SCF,MP2, and CEPA-1 calculations on the OH ‥ O hydrogen bonded complexes (H2O)2 and (H2O-H2CO)

Counterpoise corrected ab initio calculations are reported for (H₂O)₂ and H₂O-H₂CO. Geometry searches were done in the moment-optimized basis DZP' at the SCF, MP2, and CEPA-1 levels of theory, followed by more accurate single-point calculations in basis ESPB, which includes bondfunctions to saturate the dispersion energy. The final equilibrium binding energies obtained are ?4.7 ±0.3 kcal/mol for a near-linear (H₂O)₂ structure and ?4.6 ±0.3 kcal/mol for a strongly bent HOH ‥ OCH₂ structure. The energy difference between these systems is much smaller than in all previous ab initio work. Cyclic (C_2h) and bifurcated (C_2v) transition structures for (H₂O)₂ are located at 1.0 ±0.1 kcal/mol and 1.9 ±0.3 kcal/mol above the global minimum, respectively. A new partitioning scheme is presented that rigorously partitions the MP2 correlation interaction energy in intra and intermolecular (dispersion) contributions. These terms are large (up to 2 kcal/mol) but of opposite sign for most geometries studied and hence their overall effect upon the final structures is relatively small. The relative merits of the MP2 and CEPA-1 approaches are discussed are discussed and it is concluded that for economical reasons MP2 is to be preferred, especially for larger systems.     

A new approach to untargeted integration of high resolution liquid chromatography–mass spectrometry data

Because of its high sensitivity and specificity, hyphenated mass spectrometry has become the predominant method to detect and quantify metabolites present in bio-samples relevant for all sorts of life science studies being executed. In contrast to targeted methods that are dedicated to specific features, global profiling acquisition methods allow new unspecific metabolites to be analyzed. The challenge with these so-called untargeted methods is the proper and automated extraction and integration of features that could be of relevance. We propose a new algorithm that enables untargeted integration of samples that are measured with high resolution liquid chromatography–mass spectrometry (LC–MS). In contrast to other approaches limited user interaction is needed allowing also less experienced users to integrate their data. The large amount of single features that are found within a sample is combined to a smaller list of, compound-related, grouped feature-sets representative for that sample. These feature-sets allow for easier interpretation and identification and as important, easier matching over samples. We show that the automatic obtained integration results for a set of known target metabolites match those generated with vendor software but that at least 10 times more feature-sets are extracted as well. We demonstrate our approach using high resolution LC–MS data acquired for 128 samples on a lipidomics platform. The data was also processed in a targeted manner (with a combination of automatic and manual integration) using vendor software for a set of 174 targets. As our untargeted extraction procedure is run per sample and per mass trace the implementation of it is scalable. Because of the generic approach, we envision that this data extraction lipids method will be used in a targeted as well as untargeted analysis of many different kinds of TOF-MS data, even CE- and GC–MS data or MRM. The Matlab package is available for download on request and efforts are directed toward a user-friendly Windows executable.     

An exactly solvable non-linear Boltzmann equation

The initial value problem for a model Boltzmann equation of a two dimensional gas with a continuous or discrete energy distribution function and a transition probability δ(? - ?') is solved exactly; ? and ?' are the total energies before and after collision.     

Mössbauer study of magnetic ordering in K2FeF4

The sublattice magnetization of the quadratic-layer basal-plane antiferromagnet K₂FeF₄ has been studied by use of Mössbauer spectroscopy. A distribution of Néel temperatures with a width ～3 K is found at a mean T_N = 67.2±0.3 K. For 0.3 < T/T_N < 0.99 the sublattice magnetization is described by a power law with critical exponent β = 0.17±0.01.