publications

2025

1. 

   Oxide-dispersion-enabled laser additive manufacturing of high-resolution copper

   Shuo Qu^*, Liqiang Wang^*, Shengbiao Zhang^*, Chenfeng Yang, Hou Yi Chia , Gengbo Wu, Zongxin Hu, Junhao Ding, Wentao Yan, Yang Zhang, and others

   Nature Communications, 2025

   DOI

   

2. 

   Determining the bonding–degradation trade-off at heterointerfaces for increased efficiency and stability of perovskite solar cells

   Jinxi Chen^*, Xi Wang^*, Tao Wang, Jia Li, Hou Yi Chia , Haoming Liang, Shibo Xi, Shunchang Liu, Xiao Guo, Renjun Guo, and others

   Nature Energy, 2025

   DOI

   

2024

1. 

   Unveiling gas–liquid metal reactions in metal additive manufacturing: High-fidelity modeling validated with experiments

   Hou Yi Chia , Yanming Zhang, Lu Wang, and Wentao Yan

   Acta Materialia, 2024

   (I.F. 13.20)

   DOI

   

2. 

   Physics-assisted transfer learning metamodels to predict bead geometry and carbon emission in laser butt welding

   Jianzhao Wu, Chaoyong Zhang, Amanda Giam, Hou Yi Chia , Huajun Cao, Wenjun Ge, and Wentao Yan

   Applied Energy, 2024

   I.F. 11.2

   DOI

   

2023

1. 

   Influence of oxygen content on melt pool dynamics in metal additive manufacturing: High-fidelity modeling with experimental validation

   Hou Yi Chia , Lu Wang, and Wentao Yan

   Acta Materialia, 2023

   (I.F. 9)

   Most downloaded paper in the past 90 days DOI

   

   Most downloaded paper in the past 90 days

2. 

   High-Fidelity Modeling of Metal Additive Manufacturing

   Hou Yi Chia and Wentao Yan

   Additive Manufacturing Technology: Design, Optimization, and Modeling, 2023

   

3. 

   A precipitation strengthened high entropy alloy with high (Al+Ti) content for laser powder bed fusion: Synergizing in trinsic hot cracking resistance and ultrahigh strength

   Shiwei Wu, Hou Yi Chia , Tianlong Zhang, Yuefei Jia, Yongkun Mu, Qing Zhang, Yung Zhen Lek, Daijun Hu, Lei Fan, and Wentao Yan

   Acta Materialia, 2023

   DOI

   

2022

1. 

   Process parameter optimization of metal additive manufacturing: a review and outlook

   Hou Yi Chia , Jianzhao Wu, Xinzhi Wang, and Wentao Yan

   Journal of Materials Informatics, 2022

   Best Paper Award 2023, Journal of Material Informatics Abs DOI

   

   Selected as cover page for issue, Best Paper Award 2023

   The selection of appropriate process parameters is crucial in metal additive manufacturing (AM) as it directly influences the defect formation and microstructure of the printed part. Over the past decade, research efforts have been devoted to identifying "optimal" processing regimes for different materials to achieve defect-free manufacturing, which mostly involve costly trial-and-error experiments and computationally expensive mechanistic simulations. Hence, it is apropos to critically review the methods used to achieve the optimal process parameters in AM. This work seeks to provide a structured analysis of current methodologies and discuss systematic approaches toward general optimization work in AM and the process parameter optimization of new AM alloys. A brief review of process-induced defects due to process parameter selection is given and the current methods for identifying "optimal processing windows" are summarized. Research works are analyzed under a standard optimization framework, including the design of experiments and characterization, modelling and optimization algorithms. The research gaps that preclude multi-objective optimization in AM are identified and future directions toward optimization work in AM are discussed. With growing capabilities in AM, we should reconsider the definition of the "optimal processing region".

2. 

   Mechanism of keyhole pore formation in metal additive manufacturing

   Lu Wang, Yanming Zhang, Hou Yi Chia , and Wentao Yan

   npj Computational Materials, 2022

   (I.F. 13.20)

   DOI