JOJMS HomeResearch Article April 10, 2026
Machine Learning-Based Dynamic Performance Prediction and Structural Parameter Optimization of a Two-Stage Hydrogen Pressure Reducing Valve
Huaxing Zhai*, Yu Zhang, Shuxun Li, Wei Li and Lingxia Yang
JOJ Material Science is a multidisciplinary open access, peer reviewed Journal that accomplishes in all aspects of new materials & their advancements. Material Science is a versatile subject, spanning the physics, engineering applications, chemistry of matter and industrial manufacturing processes. The theory behind the material science involves discovering and designing new materials, analyzing their properties and structure. It is also vital for developments in nanotechnology, quantum computing and nuclear fusion, as well as medical technologies such as bone replacement materials. This platform provides a global stage for material scientists aim to publish full-length papers, Short Communications, Reviews, Original research results on ceramics, metals, polymers, Semiconductors, Composites, etc.
Huaxing Zhai*, Yu Zhang, Shuxun Li, Wei Li and Lingxia Yang
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Dudu Mertgenç Yoldaş*, Senai Yalçinkaya and Mehmet Fatih Yoldaş
Tathagata Bhattacharjya* Department of Materials Engineering
Qian Qiao, Dawei Guo*, Hongchang Qian, Zhong Li , Guoshun Yang, Chi Tat Kwok and Lap Mou Tam*
Qian Qiao , Yongyong Lin, Dawei Guoa,*, Chi Tat Kwokd, Guoshun Yange , Mengyu Lie and Lap Mou Tama*
Open Access by Juniper Publishers is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at www.juniperpublishers.com. 
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