Optimization of mechanical properties of multiscale hybrid polymer nanocomposites: A combination of experimental and machine learning techniques

Machine learning (ML) models provide fast and accurate predictions of material properties at a low computational cost. Herein, the mechanical properties of multiscale poly(3-hydroxybutyrate) (P3HB)-based nanocomposites reinforced with different concentrations of multiwalled carbon nanotubes (MWCNTs), WS2 nanosheets and sepiolite (SEP) nanoclay have been predicted. The nanocomposites were prepared via solution casting. SEM images revealed that the three nanofillers were homogenously and randomly dispersed into the matrix. A synergistic reinforcement effect was attained, resulting in an unprecedented stiffness improvement of 132% upon addition of 1:2:2 wt% SEP:MWCNTs:WS2. Conversely, the increments in strength were only moderates (up to 13.4%). A beneficial effect in the matrix ductility was also found due to the presence of both nanofillers. Four ML approaches, Recurrent Neural Network (RNN), RNN with Levenberg's algorithm (RNN-LV), decision tree (DT) and Random Forest (RF), were applied. The correlation coefficient (R2), mean absolute error (MAE) and mean square error (MSE) were used as statistical indicators to compare their performance. The best-performing model for the Young's modulus was RNN-LV with 3 hidden layers and 50 neurons in each layer, while for the tensile strength was the RF model using a combination of 100 estimators and a maximum depth of 100. An RNN model with 3 hidden layers was the most suitable to predict the elongation at break and impact strength, with 90 and 50 neurons in each layer, respectively. The highest correlation (R2 of 1 and 0.9203 for the training and test set, respectively) and the smallest errors (MSE of 0.13 and MAE of 0.31) were obtained for the prediction of the elongation at break. The developed models represent a powerful tool for the optimization of the mechanical properties in multiscale hybrid polymer nanocomposites, saving time and resources in the experimental characterization process

Machine learning for property prediction and optimization of polymeric nanocomposites: a state-of-the-art

Recently, the field of polymer nanocomposites has been an area of high scientific and industrial attention due to noteworthy improvements attained in these materials, arising from the synergetic combination of properties of a polymeric matrix and an organic or inorganic nanomaterial. The enhanced performance of those materials typically involves superior mechanical strength, toughness and stiffness, electrical and thermal conductivity, better flame retardancy and a higher barrier to moisture and gases. Nanocomposites can also display unique design possibilities, which provide exceptional advantages in developing multifunctional materials with desired properties for specific applications. On the other hand, machine learning (ML) has been recognized as a powerful predictive tool for data-driven multi-physical modelling, leading to unprecedented insights and an exploration of the system's properties beyond the capability of traditional computational and experimental analyses. This article aims to provide a brief overview of the most important findings related to the application of ML for the rational design of polymeric nanocomposites. Prediction, optimization, feature identification and uncertainty quantification are presented along with different ML algorithms used in the field of polymeric nanocomposites for property prediction, and selected examples are discussed. Finally, conclusions and future perspectives are highlighted

A New Method for Current-Voltage Curve Prediction in Photovoltaic Modules

In this work, a new method for obtaining the current-voltage curve for crystalline silicon and thin-film flat panels is presented. It is based on the single-diode model, with a variable shunt resistance and series resistance. New expressions for the shunt resistance and open circuit voltage as a function of the temperature and irradiance are deduced. Besides, a procedure to translate the series resistance to arbitrary conditions is proposed. The diode ideality factor and shunt resistance are obtained by optimization. The rest of the parameters that appear in the current-voltage curve are obtained from the module measurements by means of theoretical expressions. The procedure for obtaining the current-voltage curve under arbitrary operating conditions is also described. The results obtained with the developed model are compared with experimental measurements in cadmium telluride and amorphous silicon modules, and with results published in the literature for other technologies. The model faithfully reproduces the experimental values. For all the modules, the root mean square error for the maximum power is lower than 2% (below 1.5% in most cases). These errors are lower than those reported in the literature for other models. In particular, the results are significantly more exact in the case of thin-film modules

Evaluación de la colección de libros y manuscritos antiguos de la Biblioteca de Humanidades de la Universidad de Zaragoza para su digitalización: contexto, criterios y proyecto piloto.

En este Trabajo Fin de Grado se ha llevado a cabo la evaluación de la colección de libros y manuscritos antiguos de la Biblioteca de Humanidades, perteneciente a la Facultad de Filosofía y Letras de la Universidad de Zaragoza, para su posterior digitalización. La Biblioteca, con el objetivo de poner a disposición de usuarios e investigadores sus colecciones de fondo antiguo, inició un proyecto de digitalización de los documentos pertenecientes a este fondo en el mes de abril de 2022 bajo la dirección de especialistas en diferentes campos. En este trabajo de fin de grado se evalúan y priorizan los documentos de los siglos XV al XVII de cara a su digitalización, por lo que este trabajo constituye una colaboración con dicho, aplicando así la investigación a un contexto real. Se ha realizado un estado de la cuestión en el que se ha analizado la importancia del patrimonio cultural, documental y bibliográfico, así como la definición de estos conceptos; se ha definido el concepto de libro y fondo antiguo, su importancia dentro de una institución, y el concepto de tasación y valoración del libro; además, se han presentado las principales bases de datos o bibliotecas y colecciones digitales de este tipo de documentos con especial atención a las que se han utilizado. Por último, se ha indicado la importancia de la digitalización como estrategia de preservación y difusión de materiales, el papel que desarrolla la cooperación bibliotecaria en este aspecto y los criterios a seguir en un proceso de digitalización, prestando especial atención a los establecidos por la propia Biblioteca de Humanidades. Como punto final del trabajo, se ha comprobado la aplicabilidad de los criterios establecidos para llevar a cabo un correcto proyecto de digitalización sobre el fondo antiguo de la Biblioteca María Moliner.<br /

The Effect of Hexamethylene Diisocyanate-Modified Graphene Oxide as a Nanofiller Material on the Properties of Conductive Polyaniline

Conducting polymers like polyaniline (PANI) have gained a lot of interest due to their outstanding electrical and optoelectronic properties combined with their low cost and easy synthesis. To further exploit the performance of PANI, carbon-based nanomaterials like graphene, graphene oxide (GO) and their derivatives can be incorporated in a PANI matrix. In this study, hexamethylene diisocyanate-modified GO (HDI-GO) nanosheets with two di erent functionalization degrees have been used as nanofillers to develop high-performance PANI/HDI-GO nanocomposites via in situ polymerization of aniline in the presence of HDI-GO followed by ultrasonication and solution casting. The influence of the HDI-GO concentration and functionalization degree on the nanocomposite properties has been examined by scanning electron microscopy (SEM), Raman spectroscopy, X-ray di raction (XRD), thermogravimetric analysis (TGA), tensile tests, zeta potential and four-point probe measurements. SEM analysis demonstrated a homogenous dispersion of the HDI-GO nanosheets that were coated by the matrix particles during the in situ polymerization. Raman spectra revealed the existence of very strong PANI-HDI-GO interactions via - stacking, H-bonding, and hydrophobic and electrostatic charge-transfer complexes. A steady enhancement in thermal stability and electrical conductivity was found with increasing nanofiller concentration, the improvements being higher with increasing HDI-GO functionalization level. The nanocomposites showed a very good combination of rigidity, strength, ductility and toughness, and the best equilibrium of properties was attained at 5 wt % HDI-GO. The method developed herein opens up a versatile route to prepare multifunctional graphene-based nanocomposites with conductive polymers for a broad range of applications including flexible electronics and organic solar cells

Augment reality and virtual reality for the improvement of spatial competences in Physical Education

Young and mobile are an intense combination in entertainment. Mobile phones can also be a powerful tool in improving some teaching parameters, also in Physical Education. This research aims to test if Augmented Reality and Virtual Reality with mobile phones can have an impact on Physical Education students and their abilities in spatial orientation and distance estimation. In the investigation we have created two virtual and augmented scenarios, and a quantitative methodology has been used to analyze and contrast the learning tests carried out. The results show that these augmented worlds improve spatial orientation and estimation capacity. The study shows that it is convenient to develop activities and digital scenarios to incorporate mobile augmented reality in the learning of spatial orientation, at the same time as teaching skills are improved

Study of the optimal waveforms for non-destructive spectral analysis of aqueous solutions by means of audible sound and optimization algorithms

Acoustic analysis of materials is a common non-destructive technique, but most efforts are focused on the ultrasonic range. In the audible range, such studies are generally devoted to audio engineering applications. Ultrasonic sound has evident advantages, but also severe limitations, like penetration depth and the use of coupling gels. We propose a biomimetic approach in the audible range to overcome some of these limitations. A total of 364 samples of water and fructose solutions with 28 concentrations between 0 g/L and 9 g/L have been analyzed inside an anechoic chamber using audible sound configurations. The spectral information from the scattered sound is used to identify and discriminate the concentration with the help of an improved grouping genetic algorithm that extracts a set of frequencies as a classifier. The fitness function of the optimization algorithm implements an extreme learning machine. The classifier obtained with this new technique is composed only by nine frequencies in the (3–15) kHz range. The results have been obtained over 20,000 independent random iterations, achieving an average classification accuracy of 98.65% for concentrations with a difference of ±0.01 g/L

E-Learning in the Teaching of Mathematics: An Educational Experience in Adult High School

We acknowledge the researchers of the research group AREA (HUM-672), which belongs to the Ministry of Education and Science of the Junta de Andalucía and is registered in the Department of Didactics and School Organization of the Faculty of Education Sciences of the University of Granada.Currently, the e-learning method, due to the period of confinement that is occurring due to COVID-19, has increased its use and application in the teaching and learning processes. The main objective of this research is to identify the effectiveness of the e-learning method in the teaching of mathematics with adults who are in high school, in contrast to the traditional expository method. The study developed is quantitative, descriptive and correlational. The research design is quasi-experimental, with a control group and an experimental group. The results show that the use of the e-learning method has a positive influence on motivation, autonomy, participation, mathematical concepts, results and grades. It can be concluded that the e-learning method leads to improvement in adult students who are studying the mathematical subject in the educational stage of high school, provided that it is compared with the expository method. Therefore, this method is considered effective for its implementation in adults.Corporacion Escuela Tecnologica del Oriente ISPRS-2017-720Secretariat of Education of Santander ISPRS-2017-7202AreA HUM/672 Research Group of the University of Granada ISPRS-2017-720

Do Age, Gender and Poor Diet Influence the Higher Prevalence of Nomophobia among Young People?

We acknowledge the researchers of the research group AREA (HUM-672), which belongs to the Ministry of Education and Science of the Junta de Andalucía and is registered in the Department of Didactics and School Organization of the Faculty of Education Sciences of the University of Granada.The use of Information and Communication Technologies (ICT) is generating the emergence of new pathologies such as nomophobia. The aim of this research was to analyze the prevalence of nomophobia among young people, as well as to check whether the level of nomophobia is higher in males or females and in those students who claim to have less healthy nutrition due to the use of their mobile phones. The research method was based on a correlational and predictive design with a quantitative methodology. The measurement tool used is the Nomophobia Questionnaire (NMP-Q). The participating sample was 1743 students between 12 and 20 years old from different educational stages of the Autonomous City of Ceuta (Spain). The results show that highest rates of nomophobia were found in relation to the inability to communicate and contact others immediately. About gender, women have higher rates of nomophobia than men. In relation to age, no significant differences were found; thus, the problem may affect all ages equally. Finally, students who think that their smartphone use is detrimental to their good nutrition show higher levels on the scale provided.Corporacion Escuela Tecnologica del Oriente ISPRS-2017-7202Secretariat of Education of Santander ISPRS-2017-7202AreA HUM/672 Research Group of the University of Granada ISPRS-2017-720