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Nokeun Park

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Articles by Nokeun Park

An advanced machine learning framework for predicting and experimentally validating Nb and Ta effects on the mechanical behavior of high-entropy alloys with reduced experimental dependency

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By Sandeep Kumar Jain, Ayan Bhowmik, Nokeun Park, Ankur Srivastava Verified, Pradyumn Kumar Arya
| Nature Verified
Abstract This study employs machine learning (ML) models such as Decision Tree (DT), Extra Tree (ET), K-Nearest Neighbors (KNN), Support Vector Regressor (SVR) and Lasso to predict how Ta and Nb content effects the mechanical behavior of the CoCrFeNi HEAs at diverse compositions. ET and KNN models developed as the most effective forecasters, accomplishing high R2 values of 0.985 and 0.984 respectively.
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Machine Learning-Based Prediction of Atmospheric Corrosion Rates Using Environmental and Material Parameters

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By SAURABH TIWARI, Nokeun Park, Khushbu Dash
| brnw.ch
1. Introduction Atmospheric corrosion is one of the most economically significant forms of material degradation worldwide, with annual losses estimated at 3%–4% of the global GDP, equivalent to approximately 2.5 trillion USD [1,2]. This phenomenon occurs when metallic materials are exposed to atmospheric environments containing moisture, oxygen, and various pollutants, leading to electrochemical reactions that deteriorate structural integrity over time.
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Machine Learning Approaches for Predicting Mechanical Performance and Reducing Experimentation in Refractory High‐Entropy Alloys

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By Sandeep Kumar Jain, Naresh Kumar Wagri, Nokeun Park, Ayan Bhowmik
| Wiley Online Library Verified
Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adem202403052-sup-0001-SuppData-S1.pdf697.8 KB Supplementary Material References 1, , , , , , , , , J. Alloys Compd. 2020, 823, 153886. 2, , , Int. J. Refract. Met. Hard Mater. 2024, 120, 106572. 3, , , , , Mater. Sci. Eng.: A 2019, 756, 528. 4, , , , , , , , J. Alloys Compd. 2018, 760, 15. 5, , , , Arab. J. Sci. Eng. 2023, 49, 1969. 6, , , , , , , , , , , , J. Alloys Compd. 2016, 680, 116. 7, , , Arab. J. Sci.
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Phase Stability, Microstructure, and Mechanical Properties of Spark Plasma Sintered Nanocrystalline Boron-Doped AlCoFeMnNi High-Entropy Alloy

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By Abbas Bahrami, Nokeun Park, Sahar Pourmohammadi, Ali Mohammadnejad
| MDPI
Abstract : The microstructure and mechanical properties of mechanically alloyed and spark plasma sintered AlCoFeMnNi-xB (x = 0, 0.5, 1, and 5 at. %) high-entropy alloys (HEAs) have been investigated. Boron-doped HEAs were synthesized using mechanical alloying up to 50 h of milling. Synthesized powders were then consolidated at 850, 900, and 950 °C for 10 min under a uniaxial pressure of 40 MPa using spark plasma sintering (SPS).
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