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Morphological Characterization and Tribological Properties of TiCoNi Alloy Coatings on Ti–6Al–4V Alloy via Laser Deposition
(Springer, 2024-09-17) Adesina, Olanrewaju
The goal of this work is to improve the Ti–6Al–4V alloy's hardness and tribological behavior. Coaxial laser surface clad ding was used to develop intermetallic layers of nickel (Ni), cobalt (Co), and titanium (Ti). Laser power of 900 W, beam
spot size of 3 mm, powder feed rate of 1.0 g/min, and gas fow rate of 1.2 L/min are the optimized parameters used for
laser depositions. The laser scan speeds were adjusted between 0.6 and 1.2 m/min. Investigations were conducted into the
efects of powder admixture and laser parameters on the fabricated coatings' microstructure, tribological behavior and
hardness. X-ray difractometry (XRD), energy dispersive spectroscopy (EDS) with Scanning electron microscopy (SEM)
was employed for the characterization of the microstructural evolution and phase identifcation, respectively. Additionally,
the tribological experiment was conducted via UMT-2 –CETR reciprocating tribometer, and the coatings’ micro-hardness
characteristics were examined using EmcoTEST DURASCAN. The micrographs exhibit no signs of porousness, cracks,
or stress introduction, according to the results. For every manufactured sample, good metallurgical adhesion was obtained.
By comparing the hardness of the ternary coating (Co–Ni–10Ti deposited at a scan speed of 1.2 m/min, with a hardness of
980 HV) to the substrate (Ti–6Al–4V, with a hardness of 330 HV), a hardness increase of approximately 2.96 times was
observed. Furthermore, the Co–Ni–10Ti coating, deposited at a scan speed of 1.2 m/min, demonstrated a 51.1% reduction
in the coefcient of friction (COF) compared to the base alloy, indicating superior anti-wear performance. The enhanced
properties are attributed to the formation of hard intermetallic compounds such as Ti–Co, Co2Ti, Al5Co2, and Ni3Ti, along
with their uniform distribution and fnely tuned grain sizes.
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Statistical modeling of Si‑based refractory compounds of bamboo leaf and alumina reinforced Al–Si–Mg alloy hybrid composites
(natureportfolio, 2023) Adesina, Olanrewaju
Wear properties of Al–Mg–Si alloy matrix hybrid composites made with Si‑based refractory
compounds (SBRC) derived from bamboo leaf ash (BLA) as complimentary reinforcement with alumina
have been studied. The experimental result indicate that optimum wear loss was obtained at higher
sliding speed. The wear rate of the composites increased with an increase in BLA wt. %, with the
composites having 4%SBRC from BLA + 6% alumina (B4) showing the least wear loss for the different
sliding speeds and wear loads considered. With increasing BLA weight percent, the composites’
wear mechanism was mostly abrasive wear. Numerical optimization results using central composite
design (CCD) reveal that at a wear load of 587.014N, sliding speed of 310.053 rpm and B4 hybrid filler
composition level respectively, minimum responses in wear rate (0.572mm2/min), specific wear rate
(0.212cm2/g.cm3) and wear loss (0.120 g) would be obtained for the developed AA6063 based hybrid
composite. Perturbation plots indicate that the sliding speed have more impact on wear loss, while
wear load have significant impact on the wear rate and specific wear rate.
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Surface Modifcation and Corrosion Performance of Laser Cladded Co–Ni on Ti–6Al–4 V in 0.5 M H2SO4 Environment
(Springer, 2024-09-06) Adesina, Olanrewaju
This study investigates the laser cladding of Co and Ni powders onto Ti–6Al–4 V substrates, varying the admixed percent ages while adjusting laser processing parameters. The infuence of nickel and cobalt contents on the microstructure, phase
composition, and electrochemical behavior of the laser-clad Ti–6Al–4 V coatings were analyzed. Coating morphology
and phases were characterized using scanning electron microscopy (SEM) equipped with energy dispersive spectrometry
(EDS), and X-ray difractometry (XRD), respectively. The corrosion resistance of Ti–6Al–4 V, both with and without Ni–Co
additions, in 0.5 M H2SO4 was evaluated using potentiodynamic polarization technique. Results indicated that the coatings
exhibited excellent metallurgical compatibility with the substrate. Additionally, the high scan speed laser-clad samples
showed enhanced corrosion resistance compared to those processed at low speeds. The potentiodynamic polarization analysis
revealed passive behavior in all specimens, with higher cobalt content notably enhancing passivity and corrosion resistance
by suppressing the anodic reaction
Item
Morphological evolution and strength performance of green-aluminium-7075 hybrid composites modeledbyresponse surface analysis
(Springer, 2023-06-03) Adesina, Olanrewaju
In developing countries, the importation of synthetic ceramic particles for particulate reinforcement of metal matrixes is
costly, so locally sourced and sustainable alternatives are sought after Rice husk ash (RHA) at 3–12 wt.%, glass powder (GP)
at 2–10 wt.%, and stirring temperature (ST) at 600–800 °C were evaluated for their effects on the elemental distribution,
microstructure,andtensileperformanceofaluminum-7075greencomposite.Responsesurfacewasutilizedintheexperimental
design and statistical analysis of the experimental results for the purpose of determining the optimal combination of the three
input variables. Yield, ultimate tensile, flexural, and impact strengths, as well as microhardness and compressive strength,
are examined as responses. To optimize these parameters, response surface analysis was incorporated into the experimental
design, modeling, and optimization procedures. Variation in experimental variables led to microstructural evolution, which in
turn caused variation in performance. Response surfaceanalysis (RSA)revealed thattheinputfactors contributed significantly
to each response, resulting in regression models statistically suited to represent the experimental data, as confirmed by the
diagnostic plots. As a consequence of the optimization, a combination of 7.2% RHA, 6.2 GP, and 695 °C with a desirability
of 0.91 was deemed optimal. A comparison between the predicted values for the responses and the values from the validation
experiment revealed that each response had an error < 5%. Consequently, the models are certified adequate for response
prediction with a confidence level of 95%, and the optimal combination is adequate for the composite’s design.
Item
Microstructure, Process Optimization, and Strength Response Modelling of Green-Aluminium-6061 Composite as Automobile Material
(Ceramics, 2023-02-01) Adesina, Olanrewaju
The use of ashes derived from various waste sources as supplements to synthesized ceramic
reinforcement in metal matrices has been established. However, studies involving a combination
of particulates from three different sources are rare. In a bid to further knowledge in this aspect
of research and develop a green aluminium composite for automobile applications, the present
investigation studied the implication of adding palm kernel shell ash (PKA), rice husk ash (RHA),
and waste steel particles (STP) to the morphology and strength behaviour of Al-6061-T6 alloy. The
experimental design was undertaken via the Box–Behnken design (BBD) of the response surface
method. A 4% STPat a constant dose was mixed with PKA and RHA at varying proportions and
stirring temperatures according to the BBD. The experimental outcome revealed that the responses
were greatly influenced by microstructural evolution. From the surface plots, 2–4% RHA and PKA
enhanced tensile and flexural strengths, while 4–6% led to a decline in strength. Meanwhile, 2–6% of
the particles are favourable to the enhancement of tensile and compressive strengths and moduli.
Temperaturesbetween700and800 Cfavoredresponseimprovement,whereastemperaturesbetween
800 and 900 Cweredetrimental to responses. Developed regression models for the responses were
validated to be good representations of the experimental outcomes. The optimum mix was obtained
at 4.81% PKA,5.41%RHA,andastirringtemperatureof803 C.Thevalidationexperimentconducted
portrayed reliable responses with <5% deviation from the predicted values, thereby certifying the
models to be statistically fit for future predictions.