0000000000411781
AUTHOR
Kari Tuppurainen
NMR spectroscopy in environmental chemistry:1H and13C NMR chemical shift assignments of chlorinated dibenzothiophenes based on two-dimensional NMR techniques andab initio MO and DFT/GIAO calculations
A computationally feasible quantum chemical model for 13C NMR chemical shifts of PCB-derived carboxylic acids.
Two quantum chemical models have been derived for the prediction of 13C NMR chemical shifts of novel PCB acids obtained from PCBs by catalytic carbonylation. 13C isotropic shielding constants were calculated employing the GIAO (gauge-independent atomic orbital) method with density functional theory (DFT). The best results were obtained by cluster calculations, which took the solvent effects into account properly. In this approach, a solvent molecule (acetone) was attached by a hydrogen bond to every hydrogen atom present in a PCB acid, and the geometry of the molecular cluster was optimized employing the AM1 method. For 158 chemical shifts, the cross-validated standard error was 2.8 ppm and…
Urea as a PCDD/F inhibitor in municipal waste incineration.
Emissions of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from municipal waste incineration have been widely studied because of their extensive toxicity, and many efforts have been made to restrict their emissions. Although a number of chemical compounds have been shown in laboratory-scale tests to inhibit the formation of PCDD/Fs, few have been tested in pilot- or full-scale plants. This work evaluates the effect of urea as a PCDD/F inhibitor in a pilot-scale incinerator that uses refuse-derived fuel (RDF). The decomposition of urea under the test conditions was also studied using detailed kinetic modeling. An aqueous solution of urea was injected into the flue gas stream …
Comprehensive Strategy for Proton Chemical Shift Prediction: Linear Prediction with Nonlinear Corrections
A fast 3D/4D structure-sensitive procedure was developed and assessed for the chemical shift prediction of protons bonded to sp3carbons, which poses the maybe greatest challenge in the NMR spectral parameter prediction. The LPNC (Linear Prediction with Nonlinear Corrections) approach combines three well-established multivariate methods viz. the principal component regression (PCR), the random forest (RF) algorithm, and the k nearest neighbors (kNN) method. The role of RF is to find nonlinear corrections for the PCR predicted shifts, while kNN is used to take full advantage of similar chemical environments. Two basic molecular models were also compared and discussed: in the MC model the desc…