journal article·2025-09

Design and evaluation method of erosion-resistant and wear-resistant CoCrFeMnNi high-entropy alloy coating based on molecular dynamics simulation and machine learning

Yunhai Liu, Jiawei Xie, Lang Tang

Corrosion Science· Volume 254
Publisher page

Abstract

No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.

Source: Not provided · Quality: missing

Research context

OpenAlex topics: High Entropy Alloys Studies · High-Temperature Coating Behaviors · Advanced materials and composites

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (52)

Show source-provided references
1. Prediction of thickness loss in a standard 90 elbow using erosion-coupled dynamic mesh
2. Numerical simulation of solid particle erosion in pipe bends for liquid–solid flow10.1016/j.powtec.2016.02.030 ↗
3. Study on erosion wear of fracturing pipeline under the action of multiphase flow in oil & gas industry10.1016/j.jngse.2016.04.056 ↗
4. Atomic-scale analysis of mechanical and wear characteristics of AlCoCrFeNi high entropy alloy coating on Ni substrate10.1016/j.jmapro.2022.12.009 ↗
5. Atomistic simulation of tribology behaviors of Ti-based FeCoNiTi high entropy alloy coating during nanoscratching10.1016/j.vacuum.2023.112124 ↗
6. Molecular dynamics simulation and machine learning of mechanical response in non-equiatomic FeCrNiCoMn high-entropy alloy10.1016/j.jmrt.2021.06.021 ↗
7. Atomic erosion behavior and influence mechanism of (CoCrFeMn) 1–x Ni x high-entropy alloy coating on fracturing pump valves during stimulation operation10.1021/acs.langmuir.4c03092 ↗
8. Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study10.1038/s41524-017-0060-9 ↗
9. Effect of strain rate on the tensile behavior of CoCrFeNi and CoCrFeMnNi high-entropy alloys10.1007/s11665-019-04176-y ↗
10. Effect of oil-based drilling fluid on the evolution of friction interface: a reactive molecular dynamics study at different temperatures10.1016/j.triboint.2023.108820 ↗
11. Effect of hydrogen concentration on the friction evolution mechanism of few-layer graphene: a molecular dynamics study in nanoscratch processes10.1016/j.susc.2023.122414 ↗
12. Effects of cracking on the deformation anisotropy of GaAs with different crystal orientations during scratching using molecular dynamics simulations10.1016/j.triboint.2022.108200 ↗
13. Effects of microstructure and temperature on the mechanical properties of nanocrystalline CoCrFeMnNi high entropy alloy under nanoscratching using molecular dynamics simulation10.1016/j.jallcom.2021.159516 ↗
14. Shock-induced deformation and spallation in CoCrFeMnNi high-entropy alloys at high strain-rates10.1016/j.ijplas.2023.103691 ↗
15. Accelerated design for high-entropy alloys based on machine learning and multiobjective optimization10.1021/acs.jcim.3c00916 ↗
16. Artificial intelligence enhanced molecular simulations10.1021/acs.jctc.3c00214 ↗
17. Utilizing an intelligent machine learning strategy for predicting the tensile strength and ductility properties of nitrogen doped CoCrFeMnNi based high entropy alloys10.1016/j.jallcom.2023.173089 ↗
18. Machine learning approach for predicting yield strength of nitrogen-doped CoCrFeMnNi high entropy alloys at selective thermomechanical processing conditions10.1016/j.jmrt.2023.03.146 ↗
19. Fast parallel algorithms for short-range molecular dynamics10.1006/jcph.1995.1039 ↗
20. LAMMPS-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales10.1016/j.cpc.2021.108171 ↗
21. Nanotribological behaviors of high-entropy alloys CoCrFeMnNi and medium-entropy alloys Ni0. 4Al0. 3Co0. 3, Ni0. 4Cr0. 3Fe0. 3 under different conditions: a molecular dynamics study
22. Atomic erosion behavior and influence mechanism during erosion impact of TiC coatings with different crystal faces in oil production environment: a molecular dynamics simulation10.1016/j.triboint.2024.109320 ↗
23. Molecular Dynamics Investigation of Erosion Behavior and Mechanism of TiN Coatings at the Nanoscale: Implications for Wear in Oil Fracturing Environment10.1021/acsanm.4c04019 ↗
24. Investigation of nano-tribological behaviors and deformation mechanisms of Cu-Ni alloy by molecular dynamics simulation10.1016/j.triboint.2023.108258 ↗
25. Study of tribological property of laser-cladded FeCoCrNiMnx high-entropy alloy coatings via experiment and molecular dynamics simulation10.1016/j.triboint.2023.109106 ↗
26. Study on wear behavior of FeNiCrCoCu high entropy alloy coating on Cu substrate based on molecular dynamics10.1016/j.apsusc.2021.151236 ↗
27. Nano-tribological behavior of high-entropy alloys CrMnFeCoNi and CrFeCoNi under different conditions: a molecular dynamics study10.1016/j.wear.2020.203583 ↗
28. Linear regression10.1002/wics.1198 ↗
29. Ridge regression10.1002/wics.14 ↗
31. Lightgbm: a highly efficient gradient boosting decision tree
32. Predicting failure in the US banking sector: an extreme gradient boosting approach10.1016/j.iref.2018.03.008 ↗
33. CatBoost for big data: an interdisciplinary review10.1186/s40537-020-00369-8 ↗
34. Saunders · 1998
35. XGBoost model for chronic kidney disease diagnosis10.1109/TCBB.2019.2911071 ↗
36. CatBoost: unbiased boosting with categorical features
37. Machine learning-enabled framework for the prediction of mechanical properties in new high entropy alloys10.1016/j.jallcom.2022.164578 ↗
38. Efficient design of lightweight AlCrFeNiTi-based high-entropy alloys via computational thermodynamics and interpretable machine learning10.1016/j.vacuum.2024.113290 ↗
39. High-throughput simulation combined machine learning search for optimum elemental composition in medium entropy alloy10.1016/j.jmst.2020.08.008 ↗
40. A revision of the Fe-Ni phase diagram at low temperatures (< 400C)10.1007/BF02665999 ↗
41. Determination of the Fe− Ni phase diagram below 400C10.1007/BF02667589 ↗
42. Lecture notes on ridge regression
43. Machine learning accelerated design of a family of AlxCrFeNi medium entropy alloys with superior high temperature mechanical and oxidation properties10.1016/j.corsci.2022.110805 ↗
44. Ardabili, S., A. Mosavi, and A.R. Várkonyi-Kóczy. Advances in machine learning modeling reviewing hybrid and ensemble methods, in: International Conference on Global Research and Education, 2019. Springer.10.20944/preprints201908.0203.v1 ↗
45. Prediction of compressive strength of concrete: critical comparison of performance of a hybrid machine learning model with standalone models10.1061/(ASCE)MT.1943-5533.0002902 ↗
46. Atomistic-scale simulations of the chemomechanical behavior of graphene under nanoprojectile impact10.1016/j.carbon.2015.11.052 ↗
47. Surface damage of CuZr metallic glass by hypervelocity nano-projectile: a molecular dynamics study10.1016/j.commatsci.2017.09.019 ↗
48. Tribological characterization of hybrid chromium nitride thin layer synthesized on titanium
49. Study on the erosion resistance of different TiN crystal planes by molecular dynamics
50. Molecular dynamics simulation and machine learning-based analysis for predicting tensile properties of high-entropy FeNiCrCoCu alloys10.1016/j.jmrt.2023.07.023 ↗
51. Nanoscale insights into the anti-erosion performance of concrete: a molecular dynamics study10.1016/j.apsusc.2022.153403 ↗
52. A machine learning interatomic potential for high entropy alloys10.1016/j.jmps.2024.105639 ↗