Lithium Cell Spectroscopic Sorting for Direct Recycling
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Solution Overview
Problem
Existing sorting processes for energy storage devices, particularly lithium-ion batteries (LIBs), are inefficient in separating based on material chemistries, leading to challenges in recycling and requiring costly and environmentally harmful methods.
Innovation Solution
A system utilizing electromagnetic radiation and spectroscopy to determine the chemical composition of energy storage devices, combined with physical sensing, enables precise sorting by material chemistry, followed by automated packaging for safe transportation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing sorting processes treat LIBs as a monolithic category, then the sorting process is simplified, but the recycling efficiency and material recovery quality deteriorate
Solution Approach 1:
The patent segments LIBs into different categories based on their material chemistries (cathode materials, anode materials, electrolytes, binders). This segmentation enables targeted recycling processes for each material type, improving recycling efficiency and material recovery quality while maintaining manageable process complexity through systematic classification.
Solution Approach 2:
The patent applies local quality by identifying and sorting specific material components within LIBs (different cathode materials like LCO, NMC, LFP; different anode materials; different electrolyte compositions). This allows each material type to be directed to appropriate recycling processes optimized for its specific properties, enhancing overall recycling effectiveness.
2Measurement precision
If advanced spectroscopy and sensing systems are implemented for precise chemical composition analysis, then sorting accuracy improves, but system complexity and cost increase
Solution Approach 1:
The patent replaces manual or simple mechanical sorting methods with spectroscopy-based detection systems (Raman, FTIR, XRD) and physical sensing (mass spectrometry, NMR). These systems automatically identify material chemistries through electromagnetic radiation interaction, providing precise chemical composition analysis without complex mechanical intervention, thereby improving sorting accuracy while managing system complexity through automated analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances recycling efficiency, reduces production costs, and minimizes environmental impact by accurately separating and packaging LIBs, facilitating direct recycling and safer transportation.
Implementation Method 1
detecting an output radiation reflected or backscattered by the energy storage device
Implementation Method 2
detecting an output radiation reflected or backscattered by the energy storage device
Implementation Method 3
detecting an output radiation reflected or backscattered by the energy storage device. The method also includes determining a second electromagnetic spectrum of the output radiation
Data Source
AI summary
A method includes using machine learning to classify and sort energy storage devices based on at least one of the detected chemical or physical properties. In some embodiments, the method can include irradiating an energy storage device with an input radiation and detecting the output radiation reflected or backscattered by the energy storage device. The method may further include detecting a physical property of the energy storage device.