Informática de materiales en el estudio de propiedades físicas de nanotubos de carbono
DOI:
https://doi.org/10.5281/zenodo.14193613Palabras clave:
Aprendizaje automático, inteligencia artificial, nanotecnología, nanoestructuras base carbonoResumen
La informática de materiales (IM) constituye un nuevo paradigma en el estudio de nanomateriales, donde enfoques de aprendizaje automático (AA) se implementan en la nanotecnología. La IM es una poderosa herramienta en el estudio de nanotubos de carbono (NTC), los cuales poseen propiedades físicas excepcionales, llevándolos a ser utilizados en óptica, química, informática y medicina, entre otras áreas. Este trabajo describe las investigaciones más recientes en IM aplicado a los NTC. Se explican detalladamente los algoritmos de AA utilizados en el estudio de NTC, tales como redes neuronales artificiales, árboles de decisión y máquinas de vectores de soporte. Asimismo, se exponen los estudios donde enfoques de simulación computacional han sido útiles para desarrollar modelos predictivos de propiedades y comportamientos de NTC. Se identifican preguntas de investigación abiertas en el análisis de propiedades físicas como la conductividad térmica y los modos vibratorios de NTC, donde la IM podría apoyar para su mayor comprensión, ayudando en el desarrollo de nanosensores. Finalmente, la IM puede ayudar en reducir costos de tiempo y recursos en la caracterización de propiedades físicas de nanomateriales.
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Derechos de autor 2024 Mtro. Luis Enrique Vivanco Benavides, Dra. Cecilia Mercado Zúñiga, Dra. María Teresa Torres Mancera, Dra. María Yesenia Díaz Cárdenas
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