Batch process monitoring using on-line MIR spectroscopy

Many high quality products are produced in a batch wise manner. One of the characteristics of a batch process is the recipe driven nature. By repeating the recipe in an identical manner a desired end-product is obtained. However, in spite of repeating the recipe in an identical manner, process differences occur. These differences can be caused by a change of feed stock supplier or impurities in the process. Because of this, differences might occur in the end-product quality or unsafe process situations arise. Therefore, the need to monitor an industrial batch process exists. An industrial process is usually monitored by process measurements such as pressures and temperatures. Nowadays, due to technical developments, spectroscopy is more and more used for process monitoring. Spectroscopic measurements have the advantage of giving a direct chemical insight in the process. Multivariate statistical process control (MSPC) is a statistical way of monitoring the behaviour of a process. Combining spectroscopic measurements with MSPC will notice process perturbations or process deviations from normal operating conditions in a very simple manner. In the following an application is given of batch process monitoring. It is shown how a calibration model is developed and used with the principles of MSPC. Statistical control charts are developed and used to detect batches with a process upset.     

Subpicosecond hard x-ray streak camera using single-photon counting

We have developed and characterized a hard x-ray accumulating streak camera that achieves subpicosecond time resolution by using single-photon counting. A high repetition rate of 2 kHz was achieved by use of a readout camera with built-in image processing capabilities. The effects of sweep jitter were removed by using a UV timing reference. The use of single-photon counting allows the camera to reach a high quantum efficiency by not limiting the divergence of the photoelectrons.     

An online nano‐LC‐ESI‐FTICR‐MS method for comprehensive characterization of endogenous fragments from amyloid β and amyloid precursor protein in human and cat cerebrospinal fluid

Amyloid precursor protein (APP) is the precursor protein to amyloid β (Aβ), the main constituent of senile plaques in Alzheimer's disease (AD). Endogenous Aβ peptides reflect the APP processing, and greater knowledge of different APP degradation pathways is important to understand the mechanism underlying AD pathology. When one analyzes longer Aβ peptides by low‐energy collision‐induced dissociation tandem mass spectrometry (MS/MS), mainly long b‐fragments are observed, limiting the possibility to determine variations such as amino acid variants or post‐translational modifications (PTMs) within the N‐terminal half of the peptide. However, by using electron capture dissociation (ECD), we obtained a more comprehensive sequence coverage for several APP/Aβ peptide species, thus enabling a deeper characterization of possible variants and PTMs. Abnormal APP/Aβ processing has also been described in the lysosomal storage disease Niemann–Pick type C and the major large animal used for studying this disease is cat. By ECD MS/MS, a substitution of Asp7 → Glu in cat Aβ was identified. Further, sialylated core 1 like O‐glycans at Tyr10, recently discovered in human Aβ (a previously unknown glycosylation type), were identified also in cat cerebrospinal fluid (CSF). It is therefore likely that this unusual type of glycosylation is common for (at least) species belonging to the magnorder Boreoeutheria. We here describe a detailed characterization of endogenous APP/Aβ peptide species in CSF by using an online top‐down MS‐based method. Copyright © 2012 John Wiley & Sons, Ltd.     

Weight diagrams for lie group representations: A computer implementation of Freudenthal's algorithm in ALGOL and FORTRAN

Implementations in FORTRAN and ALGOL of the Dynkin and Freudenthal algorithms for computing weight systems and for determining the multiplicities of the weights for irreducible representations of simple Lie algebras are described. Reasonable computing times are found for algebras of rank less than or equal to 8 and for representations of dimension less than 1000.     

Electrospray ionization ion-trap multiple-stage mass spectrometry of Quillaja saponins

Fifteen identified C-18 fatty acyl-containing saponin structures from Quillaja saponaria Molina have been investigated by electrospray ionization ion-trap multiple-stage mass spectrometry (ESI-IT-MS(n)) in positive ion mode. Their MS(1)-MS(3) spectra were analyzed and ions corresponding to useful fragments, important for the structural identification of Quillaja saponins, were recognized. A few key fragments could describe the structural variations in the C-3 and the C-28 oligosaccharides of the Quillaja saponins. A flowchart involving a stepwise procedure based on key fragments from the MS(1)-MS(3) spectra of these saponins, together with key fragments from these saponins and 13 previously investigated saponins, was constructed for the identification of structural elements in Quillaja saponins. Peak intensity ratios in MS(3) spectra were found to be correlated to structural features of the investigated saponins and is therefore of value for the identification of regioisomers.     

Calculations of solute and solvent entropies from molecular dynamics simulations

The translational, rotational and conformational (vibrational) entropy contributions to ligand-receptor binding free energies are analyzed within the standard formulation of statistical thermodynamics. It is shown that the partitioning of the binding entropy into different components is to some extent arbitrary, but an appropriate method to calculate both translational and rotational entropy contributions to noncovalent association is by estimating the configurational volumes of the ligand in the bound and free states. Different approaches to calculating solute entropies using free energy perturbation calculations, configurational volumes based on root-mean-square fluctuations and covariance matrix based quasiharmonic analysis are illustrated for some simple molecular systems. Numerical examples for the different contributions demonstrate that theoretically derived results are well reproduced by the approximations. Calculation of solvent entropies, either using total potential energy averages or van't Hoff plots, are carried out for the case of ion solvation in water. Although convergence problems will persist for large and complex simulation systems, good agreement with experiment is obtained here for relative and absolute ion hydration entropies. We also outline how solvent and solute entropic contributions are taken into account in empirical binding free energy calculations using the linear interaction energy method. In particular it is shown that empirical scaling of the nonpolar intermolecular ligand interaction energy effectively takes into account size dependent contributions to the binding free energy.     

Investigation of the formation process of MCs+-molecular ions during sputtering

In secondary ion mass spectrometry, the detection of MCs+ clusters (with M an element of the specimen) under a Cs bombardment is frequently used for the quantification of major elements. Despite some very good results obtained by this method, some problems still remain. In order to gain some more insight into these problems, the formation mechanism of the MCs+ clusters is investigated using a Monte Carlo model. It is shown that the majority of the constituent particles of the formed clusters are initially first or second neighbor atoms at the surface and that the velocity distribution of the MCs+ clusters becomes broader and peaked at higher velocities with increasing surface binding energy of the M atom. In addition, it is demonstrated that the interaction potential between the M and Cs+ particle has no influence on the velocity distribution of the MCs+ clusters. On the other hand, the cluster formation probability, defined as the probability that a sputtered M and Cs+ particle will form a MCs+ cluster, is extremely sensitive to this interaction potential. It is also shown that the cluster formation probability decreases with increasing surface binding energy. Finally, a good correspondence is obtained between the calculated and experimental velocity distributions of MCs+ clusters sputtered from different monoatomic materials. As a consequence, the Monte Carlo model and the discussed results can be validated.