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Photoluminescence: Applications01:14

Photoluminescence: Applications

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Photoluminescence offers a wide range of applications due to its inherent sensitivity and selectivity. This technique allows for both direct and indirect analyses of the analyte. Direct quantitative analysis is possible when the analyte exhibits a favorable quantum yield for fluorescence or phosphorescence. However, an indirect analysis may be feasible if the analyte is not fluorescent or phosphorescent, or if the quantum yield is unfavorable. Indirect methods include reacting the analyte with...
403

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Area of Science:

  • Materials Science
  • Environmental Science
  • Chemical Engineering

Background:

  • Rare earth elements (REEs) are critical strategic resources facing overexploitation and environmental concerns.
  • Recycling REEs from secondary sources like waste fluorescent lamps (WFLs) offers a sustainable solution.
  • Traditional pyrometallurgy and acid leaching methods require extensive optimization, increasing costs and risks.

Purpose of the Study:

  • To develop machine learning (ML) models for optimizing the leaching of six REEs (Tb, Y, Eu, La, Gd) from WFLs.
  • To reduce the cost and environmental impact associated with REE recovery.
  • To provide a rapid method for determining optimal leaching parameters.

Main Methods:

  • Application of machine learning (ML) to predict REE leaching efficiency.
  • Utilizing particle size and waste feed composition as primary input features.
  • Feature importance analysis to identify key factors influencing REE leaching.

Main Results:

  • ML models accurately predicted REE leaching based on particle size and elemental composition (Mg, Al, Fe, Sr, Ca, Ba, Sb).
  • Feature importance analysis revealed significant impacts of particle size and specific elements on REE leaching.
  • Influence rules of these factors on different REEs were elucidated.

Conclusions:

  • ML models enable rapid determination of optimal parameters for REE recycling from WFLs.
  • This intelligent approach significantly lowers recovery costs and minimizes environmental risks.
  • The study establishes a pathway for the smart recycling of strategic REEs from waste materials.