This study investigates the tribological behavior of Al5083 alloy reinforced with AlCoCrFeNiSi high-entropy alloy (HEA) particles using friction stir processing (FSP). Wear characteristics were analyzed using pin-on-disc experiments across varying HEA volume percentages, disc speeds, and test durations, revealing significant improvements in wear resistance with increasing HEA content. Machine learning techniques, including artificial neural networks (ANN) and long short-term memory (LSTM) networks, were employed to predict specific wear rate (SWR) and coefficient of friction (COF) with high accuracy. The ensemble model combining ANN and LSTM architectures achieved R-squared values of 0.9653 for SWR and 0.9718 for COF, with a root mean square error (RMSE) of 0.024 and 0.017 for SWR and COF respectively, indicating robust predictive capabilities. Cross-validation further validated the model's effectiveness, achieving an average prediction error of 2.13% for SWR and 1.89% for COF. Response surface methodology (RSM) optimization refined process parameter relationships, identifying conditions that minimize SWR to 3.57 × 10–6 mm³/Nm and COF to 0.237. Scanning electron microscopy (SEM) analysis of worn surfaces confirmed the effectiveness of HEA reinforcement in mitigating wear mechanisms, enhancing the material's durability by 45% compared to the unreinforced alloy. This comprehensive approach advances the understanding of HEA-reinforced composites. It provides practical insights for optimizing material performance in industrial applications, contributing to developing high-performance materials tailored for durability and wear resistance.
SuganeswaranKMuthukumarPSathiskumarR, et al.Evaluation of microstructural, tribological and tensile characteristics of AA7075 surface composites fabricated through friction stir process. Proc Inst Mech Eng Part E J Process Mech Eng2023; 237: 1–14.
2.
SuganeswaranKMuthukumarPParameshwaranR, et al.Optimization of FSP parameters to fabricate AA7075-based surface composites using Taguchi technique and TOPSIS approach. J Adhes Sci Technol2023; 37: 817–841.
3.
AkbariMAsadiPSadowskiT. A review on friction stir welding/processing: numerical modeling. Materials (Basel)2023; 16: 5890. Epub ahead of print 2023.
4.
KlobčarDPušavecFBračunD, et al.Influence of friction riveting parameters on the dissimilar joint formation and strength. Materials (Basel)Epub ahead of print 2022; 15: 6812.
5.
SharmaVMallickAKumarK. Effect of graphene nanoplates on the mechanical and corrosion properties of aluminium nanocomposite fabricated by powder metallurgy. Tribol Mater2023; 2: 154–161.
6.
LinnZCSweWWMSoeAK, et al.Experimental and numerical analysis on the thermal performance of the aluminium absorber. Tribol Mater2023; 2: 162–171.
7.
SanninoAPRackHJ. Dry sliding wear of discontinuously reinforced aluminum composites: review and discussion. Wear1995; 189: 1–19.
8.
VenclAVučetićFBobićB, et al.Tribological characterisation in dry sliding conditions of compocasted hybrid A356/SiC p /Gr p composites with graphite macroparticles. Int J Adv Manuf Technol2019; 100: 2135–2146.
9.
VenclAVaxevanidisNMKandevaM. A bibliometric analysis of scientific research on tribology of composites in Southeastern Europe. IOP Conf Ser Mater Sci EngEpub ahead of print 2020; 724: 012012.
10.
VenclABobićIStankovićM, et al.Influence of secondary phases in A356 MMCs on their mechanical properties at macro- and nanoscale. J Brazilian Soc Mech Sci Eng2020; 42: 1–12.
11.
EzatpourHRJalalabadiMHuoY, et al.Microstructure, mechanical and tribological properties of Mg/CoCrFeNiMoTi high entropy alloy composites produced via FSP. Eng Fail Anal2024; 161: 108281.
12.
AnaniadisEArgyrisKTMatikasTE, et al.Microstructure and corrosion performance of aluminium matrix composites reinforced with refractory high-entropy alloy particulates. Appl Sci2021; 11: 1–12.
13.
KannanCRamanujamRBalanASS. Mathematical modeling and optimization of tribological behaviour of Al 7075 based hybrid nanocomposites. Proc Inst Mech Eng Part J J Eng Tribol2021; 235: 1561–1574.
14.
Erfani MobarakehSADehghaniK. Microstructural evolutions and corrosion behavior of nanocomposite AlCoCrFeNi2.1 high-entropy alloy produced via friction stir processing. J Mater Res Technol2024; 30: 8345–8358.
15.
RagunathSRadhikaNKrishnaSA, et al.A study on microstructural, mechanical properties and optimization of wear behavior of friction stir processed AlCrCoFeNi high entropy alloy reinforced SS410 using response surface methodology. Heliyon2024; 10: e24429.
16.
Anton Savio LewiseKEdwin Raja DhasJ. FSSW Process parameter optimization for AA2024 and AA7075 alloy. Mater Manuf Process2022; 37: 34–42.
17.
KandasamySRathinasamyPNagarajanN, et al.Assessment of erosion rate on AA7075 based surface hybrid composites fabricated through friction stir processing by taguchi optimization approach. J Adhes Sci Technol2022; 36: 584–605.
18.
SonalSLeeJ. Recent advances in additive manufacturing of high entropy alloys and their nuclear and wear-resistant applications. Metals (Basel)2021; 11: 1–47.
19.
OnawaleOTCobbinahPVMatizamhukaWR, et al.Synthesis route, microstructural evolution, and mechanical property relationship of high-entropy alloys (HEAs): a review. Mater 2021; 14: 3065.
20.
MenJPaidarMEslami-FarsaniR, et al.Investigation on microstructure, mechanical and tribological properties of friction stir processing of AZ31/AlFeCrMoNb surface composite. Mater Chem Phys2024; 317: 129149.
21.
VermaPKSinghA. Mechanical and dry sliding tribological characteristics of aluminium matrix composite reinforced with high entropy alloy particles. Tribol Int2024; 191: 109055.
22.
LiuLXiaHTangY, et al.Microstructure and mechanical properties of CoCrCuFeNi high-entropy alloys synthesized by powder metallurgy and spark plasma sintering. J Mater Eng Perform2023; 1: 1–11.
23.
LiYTangBWuH, et al.Microstructure and wear behavior of AlCoCrFeNiTi0.5 high entropy alloy coating prepared by electron beam cladding on Ti-6Al-4V substrate. J Mater Eng Perform2023; 33: 11240–11249.
24.
VermaPKSinghAKumarA. Microstructure characterization and phase evolution of equiatomic AlCoMoFeNi high entropy alloy synthesized by mechanical alloying. Mater Chem Phys2024; 318: 129325.
25.
OgunbiyiOTianYAkinwandeAA, et al.AA7075/HEA Composites fabricated by microwave sintering: assessment of the microstructural features and response surface optimization. Intermetallics2023; 155: 107830.
26.
KareemSAAnaeleJUAikulolaEO, et al.Aluminium matrix composites reinforced with high entropy alloys: a comprehensive review on interfacial reactions, mechanical, corrosion, and tribological characteristics. J Mater Res Technol2024; 30: 8161–8186.
27.
BhartiSGhetiyaNDPatelKM.Micro-hardness and wear behavior of AA2014/Al2O3 surface composite produced by friction stir processing. SN Appl Sci2020; 2: 1760
28.
RagunathSRadhikaNAravind KrishnaS, et al.Enhancing microstructural, mechanical and tribological behaviour of AlSiBeTiV high entropy alloy reinforced SS410 through friction stir processing. Tribol Int2023; 188: 108840.
29.
AkinwandeAAKumarMSAdesinaOS, et al.Tribological performance of a novel 7068-aluminium/lightweight-high-entropy-alloy fabricated via powder metallurgy. Mater Chem Phys2023; 308: 128207.
30.
WangJTLiuAXZhangYK, et al.Influence of process parameters on wear resistance of surfaces modified by friction stirring processing in 7075 aluminum alloy. Met Mater Int2024; 1: 1–11.
31.
SaravanakumarSSathiyamurthySPathmanabanP, et al.Integrating machine learning and response surface methodology for analyzing anisotropic mechanical properties of biocomposites. Compos Interfaces2024; 31: 1–28.
32.
SengottaiyanSSubbarayanSViswanathanV, et al.Optimized machine learning with hyperparameter tuning and response surface methodology for predicting tribological performance in bio-composite materials. Polym Compos2024; 1: 1–19.
33.
AsadiPAlihaMRMAkbariM, et al.Multivariate optimization of mechanical and microstructural properties of welded joints by FSW method. Eng Fail Anal2022; 140: 106528.
34.
StojanovićBGajevićSKostićN, et al.Optimization of parameters that affect wear of A356/Al2O3 nanocomposites using RSM, ANN, GA and PSO methods. Ind Lubr Tribol2022; 74: 350–359.
35.
FountasNAKechagiasJDVaxevanidisNM. Swarm intelligence algorithms for optimising sliding wear of nanocomposites. Tribol Mater2024; 3: 44–50.
36.
VorkapićMMladenovićIPergalM, et al.Optimisation of tensile stress of poly(lactic acid) 3D printed materials using response surface methodology. Tribol Mater2022; 1: 70–80.
37.
SaravanakumarSSathiyamurthySVinothV. Enhancing machining accuracy of banana fiber-reinforced composites with ensemble machine learning. Meas J Int Meas Confed2024; 235: 114912.
38.
RajamanickamSKManoharanMGanesanS, et al.Mechanical and morphological characteristics study of chemically treated banana fiber reinforced phenolic resin composite with vajram resin. J Nat Fibers2022; 19: 4731–4746.
39.
AbhayaSRajaramanRKalavathiS, et al.Positron annihilation studies on FeCrCoNi high entropy alloy. J Alloys Compd2015; 620: 277–282.
40.
SinghDSarvaiyaJ. Development of AA5052/TiO2/SiC hybrid surface composites using upward material flow through multipass friction stir processing. J Adhes Sci Technol2023; 37: 3335–3357.
41.
YuvarajNAravindanSVipin. Fabrication of Al5083/B4C surface composite by friction stir processing and its tribological characterization. J Mater Res Technol2015; 4: 398–410.
42.
GaoJWangXZhangS, et al.Producing of FeCoNiCrAl high-entropy alloy reinforced Al composites via friction stir processing technology. Int J Adv Manuf Technol2020; 110: 569–580.
43.
ZhangYLeiGLuoK, et al.Tribological behavior of high-entropy alloy particle reinforced aluminum matrix composites and their key impacting factors. Tribol Int2022; 175: 107868.
44.
GirishGAnandakrishnanV. Optimization of dry sliding wear parameters of recursive friction stir processed aluminium 7075 alloy. Proc Inst Mech Eng Part J J Eng Tribol2021; 235: 1222–1231.
45.
SeenivasanSSatishkumarPPrakashKS, et al.Optimized deep learning regression assisted wear rate analysis of Cu-AlCoCrCuFe HEA composite. AIP Adv 2024; 14: 055002.
46.
KayaNÇetinkayaCKarakoçH, et al.Effect of process parameters of Al5083/SiC surface composites fabricated by FSP on microstructure, mechanical properties and wear behaviors. Mater Chem Phys2024; 315: 128991.
47.
RaoTBPonugotiGR. Characterization, prediction, and optimization of dry sliding wear behaviour of Al6061/WC composites. Trans Indian Inst Met2021; 74: 159–178.
48.
KumaravelSSureshP. Optimization of friction stir processing parameters to improve mechanical properties and microstructure of Al5083 aluminum alloy reinforced with AlCoCrFeNiSi high-entropy alloy. Phys Scr2024; 99: 105903.
49.
AdinHSağlamZAdinMŞ. Numerical investigation of fatigue behavior of non-patched and patched aluminum/composite plates. Eur Mech Sci2021; 5: 168–176.
50.
GirishGAnandakrishnanV. Fabrication of Al-Zn-Mg-Cu matrix composite by multi-pass recursive friction stir processing and its characterization. J Mater Eng Perform2021; 30: 5868–5888.
51.
GirishGAnandakrishnanV. A study on the microstructure, hardness, and tribological behavior of aluminum-based metal–matrix composite fabricated through recursive friction stir processing. Proc Inst Mech Eng Part L J Mater Des Appl2021; 235: 671–683.
52.
Shyam KumarCNYadavDBauriR, et al.Effects of ball milling and particle size on microstructure and properties 5083 Al–Ni composites fabricated by friction stir processing. Mater Sci Eng A2015; 645: 205–212.
53.
BauriRYadavDKumarS, , et al.Optimized process parameters for fabricating metal particles reinforced 5083 Al composite by friction stir processing. Data Br2015; 5: 309–313.
54.
AsadiPMirzaeiMHAkbariM. Modeling of pin shape effects in bobbin tool FSW. Int J Light Mater Manuf2022; 5: 162–177.
55.
YuHZhuXWangJ, et al.Differences between tensile properties of WAAM SS304 components in different directions. steel Res Int2023; 94: 2300013.
56.
SeenivasanSSoorya PrakashKNandhakumarS, et al.Influence of AlCoCrCuFe High Entropy Alloy particles on the microstructural, mechanical and tribological properties of copper surface composite made through friction stir processing. Proc Inst Mech Eng Part C J Mech Eng Sci2021; 235: 5555–5566.
57.
AkbariMAsadiPAsiabarakiHR. Investigation of wear and microstructural properties of A356/ TiC composites fabricated by FSP. Surf Rev Lett2022; 29: 10.
58.
SengottaiyanSSubbarayanSViswanathanV, et al.Effect of alumina on epoxy composites with banana fiber: mechanical, water resistance and degradation property analysis. Fibers and Polymers2024; 25: 275–287.
59.
SathiyamurthySSaravanakumarSVinothV. Enhancing tribological performance of hybrid fiber-reinforced composites through machine learning and response surface methodology. J Reinf Plast Compos2024; 1: 073168.
60.
KibreteFTrzepiecińskiTGebremedhenHS, et al.Artificial intelligence in predicting mechanical properties of composite materials. J Compos Sci2023; 7: 64.
61.
Jagadish BhowmikSRayA. Prediction of surface roughness quality of green abrasive water jet machining: a soft computing approach. J Intell Manuf2019; 30: 2965–2979.
62.
PrabhuRKanthababuM. Prediction of surface roughness and depth of cut in abrasive waterjet milling of alumina ceramic using machine learning algorithms. Expert Syst Appl2024; 246: 123168.
63.
BaranirajASathiyagnanamAPVenkateshR, et al.Characterization effect of pozzolanic waste-reinforced A356 alloy composites by liquid metallurgy semisolid stir cast. J Mater Eng Perform2023; 32: 09020.
64.
PeriyappillaiGSathiyamurthySSaravanakumarS. Optimized machine learning prediction and RSM optimization of mechanical properties in boiled eggshell filler-added biocomposites. Fibers Polym2024; 25: 3115–3133.
65.
SaravanakumarSSathiyamurthySAnanthiN, et al.Optimization of drilling characteristics of Al2O3 and boiled eggshell filler-added hybrid bio composite from agriculture residue. Biomass Convers Biorefinery2023; 1: 1–15.
66.
SathiyamurthySSaravanakumarSAnanthiN, et al.Optimization of fiber length and filler content for improving the mechanical behaviour of musa acuminate fiber-reinforced epoxy composite using response surface methodology. J Ceram Process Res2023; 24: 683–692.
67.
VeličkovićSStojanovićBBabićM, et al.Optimization of tribological properties of aluminum hybrid composites using Taguchi design. J Compos Mater2017; 51: 2505–2515.
68.
SoundararajanSMuthukuttiGPKumarasamySP, et al.Investigating the tribological characteristics of copper surface composites reinforced with high entropy alloy (AlCoCrCuFe) through friction stir processing. Sci Rep2023; 13: 1–16.
69.
RadhikaNKrishnaSABasakAK, et al.Microstructure and tribological behaviour of CoCrCuFeTi high entropy alloy reinforced SS304 through friction stir processing. Sci Rep2024; 14: 1–14.
70.
PeriasamyKSivashankarNChandrakumarS, et al.Measurement of friction and wear in aluminum alloy Al7075/Sic & Gr processed by friction stir method. Int J Innov Technol Explor Eng2020; 9: 278–281.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
