| Autor: |
Quezada-Aldaco MG; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico., Delgado E; Food Science and Technology, Department of Family and Consumer Sciences, New Mexico State University, P.O. Box 30001, Las Cruces, NM 88003-8001, USA., Zazueta-Álvarez DE; Ingeniería en Tecnología Ambiental, Universidad Politécnica de Durango, Carretera Durango-México Km 9.5, Durango 34300, Mexico., Martínez-Gómez VJ; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico., Medrano-Roldán H; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico., Vázquez-Ortega PG; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico., Hernández-Rodarte FS; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico., Reyes-Jáquez D; Department of Chemical and Biochemical Engineering, National Technological Institute of Mexico (TecNM)-Durango Institute of Technology (ITD), Blvd. Felipe Pescador 1830, Nueva Vizcaya, Durango 34080, Mexico. |
| Abstrakt: |
Molecular dynamics (MD) techniques offer significant potential for optimizing mineral extraction processes by simulating economically or physically restrictive conditions at the laboratory level. Lithium, a crucial metal in the electromobility era, exemplifies the need for ongoing re-evaluation of extraction techniques. This research aims to simulate the crystal structures of mineral species present in a polylithionite mineral concentrate [KLi 2 Al(Si 4 O 10 )(F,OH) 2 ] using crystallographic data obtained from X-ray diffraction analysis. This study focuses on optimizing these structures, validating them through density comparisons, and determining the interaction parameter between the identified phases and lithium oxide (Li 2 O). The X-ray diffraction analysis revealed five predominant mineral phases: quartz (SiO 2 ), calcite [Ca(CO 3 )], pyrite (FeS 2 ), cassiterite (SiO 2 ), and a compound Pb 6 O 2 (BO 3 ) 2 SO 4 . Structural data, including lattice parameters, space groups, and atomic coordinates, were used to construct the crystal structures with Materials Studio 8.0, employing the Crystal Builder module. Optimization was performed using the Forcite module with the Smart optimization algorithm and the Universal force field. The interaction parameter (χ) indicated an affinity between lithium oxide and pyrite, as well as between calcite and quartz. |
