About Me

Mingpei Cang is a PhD candidate in smart manufacturing at the Hong Kong University of Science and Technology. His research interests include process optimization of high-resolution projection SLA 3D printer, development of in-situ monitoring solutions for SLA 3D printing, and design of mechanical metamaterials.

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Interests
  • Projection stereolithography
  • Lattice structures design
Education

  • PhD in Smart Manufacturing

    The Hong Kong University of Science and Technology

  • BEng in Engineering Mechanics

    Dalian University of Technology

📚 My Research

I’m a PhD candidate in Smart Manufacturing at the Hong Kong University of Science and Technology, where I work on high-precision projection stereolithography and mechanical metamaterials under supervison of Dr. Huachen Cui and Prof. Michael Yu Wang.

My research focuses on

  1. enabling high resolution SLA via process optimizaiton,
  2. developing real-time in-situ monitoring systems for SLA, and
  3. designing high-performance lattice structures as mechanical metamaterials.

I’m always open to collaboration with researchers and engineers working on manufacturing science, mechanical design, or computational modeling. Please reach out to collaborate!

Projects
Geometric characteristics analysis and design of bone-mimicking lattices
Geometry Processing

Geometric characteristics analysis and design of bone-mimicking lattices

In this project, I engineered advanced bone-mimicking scaffolds by integrating computational geometry analysis with implicit modeling techniques. My primary role was to define and replicate the precise topological features of native bone to create functionally superior lattice structures for tissue engineering. Advanced Geometric Analysis: ⦁ Processed high-resolution µCT scans of bone tissue to generate high-fidelity triangle meshes. ⦁ Implemented a multiscale fitting method using the C++ library libigl to calculate principal (κ1​,κ2​) and Gaussian (K) curvatures at each vertex, quantifying the local surface shape. ⦁ Characterized the bone’s unique Interface Shape Distribution (ISD) by applying bivariate Kernel Density Estimation (KDE) to the curvature data, providing a quantitative benchmark for bio-mimicry. Our analysis confirmed the prevalence of hyperboloidal (saddle-shaped) surfaces, a key driver for osteogenesis. Implicit Modeling & Lattice Design: ⦁ Utilized MATLAB to programmatically generate complex, porous architectures based on Triply Periodic Minimal Surfaces (TPMS), including Gyroid and Diamond structures. ⦁ We developed gradient and hybrid-gradient (hybrid-G) lattices by manipulating the implicit TPMS equations to vary porosity and combine geometries, directly mimicking the heterogeneity found in native bone. ⦁ Engineered all models to match the target average porosity (70%) of the bone specimen by precisely offsetting the implicit surfaces. Computational Verification & Visualization: ⦁ Validated our lattice designs by performing the same rigorous curvature analysis on them and comparing their ISDs against the original bone data benchmark. ⦁ Employed Paraview to create detailed 3D visualizations of the Gaussian curvature fields, confirming that hybrid-G design most accurately replicated the critical hyperboloidal characteristics of the target tissue. Publications related to this project: 10.1016/j.mser.2024.100876

High resolution projection stereolithography via process optimization
In-situ monitoring of stereolithography - printing defects and dimension mismatch
Optimization of manufacturability and compression strength for open-cell plates lattices
Lattice Struture Design

Optimization of manufacturability and compression strength for open-cell plates lattices

In this project, we developed and validated a novel design methodology to enhance the manufacturability and buckling strength of metallic plate lattices. The core challenge was to introduce micro-holes for powder removal in additive manufacturing without the typical reduction in mechanical performance, particularly against buckling failure in low-density structures. Theoretical & Numerical Method Development: ⦁ We established a design framework rooted in a Rayleigh quotient-based theoretical criterion to identify the optimal locations for micro-holes that actively increase the critical buckling load of a plate. ⦁ To implement this, we developed a robust numerical method to evaluate the second-order derivatives of the buckling eigenmode. This was achieved by directly utilizing the shape functions of 8-node second-order shell elements (S8R) within Abaqus. Finite Element Analysis & Design Optimization: ⦁ We applied this methodology to design optimized Simple Cubic (SC), Body-Centered Cubic (BCC), and Face-Centered Cubic (FCC) perforated plate lattices. ⦁ Using Abaqus/Standard and Abaqus/Explicit, we performed a comprehensive suite of simulations, including linear eigenvalue buckling on Representative Volume Element (RVE) models with periodic boundary conditions, nonlinear post-buckling analysis incorporating geometric and material nonlinearities, and large-deformation compression simulations on full-scale models. ⦁ Our analysis successfully demonstrated that the optimized designs increased critical buckling stress by up to 15.1% compared to unperforated lattices, while maintaining comparable post-buckling compressive strength. Experimental Validation & Characterization: (by our collaborators) ⦁ We fabricated the optimized lattice specimens using μ-LPBF with SS316L powder. ⦁ Through quasi-static compression testing, we experimentally verified that the fabricated lattices exhibit superior mechanical properties. Publications related to this project: 10.1016/j.matdes.2024.113544

Optimization of buckling strength for truss lattice with freeform cross-sections
Lattice Struture Design

Optimization of buckling strength for truss lattice with freeform cross-sections

This project focuses on analysis and optimization of thin struts in lattice core sandwich panels. Lightweight lattice cores are easy to fail by buckling due to its long slenderness ratio. We optimized thin struts in lattice core sandwich structures to improve buckling resistance. The key innovation was an efficient, bottom-up methodology that avoids computationally expensive optimizations on entire structures. Methodology & Strut Optimization We developed an efficient, bottom-up design methodology to improve the buckling strength of lattice core sandwich structures. The strategy involved first identifying the optimal, non-uniform cross-sections of individual struts by maximizing their buckling eigenvalues using a Python-Abaqus scripted workflow. Strut profiles were modeled with a Fourier Series (FS) representation, and a key finding was that the optimal shapes are proportionally scalable, creating a reusable library of high-performance struts. Lattice Design & Simulation We designed four distinct non-uniform lattice cores (Kagome, BCC, BCCZ, and Six-fold) by strategically replacing uniform struts with pre-optimized shapes based on their specific, identified buckling modes (first or second-order). Comprehensive eigenvalue and nonlinear post-buckling (Riks method) analyses in Abaqus confirmed these designs achieved a 16-21% improvement in critical buckling load over uniform counterparts. Experimental Validation We validated the designs by fabricating BCC and Six-fold specimens from Nylon 12 powder using Selective Laser Sintering (SLS). Quasi-static compression tests demonstrated a measured compressive strength improvement of 18.77% for the BCC structure and 10.00% for the Six-fold. We also developed a high-fidelity nonlinear FE model that incorporated material plasticity and a measured 80µm surface roughness layer, achieving excellent agreement with experimental peak loads and failure mechanisms. Publications related to this project: 10.1080/0305215X.2022.2163239

Recent & Upcoming Talks
Achieving Sub-pixel Level Feature Size for Projection Stereolithography via Precise Spatial and Temporal Control of Photopolymerization
Process Optimization of PµSL for Assembly-Free Fabrication of Micro Transmission Mechanisms
Recent Publications
Annan Chen#, Jin Su#, Muran Zhou#, Mingpei Cang, Yinjin Li, Yunsong Shi, Zhen Zhang, Yangzhi Zhu, Bin Su, Yang Liu, Zuo-Guang Ye, Yusheng Shi, Jüergen Röedel, Huachen Cui, Haibo Zhang*, Kun Zhou*, Jian Lu*, Chunze Yan* (2025). Biocompatible piezoelectric lattice materials with ultrasound-regulated multimodal responses. Materials Science and Engineering: R: Reports.
Cite Project DOI URL
Lei Zhang#, Mingpei Cang#, Junhao Ding, Winston Wai Shing Ma, Xiangyang Zhu, Yang Lu, Xu Song, Huachen Cui*, Michael Yu Wang* (2025). Metallic perforated plate lattices with superior buckling strength. Materials & Design.
Cite Project DOI URL
Mingpei Cang#, Lei Zhang#, Yiqiang Wang*, Jin Fu, Zhen Luo, Zhan Kang, Ming Wang Fu, Michael Yu Wang (2023). An efficient method for design of lattice core sandwich structures with superior buckling strength under compression. Engineering Optimization.
Cite Project DOI URL