Low Temperature Physics at the Laboratoire National des Champs Magnétiques Pulsés in Toulouse

An overview over past and present activities and future developments at the Toulouse pulsed magnetic field facility is given, both as far as technical developments of the infrastructure, as well as low temperature physics performed at the LNCMP are concerned.     

Volumetric Change and Surface Properties of Temperature-Sensitive Polyvinylalcohol (PVA) Hydrogel

Polyvinylalcohol (PVA) polymer gel is a temperature sensitive polymeric gel, with a critical transition temperature (with H₂O) of 310 K. At higher than 310 K, this temperature sensitive polymer gel shrinks because of discharging water, whereas at lower temperatures, the gel swelled because of absorbing water. The reversibility of the gel's volume change was confirmed by temperature swing. The adsorption behavior of an organic compound onto the PVA polymer gel in water was tested at various temperatures. The amount of adsorbed organic compound increased remarkably at temperatures higher than about 310 K. Then, it was confirmed that the organic compound in PVA polymer gel could be reversibly adsorbed and desorbed by a temperature change between 293 and 323 K. The mechanism of adsorption of the organic compound onto the PVA polymer gel could be explained by hydration and dehydration of polymer gel.     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.     

Modification of ASM3 for the determination of biomass adsorption/storage capacity in bulking sludge control.

The selector activated sludge (SAS) systems are known to prevent excessive growth of filamentous microorganisms responsible for bulking sludge, but these systems were hardly ever modelled. This study aimed to develop a model capable of predicting rapid substrate removal in the SAS systems. For this purpose, the Activated Sludge Model No. 3 (ASM3) was extended with three processes (adsorption, direct growth on the adsorbed substrate under aerobic or anoxic conditions). The modified ASM3 was tested against the results of batch experiments with the biomass originating from two full-scale SAS systems in Germany. The endogenous biomass was mixed with various readily biodegradable substrates (acetate, peptone, glucose and wastewater) and the utilisation of substrate (expresses as COD) and oxygen uptake rates (OURs) were measured during the experiments. In general, model predictions fitted to the experimental data, but a considerable number of kinetic (5) and stoichiometric (2) parameters needed to be adjusted during model calibration. The simulation results revealed that storage was generally a dominating process compared to direct growth in terms of the adsorbed substrate utilisation. The contribution of storage ranged from 65-71% (Plant A) and 69-92% (Plant B).     

An investigation of sugar extraction methods and the use of microwave power for date syrup processing: efficiency and color related considerations.

This study investigates the effect of extraction methods on the color of date syrup and the potential use of microwave power for syrup processing. Sugar solutions were extracted from dates by boiling, soaking and blending. Color and sugar content of the extracted solutions were measured, and the percentage of sugar extracted form the total fruit sugar determined. Boiling was found to be the most efficient method of extraction whereby 74% of total samples sugar was extracted. In contrast, only 54.2% of fruit sugar was extracted by blending and 42% by soaking. In addition, solutions extracted by soaking and blending had a foaming problem in the subsequent concentration process. The extraction method had no effect on the product final color. The extracted solution was concentrated using two heating methods: conventional and microwave heating at a 600 W capacity and a frequency of 2450 MHz applied at three power levels: 10, 7, and 6. In the heating process, 180 minutes were needed to achieve a 77% degrees Brix using convective heating, while it took 81, 138, and 166 minutes of microwave heating at power level 10, 7, and 6, respectively to achieve the same concentration. Water activity of the syrup was measured within a sugar content range of 50 to 80% degrees Brix and the sugar concentration at which the product is shelf stable was determined at 76%.     

Development of a Continuous Segmented Flow Tubular Reactor and the “Scale‐out” Concept – In Search of Perfect Powders

The synthesis of powders with controlled shape and narrow particle size distributions is still a major challenge for many industries. A continuous Segmented Flow Tubular Reactor (SFTR) has been developed to overcome homogeneity and scale‐up problems encountered when using batch reactors. Supersaturation is created by mixing the co‐reactants in a micromixer inducing precipitation; the suspension is then segmented into identical micro‐volumes by a non‐miscible fluid and sent through a tube. These micro‐volumes are more homogeneous when compared to large batch reactors leading to narrower size distributions, better particle morphology, polymorph selectivity and stoichiometry. All these features have been demonstrated on single tube SFTR for different chemical systems. To increase productivity for commercial application the SFTR is being “scaled‐out” by multiplying the number of tubes running in parallel instead of scaling‐up by increasing their size. The versatility of the multi‐tube unit will allow changes in type of precipitate with a minimum of new investment as new chemistry can be researched, developed and optimised in a single tube SFTR and then transferred to the multi‐tube unit for powder production.