La era del Grafeno comenzó con el trabajo seminal de Novoselov et al., que aisló láminas de cristal de grafito de un solo átomo de espesor. A bajas temperaturas, la densidad de los estados en grafeno exhibe un espacio en forma de V, y a bajas energías su relación de dispersión es lineal. Los electrones se comportan como partículas fermiónicas sin masa, obedeciendo a la ecuación de Dirac. Sin embargo, el grafeno no tiene brecha o (gap en inglés) y no se puede usar en microelectrónica. Por lo tanto, es necesario abrir y controlar esa brecha sin cambiar su movilidad. Una forma efectiva de abrir una brecha de banda es empleando el confinamiento electrónico, que es naturalmente presente en la estructura geométrica de nanocintas, colocando estos sistemas en excelentes candidatos para sustituir al silício en aplicaciones tecnológicas. Sin embargo, desde el punto de vista experim...

Topological one-dimensional superconductors can sustain zero energy modes protected by diferent kinds of symmetries in their extremities. Observing these excitations in the form of Majorana fermions is one of the most intensive quests in condensed matter physics. We are interested in another class of one-dimensional topological systems in this work, namely topological insulators. Which present symmetry-protected end modes with robust properties and do not require the low temperatures necessary for topological superconductivity. We consider a device in the form of a single electron transistor coupled to the simplest kind of topological insulators, namely chains of atoms with hybridized sp orbitals. We study the thermoelectric properties of the device in the trivial, non-trivial topological phases and at the quantum topological transition of the chains. We show that the device’s electric...

With the advancement of technology, remote work and virtual classes have become increasingly common, leading to prolonged periods in front of computers and, consequently, to discomfort and even lower back pain. This study compares machine learning algorithms to identify and prevent low back pain, a common health problem. A predictive model for early diagnosis and prevention of these injuries was developed using datasets from open data repositories. Six machine learning models were used to train the data. Results showed that logistic regression was the most effective model, with performance curves of 70%, 90%, and 99%. Performance metrics indicated 86% accuracy, 85% recall, and 86% F1-score. Accuracy of 70%, recall of 71%, and F1-score of 63% reflect the robust ability of the model to address the problem. In addition, an intuitive interface was implemented using Gradio Software to improve...