The material at the heart of the study is LM26, a widely used aluminium casting alloy prized for its performance at elevated temperatures. By stirring graphite particles and fly ash into the molten alloy through a stir-casting route, the researchers produced a hybrid composite in which soft, self-lubricating graphite coexists with hard, inexpensive fly ash particles. This combination is attractive because graphite can form lubricating films at sliding interfaces while fly ash, a by-product of coal combustion, adds hardness at almost no material cost. The catch is that the final properties of such composites depend heavily on the microstructure of the aluminium matrix, and that microstructure can be deliberately reshaped through heat treatment.

Solution treatment works by heating the alloy to a temperature high enough to dissolve brittle intermetallic phases into the matrix, holding it there to homogenize the structure, and then cooling at a controlled rate to lock in a supersaturated solid solution. The temperature chosen determines how much of the second phase dissolves, the holding time governs how completely that dissolution proceeds, and the cooling method dictates whether dissolved elements remain in solution or precipitate out again. Each of these three levers can alter the hardness of the matrix, the strength of the bond between matrix and reinforcement, and ultimately the way the composite behaves when its surface slides against a counterbody.

To map this three-dimensional parameter space efficiently, the team employed a Taguchi L27 orthogonal array, an experimental design that allows three factors at three levels each to be evaluated with just twenty-seven carefully chosen runs instead of a full factorial sweep. Solution treatment temperatures of 450, 500 and 550 degrees Celsius were paired with holding times of 2, 4 and 6 hours, and each combination was subjected to one of three cooling routes: slow furnace cooling, moderate air cooling or rapid water quenching. After treatment, every specimen was measured for hardness in Brinell numbers, tested for wear rate under dry sliding conditions, and characterized for its coefficient of friction, giving three response variables that often pull in different directions.

The measured values revealed a substantial spread across the treatment conditions. Hardness ranged from 42.3 to 51.2 Brinell hardness numbers, wear rates spanned 0.000667 to 0.000750 cubic millimetres per minute, and coefficients of friction fell between 0.4002 and 0.4501. These are not trivial differences for a component designer: a roughly twenty percent swing in hardness and a corresponding improvement in wear and friction performance can translate directly into longer service life and lower energy losses in sliding machinery. The results showed that as the heat treatment conditions were optimized, hardness climbed from its lowest to highest value while wear rate and friction simultaneously dropped, demonstrating that the three responses can be improved together rather than traded off against one another.

Because no single run was guaranteed to be best on all three counts at once, the researchers turned to TOPSIS, a multi-criteria decision-making technique that ranks each experimental condition by its relative closeness to an ideal solution, defined as the hypothetical condition with the best possible value for every response. The standout performer was Experiment 18, corresponding to a solution treatment at 500 degrees Celsius, a 6-hour hold and water quenching, which achieved the highest relative closeness value of 0.8933. This combination came closest to the ideal balance of maximum hardness with minimum wear and friction among all twenty-seven tested conditions.

Factor-level analysis, which averages the response across all runs containing a given parameter level, pointed to a slightly different optimum within the investigated design space: 550 degrees Celsius, 6 hours and water quenching, designated A3B3C3. The discrepancy between the single best run and the factor-level optimum illustrates a familiar feature of Taguchi analysis, where averaging effects can suggest combinations not directly tested. Both findings, however, converge on the same practical message: longer holding times and rapid water quenching favour the combined tribological response, while the temperature picture rewards careful selection within the studied range.

Analysis of variance added quantitative weight to these observations by partitioning the influence of each parameter on each response. Temperature emerged as the dominant factor for wear rate, coefficient of friction and the overall TOPSIS grade, meaning that the dissolution behaviour of the aluminium matrix during solution treatment exerts the strongest control over how the composite wears and slides. Cooling method, by contrast, had the greatest influence on hardness, consistent with the idea that quenching rate determines how much dissolved solute is retained in solution and how fine the resulting structure becomes. Holding time contributed across all responses but generally played a supporting role to temperature and cooling rate.

Scanning electron microscopy provided the microstructural context for these numbers, allowing the researchers to examine how the graphite and fly ash particles were distributed within the aluminium matrix. A reasonably uniform dispersion of reinforcements is essential for consistent tribological behaviour, since clustered particles can act as stress concentrators and debris sources during sliding, while well-distributed graphite can continuously replenish lubricating films at the wear surface. The microscopy work tied the macroscopic wear and friction measurements back to the underlying structure of the composite, reinforcing the link between heat treatment, microstructure and performance.

The broader significance of the study lies in its demonstration that post-casting heat treatment is not an afterthought for hybrid aluminium matrix composites but a primary design variable. For industries seeking to substitute lightweight composites for heavier ferrous components in engines and braking systems, the ability to dial in wear and friction performance through a documented treatment recipe, validated by a transparent Taguchi-TOPSIS workflow, offers a practical path from laboratory material to engineering component. The findings also highlight the value of fly ash, an industrial waste stream, as a functional reinforcement, aligning improved tribological performance with lower material cost and a measure of environmental benefit.

Subject of Research: Heat treatment optimization of LM26/graphite/fly ash hybrid aluminium matrix composites for tribological performance

Article Title: Effect of Heat treatment parameters on the tribological performance of LM26/graphite/fly ash hybrid aluminium matrix composites using Taguchi-TOPSIS optimization

Article References: Chellamuthu, P., Angappan, P., Duraisamy, P., Agarwal, A., & Dorji, K. (2026). Effect of Heat treatment parameters on the tribological performance of LM26/graphite/fly ash hybrid aluminium matrix composites using Taguchi-TOPSIS optimization. PLOS One, 21(10), e0360156. https://doi.org/10.1371/journal.pone.0360156

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360156

Keywords: aluminium matrix composites, LM26 alloy, graphite, fly ash, heat treatment, solution treatment, Taguchi method, TOPSIS, tribology, wear rate, coefficient of friction, stir casting

The research, published in Polymer Bulletin by Muhammad Taqi-uddeen Safian, Pandian Bothi Raja and Mohamad Nasir Mohamad Ibrahim, describes the synthesis and optimization of a lignin-acrylamide composite, abbreviated LAA, designed specifically to protect carbon steel in water-based mud. Lignin is the aromatic polymer that gives wood its rigidity, and it is generated in enormous quantities as a by-product of the pulp and paper industry and of palm oil processing. Rather than being burned for low-grade heat, this phenolic-rich material can be chemically upgraded. The Malaysian team started with soda lignin, a type of lignin produced by alkaline pulping, and polymerized it with acrylamide, a water-soluble monomer, to create a graft composite with far better solubility in the aqueous drilling fluid than raw lignin, which tends to aggregate and settle out of solution.

Solubility is not a cosmetic detail; it is the gatekeeper of performance. A corrosion inhibitor can only protect steel if it can reach the metal surface, adsorb onto it and form a protective film that blocks the electrochemical reactions of corrosion. Lignin’s aromatic rings and hydroxyl groups provide plenty of anchoring sites for adsorption, but the native polymer’s poor dispersibility in brines and muds has long limited its practical use. By grafting acrylamide chains onto the lignin backbone, the researchers created an amphiphilic molecule that dissolves readily in the mud while still presenting the aromatic and amide functional groups that bind to steel surfaces. The result is a composite that behaves like a designed corrosion inhibitor rather than a raw biomass extract.

Getting the synthesis right, however, is a multi-variable puzzle. The yield of the grafting reaction depends on temperature, reaction time, the ratio of acrylamide to lignin and the concentration of the catalyst that initiates polymerization. Testing every combination would be prohibitively expensive, so the team deployed two complementary statistical optimization strategies. The first was the Taguchi method, a design-of-experiments technique that uses specially constructed orthogonal arrays to screen many factors with a small number of runs. Taguchi analysis produced a clear hierarchy of influence: temperature mattered most, followed by reaction time, then the acrylamide-to-lignin ratio, with catalyst concentration playing the smallest role. The model predicted a maximum composite yield of 4.893 grams under its optimal conditions.

The second strategy, response surface methodology based on a central composite design, went a step further. Where Taguchi screening identifies which factors matter and roughly where the optimum lies, response surface methodology builds a mathematical surface describing how the yield responds to simultaneous changes in each variable, then refines the optimum through analysis of variance. The CCD-RSM model predicted a maximum yield of 4.653 grams, remarkably close to the Taguchi prediction. Both approaches converged on the same operating window: a reaction temperature near 90 degrees Celsius, a reaction time of about four hours, and an acrylamide-to-lignin ratio of approximately two. This kind of head-to-head comparison of the two optimization frameworks, coupled with validation under drilling-fluid conditions, is what the authors identify as the central novelty of the study.

The convergence matters because it gives engineers confidence that the optimum is real rather than an artifact of one statistical model. Temperature dominating the hierarchy makes chemical sense: graft polymerization of acrylamide onto lignin depends on generating reactive radical sites on the lignin backbone, and higher temperatures accelerate both initiator decomposition and chain growth. But push too far and side reactions, chain termination and lignin degradation begin to erode the yield. The four-hour reaction time and the two-to-one monomer ratio represent the balance point where the grafting reaction has run to near completion without the polymerization running away into homopolymer formation. In effect, the statistics mapped the energetic sweet spot of a complex free-radical grafting reaction.

With the optimized LAA in hand, the researchers moved from the synthesis bench to the drilling-fluid laboratory, and this is where the work distinguishes itself from much of the green-corrosion-inhibitor literature. Many candidate inhibitors are evaluated only in simple salt solutions at ambient temperature, conditions that bear little resemblance to a downhole environment. Safian and colleagues instead aged their water-based mud containing the LAA additive at 90 degrees Celsius for 16 hours under API-type conditions, the standardized testing protocol of the American Petroleum Institute that mimics the thermal and mechanical stress a mud experiences during actual circulation. Only after this aging did they assess corrosion protection using weight-loss testing on carbon steel coupons, the industry’s most direct measure of how much metal a fluid destroys over time.

The results were striking. The optimized lignin-acrylamide composite achieved a maximum corrosion inhibition efficiency of 73.5 percent at a dosage of just 500 parts per million. In other words, a half-gram of plant-derived polymer per liter of mud stripped nearly three-quarters of the corrosive attack on the steel. The mechanism is consistent with what is known about lignin-based inhibitors: the aromatic rings and polar functional groups adsorb onto the steel surface, creating a barrier layer that impedes both the anodic dissolution of iron and the cathodic reduction reactions that drive corrosion. The acrylamide grafts improve the integrity and coverage of this film in the hot, saline, solids-laden mud environment, where unmodified lignin would struggle to remain dispersed and adsorbed.

The implications extend beyond a single laboratory result. Drilling operations consume vast quantities of mud, and the corrosion inhibitors added to them eventually end up in cuttings waste and produced water. Regulators worldwide are tightening restrictions on heavy-metal-based and poorly biodegradable additives, and operators are actively seeking green chemistry that does not sacrifice performance. Lignin fits the brief almost perfectly: it is cheap, abundant, renewable and derived from waste streams that would otherwise be flared or landfilled. Previous studies have explored lignin and its derivatives as corrosion inhibitors in acidic pickling solutions, alkaline-chloride media and water distribution systems, and lignin-acrylamide copolymers have found uses as paper strength additives and flocculants. The Malaysian study extends this family of materials into one of the most demanding applications in industrial chemistry, a hot, aging drilling mud in contact with carbon steel.

There is, of course, still distance between a 16-hour laboratory aging test and months of continuous downhole service. Field muds encounter shear from the drill string, contamination from formation brines and hydrocarbons, and temperatures well above 90 degrees Celsius in deeper wells, all of which will stress the inhibitor film in ways a standardized test cannot fully capture. The economics of scaling the graft polymerization from grams to tons, and the interaction of LAA with the other mud additives such as viscosifiers and fluid-loss agents, will also need attention. But the study provides something rare in the bio-based inhibitor field: a statistically rigorous synthesis optimum, cross-validated by two independent design methods, and a performance figure earned under industry-standard aging conditions rather than idealized bench chemistry. As drilling companies confront both corroding infrastructure and tightening environmental rules, a polymer built from palm and pulp waste that shields steel at 500 parts per million is exactly the kind of dual-purpose solution the industry has been waiting for.

Subject of Research: Bio-based lignin-acrylamide corrosion inhibitors for water-based drilling mud

Article Title: Bio-based lignin-acrylamide corrosion inhibitor for water-based mud: Taguchi -RSM optimization, and API-aging validation

Article References: Safian, M. T.-U., Bothi Raja, P., & Mohamad Ibrahim, M. N. (2026). Bio-based lignin-acrylamide corrosion inhibitor for water-based mud: Taguchi -RSM optimization, and API-aging validation. Polymer Bulletin, 83(11), Article 624. https://doi.org/10.1007/s00289-026-06673-2

Image Credits: AI Generated

DOI: 10.1007/s00289-026-06673-2

Keywords: lignin, acrylamide, corrosion inhibitor, water-based mud, drilling fluid, Taguchi method, response surface methodology, carbon steel, oil palm waste, green chemistry, API aging, polymer bulletin

Investment casting is one of metallurgy’s oldest processes, with roots stretching back to early weapons, jewelry, and religious art. It remains prized today for aerospace turbine blades and biomedical components because it delivers exceptional surface finish, dimensional accuracy, and the ability to reproduce complex shapes. In Nepal, the technique has been used since at least the sixth century A.D. to produce the bronze and gilded deities that fill temples and monasteries across the Himalayas. The process is intensely manual: a sculptor first carves a detailed wax master pattern, which is encased in a rubber mold from which multiple wax replicas can be made. These replicas are assembled with gating systems, dipped in a traditional slurry of cow dung and clay, reinforced with metal wires, dewaxed, preheated, and finally filled with molten metal. After cooling, each piece demands hours of filing, chiseling, and hand-applied gold plating.

That artisanal character comes at a cost. Defect rates in Nepali sculpture casting hover around thirty percent, and sculptures can take anywhere from one month to two years to complete depending on size. Because global economic shifts and advancing technology are squeezing demand for Nepali cast sculptures, improving casting design, modeling, and production efficiency has become essential for the industry’s survival. The research team, led by Zenisha Shrestha with Abhishek Pandey and Bijendra Prajapati, set out to determine whether systematic parameter optimization, never before applied to this traditional setting, could meaningfully improve dimensional accuracy in gilding metal, an alloy of ninety percent copper and ten percent zinc that is the most widely used sculpture material in Nepal.

The researchers chose a sword as their test specimen, selected for its cultural relevance in Nepali society and its relatively simple geometry, which makes dimensional analysis tractable. The design was modeled in SOLIDWORKS, with the gating system developed through the modulus method to reflect designs typical of sculpture manufacturing. From an Ishikawa cause-and-effect analysis of casting stability, the team identified three controllable parameters: the number of slurry coating layers, the mold preheat temperature, and the metal pouring temperature. Factors such as wax composition, alloy composition, slurry composition, cooling methods, and environmental conditions were treated as noise parameters that could not be easily controlled in the workshop.

The experimental design followed a Taguchi L9 orthogonal array, allowing nine carefully chosen experiments to explore the parameter space efficiently. Slurry coatings ranged from two to four layers, preheat temperatures spanned 500 to 600 degrees Celsius, and pouring temperatures covered the 1150 to 1200 degree Celsius range typical of Nepali sculpture foundries. Each coating choice involves a trade-off: thin shells save material and time but risk bulging and leaking under the metallostatic pressure of pouring, while thicker coatings prevent defects and improve heat retention at the cost of longer processing. Preheating the mold reduces thermal shock and premature freezing of the melt, improving fill of thin sections, though excessive preheat can accelerate mold-metal reactions and increase surface-connected porosity. Higher pouring temperatures superheat the metal above its melting point, preventing unfilled sections in intricate features.

Four response variables were measured for each casting: weight, length, breadth, and thickness. Before optimization, the team verified data quality through normality testing with probability plots and the Anderson-Darling test, confirming that all responses followed normal distributions. Pareto tests and analysis of variance at a 95 percent confidence level then established that all three process parameters significantly influenced every response variable. The number of coatings emerged as the dominant factor, contributing 44.42 percent of the variance in weight, 48.01 percent in length, 58.81 percent in breadth, and 41.82 percent in thickness. Pouring temperature exerted its greatest influence on weight at 39.31 percent and length at 31.38 percent, while preheat temperature most strongly affected breadth and thickness. Residual plots showed randomly distributed errors, confirming the reliability of the statistical model.

Because dimensional accuracy depends on optimizing all four responses simultaneously, the researchers turned to multi-response optimization. Grey relational analysis, a technique designed for systems with limited information, converts multiple responses into a single grey relational grade by normalizing the data and calculating correlation coefficients, using an identification coefficient of 0.5 consistent with prior studies. The innovation here was the coupling of grey relational analysis with principal component analysis, which uses eigenvectors to derive objective weights for each response rather than assuming they matter equally. The first principal component captured 81.9 percent of the data’s variance and identified length as the most significant response. Experiment 3, combining a 500 degree Celsius preheat, a 1200 degree Celsius pour, and four coating layers, ranked highest under both the standard and PCA-weighted grades, and both methods converged on the same optimal setting, strengthening confidence in the result.

The confirmatory experiment delivered striking improvements. The weighted grey relational grade rose from 0.357 under initial conditions to 0.966 under optimal conditions, closely matching the predicted value of 0.9677. Weight deficit fell from 3.160 percent to 0.682 percent, length shrinkage dropped from 4.860 percent to 0.545 percent, breadth shrinkage plummeted from 6.156 percent to 1.067 percent, and thickness shrinkage declined from 4.200 percent to 1.800 percent. In practical terms, a cast sword produced under the optimized parameters now deviates from its wax pattern by barely one percent in its principal dimensions, meaning far less manual filing and correction before gold plating. Given that finishing work is among the most labor-intensive stages of sculpture production, even modest dimensional improvements translate into significant reductions in lead time and cost.

The implications extend well beyond Nepal’s foundries. The authors note that the GRA-PCA methodology can be adapted to any complex manufacturing process where multiple conflicting objectives must be balanced, including precision casting of aerospace turbine blades, biomedical device manufacturing where dimensional control is critical, and automotive component casting where strength, weight, and tolerances compete. For Nepal, the study represents the first application of advanced multi-response optimization to traditional sculpture casting, and it arrives at a pivotal moment for an industry whose economic viability depends on competing with industrialized producers. Future work, the researchers suggest, could examine surface roughness, mechanical properties, and additional process parameters. But the central message is already clear: fourteen centuries of artisanal wisdom and twenty-first-century statistical rigor are not adversaries. When the number of coatings, the preheat temperature, and the pouring temperature are tuned together, the ancient art of Himalayan metal sculpture can achieve a precision its original masters could scarcely have imagined, preserving both a cultural heritage and the livelihoods of the craftsmen who sustain it.

Subject of Research: Multi-response optimization of investment casting parameters to improve the dimensional accuracy of gilding metal sculptures in traditional Nepali manufacturing.

Article Title: Improvement of dimensional accuracy in gilding metal sculpture manufacturing using grey relational analysis coupled with principal component analysis

Article References: Shrestha, Z., Pandey, A., & Prajapati, B. (2026). Improvement of dimensional accuracy in gilding metal sculpture manufacturing using grey relational analysis coupled with principal component analysis. Heliyon, 12(14), Article e45412. https://doi.org/10.1016/j.heliyon.2026.e45412

Image Credits: AI Generated

DOI: 10.1016/j.heliyon.2026.e45412

Keywords: investment casting, grey relational analysis, principal component analysis, Taguchi method, dimensional accuracy, gilding metal, Nepal sculpture manufacturing, shrinkage reduction, ANOVA, multi-response optimization, Kathmandu Valley, metal casting

The choice of matrix alloy was deliberate. AA6061 is a wrought aluminium alloy prized for its excellent thermal and physical properties, its corrosion resistance, and the ease with which it can be fabricated into machine parts, structural elements and aerospace components. Yet like most commercial alloys, it has limits in strength and wear performance that can restrict its use in demanding tribological applications such as brakes, bearings and gears. Materials scientists have long explored ways to tailor aluminium by adding hard ceramic or mineral particles, including silicon carbide, alumina, fly ash, red mud and zircon silicate, and previous studies have generally found that such reinforcements boost hardness and strength while often reducing density. What makes the new work distinctive is the use of marble dust, an abundant industrial waste stream from Rajasthan’s stone industry, which turns a disposal problem into a feedstock for advanced materials.

To create the composites, the team used a semi-automatic stir-casting process, one of the most economical and widely adopted liquid-state fabrication routes for metal matrix composites. Cleaned and cut AA6061 alloy rods were melted in a graphite crucible at 720 degrees Celsius, and the molten metal was fluxed to remove impurities. Around 2 weight percent of magnesium, added in the form of MgO, was stirred into the melt to improve wettability, a critical step because poorly wetted particles tend to cluster rather than disperse. Meanwhile, the marble dust was preheated to about 400 degrees Celsius for half an hour to drive off moisture and lower the surface energy of the particles, which further promotes uniform mixing. The heated reinforcement was then added incrementally while a graphite stirrer agitated the melt at 250 revolutions per minute for five minutes. The melt was superheated slightly to maintain fluidity and poured into a permanent mould, producing cast plates from which standard test specimens were machined.

Five compositions were prepared, spanning 0 to 6 weight percent marble dust in 1.5 percent increments, labelled M0 through M6. The researchers evaluated density, void content, tensile strength, flexural strength, hardness and impact strength for each formulation. A clear trend emerged: as the marble dust content increased, the void fraction dropped from roughly 12.5 percent to 6.66 percent, while every measured mechanical property improved. Tensile strength rose from about 238 megapascals in the unreinforced alloy to roughly 277 megapascals at 6 percent reinforcement. Hardness climbed from 75 to 90 on the Rockwell B scale, flexural strength increased from 180 to about 205 megapascals, and impact strength grew from 16.5 to 21 kilojoules per square metre. The team attributes these gains to two mechanisms: the rising dislocation density and the build-up of a stronger matrix-particle interface, which reduces voids and improves load transfer, and the ability of hard particles to act as barriers to dislocation motion, producing classic dispersion strengthening.

The tribological behaviour of the composites was assessed under dry sliding conditions, with the specific wear rate ranging from about 2.006 to 2.528 times ten to the minus six cubic millimetres per newton-metre. Three operating variables were systematically varied: normal load from 10 to 50 newtons, sliding distance from 800 to 4000 metres, and sliding velocity from 1 to 2 metres per second. Across the composition range, wear rate and friction coefficient increased with each of these parameters but fell as marble content rose. The M6 composite, containing the maximum 6 weight percent reinforcement, consistently delivered the lowest wear and friction. The researchers explain this through the same microstructural logic that governs the mechanical results: fewer voids mean a more continuous, better-bonded material that transfers load efficiently between matrix and particles, so the surface resists softening, ploughing and debris generation during sliding.

Scanning electron microscopy of the worn surfaces revealed the underlying wear mechanisms in vivid detail. At the lowest load of 10 newtons, the M6 composite displayed clean primary surfaces with minimal debris, evidence of its intactness and strength. At 20 newtons, mild ploughing and pitting appeared, and by 30 newtons deep ploughing grooves and a secondary layer of laminated wear debris became visible. At 40 and 50 newtons the damage turned aggressive, with massive debris layers and extensive pitting. The team attributes this escalation to rising interfacial temperatures at higher loads, which soften the surface, promote debonding and generate hard debris particles that then scour the interface in a destructive three-body abrasion mechanism. These micrographs directly link the macroscopic wear measurements to observable surface physics.

To optimise the sliding wear process, the researchers turned to Taguchi’s design of experiments, arranging trials in an L25 orthogonal array and using signal-to-noise ratios with a smaller-the-better objective to minimise wear. Analysis of variance on the results showed that normal load was the most influential parameter, contributing 33.33 percent of the variability in specific wear rate, followed by sliding distance at 13.36 percent, reinforcement content at 12.98 percent and sliding velocity at 9.64 percent. The highest F-value, 2.49 for normal load, confirmed its dominant role. The optimal parameter combination produced a signal-to-noise ratio of 58.60 decibels, and a confirmation experiment run at randomly selected settings validated the model with an error of only 3.6 percent, demonstrating that Taguchi’s approach can reliably guide wear-minimising process design for these materials.

Perhaps the most novel element of the study is its use of hybrid multi-criteria decision-making techniques to rank the five composites across all their performance metrics simultaneously. The two-phase AHP-TOPSIS algorithm first converts expert judgment about the relative importance of criteria into quantitative weights using Saaty’s nine-point scale, checking consistency to ensure the weights are trustworthy, and then measures each alternative’s closeness to an ideal solution. The hybrid AHP-R method follows the same first phase but uses reciprocal rank-based weighting in the second. In both analyses, the criteria hierarchy placed hardness, tensile strength, flexural strength and impact strength at the top, with density and wear rate weighted lower, and the consistency ratio of roughly 0.0044 fell far below the accepted 10 percent threshold. Critically, the two independent ranking methods converged on exactly the same order: M6 outperformed M4.5, which beat M3, with M1.5 and M0 trailing, confirming the subjective assessment that the highest marble content is optimal.

The convergence of experimental measurement, statistical optimisation and decision theory gives the findings unusual robustness, and the practical implications are considerable. The authors suggest that composites with low void content and strong mechanical properties are well suited to tribological applications, and that these marble-dust-reinforced aluminium alloys could serve as substitute materials in rollers, brakes, guideways, bearings and gears. Because the reinforcement is essentially industrial waste, the cost and environmental footprint of producing the composites should be far lower than those of conventional ceramic-reinforced alternatives. The work also adds to a growing body of literature showing that hybrid decision-making algorithms such as AHP-TOPSIS and AHP-R, borrowed from operations research, can rapidly and objectively rank material alternatives, sparing engineers from grappling with conflicting criteria by intuition alone.

The study was conducted with support from the Advanced Research Lab for Tribology and the Material Research Centre at Malaviya National Institute of Technology Jaipur, and the authors report no competing interests. While the research remains at the laboratory scale, the combination of a cheap, abundant reinforcement, a scalable casting process and statistically validated performance gains suggests a credible pathway from quarry waste to engineered components. For industries under pressure to cut both costs and carbon, the message of this work is striking: the material of the future for lightweight, wear-resistant metal parts may already be piling up in the dust of India’s marble workshops, waiting to be stirred into the melt.

Subject of Research: Marble dust particle-reinforced AA6061 aluminium matrix composites evaluated for mechanical strength and sliding wear performance using hybrid decision-making techniques

Article Title: Mechanical and sliding wear performance analysis of AA6061 − marble particulates reinforced alloy composites via hybrid decision-making techniques

Article References: Kumar, A., & Kumar, M. (2026). Mechanical and sliding wear performance analysis of AA6061 − marble particulates reinforced alloy composites via hybrid decision-making techniques. Journal of Materials Science: Metallurgy, 1(1), Article 15. https://doi.org/10.1007/s44492-026-00015-z

Image Credits: AI Generated

DOI: 10.1007/s44492-026-00015-z

Keywords: AA6061 alloy, marble dust particulates, metal matrix composites, stir casting, sliding wear, mechanical properties, Taguchi method, ANOVA, hybrid AHP-TOPSIS, AHP-R method, tribology, automotive materials