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Jun-Jing HeDr. | Master |
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Degree: Dr. Post: Research direction: Predictive Fundamental Materials Theory Career: Graduate School: KTH Royal Institute of Technology Office phone: Address: Email: junjing@kth.se Postcode: |
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Resume Jun-Jing He, Male, 1986, Doctoral degree, KTH Royal Institute of Technology. Education 2012.10 - 2016.11, Doctor degree, KTH Royal Institute of Technology Supervisors: Prof. Rolf Sandström and Prof. Pavel Korzhavy Work Experience 2018 - now, Lecturer, Master's Supervisor, Hangzhou Dianzi University Social Position Reviewers for International Journals, e.g., Advanced Materials, Int. J. Plasticity, Int. J. Fatigue, etc. Research Field Fundamental creep models; High-temperature metallic structural materials; Creep damage mechanisms; Creep life assessment; Creep rupture prediction; Machine learning; Multiscale theoretical models. International center for Predictive Fundamental Materials Theory
Pedagogical Projects Principal Investigator, HDU Pedagogical reform project; 2022-2023 Project title: Exploring efficient classroom teaching based on Material Structure and Properties. Pedagogical Publications Jun-Jing He*, et al., 2022, Exploring the practical teaching issues and their solutions based on Metallic Materials, Guangzhou Chemical Industry. Jun-Jing He*, et al., 2021, Exploration on Online and Offline Mixed Teaching Mode for Principles of metals, Guangzhou Chemical Industry. Pedagogical Awards and Merits o 2022, Teaching Star, Honor of MEE, HDU. o 2021, First prize, No. 1, Rewards for excellent course in MEE, HDU. o 2020, Second Prize of 13th Teaching Skills Competition of HDU. Longitudinal research
1. Principal Investigator, National Natural Science Foundation of China (NSFC); CNY 310000; 2020-2022. Fundamental creep models of austenitic stainless steels: grain size effects and creep cavitation 2. Principal Investigator, Natural Science Foundation of Zhejiang Province, CNY 100000; 2022-2024. Prediction of creep ductility of austenitic steels based on micro-mechanism and Neural Network 3. Participant, Natural Science Foundation of Zhejiang Province Key projects, CNY 300000; 2022-2024. Transverse scientific research
Publications
1. L. Kuang, et al. 2024, Atomically dispersed high-loading Pt-Fe/C metal-atom foam catalyst for oxygen reduction in fuel cells, J. Alloys Compd. IF: 6.2 2. Jun-Jing He*, Rolf Sandström*, et al. 2023, Evaluating creep rupture life in austenitic and martensitic steels with soft-constrained machine learning, JMR&T. IF: 6.4 3. Jun-Jing He*, Rolf Sandström*, et al. 2023, Application of soft constrained machine learning algorithms for creep rupture prediction of an austenitic heat resistant steel Sanicro 25, JMR&T. IF: 6.4 4. Jun-Jing He*, Rolf Sandström*, et al., 2023, The role of strength distributions for premature creep failure, JMR&T. IF: 6.4 5. Jun-Jing He*, Rolf Sandström*, 2022, Creep Rupture Prediction Using Constrained Neural Networks with Error Estimates, Mater High Temp. 6. Junjing He*, Rolf Sandström, 2019, Application of Fundamental Models for Creep Rupture Prediction of Sanicro 25 (23Cr25NiWCoCu), Crystals. 7. Junjing He*, Rolf Sandström, 2017, Basic modelling of creep rupture in austenitic stainless steels, TAFM. IF: 5.3 8. Junjing He*, Rolf Sandström, et al., 2017, Low cycle fatigue properties of a nickel based superalloy Haynes 282 for heavy components, JMEP. 9. Junjing He*, Rolf Sandström, 2016, Creep cavity growth models for austenitic stainless steels, MSEA. IF: 6.4 10. Junjing He*, Rolf Sandström, 2016, Formation of creep cavities in austenitic stainless steels. J Mater Sci. IF: 4.5 11. Junjing He*, Rolf Sandström, 2015, Modelling grain boundary sliding during creep of austenitic stainless steels. J Mater Sci. IF: 4.5 12. Rolf Sandström, Jun-Jing He*, 2022, Error estimates in extrapolation of creep rupture data and its application to an austenitic stainless steel, Materials at High Temperatures. 13. Rolf Sandström*, Jun-Jing He, 2022, Prediction of creep ductility for austenitic stainless steels and copper, Materials at High Temperatures. 14. Rolf Sandström*, Junjing He, 2021, Error Estimates in Extrapolation of Creep Rupture Data: Applied to an Austenitic Stainless Steel, ASME PVP2021, Virtual, Online, 2021. 16. Jing Zhang, Pavel A. Korzhavyi, Junjing He, 2020, Investigation on elastic and thermodynamic properties of Fe25Cr20NiMnNb austenitic stainless steel at high temperatures from first principles, Computational Materials Science. 17. Rolf Sandström*, Junjing He, 2017, Survey of creep cavitation in fcc metals, Study of Grain Boundary Character. InTech. 18. Junjing He*, Rolf Sandström, Stojan Vujic, 2016, Creep, low cycle fatigue and creep-fatigue properties of a modified HR3C. Procedia Structural Integrity 2, pp. 871-878. 19. Junjing He*, Rolf Sandström, 2016, Brittle rupture of austenitic stainless steels due to creep cavitation. Procedia Structural Integrity. 20. Junjing He*, Rolf Sandström, 2015, Growth of Creep Cavities in Austenitic Stainless Steels. 8th European Stainless Steel & Duplex Stainless Steel Conference, Graz. International Conferences Contributions 1. 2023, 11th China-Japan Bilateral Symposium on High Temperature Strength of Materials, China 2. 2022, 14th National High-Temperature Materials, China. 3. 2022, 8th China Structural Materials, China 4. 2021, Creep2021, Digital, FAU, Germany. 5. 2021, Pressure Vessels & Piping PVP 2021, The American Society of Mechanical Engineers, Online. US. 6. 2019, 3r Forum of Materials Genome Engineering, China. 7. 2016, 21st European Conference on Fracture (ECF21), Italy. 8. 2015, Creep 2015, France. 9. 2015, 8th European Stainless Steel & Duplex Stainless Steel, Austria. Patents 1. Jun-Jing He*, et al. 2022, A method of predicting premature creep failure of high temperature alloys based on strength distribuiton. 2. Jun-Jing He*, et al. 2022, A method of predicting the creep properties of structural metallic materials based on hard constrained Neural Networks. 3. Jun-Jing He*, et al. 2022, A method of predicting the creep performance of high temperature alloys based on soft constrained Neural Networks. Books
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