Neural network photothermal depth profiling of a heat source distribution.application to water migration in starch sheets

The determination of the water migration profile in starch is used as an ex perimental model system for the depth profiling of heat source distribution s. A depth dependent water concentration, which has diffused into the sampl e during a timed exposure to a humid atmosphere, acts as a specific positio n dependent heat source. The direct and inverse relation between the water content and the frequency spectrum of a photothermal signal detected by a p yroelectric tranducer in contact with the sample is investigated. The inver se problem is treated by a neural network and a table lookup method. The pr ofile reconstruction is illustrated for simulated and experimental cases.