Erik Unneberg
Norwegian Defence Research Establishment
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Featured researches published by Erik Unneberg.
Journal of Chromatography A | 2010
Bent Tore Røen; Erik Unneberg; John Aasulf Tørnes; Elsa Lundanes
A method for trace determination of sulphur mustard (HD) and some of its cyclic decomposition compounds in water samples has been developed using headspace-trap in combination with gas chromatography-mass spectrometry (GC-MS). Factorial design was used for optimisation of the method. The trap technology allows enrichment and focusing of the analytes on an adsorbent, hence the technique offers better sensitivity compared to conventional static headspace. A detection limit of 1ng/ml was achieved for HD, while the cyclic sulphur compounds 1,4-thioxane, 1,3-dithiolane and 1,4-dithiane could be detected at a level of 0.1ng/ml. The method was validated for the stable cyclic compounds in the concentration range from the limit of quantification (LOQ: 0.2-0.4ng/ml) to hundred times LOQ. The within and between assay precisions at hundred times LOQ were 1-2% and 7-8% relative standard deviation, respectively. This technique requires almost no sample handling, and the total time for sampling and analysis was less than 1h. The method was successfully employed for muddy river water and sea water samples.
Journal of Chromatography A | 2010
Bent Tore Røen; Erik Unneberg; John Aa. Tørnes; Elsa Lundanes
Methods for trace determination of sulphur mustard (HD) and some related cyclic sulphur compounds in soil samples have been developed using headspace-trap in combination with gas chromatography-mass spectrometry (GC-MS). Two quite different types of soil were employed in the method optimisation (sandy loam and silty clay loam). Prior to analysis, water saturated with sodium chloride was added to the samples, at a water to soil ratio of 1:1. A detection limit of 3 ng/g was achieved for HD, while the cyclic sulphur compounds 1,4-thioxane, 1,3-dithiolane and 1,4-dithiane could be detected at 0.2-0.7 ng/g. The methods were validated in the concentration range from the limit of quantification (LOQ) to hundred times LOQ. The within assay precision at fifty times LOQ was 6.9-7.3% relative standard deviation (RSD) for determination of the cyclic sulphur compounds, and 15% RSD for determination of HD. Recoveries were in the range of 43-60% from the two soil types. As the technique requires very little sample preparation, the total time for sample handling and analysis was less than 1h. The technique was successfully employed for the determination of cyclic sulphur compounds in a sediment sample from an old dumping site for chemical munitions, known to contain HD degradation products.
Molecular Physics | 2016
Eirik Kjønstad; John F. Moxnes; Tomas Lunde Jensen; Erik Unneberg
ABSTRACT The molecular surface has been suggested to be a region of the molecule, where information of non-covalent intermolecular interactions is present. Many workers have pursued this idea by constructing models based on statistical parameters Φ extracted from the electrostatic potential on a particular molecular surface. We claim that a better approach is to define a family of equivalent molecular surfaces, each associated with a particular electron density ε. The demand that any model must give the same predictions on all such molecular surfaces yields a mathematical requirement restricting the space of permissible parameters. We prove that linear single-variable models of the form property = α Φ + β will only yield invariant predictions if the parameter values of Φ computed on equivalent surfaces are linearly related. This claim is not restricted to the use of the electrostatic potential, but holds for any parameter extracted from the surface of molecules. By using a set of 44 molecules, we also demonstrate that a frequently used aspect of the electrostatic potential, that of ‘imbalance’ of negative and positive values, fails to satisfy the linearity requirement. It is argued that multi-variable models should only include parameters that satisfy the single-variable requirement.
Molecular Physics | 2016
Eirik Kjønstad; John F. Moxnes; Tomas Lunde Jensen; Erik Unneberg
ABSTRACT The crystal density of neutral and ionic molecular crystals is remarkably well approximated by the enclosed volume of molecular surfaces, where these surfaces are defined as regions of constant and small electron density. Several workers have proposed that estimates may be improved if one includes quantities extracted from the electrostatic potential on the surface of the molecule. The variation of the potential and the imbalance of positive and negative values have been considered to be of importance. In this study we demonstrate that whereas variation is important for improving crystal density predictions, imbalance is not. We present a density functional theory study on a set of 44 neutral molecular crystals. Ten-fold cross-validations were performed on models that incorporate variation, imbalance and combinations of both. Geometries were optimised using B3LYP and basis sets of type 6-31G(d). Electron densities and electrostatic potentials were computed with B3LYP and M05. Regardless of functional, models that correct for variation yield a relative decrease of 15%–18% in root-mean-square error of prediction. This correction appears to sharpen the error distribution about zero. Models based on imbalance yield no improvement, and we argue that it plays an insignificant role.
Propellants, Explosives, Pyrotechnics | 2012
Eva Landsem; Tomas Lunde Jensen; Finn Knut Hansen; Erik Unneberg; Tor E. Kristensen
Propellants, Explosives, Pyrotechnics | 2013
Eva Landsem; Tomas Lunde Jensen; Tor E. Kristensen; Finn Knut Hansen; Tore Benneche; Erik Unneberg
Propellants, Explosives, Pyrotechnics | 2013
John F. Moxnes; Tomas Lunde Jensen; Eimund Smestad; Erik Unneberg; Ove Dullum
Propellants, Explosives, Pyrotechnics | 2012
Eva Landsem; Tomas Lunde Jensen; Finn Knut Hansen; Erik Unneberg; Tor E. Kristensen
Propellants, Explosives, Pyrotechnics | 2015
Trond Heldal Hagen; Tomas Lunde Jensen; Erik Unneberg; Yngve Stenstrøm; Tor E. Kristensen
Computational Materials Science | 2010
Ole Martin Løvvik; Tomas Lunde Jensen; John F. Moxnes; Ole Swang; Erik Unneberg