Research 

This project addresses the need for more sustainable methods of LiOH production by exploring ethanol-based antisolvent crystallization as an alternative to traditional energy- and water-intensive processes.

The experimental data will support the development of thermodynamic models to predict the solid–liquid equilibrium of this ternary system and determine the optimal amount of ethanol needed. 

The ongoing project focuses on optimizing lithium hydroxide crystallization under an ethanol-based antisolvent system, addressing yield, crystal size and purity control, crystal characterization, and solvent recovery via membrane separation

They are developing biopolymer-based adsorbents to recover lithium from wastewater and brine sources. These materials are eco-friendly, cost-effective, and designed to offer a sustainable alternative to conventional extraction methods. Their research focuses on renewable polymers such as chitosan and cellulose, with the goal of supporting the growing demand for lithium through direct lithium extraction (DLE).

Utilize the machine learning and deep learning model to predict experiments results and reaction dominant factor, image processing of bitumen samples to analyze the composition and flotation within elements

This project explores the application of deep eutectic solvents (DESs) as alternative green solvents to replace conventional organic solvents in lithium separation processes. DESs, formed by mixing hydrogen bond donors and acceptors, offer tunable physicochemical properties, low volatility, and environmental compatibility.  They are promising candidates for selective lithium extraction from brines and complex matrices.

This project involves the use of molecular dynamics simulation tools, such as GROMACS, to replicate and investigate the antisolvent crystallization process of lithium hydroxide (LiOH) in water-ethanol solutions. The study presents visualizations alongside analyses of thermodynamic properties, solubility behavior, and spatial distribution trends.