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<p>Aflatoxin B1 (AFB1) is one of the most toxic and carcinogenic mycotoxins commonly found in food products, creating an urgent need for rapid, highly sensitive, and reliable detection platforms. Although numerous electrochemical immunosensors and aptasensors have been developed for AFB1 monitoring, the simultaneous optimization of magnetic trapping, analyte transport, and electron-transfer efficiency remains insufficiently understood. The major objective of this work was therefore to develop a predictive multiphysics modeling framework for the rational design and optimization of a Fe₃O₄–Au core–shell electrochemical aptasensor for low-limit AFB1 detection. A three-dimensional COMSOL Multiphysics model was developed by coupling magnetic field distribution, magnetophoretic nanoparticle transport, Fickian analyte diffusion, Langmuir adsorption kinetics, charge conservation, and Butler–Volmer electrochemical reactions. The effects of Fe₃O₄ core radius, Au shell thickness, and nanoisland spacing on sensor performance were systematically investigated using a composite figure of merit integrating electrochemical current, magnetic force, and active aptamer area. The simulations identified an optimized configuration consisting of a 50&#xa0;nm Fe₃O₄ core radius, 15&#xa0;nm Au shell thickness, and 400&#xa0;nm nanoisland spacing. Under these conditions, the aptasensor achieved a predicted peak current of ~ 66 nA, sensitivity of 6.7 nA/nM, and a low detection limit of approximately 0.12&#xa0;nM within a linear detection range of 0.1–10&#xa0;nM. The simulated calibration behavior showed good agreement with reported experimental trends (R<sup>2</sup> ≈ 0.988), while uncertainty analysis confirmed robust sensor performance under parameter variations. The results demonstrate that multiphysics-guided optimization of Fe₃O₄–Au nanoarchitectures can significantly enhance electrochemical sensing performance and provides a valuable computational strategy for the development of next-generation electrochemical aptasensors for food safety applications.</p>

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Multiphysics simulation and optimization of a Fe3O4–Au core–shell electrochemical aptasensor for ultrasensitive detection of aflatoxin B1

  • 期刊论文

  • 发表日期：

    2026年6月1日

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  • Faiz Mahmood,
  • Noman Nazeer,
  • Shayan Amiri,
  • Vikram V. Patel,
  • K. S. Kiran,
  • Sanjeev Kumar,
  • Gazal Sharma,
  • Mahnur Jafarli,
  • Ruziyeva Gulsara,
  • M. Atif

摘要

Aflatoxin B1 (AFB1) is one of the most toxic and carcinogenic mycotoxins commonly found in food products, creating an urgent need for rapid, highly sensitive, and reliable detection platforms. Although numerous electrochemical immunosensors and aptasensors have been developed for AFB1 monitoring, the simultaneous optimization of magnetic trapping, analyte transport, and electron-transfer efficiency remains insufficiently understood. The major objective of this work was therefore to develop a predictive multiphysics modeling framework for the rational design and optimization of a Fe₃O₄–Au core–shell electrochemical aptasensor for low-limit AFB1 detection. A three-dimensional COMSOL Multiphysics model was developed by coupling magnetic field distribution, magnetophoretic nanoparticle transport, Fickian analyte diffusion, Langmuir adsorption kinetics, charge conservation, and Butler–Volmer electrochemical reactions. The effects of Fe₃O₄ core radius, Au shell thickness, and nanoisland spacing on sensor performance were systematically investigated using a composite figure of merit integrating electrochemical current, magnetic force, and active aptamer area. The simulations identified an optimized configuration consisting of a 50 nm Fe₃O₄ core radius, 15 nm Au shell thickness, and 400 nm nanoisland spacing. Under these conditions, the aptasensor achieved a predicted peak current of ~ 66 nA, sensitivity of 6.7 nA/nM, and a low detection limit of approximately 0.12 nM within a linear detection range of 0.1–10 nM. The simulated calibration behavior showed good agreement with reported experimental trends (R2 ≈ 0.988), while uncertainty analysis confirmed robust sensor performance under parameter variations. The results demonstrate that multiphysics-guided optimization of Fe₃O₄–Au nanoarchitectures can significantly enhance electrochemical sensing performance and provides a valuable computational strategy for the development of next-generation electrochemical aptasensors for food safety applications.