0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Sign in to save

Waste-to-sensor upcycling of polyethylene terephthalate over Ag/Zr-MOF photocatalyst for microplastic degradation and AI-assisted heavy metal detection

Figshare 2026
Minse Kim, J H Choi, Kisung Lee, Subin Lee, Jaewon Lee, Jeong-Ann Park, Kwang Suk Lim, Suk-Jin Ha, Hyun‐Ouk Kim

Summary

Scientists created a special material that breaks down plastic bottle waste (PET) using light, turning it into useful chemical byproducts instead of just microplastic pollution. Remarkably, one of these byproducts can act as a built-in sensor that glows differently when it detects toxic heavy metals like copper and iron in water, with AI helping to measure exact contamination levels. This "waste-to-sensor" approach offers a promising two-in-one solution: cleaning up plastic waste while simultaneously monitoring water safety, though it's still early-stage research before this could be used widely.

Polymers

Abstract This study aims to develop an integrated waste to sensor platform that couples photocatalytic PET depolymerization with on stream quantification of coexisting heavy metals. We achieve this by preparing AIM-202 through surface coordination of Ag to a water stable Zr-aspartate MOF (MIP-202), creating Ag0/Agδ+ electron sink sites that enhance charge separation and reactive oxygen species generation while preserving the parent framework. The material was characterized by FT-IR, XRD, XPS, photoluminescence, KPFM, and EPR, and its photocatalytic activity was evaluated under Xe lamp irradiation. AIM-202 (5 mg mL–1) oxidized PET with increased FT-IR oxidation indices and surface pitting, and generated soluble products that increased from 151.40 µmol (week 1) to 277.27 µmol (week 2), corresponding to 11.63% and 28.68% conversion to quantified byproducts. The PET derived fluorophore 2-hydroxyterephthalate enabled fluorescence quenching based Cu2+ and Fe3+ sensing, and physics guided models refined with lightweight machine learning provided robust concentration back calculation. The novelty lies in a closed loop design in which MOF mediated depolymerization simultaneously produces the sensing reporter and enables data assisted quantification, supporting scalable remediation and monitoring within a single integrated scheme.

Share this paper