<p>El premio Nobel de Química 2021 fue otorgado a Benjamin List y David W. C. MacMillan por el desarrollo de la organocatálisis asimétrica. El propósito de este artículo es explicar de qué se trata esta herramienta sintética, historia previa a la invención de la organocatálisis y los trabajos que iniciaron este campo por la activación vía enamina e iminio descubiertas por los galardonados al Nobel. Adicionalmente, se menciona la catálisis por enlace de hidrógeno y bifuncional. Se ilustra el alcance de la organocatálisis en la síntesis de los antivirales letermovil y oseltamivir y una sugerencia de cómo incluir la organocatálisis en los cursos de licenciatura.</p>

The energy supply sector faces significant challenges, such as the ongoing COVID-19 pandemic and the ongoing conflict in Ukraine, which affect the stability and efficiency of the energy system. In this study, we highlight the importance of electricity pricing and the need for accurate models to estimate electricity consumption and prices, with a focus on Spain. Using hourly data, we implemented various machine learning models, including linear regression, random forest, XGBoost, LSTM, and GRU, to forecast electricity consumption and prices. Our findings have important policy implications. Firstly, our study demonstrates the potential of using advanced analytics to enhance the accuracy of electricity price and consumption forecasts, helping policymakers anticipate changes in energy demand and supply and ensure grid stability. Secondly, we emphasize the importance of having access to high-quality data for electricity demand and price modeling. Finally, we provide insights into the strengths and weaknesses of different machine learning algorithms for electricity price and consumption modeling. Our results show that the LSTM and GRU artificial neural networks are the best models for price and consumption modeling with no significant difference.