Jianxiang Zhao

About Me

I am a postdoctoral fellow in the Department of Mechanical and Industrial Engineering at the University of Toronto, working in the Microcellular Plastics Manufacturing Laboratory with Prof. Chul B. Park.

I work on porous polymers in which structure, not added chemistry, sets the function. Supercritical CO₂ foaming, aerogel synthesis, multilayer coextrusion, and laser micro/nanostructuring each fix pore and layer geometry on a different length scale, from tens of nanometers to hundreds of micrometers. These are the scales that govern solar scattering, mid-infrared emission, heat transport, and mechanical response.

Two directions define my current work.

Passive cooling and adaptive thermal management. I design foams, aerogels, and layered films for passive daytime radiative cooling (PDRC), including shape-memory architectures whose insulation and optical response change with ambient conditions. Our aerogels form a broad, bimodal pore distribution. The two populations serve different functions: pores below the mean free path of air suppress gas-phase conduction, while micron-scale pores scatter across the solar band. This distribution currently emerges from the synthesis rather than being set by it, so a central question in this work is which processing variables move the two pore populations independently. The polymer backbone supplies mid-infrared emissivity, and foaming and coextrusion carry these structures into mechanically robust, continuously processable forms.

Physics-constrained machine learning for polymer processing. Foaming and drying datasets are small and noisy, and each run is expensive, so purely data-driven models extrapolate poorly. I constrain learned models with the governing physics of these processes: gas solubility and diffusion, nucleation kinetics, pore growth, and melt rheology. The constraints reduce unphysical predictions outside the sampled process window. Two near-term targets follow: inverse design of pore architecture from a specified optical or thermal performance, and model-based control of continuous extrusion foaming.

Education

• Ph.D., Mechanical Engineering, University of Toronto, 2025
  Advisor: Prof. Patrick C. Lee
• M.Sc., Chemical Process Equipment, Zhejiang University, 2020
  Advisor: Prof. Zhongbin Xu
• B.Sc., Control Engineering, Xi'an Jiaotong University, 2017

Research Interests

• Multifunctional polymeric materials and advanced manufacturing
• Micro/nano-cellular and micro/nano-layered structures
• Supercritical CO₂ foaming and cellular structure control
• Passive daytime radiative cooling and adaptive thermal management
• Polymer/mineral composites for optical and thermal management
• Shape-memory and adaptive polymer foams
• Energy-efficient building envelopes
• Physics-constrained machine learning for polymer processing
• LLM-based automation in polymer processing research

Technical Expertise

• Multilayer coextrusion of micro/nano-layered films, 17 to 500+ layers
• Supercritical CO₂ foaming, including confined foaming in layered structures
• In situ visualization of cell nucleation and growth under high-pressure CO₂
• Solar reflectance and mid-infrared emissivity measurement (UV-Vis-NIR, FTIR) for radiative cooling
• Thermal conductivity and steady-state insulation measurement
• In situ micro-tensile testing of thin films
• CO₂ and UV laser micro/nanostructuring, including laser-induced forward transfer
• Porous microcapillary film extrusion and gas-assisted microextrusion

Collaboration

I am interested in collaborations on radiative cooling and adaptive thermal management materials, confined foaming and layered polymer processing, and scale-up of these structures toward building and textile applications. I am also open to work applying machine learning to foaming and processing data. Email is the best way to reach me.

Publications

Services

Journal Reviewer

20+ manuscripts reviewed, including for Chemical Engineering Journal, Progress in Additive Manufacturing, and Polymer-Plastics Technology and Materials.

Patents

• A movable-block variable-differentiation-cross section extrusion die for preparing micro-nano structures. CN110253856A
• A method for generating foamed microcapillary films with a dual network of interconnected pores and internal channels. PCT/CN2019/096518

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