Eliminación de oro de minerales auríferos mediante alfa-ciclodextrina: metodología de superficie de respuesta y optimizaciones de redes de análisis neuronal artificial
DOI:
https://doi.org/10.5935/jetia.v9i42.879Resumen
Este artículo explora el uso de alfa ciclodextrina (α-CD) para la extracción de oro de minerales auríferos en la República Democrática del Congo (RDC). La investigación tiene como objetivo identificar las condiciones óptimas de eliminación de oro utilizando la Metodología de superficie de respuesta (RSM) y las Redes neuronales artificiales (ANN). Inicialmente, las muestras de mineral se recolectaron y procesaron para mejorar la lixiviación al reducir el tamaño de las partículas. El proceso de lixiviación empleó un agua regia modificada con ácido bromhídrico debido al fuerte reconocimiento molecular entre el ion bromuro de oro y la α-CD. Durante la experimentación se ajustaron varios parámetros de lixiviación, como el tiempo, la concentración de HBr, el pH y la velocidad de agitación. RSM produjo valores óptimos de 7,27 horas, 50 g/L, 1 y 200 rpm, lo que resultó en una eliminación de oro del 98,54 %, mientras que ANN produjo valores ligeramente más bajos de 7,5 horas, 50 g/L, 1 y 200 rpm, con un 97,16 % extracción de oro. Para la recuperación de oro de α-CD, la optimización de RSM y ANN resultó en 40 minutos, 11,61 g/L y pH 5, logrando 98,87 % y 39,8 minutos, 10,71 g/L y pH 5, con una eliminación de oro del 99,98 %, respectivamente. Las pruebas de validación respaldaron estos hallazgos, lo que indica que RSM y ANN son métodos exitosos para optimizar la recuperación de oro a partir de minerales auríferos en la República Democrática del Congo.
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