The role of H-bond in the high-pressure chemistry of model molecules.

Pressure is an extraordinary tool to modify direction and strength of intermolecular interactions with important consequences on the chemical stability of molecular materials. The decrease of the distance among nearest neighbour molecules can give rise to reactive configurations reflecting the crystal arrangement and leading to association processes. In this context, the role of the H-bonds is very peculiar because their usual strengthening with rising pressure does not necessarily configure a decrease of the reaction activation energy but, on the contrary, can give rise to an anomalous stability of the system. In spite of this central role, the mechanisms by which a chemical reaction is favoured or prevented by H-bonding under high pressure conditions is a poorly explored field. Here we review a few studies where the chemical behaviour of simple molecular systems under static compression was related to the H-bonding evolution with pressure. These results are able to clarify a wealth of changes of the chemical and physical properties caused by the strengthening with pressure of the H-bonding network and provide additional tools to understand the mechanisms of high-pressure reactivity, a mandatory step to make these synthetic methods of potential interest for applicative purposes.

An artificial neural network model for the prediction of mechanical and barrier properties of biodegradable films.

Nowadays, the production of biodegradable starch-based films is of great interest because of the growing environmental concerns regarding pollution and the need to reduce dependence on the plastics industry. A broad view of the role of different components, added to starch-based films to improve their properties, is required to guide the future development. The self-organizing maps (SOMs) provide comparisons that initially were complicated due to the large volume of the data. Furthermore, the construction of a model capable of predicting the mechanical and barrier properties of these films will accelerate the development of films with improved characteristics. The water vapor permeability (WVP) analysis using the SOM algorithm showed that the presence of glycerol is very important for films with low amounts of poly (butylene adipate co-terephthalate) and confirms the role of the equilibrium relative humidity in the determination of WVP. Considering the mechanical properties, the SOM analysis emphasizes the important role of poly (butylene adipate co-terephthalate) in thermoplastic starch based films. The properties of biodegradable films were predicted and optimized by using a multilayer perceptron coupled with a genetic algorithm, presenting a great correlation between the experimental and theoretical values with a maximum error of 24%. To improve the response of the model and to ensure the compatibility of the components more information will be necessary.