# Process Analytical Technology-Integrated FT-IR and Raman Spectroscopies for Efficient Reactive Liquid–Liquid Extraction Processing in Lithium Recycling

## TL;DR

This paper presents a new method using FT-IR and Raman spectroscopy to improve lithium recycling efficiency and reduce environmental impact.

## Contribution

A novel PAT-integrated framework using in-line spectroscopy and chemometric models for reactive liquid–liquid extraction in lithium recycling.

## Key findings

- Partial least-squares regression models achieved an R² of at least 0.95 for measuring extractant concentration and saponification.
- The method reduces chemical costs by 15% and global warming potential by 20% in lithium purification.
- The return on investment for implementing this method is estimated to be under 0.4 years.

## Abstract

Lithium is a strategic metal that is essential for the
electrification
of the economy and society as it is commonly used in high-tech applications
and batteries. The EU has mandated that 25% of annual consumption
be sourced from recycling. To achieve this goal in an economic and
ecological manner, recycling processes need to improve in efficiency.
One path toward this aim is by introducing smart control enabled by
process analytical technologies (PATs). In this work, a framework
for the integration of an in-line spectroscopy system with a chemometric
model as a PAT methodological approach for a typical reactive liquid–liquid
extraction using a synergistic solvent with a β-diketone is
exemplified. The concentration of extractants and the degree of saponification
as well as the concentration of metal-ion complexes in the organic
phase are to be measured with FT-IR and Raman spectroscopies. This
is achieved by generating partial least-squares regression models
with a coefficient of regression R
2 of
minimum of 0.95 for application in a continuous process. With these,
a reduction of the chemical cost for a typical lithium purification
plant of 15% with a reduction in the global warming potential (GWP)
of 20% and a return on investment of less than 0.4 years is estimated.