Lin Gao
- Name
- Dr. Lin Gao
- Institution
- University of Alabama
- Position
- Assistant Professor
- h-Index
- 8
- ORCID
- 0000-0001-8988-7354
- Biography
Dr. Lin Gao is an Assistant Professor in the Department of Mechanical Engineering at the University of Alabama. He conducted his postdoctoral research from 2024 to 2025 at the Nuclear Science and Engineering Division of Argonne National Laboratory, where he focused on Additive Manufacturing of Nuclear Structural Materials. Dr. Gao received his PhD degree in 2023 Fall from the Materials Science and Engineering Department of the University of Virginia. Supervised by Prof. Tao Sun, his doctoral research was focused on the Additive Manufacturing of Metallic Materials and its operando synchrotron X-ray characterization, inducing high-speed X-ray imaging and high-energy X-ray diffraction.
- Expertise
- Additive Manufacturing, Materials Characterization, Materials Science and Engineering, Metallic Materials, Nuclear Materials
| "Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel" Lin Gao, Mark Christian Messner, Srinivas Aditya Mantri, Victoria Cooley, Jun-Sang Park, Xuan Zhang, [2025] Acta Materialia · DOI: 10.1016/j.actamat.2025.121491 | |
| "Characterization of in-situ and ex-situ ion-irradiated additively manufactured 316L and 316H stainless steels" Stephen Taller, Andrea M. Jokisaari, Yiren Chen, Rongjie Song, Xuan Zhang, Lin Gao, Peter M. Baldo, Dzmitry Habaruk, Meimei Li, Wei-Ying Chen, [2025] Journal of Nuclear Materials · DOI: 10.1016/j.jnucmat.2025.156044 | |
| "A mechanistic study on environment gas in laser powder bed fusion" Samuel J. Clark, Lin Gao, Kamel Fezzaa, Tao Sun, Zhongshu Ren, [2025] Additive Manufacturing · DOI: 10.1016/j.addma.2025.104886 | |
| "Evolution of dislocations during the rapid solidification in additive manufacturing" Yan Chen, Xuan Zhang, Sean R. Agnew, Andrew C. Chuang, Tao Sun, Lin Gao, [2025] Nature Communications · DOI: 10.1038/s41467-025-59988-5 | |
| "An operando synchrotron study on the effect of wire melting state on solidification microstructures of Inconel 718 in wire-laser directed energy deposition" Andrew C. Chuang, Peter Kenesei, Zhongshu Ren, Lilly Balderson, Tao Sun, Lin Gao, [2024] International Journal of Machine Tools and Manufacture · DOI: 10.1016/j.ijmachtools.2023.104089 | |
| "Tailoring material microstructure and property in wire-laser directed energy deposition through a wiggle deposition strategy" Jishnu Bhattacharyya, Wenhao Lin, Zhongshu Ren, Andrew C. Chuang, Pavel D. Shevchenko, Viktor Nikitin, Ji Ma, Sean R. Agnew, Tao Sun, Lin Gao, [2023] Additive Manufacturing · DOI: 10.1016/j.addma.2023.103801 | |
| "Stable Multicomponent Multiphase All Active Material Lithium-Ion Battery Anodes" Lin Gao, Tao Sun, Gary M. Koenig, Chen Cai, [2023] ACS Applied Materials & Interfaces · DOI: 10.1021/acsami.3c02896 | |
|
"Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion"
Lin Gao, Samuel J. Clark, Kamel Fezzaa, Pavel Shevchenko, Ann Choi, Wes Everhart, Anthony D. Rollett, Lianyi Chen, Tao Sun, Zhongshu Ren,
[2023]
Science
· DOI: 10.1126/science.add4667
Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems. |
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|
"Machine learning-aided real-time detection of keyhole pore generation in laser powder bed fusion"
Lin Gao, Samuel J. Clark, Kamel Fezzaa, Pavel Shevchenko, Ann Choi, Wes Everhart, Anthony D. Rollett, Lianyi Chen, Tao Sun, Zhongshu Ren,
[2023]
Science
· DOI: 10.1126/science.add4667
· EID: 2-s2.0-85145645594
· ISSN: 1095-9203
Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems. |
|
| "The growth mechanisms of θ′ precipitate phase in an Al-Cu alloy during aging treatment" Kai Li, Song Ni, Yong Du, Min Song, Lin Gao, [2021] Journal of Materials Science & Technology · DOI: 10.1016/j.jmst.2020.05.046 · ISSN: 1005-0302 | |
| "Structural instability of plate-shaped θ’ precipitates in an aged Al-Cu alloy" Lin Gao, Kai Li, Yong Du, Min Song, Yanli Gong, [2020] Philosophical Magazine Letters · DOI: 10.1080/09500839.2020.1810861 · ISSN: 0950-0839 | |
| "Effects of θ′ precipitates on the mechanical performance and fracture behavior of an Al–Cu alloy subjected to overaged condition" Xiaoqin Ou, Song Ni, Kai Li, Yong Du, Min Song, Lin Gao, [2019] Materials Science and Engineering: A · DOI: 10.1016/j.msea.2019.138091 · ISSN: 0921-5093 | |
| "Transformation of fracture mode of an Al-Mg-Si-Cu alloy subject to aging treatment" Lixin Zhang, Ji Gu, Xiaoqin Ou, Song Ni, Kai Li, Yong Du, Min Song, Lin Gao, [2018] Materials Science and Engineering: A · DOI: 10.1016/j.msea.2018.08.028 · ISSN: 0921-5093 | |
| Source: ORCID/CrossRef using DOI | |
About Us
The Nuclear Science User Facilities (NSUF) is the U.S. Department of Energy Office of Nuclear Energy's only designated nuclear energy user facility. Through peer-reviewed proposal processes, the NSUF provides researchers access to neutron, ion, and gamma irradiations, post-irradiation examination and beamline capabilities at Idaho National Laboratory and a diverse mix of university, national laboratory and industry partner institutions.
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