The research team, led by Soroush Hajihasani with Mohsen Amouzadeh Omrani, Hassan Divandari, and Ali Seyedkazemi, tackled one of the most stubborn trade-offs in sustainable road engineering. Reclaimed asphalt pavement, or RAP, is milled-off old road material that can replace virgin aggregate in new mixtures, cutting costs, conserving quarried stone, and reducing the energy footprint of construction. But the binder coating RAP particles has been oxidized by years of sun, air, and traffic. In this study the recovered RAP binder showed a penetration of only 32, a softening point of 58 degrees Celsius, a ductility of just 7.3 centimeters, and a high rotational viscosity of 2.77 pascal-seconds, all signatures of a severely aged, brittle material. That brittleness raises mixture stiffness, which sounds like a benefit, yet it sharply reduces the pavement’s ability to accommodate repeated stretching, so RAP-rich mixtures typically crack earlier than their virgin counterparts.

The researchers’ answer was a composite healing system rather than a single additive. Nano sodium alginate, synthesized as spherical to sub-spherical particles ranging from roughly 80 to 280 nanometers, with median hydrodynamic diameters of 145 nanometers, serves as a dispersion matrix for a commercial oil-based rejuvenator known as Cargill-1252, stabilized with poly(ethyl methacrylate) and plasticized with ethyl glycol. The rejuvenator supplies the primary softening and restorative chemistry, while the alginate nano-network keeps it uniformly distributed and thermally stable within the binder. The team blended the system into asphalt heated to 150 degrees Celsius using a high-shear mixer running at its maximum speed of 6000 revolutions per minute, and field-emission scanning electron microscopy confirmed that the nano-structured network remained intact and evenly dispersed after this aggressive treatment.

X-ray diffraction of the modified binder revealed why the system behaves the way it does. The pattern was dominated by a sharp peak near 22 degrees that matched the reference structure of stearic acid with a match index of 91.91 percent, with secondary signatures of sodium stearate and sodium citrate. In other words, fatty-acid molecules from the rejuvenator crystallize into ordered, needle-like domains as the binder cools, forming a semi-solid physical framework through self-assembly rather than chemical reaction. The authors interpret this ordered crystalline network as a structural scaffold that anchors the binder, resists permanent deformation, yet lowers the energy needed for molecular rearrangement when the material is later stressed or warmed, precisely the conditions under which self-healing must operate.

To test performance, the team prepared Marshall-designed mixtures with limestone aggregate and a penetration-grade 85-100 base binder, using RAP replacement levels of zero, fifty, and one hundred percent. Notably, they applied a conservative black-rock assumption, crediting none of the aged RAP binder toward the design binder content and adding a constant five percent virgin binder to every mixture. Beams were then subjected to four-point bending fatigue tests at 20 degrees Celsius under constant-strain control at two severities, 400 and 800 microstrain, following ASTM D7460, with failure defined as a fifty percent reduction in initial stiffness. Half the specimens were vacuum-saturated to seventy to eighty percent saturation under the AASHTO T283 protocol to simulate moisture damage. Healing was introduced by pausing the test for a sixty-minute rest once the damage threshold was reached, then restarting and measuring how much stiffness returned.

The results under moderate dry loading at 400 microstrain tell the story vividly. Unmodified mixtures grew stiffer as RAP content rose, with initial moduli climbing from 1.45 gigapascals for the virgin mixture to 2.22 and 2.68 gigapascals for the fifty and one hundred percent RAP mixes, yet fatigue life collapsed from 29,300 cycles to 18,600 and then 11,800 cycles. Adding the nano-alginate rejuvenator reversed the trend without simply softening the material. The virgin mixture’s life jumped 94 percent to 56,700 cycles, the fifty percent RAP mix gained 69 percent, and the fully recycled mix surged 106 percent to 24,300 cycles, all while its initial modulus barely changed. Healing indices followed suit, rising from 41 to 50 percent for the virgin mix, from 32 to 43.3 percent at fifty percent RAP, and from 25.4 to 36 percent at full RAP replacement.

Severity and water made everything harder, and that is where the rejuvenator proved most valuable. At 800 microstrain under dry conditions, the unmodified one hundred percent RAP mixture lasted a mere 4,200 cycles, but with the rejuvenator it survived 10,300 cycles, an improvement of roughly 145 percent. Under the harshest combination, 800 microstrain plus moisture saturation, the fully recycled control failed after only about 3,470 cycles, while the rejuvenated version reached 5,870 cycles, and the fifty percent RAP mix with the additive extended its life from 5,430 to 10,400 cycles, roughly 92 percent better. Across every condition tested, the rejuvenated RAP-containing mixtures were the only recycled formulations to meet the study’s minimum criteria for modulus retention and fatigue durability in wet states, suggesting that restoring binder mobility can partially compensate for the compounding damage of aging, strain, and water.

The economics add an important dose of realism. Using normalized unit costs for a hypothetical one-kilometer, three-lane pavement section requiring about 3,274 tonnes of asphalt, RAP alone trimmed initial costs by 4.8 percent at fifty percent replacement and 9.5 percent at full replacement. The rejuvenator, priced as a complete composite system at six dollars per kilogram, pushed initial costs up by 25.1 percent for the RAP-free modified mix, though higher RAP content clawed much of that back, leaving the fifty and one hundred percent RAP rejuvenated mixes about 20.3 and 15.5 percent above the conventional control. The authors are careful to note this is an initial-cost comparison only; converting the laboratory fatigue gains into real maintenance savings would require field-calibrated performance models and life-cycle analysis.

What emerges is a nuanced but genuinely exciting picture for the future of circular road construction. Stiffness alone, the study shows, is a misleading indicator of pavement quality, because the stiffer RAP mixtures consistently failed sooner. The sweet spot in this dataset was the fifty percent RAP mixture with the nano-alginate rejuvenator, which combined substantial recycled content, fatigue-life gains of roughly 68 to 94 percent depending on condition, and healing indices several points higher than its unmodified counterpart. The authors caution that their findings rest on a single RAP stockpile, one additive dosage, and laboratory protocols, and that field trials, multiple RAP sources, long-term aging studies, and complementary microstructural techniques such as FTIR and calorimetry are needed before the technology reaches specifications. Even so, the demonstration that a seaweed-based nanomaterial can teach fully recycled asphalt to heal itself marks a compelling step toward roads that repair their own cracks, one rest period at a time.

Subject of Research: Self-healing performance of a nano sodium alginate-based rejuvenator in reclaimed asphalt pavement mixtures evaluated by four-point bending fatigue testing

Article Title: Self‑healing performance of nano sodium alginate–based rejuvenator in asphalt mixtures containing reclaimed asphalt pavement using four‑point bending fatigue test

Article References: Soroush, H., Mohsen, A. O., Hassan, D., & Ali, S. (2026). Self‑healing performance of nano sodium alginate–based rejuvenator in asphalt mixtures containing reclaimed asphalt pavement using four‑point bending fatigue test. Case Studies in Construction Materials, 25, Article e06605. https://doi.org/10.1016/j.cscm.2026.e06605

Image Credits: AI Generated

DOI: 10.1016/j.cscm.2026.e06605

Keywords: asphalt, self-healing, reclaimed asphalt pavement, nano sodium alginate, rejuvenator, four-point bending, fatigue test, sustainable pavements, X-ray diffraction, moisture conditioning, recycled materials, infrastructure

A new open-access study in Cleaner Engineering and Technology by Himasai Kiran Reddy Durgam and Prasanna Venkatesan Ramani tackles this dilemma with an unusually rigorous computational framework. The researchers describe a hybrid Z-Number Reliability-Weighted Analytic Hierarchy Process combined with a true Euclidean TOPSIS engine, applied to the upstream construction supply chain. Their goal was not simply to rank green strategies but to resolve what they call the paradoxical tension between ecological yield and economic impedance — the persistent conflict between what is best for the planet and what a firm can actually afford to implement. The result is a data-driven action priority matrix that sorts twenty-four supply chain interventions into strategic quadrants without any subjective scenario weighting.

The methodological foundation rests on four theoretical lenses. The natural resource-based view holds that embedding environmental imperatives into planning can create competitive advantage, and it governs the framework’s ‘Quick Wins’ quadrant, where relational procurement strategies achieve maximum ecological return at minimum capital cost. Resource dependence theory explains the ‘Major Projects’ quadrant, where organisations must pursue high-impact strategies such as renewables and on-site recycling despite severe infrastructure and capital dependencies. Institutional theory contextualises the ‘Thankless Tasks’ quadrant, where expensive Industry 4.0 applications such as blockchain operate as compliance traps — adopted for external legitimacy rather than genuine decarbonisation. Paradox theory then ties these competing logics together mathematically, using Euclidean spatial geometry to harmonise sustainability benefits against implementation barriers.

The reliability weighting is where the framework departs most sharply from conventional practice. Traditional multi-criteria decision-making methods, including fuzzy extensions of the Analytic Hierarchy Process, implicitly assume that every expert is equally logically consistent — a flaw the authors call fatal in complex supply chain modelling. Drawing on Zadeh’s Z-numbers, which pair a judgement with a measure of its reliability, the team instead extracted each respondent’s individual Consistency Ratio and converted it into a deterministic reliability scalar. Each expert’s crisp eigenvector was then penalised by the square root of this scalar before aggregation, so that highly consistent respondents exerted mathematically superior influence over borderline-inconsistent ones. Of 207 civil engineering professionals surveyed, 202 matrices passed the strict inclusion threshold of a Consistency Ratio below 0.10, with a mean of 0.0551.

Structural stability was validated through a ten-thousand-iteration non-parametric bootstrap resampling algorithm, which the authors deliberately chose over classical static-perturbation Monte Carlo simulations. Rather than injecting artificial uniform noise, the bootstrap resampled the pool of 202 expert matrices with replacement, capturing true inter-rater heterogeneity. The results were striking. Under standard unweighted aggregation, unreliable respondents artificially deflated the priority of raw material interventions to a mean of 0.3756; the Z-number penalty shifted the purified consensus weight to 0.3852 with a tightly constrained standard deviation of plus or minus 0.0050. The gap between the top-ranked criterion, raw material extraction and processing, and the second-ranked criterion, production, exceeded twenty standard deviations — a separation implying a near-zero probability of rank inversion within the observed sample.

The downstream TOPSIS stage introduced what the authors term techno-economic triangulation. Instead of asking managers to estimate capital expenditure in subjective surveys — a task they are rarely equipped to perform — the framework split the evaluation into two axes. The sustainability benefit axis was populated exclusively by the empirical expert data, while the implementation impedance axis was calibrated deterministically from recognised techno-economic and life cycle databases, including Ecoinvent version 3.9, the European Reference Life Cycle Database, the International Energy Agency’s Iron and Steel Technology Roadmap and the Annual Technology Baseline. Cost and complexity scores were mapped onto a discrete one-to-nine scale and averaged into a unified impedance score, deliberately assuming symmetrical elasticity between financial cost and technical difficulty to avoid injecting prior bias.

With both axes normalised into a synchronised zero-to-one Cartesian space, the true Euclidean TOPSIS engine computed exact geometric distances to the positive ideal solution of maximum benefit at zero impedance and to the negative ideal solution, yielding an absolute closeness coefficient for each of the twenty-four alternatives. The verdict was unambiguous. Choosing recyclable materials topped the ranking with a closeness coefficient of 0.8508, leveraging high sustainability yields against a minimal impedance score of just 2.0. Sourcing sustainably followed at 0.7583, with low-emission extraction suppliers third at 0.6902. At the other extreme, blockchain traceability collapsed to 0.2240 and retrofit machinery to 0.2213, their extreme capital and complexity penalties — impedance scores of seven or higher — mathematically eclipsing their localised environmental benefits.

To translate these vectors into policy, the algorithm partitioned the interventions using statistical medians rather than manually assigned boundaries, locking the impact threshold at a closeness coefficient of 0.4362 and the difficulty threshold at an impedance score of 4.50. Ten alternatives, dominated by procurement and relational strategies, landed in the Quick Wins quadrant of high impact and below-median difficulty. Two interventions — expanding renewables and on-site recycling — qualified as Major Projects, offering above-median impact but demanding substantial infrastructure scaling and phased, multi-stakeholder financing. Three fell into Fill-Ins, while nine alternatives, predominantly over-engineered technological deployments, were quarantined as Thankless Tasks. A follow-up bootstrap of the TOPSIS matrix confirmed that the top ranks, including the leading procurement strategies, carried a near-zero probability of rank inversion under bootstrapped expert variance.

The practical implications are blunt. The authors argue that enterprise capital should be aggressively diverted away from speculative digital technology and channelled into physical raw material procurement, where recyclable inputs and sustainable sourcing deliver immediate, localised decarbonisation without cannibalising core capital budgets. Institutional mandates to deploy blockchain or other Industry 4.0 tracking architectures before physical supply chains are optimised, they contend, should be suspended, because such tools function primarily as compliance mechanisms that drain capital from critical physical decarbonisation. The framework does carry acknowledged limits: the respondents were drawn predominantly from the civil engineering domain, the impedance axis is insensitive to live financial volatility, and the model performs static rather than dynamic optimisation. Future work, the authors suggest, should test priority invariance across sub-sectors and integrate adaptive stochastic optimisation with geospatial routing. For now, the message to construction firms is clear — the cheapest, most robust carbon cuts may lie not in the newest technology, but in simply choosing better materials.

Subject of Research: A reliability-weighted multi-criteria decision-making model for prioritising decarbonisation actions in upstream construction supply chains

Article Title: Z-Number reliability-weighted AHP–true Euclidean TOPSIS model for green upstream construction supply chains: A cradle-to-gate action priority matrix

Article References: Durgam, H. K. R., & Ramani, P. V. (2026). Z-Number reliability-weighted AHP–true Euclidean TOPSIS model for green upstream construction supply chains: A cradle-to-gate action priority matrix. Cleaner Engineering and Technology, 34, Article 101328. https://doi.org/10.1016/j.clet.2026.101328

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101328

Keywords: green supply chain, construction, decarbonisation, AHP, TOPSIS, Z-numbers, multi-criteria decision-making, embodied carbon, circular economy, recycled materials, bootstrap resampling, action priority matrix