Chemical Analysis Based on Nonlinearity

A large number of chemical sensors have been developed in various fields (e.g., clinical, environmental, food, and industrial) to quantitatively detect a target sample because a rapid chemical analysis (e.g., a gas warning system or a urine sugar checker) is necessary to ensure our daily life and work, and to easily check the condition of our health. Development of surface modification on the chemical sensor may help to enhance the reproducibility and sensitivity of the sensor response. In addition to the development of sensor elements, the signal processing, such as neural network, is noticed to utilise the sensor response, together with recent advancement of computational power. This suggests that the temporal change in the sensor response is utilised as abundant information, in addition to the d.c. value of the sensor response. Actually, chemical structure and concentration in taste and olfaction is transformed into nervous impulses in the nervous cell, i.e., time-dependent multi-dimensional information. Here, we notice that the excitation and pulse generation in the nervous cell are typically non-linear phenomena and it may be worthwhile to utilise the non-linearity as the multi-dimensional information for molecular recognition. In this book, novel chemical sensors based on a time-dependent non-linear response are described. The strategy may be to artificially mimic information transduction in living organisms. Between describing the significance of time-dependent information which is addressed based on non-linearity as general view, to the signal processing systems which mimic biological signal processing and are introduced in relation to the chemical analysis, this invaluable book actively involves subjects which are not directly associated with "chemical sensor" until now. However, they are expected to play an important role to develop the system of chemical analysis in the future work.Nakata, Satoshi is the author of 'Chemical Analysis Based on Nonlinearity' with ISBN 9781590337370 and ISBN 1590337379.