The first synthesis of poly(styrene)-b-poly(dimethylsiloxane)-b-poly(styrene) triblock copolymer in miniemulsion has been achieved by controlled/living radical polymerization of styrene using a modified hydroxypropyl terminated poly(dimethylsiloxane) as a transfer agent for iodine transfer polymerization. First an R,ω-hydroxypropyl poly(dimethylsiloxane) was modified by esterification with 2-bromopropionic acid. The second step consisted in a nucleophilic substitution of bromine by iodine through the reaction with sodium iodide in acetone. Then, miniemulsion polymerization of styrene was performed in the presence of sodium dodecyl sulfate as surfactant, 2,2′-azobis(isobutyronitrile) as radical initiator, and the R,ω-diiodopoly(dimethylsiloxane) as both the hydrophobe and the macrotransfer agent. Stable white latexes were obtained with a good correlation between theoretical and experimental molecular weights. Considering the process and the polymerization type, rather low polydispersity indexes (around 1.7) were reached. A kinetic study showed an increase of the molecular weight with conversion. Last, a chain extension led to a shift of the molecular weight distribution giving evidence for the living character of the triblock copolymers.

Abstract. Aircraft engines are designed to be used during several tens of years. Their maintenance is a challenging and costly task, for obvious security reasons. The goal is to ensure a proper operation of the engines, in all conditions, with a zero probability of failure, while taking into account aging. The fact that the same engine is sometimes used on several aircrafts has to be taken into account too.The maintenance can be improved if an efficient procedure for the prediction of failures is implemented. The primary source of information on the health of the engines comes from measurement during flights. Several variables such as the core speed, the oil pressure and quantity, the fan speed, etc. are measured, together with environmental variables such as the outside temperature, altitude, aircraft speed, etc.In this paper, we describe the design of a procedure aiming at visualizing successive data measured on aircraft engines. The data are multi-dimensional measurements on the engines, which are projected on a self-organizing map in order to allow us to follow the trajectories of these data over time. The trajectories consist in a succession of points on the map, each of them corresponding to the two-dimensional projection of the multi-dimensional vector of engine measurements. Analyzing the trajectories aims at visualizing any deviation from a normal behavior, making it possible to anticipate an operation failure.However rough engine measurements are inappropriate for such an analysis; they are indeed influenced by external conditions, and may in addition vary between engines. In this work, we first process the data by a General Linear Model (GLM), to eliminate the effect of engines and of measured environmental conditions. The residuals are then used as inputs to a SelfOrganizing Map for the easy visualization of trajectories.