Determining the Surface Energy of Metals Using Machine Learning
Goncharenko V.I. Oleshko V.S. Yurov V.M.
December 2025Pleiades Publishing
Journal of Machinery Manufacture and Reliability
2025#54Issue 8972 - 980 pp.
Abstract: The article is devoted to the development of an original approach to determining the value of the surface energy of metals and products made from them. A method has been developed for determining the value of surface energy based on measuring the contact potential difference, taking into account the surface hardness of the metal being studied. A machine learning model has been developed that allows the gradient boosting method to calculate the value of the surface energy. A practical example shows the application of the developed method for determining the value of the surface energy of parts made of structural and tool steels and alloys.
contact potential difference , correlation , electron work function , gradient boosting , nondestructive testing , python , surface
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Moscow Aviation Institute (National Research University), Moscow, Russian Federation
Limited Liability Partnership TSK Vostok, Karaganda, Kazakhstan
Moscow Aviation Institute (National Research University)
Limited Liability Partnership TSK Vostok
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026