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To manipulate the light–matter interaction effectively, we often rely on high refractive index inorganic nanoparticles. Such materials are contained essentially in everything that looks colorful or white: from paints to coatings but also in processed food, toothpaste, and cosmetic products. As these nanoparticles can accumulate in the human body and environment, there is a strong need to replace them with more biocompatible counterparts. In this work, we introduce various types of cellulose-based microparticles (CMPs) of four sizes with optimized dimensions for efficient light scattering that can replace traditional inorganic particles. We demonstrate that the produced materials can be exploited as highly efficient scattering enhancers, with designed optical performance. Finally, exploiting these cellulose colloids, we fabricated scattering materials and high transmittance/haze films with record performances with respect to the state-of-the-art values. The renewable and biocompatible nature of our systems, combined with their excellent optical properties, allows for the use of our cellulose-based particles in paints, LEDs, and solar cell devices and especially in applications where the biocompatibility of the component is essential, such as in food and pharmaceutical coatings.

An AI adaptation methodology designed to assist in transporting agricultural models between regions is presented. Models frequently need adaptation when transported because models developed in one region often do not produce valid results when used in a different region. The methodology prescribes the linkage of a genetic algorithm to a model. This makes the model more robust because it is able to adapt to the region in which it is being used. This methodology has been implemented within a DSS, and preliminary testing indicates this methodology has the ability to allow agricultural models developed in one area to be effectively utilized in other regions.

Molecular dynamics calculations have been used to study the effect of temperature on the dispersion of surface phonons in a registered xenon monolayer physisorbed on the graphite basal plane.

Finite element simulation techniques have been applied to the spreading process of single ceramic liquid droplets impacting on a flat cold surface under plasma-spraying conditions. The goal of the present investigation is to predict the geometrical form of the splat as a function of technological process parameters, such as initial temperature and velocity, and to follow the thermal field developing in the droplet up to solidification. A non-linear finite element programming system has been utilized in order to model the complex physical phenomena involved in the present impact process. The Lagrangean description of the motion of the viscous melt in the drops, as constrained by surface tension and the developing contact with the target, has been coupled to an analysis of transient thermal phenomena accounting also for the solidification of the material. The present study refers to a parameter spectrum as from experimental data of technological relevance. The significance of process parameters for the most pronounced physical phenomena is discussed as are also the consequences of modelling. We consider the issue of solidification as well and touch on the effect of partially unmelted material.