Microfluidic device and interfacial transport: application to biomolecules and nanostructures

The aim of my dissertation is to provide new knowledge and applications of microfluidics in a variety of problems, from materials science, devices, and biomedicine, where the control on the fluid dynamics and the local concentration of the solutions containing the relevant molecules (either materials, precursors, or biomolecules) is crucial. The control of interfacial phenomena occurring in solutions at dierent length scales is compelling in nanotechnology for devising new sensors, molecular electronics devices, memories. Microfluidic devices were fabricated and integrated with organic electronics devices. The transduction involves the species in the solution which infills the transistor channel and confined by the microfluidic device. This device measures what happens on the surface, at few nanometers from the semiconductor channel. Soft-lithography was adopted to fabricate platinum electrodes, starting from platinum carbonyl precursor. I proposed a simple method to assemble these nanostructures in periodic arrays of microstripes, and form conductive electrodes with characteristic dimension of 600 nm. The conductivity of these sub-microwires is compared with the values reported in literature and bulk platinum. The process is suitable for fabricating thin conductive patterns for electronic devices or electrochemical cells, where the periodicity of the conductive pattern is comparable with the diusion length of the molecules in solution. The ordering induced among artificial nanostructures is of particular interest in science. I show that large building blocks, like carbon nanotubes or core-shell nanoparticles, can be ordered and self-organised on a surface in patterns due to capillary forces. The eective probability of inducing order with microfluidic flow is modeled with finite element calculation on the real geometry of the microcapillaries, in soft-lithographic process. The oligomerization of A40 peptide in microconfined environment represents a new investigation of the extensively studied peptide aggregation. The added value of the approach I devised is the precise control on the local concentration of peptides together with the possibility to mimick cellular crowding. Four populations of oligomers where distinguished, with diameters ranging from 15 to 200 nm. These aggregates could not be addresses separately in fluorescence. The statistical analysis on the atomic force microscopy images together with a model of growth reveal new insights on the kinetics of amyloidogenesis as well as allows me to identify the minimum stable nucleus size. This is an important result owing to its implications in the understanding and early diagnosis and therapy of the Alzheimer’s disease

Modeling systems and vis/NIR device to improve peach and nectarine pre and post-harvest fruit maturity management

During the last decade peach and nectarine fruit have lost considerable market share, due to increased consumer dissatisfaction with quality at retail markets. This is mainly due to harvesting of too immature fruit and high ripening heterogeneity. The main problem is that the traditional used maturity indexes are not able to objectively detect fruit maturity stage, neither the variability present in the field, leading to a difficult post-harvest management of the product and to high fruit losses. To assess more precisely the fruit ripening other techniques and devices can be used. Recently, a new non-destructive maturity index, based on the vis-NIR technology, the Index of Absorbance Difference (IAD), that correlates with fruit degreening and ethylene production, was introduced and the IAD was used to study peach and nectarine fruit ripening from the “field to the fork”. In order to choose the best techniques to improve fruit quality, a detailed description of the tree structure, of fruit distribution and ripening evolution on the tree was faced. More in details, an architectural model (PlantToon®) was used to design the tree structure and the IAD was applied to characterize the maturity stage of each fruit. Their combined use provided an objective and precise evaluation of the fruit ripening variability, related to different training systems, crop load, fruit exposure and internal temperature. Based on simple field assessment of fruit maturity (as IAD) and growth, a model for an early prediction of harvest date and yield, was developed and validated. The relationship between the non-destructive maturity IAD, and the fruit shelf-life, was also confirmed. Finally the obtained results were validated by consumer test: the fruit sorted in different maturity classes obtained a different consumer acceptance. The improved knowledge, leaded to an innovative management of peach and nectarine fruit, from “field to market”.