during drilling operations. As a result, alterations will occur to the nuclear magnetic resonance (NMR) response characteristics of the original formation, causing the relaxation time of the NMR T₂ spectrum of the free fluid part to move towards a slower relaxation time. Consequently, the subsequent interpretation and petrophysical evaluation will be heavily impacted. Therefore, the actual measured T₂ spectrum needs to be corrected for invasion. For this reason, considering the low-porosity and low-permeability of sandstone gas formations in the East China Sea as the research object, a new method to correct the incorrect shape of the NMR logging T₂ spectrum was proposed in three main steps. First, the differences in the morphology of the NMR logging T₂ spectrum between oil-based mud wells and water-based mud wells in adjacent wells were analyzed based on the NMR relaxation mechanism. Second, rocks were divided into four categories according to the pore structure, and the NMR logging T₂ spectrum was extracted using the multidimensional matrix method to establish the T₂ spectrum of water-based mud wells and oil-based mud wells. Finally, the correctness of the method was verified by two T₂ spectrum correction examples of oil-based mud wells in the study area. The results show that the corrected NMR T₂ spectrum eliminates the influence of oil-based mud filtrate and improves the accuracy of NMR logging for calculating permeability.     

17O NMR investigation of phosphite hydrolysis mechanisms

The use of solution 17O NMR spectroscopy in verifying the mechanism of trialkyl phosphite hydrolysis is presented. Trimethyl phosphite was reacted with 17O-labeled H2O at different temperatures and two reactant concentrations, with the reaction being monitored by 17O NMR. Kinetic details elucidated from the NMR spectra are also discussed.