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A common goal in chemistry is to study the relationship between a measured signal and the variability of certain factors. To this end, researchers often use Design of Experiment to decide which experiments to conduct and (Multiple) Linear Regression, and/or Analysis of Variance to analyze the collected data. Among the assumptions to the very foundation of this strategy, all the experiments are independent, conditional on the settings of the factors. Unfortunately, due to the presence of uncontrollable factors, real-life experiments often deviate from this assumption, making the data analysis results unreliable. In these cases, Mixed-Effects modeling, despite not being widely used in chemometrics, represents a solid data analysis framework to obtain reliable results. Here we provide a tutorial for Linear Mixed-Effects models. We gently introduce the reader to these models by showing some motivating examples. Then, we discuss the theory behind Linear Mixed-Effect models, and we show how to fit these models by making use of real-life data obtained from an exposome study. Throughout the paper we provide R code so that each researcher is able to implement these useful model themselves., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

For solid-state NMR or for unconventional experiments only a very limited number of modern processing and simulation software packages are available. For this reason, we have developed ssNake, an NMR processing program which provides both interactive and script-based processing tools. ssNake is aimed at solid-state NMR experiments, but can also be used for liquid-state experiments. It can read various data formats, including those from all major spectrometer vendors. It has extensive fitting capabilities, which can be used for spectrum deconvolution. ssNake also provides the unique feature of being able to fit multiple spectra (or curves) simultaneously, where some or all of its parameters are shared. This method can be used, for example, to fit quadrupole spectra at various magnetic fields simultaneously. This allows the quadrupole and chemical shift parameters to be accurately determined. ssNake also provides a method of fitting using external simulation programs, such as SIMPSON. This makes fitting very versatile, as it brings together experimental data and simulation software., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Multivariate analyses are increasingly popular to explore the underlying structure of multivariate datasets, which are more and more prevalent in analytical chemistry. However, difficulties can be associated with estimating the number of components for the data with considerable coherence and noise. The method of Angle Distribution of Loading Subspace (ADLS) has been proposed to estimate the number of components for Principal Component Analysis (PCA) and PARAllel FACtor analysis (PARAFAC), which showed some advantages, in particular in the case of datasets with high coherence, over the commonly used methods (scree plot and cross-validation in PCA, and core consistency diagnostics (CORCONDIA) in PARAFAC). In this paper, we systematically improved and applied ADLS to estimate the number of components in different multivariate methods including, Multivariate Curve Resolution (MCR), PARAFAC and four-way PARAFAC. Firstly, we showed that ADLS performed better when estimating the chemical rank for MCR analysis, compared with scree plots. As well as this, we improved ADLS in multi-way analysis (three- and four-way PARAFAC) by calculating the loading subspace in advance using the Khatri-Rao product. The improved ADLS in multi-way analysis provided the correct result for the simulated three-way fluorescence datasets with unevenly distributed coherence at different dimensions, while the previous version of ADLS showed biased results and CORCONDIA / split-half analysis provided relatively unstable results. Moreover, ADLS was used to estimate the chemical rank for a four-way real-life fluorescence dataset analyzed by four-way PARAFAC. In this case the result of chemical rank results from ADLS was more precise and informative compared with CORCONDIA /split-half analysis in four-way analysis., (Copyright © 2018 Elsevier B.V. All rights reserved.)

For quadrupolar spin systems, interpretation of solid state NMR spectra can be hampered by the presence of resonances from both satellite and central transitions. This is particularly true for disordered systems, where many different quadrupolar sites exist, which can have strongly different quadrupolar coupling constants. If second order effects are too strong for obtaining meaningful MAS, MQMAS or STMAS spectra, an approach is needed to successfully separate central and satellite transitions. In this work, we provide a rigorous treatment of 2D quadrupolar nutation NMR for the study of central and satellite transitions in quadrupolar systems. Using this SATURN experiment (SAtellite Transition nUtation of quadRupolar Nuclei) spectral intensity can be assigned to contributions from either central or satellite transitions. We show that the experiment can be applied to any half-integer spin (3/2, 5/2, 7/2 and 9/2), and that spectra can be obtained that closely match simulations. We furthermore show that distributions in quadrupolar parameters do not hamper the assignment of central and satellite transitions from a SATURN experiment., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Principal Component Analysis (PCA) is widely used in analytical chemistry, to reduce the dimensionality of a multivariate data set in a few Principal Components (PCs) that summarize the predominant patterns in the data. An accurate estimate of the number of PCs is indispensable to provide meaningful interpretations and extract useful information. We show how existing estimates for the number of PCs may fall short for datasets with considerable coherence, noise or outlier presence. We present here how Angle Distribution of the Loading Subspaces (ADLS) can be used to estimate the number of PCs based on the variability of loading subspace across bootstrap resamples. Based on comprehensive comparisons with other well-known methods applied on simulated dataset, we show that ADLS (1) may quantify the stability of a PCA model with several numbers of PCs simultaneously; (2) better estimate the appropriate number of PCs when compared with the cross-validation and scree plot methods, specifically for coherent data, and (3) facilitate integrated outlier detection, which we introduce in this manuscript. We, in addition, demonstrate how the analysis of different types of real-life spectroscopic datasets may benefit from these advantages of ADLS., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Owing to the introduction of microcoils, high RF field strength nutation NMR is a viable candidate for the study of quadrupolar nuclei with strong quadrupolar couplings, not accessible using contemporary NMR techniques. We show powder 23 Na nutation spectra on sodium nitrite for RF field strengths of up to 1170kHz, that conform to theoretical predictions. For lanthanum fluoride powder, 139 La nutation spectra taken at elevated RF field amplitudes show clear discrepancies when compared to the theory. These errors are shown to be mainly caused by pulse transients at the end of the pulse, which proved to be detrimental to the shape of the nutation spectra. Using a nutation pulse which ends in a sudden frequency jump, we show that these errors can be reduced, and nutation spectra that conform to theory can be readily acquired. This enables nutation NMR for the study of quadrupolar nuclei with a strong quadrupolar coupling, bridging the gap between NMR, which can only analyse nuclei with a weak to medium quadrupolar coupling, and NQR, were extensive searching for the right quadrupolar frequency is the limiting factor., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Glucosinolates are secondary plant compounds typically found in members of the Brassicaceae and a few other plant families. Usually each plant species contains a specific subset of the ∼ 130 different glucosinolates identified to date. However, intraspecific variation in glucosinolate profiles is commonly found. Sinalbin (4-hydroxybenzyl glucosinolate) so far has been identified as the main glucosinolate of the heavy metal accumulating plant species Noccaea caerulescens (Brassicaceae). However, a screening of 13 N. caerulescens populations revealed that in 10 populations a structurally related glucosinolate was found as the major component. Based on nuclear magnetic resonance (NMR) and mass spectrometry analyses of the intact glucosinolate as well as of the products formed after enzymatic conversion by sulfatase or myrosinase, this compound was identified as 4-α-rhamnosyloxy benzyl glucosinolate (glucomoringin). So far, glucomoringin had only been reported as the main glucosinolate of Moringa spp. (Moringaceae) which are tropical tree species. There was no apparent relation between the level of soil pollution at the location of origin, and the presence of glucomoringin. The isothiocyanate that is formed after conversion of glucomoringin is a potent antimicrobial and antitumor agent. It has yet to be established whether glucomoringin or its breakdown product have an added benefit to the plant in its natural habitat., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

DNA was immobilized on highly oriented pyrolytic graphite (HOPG) surfaces modified in octadecylamine (ODA) vapor. ODA molecules, deposited from the vapor phase onto HOPG form a nanostructured surface, which was utilized as a template for DNA adsorption. Peculiarities of double- and single-stranded DNA adsorption on these surfaces were investigated with atomic force microscopy (AFM) both in air, liquid and under different salt conditions. AFM images of DNA molecules immobilized on octadecylamine modified HOPG reveal a segmented shape of biopolymers: it constitutes straight segments with sharp turns at angles 120 degrees or 60 degrees between them, reflecting the symmetry of the underlying pattern. The analysis of DNA conformations on ODA modified HOPG surface has shown that under certain conditions DNA equilibrates on the surface on the scale of the whole molecule. A persistence length estimate of 97nm was determined for those molecules. Participation of different forces in the ODA pattern driven DNA assembly is discussed.