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Abstract

This study highlights the importance of Al–Fe–Si alloys in modern engineering for their enhanced hardness, strength, and wear resistance, improving fuel efficiency in the aerospace and automotive sectors. Data-driven analysis and machine learning methods can help understand tribological occurrences by identifying links between material characteristics and tribological behavior. The research examined TiC reinforcement in aluminum nanocomposites synthesized via ultrasonic-assisted stir casting, creating five composites with TiC weight percentages from 0% to 8%. Tests conducted using pin-on-disc equipment under various conditions, including loads of 5–15 N, sliding velocities of 0.5–1.5 m/s, sliding distances of 80–120 m, and abrasive grit sizes of 80–150 µm, revealed significant findings. The Al–6TiC nanocomposite demonstrated an 18% reduction in wear-rate at 80 µm, 28.2% at 120 µm, and 24.5% at 150 µm under a 15 N load and 120 m sliding distance compared to the pure alloy. There was also a 22% friction coefficient reduction with increased loads and grit sizes. Scanning electron microscope (SEM) analysis of the worn surfaces and abrasive papers was conducted. Wear-rate data were analyzed using six machine learning models, with the gradient boosting regressor (GBR) identified as the most accurate, achieving an R2 value of 0.95. This study emphasizes the impact of the TiC content, loading conditions, and hardness on wear and friction coefficient, and shows how machine learning techniques can predict and optimize advanced aluminum nanocomposite design for engineering applications.

References

1.
Prakash
,
S.
,
Suresh
,
P.
,
Sasikumar
,
R.
, and
Suresha
,
B.
,
2024
, “
Superior Mechanical Properties of Aluminum Matrix Composites Fabricated Through Modified Matrix Encapsulated Feeding Method
,”
Trans. Indian Inst. Met.
,
3
, pp.
707
716
.
2.
Umanath
,
K.
,
Palanikumar
,
K.
, and
Selvamani
,
S. T.
,
2013
, “
Analysis of Dry Sliding Wear Behaviour of Al6061/SiC/Al2O3 Hybrid Metal Matrix Composites
,”
Composites, Part B
,
53
, pp.
159
168
.
3.
Fayomi
,
J.
,
Popoola
,
A. P. I.
,
Popoola
,
O. M.
,
Oladijo
,
O. P.
, and
Fayomi
,
O. S. I.
,
2019
, “
Results in Physics Tribological and Microstructural Investigation of Hybrid AA8011/ZrB2-Si3N4 Nanomaterials for Service Life Improvement
,”
Results Phys.
,
14
, pp.
102
469
.
4.
Rao
,
R. N.
, and
Das
,
S.
,
2011
, “
Effect of Applied Pressure on the Tribological Behaviour of SiCp Reinforced AA2024 Alloy
,”
Tribol. Int.
,
44
(
4
), pp.
454
462
.
5.
Venkatesh
,
V. S. S.
,
Ganji
,
P. R.
,
Rao
,
R. N.
, and
Bhowmik
,
A.
,
2023
, “
Tribological Characteristics of Spark Plasma Sintered Al-6 wt%SiC Composite Explored by Gray-Fuzzy Optimization Approach
,”
J. Mater. Eng.
,
33
(
15
), pp.
7915
7929
.
6.
Rao
,
R. N.
, and
Das
,
S.
,
2010
, “
Effect of Matrix Alloy and Influence of SiC Particle on the Sliding Wear Characteristics of Aluminum Alloy Composites
,”
Mater. Des.
,
31
(
3
), pp.
1200
1207
.
7.
Baradeswaran
,
A.
,
Vettivel
,
S. C.
,
Elaya Perumal
,
A.
,
Selvakumar
,
N.
, and
Franklin Issac
,
R.
,
2014
, “
Experimental Investigation on Mechanical Behaviour, Modelling and Optimization of Wear Parameters of B4C and Graphite Reinforced Aluminum Hybrid Composites
,”
Mater. Des.
,
63
, pp.
620
632
.
8.
Vinoth
,
B.
,
Alagarsamy
,
S. V.
,
Meignanamoorthy
,
M.
, and
Ravichandran
,
M.
,
2022
, “
Prediction of Tribological Performance of AA8011/wt%ZrO2 Based Composites Fabricated by Stir Casting Route
,”
Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng.
,
236
(
6
), pp.
2420
2433
.
9.
Baskaran
,
S.
,
Anandakrishnan
,
V.
, and
Duraiselvam
,
M.
,
2014
, “
Investigations on Dry Sliding Wear Behavior of In Situ Casted AA7075 – TiC Metal Matrix Composites by Using Taguchi Technique
,”
J. Mater.
,
60
, pp.
184
192
.
10.
Munivenkatappan
,
M. S. B.
,
Veeramani
,
A.
, and
Muthukannan
,
D.
,
2018
, “
Investigation of Tribological Behavior of AA8011-Zrb2 In-Situ Cast-Metal-Matrix Composites
,”
Mater. Tehnol.
,
52
(
4
), pp.
451
457
.
11.
Koksal
,
S.
,
Ficici
,
F.
,
Kayikci
,
R.
, and
Savas
,
O.
,
2012
, “
Experimental Optimization of dry Sliding Wear Behavior of In Situ AlB2/Al Composite Based on Taguchi’s Method
,”
Mater. Des.
,
42
, pp.
124
130
.
12.
Ramakoteswara Rao
,
V.
,
Ramanaiah
,
N.
, and
Sarcar
,
M. M. M.
,
2016
, “
Dry Sliding Wear Behavior of TiC-AA7075 Metal Matrix Composites
,”
Int. J. Appl. Sci. Eng.
,
14
(
1
), pp.
27
37
.
13.
Ravi Kumar
,
K.
,
Kiran
,
K.
, and
Sreebalaji
,
V. S.
,
2017
, “
Microstructural Characteristics and Mechanical Behaviour of Aluminum Matrix Composites Reinforced With Titanium Carbide
,”
J. Alloys Compd.
,
723
, pp.
795
801
.
14.
Kumar
,
A.
,
Gautam
,
R. K.
, and
Tyagi
,
R.
,
2016
, “
Dry Sliding Wear Characteristics of In Situ Synthesized Al-TiC Composites
,”
Compos. Interfaces
,
1
(
1
), pp.
469
480
.
15.
Sahin
,
Y.
,
2003
, “
Wear Behaviour of Aluminum Alloy and Its Composites Reinforced by SiC Particles Using Statistical Analysis
,”
Mater. Des.
,
14
(
2
), pp.
95
103
.
16.
Sekhar
,
A. P.
, and
Das
,
D.
,
2022
, “
Two-Body Abrasive Wear Behavior and Its Correlation With Mechanical Properties of Aged AA6063 Alloy
,”
ASME J. Tribol.
,
114
(
7
), p.
071703
.
17.
Jerome
,
S.
,
Ravisankar
,
B.
,
Mahato
,
P. K.
, and
Natarajan
,
S.
,
2010
, “
Tribology International Synthesis and Evaluation of Mechanical and High Temperature Tribological Properties of In-Situ Al–TiC Composites
,”
Tribol. Int.
,
24
(
11
), pp.
2029
2036
.
18.
Rokni
,
M. R.
,
Widener
,
C. A.
,
Ozdemir
,
O. C.
, and
Crawford
,
G. A.
,
2017
, “
Microstructure and Mechanical Properties of Cold Sprayed 6061 Al in as-Sprayed and Heat Treated Condition
,”
Surf. Coatings Technol.
,
309
, pp.
641
650
.
19.
Baradeswaran
,
A.
, and
Elaya Perumal
,
A.
,
2014
, “
Study on Mechanical and Wear Properties of Al 7075/Al2O3/Graphite Hybrid Composites
,”
Composites, Part B
,
56
, pp.
464
471
.
20.
Ch Kaushik
,
N.
, and
Rao
,
R. N.
,
2016
, “
The Effect of Wear Parameters and Heat Treatment on Two Body Abrasive Wear of Al-SiC-Gr Hybrid Composites
,”
Tribol. Int.
,
96
, pp.
184
190
.
21.
Dinesh Kumar
,
K.
,
Geeta
,
A.
, and
Rajesh
,
P.
,
2015
, “
Influence of Ultrasonic Assisted Stir Casting on Mechanical Properties of Al6061-Nano Al2O3 Composites
,”
Mater. Today Proc.
,
2
(
4–5
), pp.
3017
3026
.
22.
Hasan
,
M. S.
,
Kordijazi
,
A.
,
Rohatgi
,
P. K.
, and
Nosonovsky
,
M.
,
2021
, “
Triboinformatic Modeling of dry Friction and Wear of Aluminum Base Alloys Using Machine Learning Algorithms
,”
Tribol. Int.
,
16
(
2
), p.
107065
.
23.
Gangwar
,
S.
, and
Pathak
,
V. K.
,
2020
, “
Dry Sliding Wear Characteristics Evaluation and Prediction of Vacuum Casted Marble Dust (MD) Reinforced ZA-27 Alloy Composites Using Hybrid Improved bat Algorithm and ANN
,”
Mater. Today Commun.
,
25
, p.
101615
.
24.
Golla
,
C. B.
,
Babar Pasha
,
M.
,
Rao
,
R. N.
,
Ismail
,
S.
, and
Gupta
,
M.
,
2023
, “
Influence of TiC Particles on Mechanical and Tribological Characteristics of Advanced Aluminum Matrix Composites Fabricated Through Ultrasonic-Assisted Stir Casting
,”
Crystals
,
13
(
9
), p.
1360
.
25.
Balamurugan
,
K.
,
Shanmugam
,
V.
,
Palani
,
G.
,
Sundarakannan
,
R.
,
Sathish
,
T.
,
Linul
,
E.
,
Khan
,
S. A.
, and
Asif
,
M.
,
2023
, “
Effect of TiC/RHA on Solid Particle Erosion of Al6061 Hybrid Composites Fabricated Through a 2-Step Ultrasonic-Assisted Stir Casting Process
,”
J. Mater. Res. Technol.
,
25
, pp.
4888
4900
.
26.
Prasad Reddy
,
A.
,
Vamsi Krishna
,
P.
, and
Rao
,
R. N.
,
2019
, “
Two-Body Abrasive Wear Behaviour of AA6061-2SiC-2Gr Hybrid Nanocomposite Fabricated Through Ultrasonically Assisted Stir Casting
,”
J. Compos. Mater.
,
53
(
15
), pp.
2165
2180
.
27.
Rao
,
R. N.
,
Das
,
S.
,
Mondal
,
D. P.
,
Dixit
,
G.
, and
Tulasi Devi
,
S. L.
,
2013
, “
Dry Sliding Wear Maps for AA7010 (Al-Zn-Mg-Cu) Aluminum Matrix Composite
,”
Tribol. Int.
,
60
, pp.
77
82
.
28.
Aydin
,
F.
,
Durgut
,
R.
,
Mustu
,
M.
, and
Demir
,
B.
,
2023
, “
Prediction of Wear Performance of ZK60/CeO2 Composites Using Machine Learning Models
,”
Tribol. Int.
,
177
, p.
107945
.
29.
Trzepieciński
,
T.
,
Najm
,
S. M.
,
Ibrahim
,
O. M.
, and
Kowalik
,
M.
,
2023
, “
Analysis of the Frictional Performance of AW-5251 Aluminum Alloy Sheets Using the Random Forest Machine Learning Algorithm and Multilayer Perceptron
,”
Materials
,
16
(
15
), p.
5207
.
30.
Deliwala
,
A. A.
,
Dubey
,
K.
, and
Yerramalli
,
C. S.
,
2022
, “
Predicting the Erosion Rate of Uni-Directional Glass Fiber Reinforced Polymer Composites Using Machine-Learning Algorithms
,”
ASME J. Tribol.
,
144
(
9
), p.
091707
.
31.
Golla
,
C. B.
,
Narasimha Rao
,
R.
,
Ismail
,
S.
, and
Gupta
,
M.
,
2024
, “
Experimental Investigations With Machine Learning Techniques for Understanding of Erosion Wear in Advanced Aluminum Nanocomposites
,”
Proc. Inst. Mech. Eng. Part E J. Process Mech. Eng.
32.
Da Poian
,
V.
,
Theiling
,
B.
,
Clough
,
L.
,
McKinney
,
B.
,
Major
,
J.
,
Chen
,
J.
, and
Hörst
,
S.
,
2023
, “
Exploratory Data Analysis (EDA) Machine Learning Approaches for Ocean World Analog Mass Spectrometry
,”
Front. Astron. Space Sci.
,
10
, pp.
1
17
.
33.
Golla
,
C. B.
,
Rao
,
R. N.
, and
Ismail
,
S.
,
2024
, “
Variation in Wear Scar Penetration Depths Due to Impact Angle on the Erosion Wear of Advanced Aluminum Matrix Nanocomposites
,”
Mater. Lett.
,
370
, p.
136843
.
34.
Khan
,
M. M.
, and
Nisar
,
M.
,
2022
, “
Effect of In Situ TiC Reinforcement and Applied Load on the High-Stress Abrasive Wear Behaviour of Zinc–Aluminum Alloy
,”
Wear
,
488
(
489
), p.
204082
.
35.
Babaremu
,
K. O.
,
Joseph
,
O. O.
,
Akinlabi
,
E. T.
,
Jen
,
T. C.
, and
Oladijo
,
O. P.
,
2020
, “
Morphological Investigation and Mechanical Behaviour of Agrowaste Reinforced Aluminum Alloy 8011 for Service Life Improvement
,”
Heliyon
,
6
(
11
), p.
05506
.
36.
Ramesh
,
C. S.
,
Khan
,
S.
, and
Khan
,
Z. A.
,
2020
, “
Dry Sliding-Friction and Wear Behavior of Hot-Extruded Al6061/Si3N4/Cf Hybrid Metal Matrix Composite
,”
J. Mater. Eng. Perform.
,
16
(
7
), pp.
4474
4483
.
37.
Prasad Reddy
,
A.
,
Vamsi Krishna
,
P.
, and
Rao
,
R. N.
,
2019
, “
Tribological Behaviour of Al6061–2SiC-xGr Hybrid Metal Matrix Nanocomposites Fabricated Through Ultrasonically Assisted Stir Casting Technique
,”
Silicon
,
11
(
6
), pp.
2853
2871
.
38.
Kaushik
,
N. C.
, and
Rao
,
R. N.
,
2016
, “
Effect of Grit Size on Two Body Abrasive Wear of Al 6082 Hybrid Composites Produced by Stir Casting Method
,”
Tribol. Int.
,
102
, pp.
52
60
.
39.
David Raja Selvam
,
J.
,
Dinaharan
,
I.
,
Rai
,
R. S.
, and
Mashinini
,
P. M.
,
2019
, “
Dry Sliding Wear Behaviour of In-Situ Fabricated TiC Particulate Reinforced AA6061 Aluminum Alloy
,”
Tribol. Mater. Surfaces Interfaces
,
13
(
1
), pp.
1
11
.
40.
Kaushik
,
N. C.
, and
Rao
,
R. N.
,
2017
, “
Effect of Applied Pressure on High-Stress Abrasive Wear Behavior of Hybrid Al–Mg–Si Composites
,”
Proc. Inst. Mech. Eng. Part J J. Eng. Tribol.
,
231
(
8
), pp.
1089
1100
.
41.
Kumar
,
A.
,
Rana
,
R. S.
,
Purohit
,
R.
,
Saxena
,
K. K.
,
Xu
,
J.
, and
Malik
,
V.
,
2022
, “
Metallographic Study and Sliding Wear Optimization of Nano Si3N4 Reinforced High-Strength Al Metal Matrix Composites
,”
Lubricants
,
10
(
9
), p.
202
.
42.
Kaushik
,
N. C.
, and
Rao
,
R. N.
,
2016
, “
Effect of Applied Load and Grit Size on Wear Coefficients of Al 6082–SiC–Gr Hybrid Composites Under Two Body Abrasion
,”
Tribol. Int.
,
103
, pp.
298
308
.
43.
Kruthiventi
,
S. S. H.
, and
Ammisetti
,
D. K.
,
2023
, “
Experimental Investigation and Machine Learning Modeling of Wear Characteristics of AZ91 Composites
,”
ASME J. Tribol.
,
145
(
10
), p.
101704
.
44.
Pasha
,
M. B.
,
Rao
,
R. N.
,
Ismail
,
S.
,
Gupta
,
M.
, and
Prasad
,
P. S.
,
2024
, “
Tribo-Informatics Approach to Predict Wear and Friction Coefficient of Mg/Si3N4 Composites Using Machine Learning Techniques
,”
Tribol. Int.
,
196
, p.
109696
.
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