A new Type of Valence Tautomerism in Cobalt Dioxolene Complexes - Temperature-Induced Transition from a Cobalt(III) Catecholate to a Low-Spin Cobalt(II) Semiquinonate State

The synthesis and characterization of the monocationic cobalt(III) catecholate complex [Co(L-N4 t Bu2)(Cl2cat)]+ (L-N4 t Bu2 = N,N'-Di-tert.-butyl-2,11-diaza[3.3](2,6)pyridinophane, Cl2cat2- = 4,5-dichlorocatecholate) are presented. The complex exhibits valence tautomeric properties in solution; but, in contrast to the usually observed conversion from a cobalt(III) catecholate to a high-spin cobalt(II) semiquinonate state, valence tautomerism of [Co(L-N4 t Bu2)(Cl2cat)]+ leads to the formation of a low-spin cobalt(II) semiquinonate complex upon raising the temperature. This new type of valence tautomerism for a cobalt dioxolene complex has been unambiguously established by a detailed spectroscopic investigation using variable-temperature NMR, IR and UV-Vis-NIR spectroscopy. Determination of the enthalpies and entropies characterizing the valence tautomeric equilibria in various solutions shows that the influence of the solvent is almost exclusively entropic.

Model-based signal tracking in the quantitative analysis of time series of NMR spectra

Hard modeling of NMR spectra by Gauss-Lorentz peak models is an effective way for dimensionality reduction. In this manner high-dimensional measured data are reduced to low-dimensional information as peak centers, amplitudes or peak widths. For time series of spectra these parameters can be assumed to be smooth functions in time. We suggest to model these time-dependent parameter functions by cubic spline functions, which makes a stable quantitative analysis of NMR series possible even for crossing, highly overlapping peaks. Applications are presented for the batch distillation of methanol and diethylamine, and the reaction of acetic anhydride with 2-propanol.

Mechanistic insights into dehydrocoupling of amine boranes using dinuclear zirconocene complexes

Catalytic dehydrocoupling of H₃B·NMe₂H using Cp₂Zr(Cl)(μ-Me₃SiC₃SiMe₃)Zr(Cl)Cp₂ (1)/MeLi was studied. Spectroscopic monitoring and stoichiometric experiments show the formation and interconversion of several catalytically active Zr species.

Insights into the translational and rotational dynamics of cations and anions in protic ionic liquids by means of NMR fast-field-cycling relaxometry

Understanding the translational and rotational dynamics of cations and anions in hydrogen bonded protic ionic liquids (PIls) is still a challenge. In this study, we determine self-diffusion coefficients and rotational correlation times of both ions in triethylammonium based PILs by means of NMR Fast-Field-Cycling (FFC) relaxometry. Global fits of 1H and 19F nuclear magnetic relaxation dispersion (NMRD) curves allowed proper separation into intra and inter molecular relaxation rates for both NMR sensitive nuclei and thus a reliable description of translational and rotational motion for both ions individually. The diffusion coefficients of the cations are in the order of 6 × 10-11 m2 s-1 at room temperature and about 50 per cent larger than those of the anions. The diffusion coefficients of cations and anions in both PILs were compared with those we derived from applying an universal dispersion power law and those known from pulsed field gradient (PFG) NMR studies. Considering the Nernst-Einstein equation, molar conductivities were calculated from cationic and anionic diffusion coefficients and related to directly measured molar conductivities, allowing the determination of the degree of dissociation. The rotational correlation times τR ranging from 50 ps up to 2 ns as a function of temperature were compared with those obtained from high-field NMR quadrupolar relaxation time measurements addressing explicitly the rotation of the NH vector and giving insights into the acidic proton mobility. The Stokes-Einstein and Stokes-Einstein-Debye relations were applied to relate the diffusion coefficients and rotational correlation times to the macroscopic bulk viscosity. The results were also discussed with respect to the archetypical PIL ethylammonium nitrate.

Reaction rate ambiguities for perturbed spectroscopic data: Theory and implementation

The analysis of reaction systems and their kinetic modeling is important for both exploratory research and process design. Multivariate curve resolution (MCR) methods are state-of-the-art tools for the analysis of spectral series, but are also affected by an unavoidable solution ambiguity that impacts the obtained concentration profiles, spectra and model parameters. These uncertainties depend on the underlying model and the magnitude of the measurement perturbations. We present a general theoretical approach together with a computational method for the analysis of the solution ambiguity underlying arbitrary kinetic models. The main idea is to determine all those model parameters for which the corresponding pure component factorizations satisfy all given constraints within small error tolerances. This makes it possible to determine bands of concentration profiles and spectra that reflect the underlying ambiguity and circumscribes the potential reliability of MCR solutions. False conclusions on the uniqueness of a solution can be prevented. The procedure can be applied as a post-processing step to MCR methods as MCR-ALS, ReactLab or others. The Matlab program code is freely accessible and includes not only the proposed ambiguity analysis but also an MCR hard-modeling approach. Application studies are presented for two experimental data sets, namely for UV/Vis spectra on the relaxation of a photoexcited state of benzophenone and for Raman spectra on an aldehyde formation process.

On the analysis of chromatographic biopharmaceutical data by curve resolution techniques in the framework of the area of feasible solutions

Monitoring preparative protein chromatographic steps by in-line spectroscopic tools or fraction analytics results in medium or large sized data matrices. Multivariate Curve Resolution (MCR) serve to compute or to estimate the concentration values of the pure components only from these data matrices. However, MCR methods often suffer from an inherent solution ambiguity which underlies the factorization problem. The typical unimodality of the chromatographic profiles of pure components can support the chemometric analysis. Here we present the pure components estimation process within the framework of the area of feasible solutions, which is a systematic approach to represent the range of all possible solutions. The unimodality constraint in combination with Pareto optimization is shown to be an effective method for the pure component calculation. Applications are presented for chromatograms on a model protein mixture containing ribonuclease A, cytochrome c and lysozyme and on a two-dimensional chromatographic separation of a monoclonal antibody from its aggregate species. The root mean squared errors of the first case study are 0.0373, 0.0529 and 0.0380 g/L compared to traditional off-line analytics. The second case study illustrates the potential of recovering hidden components with MCR from off-line reference analytics.

Facile Synthesis of a Stable Side-on Phosphinyne Complex by Redox Driven Intramolecular Cyclisation

Alkyne complexes with vicinal substitution by a Lewis acid and a Lewis base at the coordinated alkyne are prospective frustrated Lewis pairs exhibiting a particular mutual distance and, hence, a specific activation potential. In this contribution, investigations on the generation of a WII alkyne complex bearing a phosphine as Lewis base and a carbenium group as Lewis acid are presented. Independently on potential substrates added, an intramolecular cyclisation product was always isolated. A subsequent deprotonation step led to an unprecedented side-on λ5 -phosphinyne complex, which is interpreted as highly zwitterionic according to visible absorption spectroscopy supported by TD-DFT. Low-temperature 31 P NMR and EPR spectroscopic measurements combined with time-dependent IR-spectroscopic monitoring provided insights in the mechanism of the cyclisation reaction. Decomposition of the multicomponent IR spectra by multivariate curve resolution and a kinetic hard-modelling approach allowed the derivation of kinetic parameters. Assignment of the individual IR spectra to potential intermediates was provided by DFT calculations.

Unraveling VEALYL Amyloid Formation Using Advanced Vibrational Spectroscopy and Microscopy

Intermediate species are hypothesized to play an important role in the toxicity of amyloid formation, a process associated with many diseases. This process can be monitored with conventional and two-dimensional infrared spectroscopy, vibrational circular dichroism, and optical and electron microscopy. Here, we present how combining these techniques provides insight into the aggregation of the hexapeptide VEALYL (Val-Glu-Ala-Leu-Tyr-Leu), the B-chain residue 12-17 segment of insulin that forms amyloid fibrils (intermolecularly hydrogen-bonded β-sheets) when the pH is lowered below 4. Under such circumstances, the aggregation commences after approximately an hour and continues to develop over a period of weeks. Singular value decompositions of one-dimensional and two-dimensional infrared spectroscopy spectra indicate that intermediate species are formed during the aggregation process. Multivariate curve resolution analyses of the one and two-dimensional infrared spectroscopy data show that the intermediates are more fibrillar and deprotonated than the monomers, whereas they are less ordered than the final fibrillar structure that is slowly formed from the intermediates. A comparison between the vibrational circular dichroism spectra and the scanning transmission electron microscopy and optical microscope images shows that the formation of mature fibrils of VEALYL correlates with the appearance of spherulites that are on the order of several micrometers, which give rise to a "giant" vibrational circular dichroism effect.

Application of a new method for simultaneous phase and baseline correction of NMR signals (SINC)

Recently, we presented a new approach for simultaneous phase and baseline correction of nuclear magnetic resonance (NMR) signals (SINC) that is based on multiobjective optimization. The algorithm can automatically correct large sets of NMR spectra, which are commonly acquired when reactions and processes are monitored with NMR spectroscopy. The aim of the algorithm is to provide spectra that can be evaluated quantitatively, for example, to calculate the composition of a mixture or the extent of reaction. In this work, the SINC algorithm is tested in three different studies. In an in-house comparison study, spectra of different mixtures were corrected both with the SINC method and manually by different experienced users. The study shows that the results of the different users vary significantly and that their average uncertainty of the composition measurement is larger than the uncertainty obtained when the spectra are corrected with the SINC method. By means of a dilution study, we demonstrate that the SINC method is also applicable for the correction of spectra with low signal-to-noise ratio. Furthermore, a large set of NMR spectra that was acquired to follow a reaction was corrected with the SINC method. Even in this system, where the areas of the peaks and their chemical shifts changed during the course of reaction, the SINC method corrected the spectra robustly. The results show that this method is especially suited to correct large sets of NMR spectra and it is thus an important contribution for the automation of the evaluation of NMR spectra.

Photochemical multivariate curve resolution models for the investigation of photochromic systems under continuous irradiation

We propose a multivariate curve resolution approach for the investigation of photochromic systems using UV-Visible spectroscopy. The incorporation of photochemical hard-models as constraints in multivariate curve resolution alternating least squares (MCR-ALS) allows extracting reaction quantum yields in situations where a complete knowledge of the system is not available. We apply this approach to the study of the photochromism of CMTE (cis-1,2-dicyano-1,2-bis(2,4,5-trimethyl-3-thienyl)ethene) under continuous monochromatic irradiation. The mechanism, involving 3 species and 2 reversible reactions, is written and translated into a kinetic constraint that can be applied to the concentration profiles within ALS. First, ambiguity of the solution obtained for photochemical model(s) is calculated and discussed for single set analysis. Multiset analysis is then proposed combining data obtained under different irradiation wavelengths to provide more reliable results. Finally, the photochemical reactivity of CMTE is widely unraveled, and some description of the mechanism observed under irradiation at 365 nm is given.

Multi-objective optimization for an automated and simultaneous phase and baseline correction of NMR spectral data

Spectral data preprocessing is an integral and sometimes inevitable part of chemometric analyses. For Nuclear Magnetic Resonance (NMR) spectra a possible first preprocessing step is a phase correction which is applied to the Fourier transformed free induction decay (FID) signal. This preprocessing step can be followed by a separate baseline correction step. Especially if series of high-resolution spectra are considered, then automated and computationally fast preprocessing routines are desirable. A new method is suggested that applies the phase and the baseline corrections simultaneously in an automated form without manual input, which distinguishes this work from other approaches. The underlying multi-objective optimization or Pareto optimization provides improved results compared to consecutively applied correction steps. The optimization process uses an objective function which applies strong penalty constraints and weaker regularization conditions. The new method includes an approach for the detection of zero baseline regions. The baseline correction uses a modified Whittaker smoother. The functionality of the new method is demonstrated for experimental NMR spectra. The results are verified against gravimetric data. The method is compared to alternative preprocessing tools. Additionally, the simultaneous correction method is compared to a consecutive application of the two correction steps.

A chemometric study in the area of feasible solution of an acid–base titration of N-methyl-6-oxyquinolone

Multivariate curve resolution methods aim at recovering the underlying chemical components from spectroscopic data on chemical reaction systems. In most cases the spectra and concentration profiles of the pure components cannot be uniquely determined from the given spectral data. Instead continua of possible factors exist. This fact is known as rotational ambiguity. The sets of all possible pure component factors can be represented in the so-called area of feasible solutions (AFS). This paper presents an AFS study of the pure component reconstruction problem for a series of UV/Vis spectra taken from an acid–base titration of N-methyl-6-oxyquinolone. Additional information on the equilibrium concentration profiles for a varying acid concentration is taken from fluorescence measurements. On this basis chemometric duality arguments lead to the construction of a unique final solution.

Multivariate curve resolution methods aim at recovering the underlying chemical components from spectroscopic data on chemical reaction systems.

On the ambiguity of the reaction rate constants in multivariate curve resolution for reversible first-order reaction systems

If for a chemical reaction with a known reaction mechanism the concentration profiles are accessible only for certain species, e.g. only for the main product, then often the reaction rate constants cannot uniquely be determined from the concentration data. This is a well-known fact which includes the so-called slow-fast ambiguity. This work combines the question of unique or non-unique reaction rate constants with factor analytic methods of chemometrics. The idea is to reduce the rotational ambiguity of pure component factorizations by considering only those concentration factors which are possible solutions of the kinetic equations for a properly adapted set of reaction rate constants. The resulting set of reaction rate constants corresponds to those solutions of the rate equations which appear as feasible factors in a pure component factorization. The new analysis of the ambiguity of reaction rate constants extends recent research activities on the Area of Feasible Solutions (AFS). The consistency with a given chemical reaction scheme is shown to be a valuable tool in order to reduce the AFS. The new methods are applied to model and experimental data.

Solute-induced perturbation of methanol–water association

Chemometric analysis of the IR and UV-Vis absorbance data revealed the pronounced effect of the stability of the associated methanol–water cluster in mixtures of solvents.