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<p>Despite the growing interest in multi-wavelength vat photopolymerization (VPP), predictive modelling of dual-reaction, multi-component resins remains limited due to the coupled effects of wavelength-dependent light attenuation, simultaneous curing kinetics, and thermal–mechanical interactions. This work addresses this gap by presenting a comprehensive multiphysics framework for dual-wavelength VPP capable of accurately predicting curing behavior in a non-orthogonal, one-pot resin containing both acrylate (HEA) and epoxy (EPOX) components. The model integrates Beer–Lambert-based optical attenuation, dual-reaction autocatalytic curing kinetics, exothermic heat generation, transient heat transfer, and polymerization-induced shrinkage within a unified simulation environment. Reaction kinetics were extracted from Photo-DSC measurements using a combination of inverse heat conduction solutions, nonlinear optimization and Bayesian inference, incorporating light attenuation effects, while experimentally measured thermal properties were directly input into COMSOL Multiphysics. An axisymmetric geometry was employed for computational efficiency and validated against controlled single-layer prints at multiple UV (365&#xa0;nm) and blue (460&#xa0;nm) intensities. In-situ infrared thermal imaging and ex-situ profilometry confirmed strong agreement with simulations, achieving root-mean-square errors as low as 0.5% for temperature and 0.4% for part thickness under practical exposure conditions. The framework was further demonstrated on non-axisymmetric dual-exposure patterns, predicting thermal fields within ~ 5&#xa0;K and capturing spatially resolved curing behavior. While developed for dual-wavelength VPP, the approach is readily applicable to conventional single-wavelength systems, offering a generalizable workflow for predictive simulation, process optimization, and rapid adaptation to new resin formulations. This methodology enables advanced multi-material VPP applications, including functionally graded structures and soft robotic devices.</p>

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Multiphysics modelling and simulation of dual-wavelength vat photopolymerization

  • 期刊论文

  • 发表日期：

    2026年7月2日

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  • Heyang Zhang,
  • Xiayun Zhao

摘要

Despite the growing interest in multi-wavelength vat photopolymerization (VPP), predictive modelling of dual-reaction, multi-component resins remains limited due to the coupled effects of wavelength-dependent light attenuation, simultaneous curing kinetics, and thermal–mechanical interactions. This work addresses this gap by presenting a comprehensive multiphysics framework for dual-wavelength VPP capable of accurately predicting curing behavior in a non-orthogonal, one-pot resin containing both acrylate (HEA) and epoxy (EPOX) components. The model integrates Beer–Lambert-based optical attenuation, dual-reaction autocatalytic curing kinetics, exothermic heat generation, transient heat transfer, and polymerization-induced shrinkage within a unified simulation environment. Reaction kinetics were extracted from Photo-DSC measurements using a combination of inverse heat conduction solutions, nonlinear optimization and Bayesian inference, incorporating light attenuation effects, while experimentally measured thermal properties were directly input into COMSOL Multiphysics. An axisymmetric geometry was employed for computational efficiency and validated against controlled single-layer prints at multiple UV (365 nm) and blue (460 nm) intensities. In-situ infrared thermal imaging and ex-situ profilometry confirmed strong agreement with simulations, achieving root-mean-square errors as low as 0.5% for temperature and 0.4% for part thickness under practical exposure conditions. The framework was further demonstrated on non-axisymmetric dual-exposure patterns, predicting thermal fields within ~ 5 K and capturing spatially resolved curing behavior. While developed for dual-wavelength VPP, the approach is readily applicable to conventional single-wavelength systems, offering a generalizable workflow for predictive simulation, process optimization, and rapid adaptation to new resin formulations. This methodology enables advanced multi-material VPP applications, including functionally graded structures and soft robotic devices.