The submicrometer fraction of the particulate matter suspended in river water is characterized by decay- programmed sedimentation field-flow fractionation (SdFFF). The power program was chosen because of its ability to yield a homogeneous fractionating power with respect to the analysis of broadly dispersed particulate samples. An appropriate search for the optimum power program setup is performed by numerical simulation. Comparison between simulated and experimental fractograms proves to be feasible in establishing the physical features of the sample (i.e., number of components, their relative dimensions, polydispersity, and absolute amount). A method is presented coupling SdFFF with electron microscopy (EM) techniques. Both the separation achieved and the sample model on which SdFFF simulation has been based are then verified using this coupled approach. Examples of EM morphological characterization on SdFFF-fractionated samples of river-borne particulate matter are reported. Under optimized power programming conditions, some effects of particulate sample treatments on SdFFF fractograms are presented. Chemical oxidation and sample aging are shown to influence the SdFFF- based, dimensional distribution of the particles. © Oxford University Press 1992.
Simulation and optimization of power-programmed sdfff: Applications for fractionating and characterizing submicrometer particulate matter in river water
PASTI, Luisa;DONDI, Francesco
1992
Abstract
The submicrometer fraction of the particulate matter suspended in river water is characterized by decay- programmed sedimentation field-flow fractionation (SdFFF). The power program was chosen because of its ability to yield a homogeneous fractionating power with respect to the analysis of broadly dispersed particulate samples. An appropriate search for the optimum power program setup is performed by numerical simulation. Comparison between simulated and experimental fractograms proves to be feasible in establishing the physical features of the sample (i.e., number of components, their relative dimensions, polydispersity, and absolute amount). A method is presented coupling SdFFF with electron microscopy (EM) techniques. Both the separation achieved and the sample model on which SdFFF simulation has been based are then verified using this coupled approach. Examples of EM morphological characterization on SdFFF-fractionated samples of river-borne particulate matter are reported. Under optimized power programming conditions, some effects of particulate sample treatments on SdFFF fractograms are presented. Chemical oxidation and sample aging are shown to influence the SdFFF- based, dimensional distribution of the particles. © Oxford University Press 1992.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.