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Microfluidics-Driven Piezophotocatalysis: An Innovative Approach for Accelerated Water Remediation Using PVDF-Transition Metal Sulfide-Based Piezocatalysts.

PubMed
Authors: Rohal A, Katoch V, Kumar A, Pandey A, Prakash B

Year

2026

Paper ID

30270

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

195

Citations

3

Abstract

The growing contamination of water resources with persistent dyes and pharmaceuticals necessitates the development of rapid and energy-efficient remediation technologies. We present a microfluidic purification reactor that synergistically integrates piezophotocatalysis with flow-engineered microstructures to enable rapid pollutant degradation. The microreactor, fabricated from polymethyl methacrylate (PMMA) via laser micromachining, was optimized with strategically positioned micropillars to induce turbulence and enhance mass transfer, with COMSOL Multiphysics simulations validating flow behavior and vorticity patterns. Catalytic functionality was introduced through an electrospun polyvinylidene fluoride (PVDF) nanofiber membrane embedded with MoS and WS nanoparticles forming an active piezophotocatalytic interface within the reactor bed. Structural, compositional, and functional characterizations identified PM15 (15 wt% MoS) and PW20 (20 wt% WS) as optimal nanocomposites, with their electromechanical response validated by a piezoelectric nanogenerator generating ≥36 V. Under optimized operating conditions, flow rate of 50 µL/min, visible-light irradiation, and ultrasonic excitation at 60 kHz, the integrated system achieved rapid degradation efficiencies of ≥94% for RhB and ≥90% for CIP within 252 s, outperforming conventional methods. A multiple linear regression model accurately predicted degradation efficiencies from key operational parameters, demonstrating the utility of data-driven process optimization. Overall, the integrated microfluidic-piezophotocatalyst platform establishes a rapid, high-throughput, and energy-efficient approach for advanced water purification.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • The growing contamination of water resources with persistent dyes and pharmaceuticals necessitates the development of rapid and energy-efficient remediation technologies.

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