Molecularly Engineered Polymer-Modified Concrete with Autonomous Self-Healing: Mechanistic Insights into Inhibitor Release Kinetics and Service Life Prediction

The durability of reinforced concrete infrastructure is critically threatened by cracking-induced corrosion, prompting the development of autonomous self-healing polymer-modified cementitious composites. This comprehensive review systematically examines the molecular engineering of polymer systems for concrete self-healing, focusing on the mechanistic understanding of inhibitor release kinetics and service life prediction. Superabsorbent polymers (SAPs) have demonstrated remarkable efficacy, achieving up to ۹۷% reduction in autogenous shrinkage and complete crack healing through internal curing and promoted autogenous healing mechanisms . Microbial self-healing systems utilizing bacteria-induced calcium carbonate precipitation have achieved crack healing depths exceeding ۴۰ mm, with healing efficiency directly correlated to crack width and bacterial metabolic activity . Polymeric corrosion inhibitors incorporating functional groups (-COOH, -NH₂, -SO₃H) exhibit inhibition efficiencies exceeding ۹۰% through chemisorption mechanisms, with the neutralizing cation critically influencing performance through distinct adsorption pathways . Smart microcapsule systems demonstrate pH-responsive release behavior, with release rates increasing at lower pH values characteristic of corrosion initiation environments . Advanced computational approaches including generalized Polynomial Chaos Expansion enable full-cycle prediction of crack healing with high reliability , while machine learning models achieve R² values of ۰.۹۹۱۸ for autogenous healing forecasting . This review concludes that integrated molecular design, controlled release mechanisms, and predictive modeling frameworks offer transformative potential for extending concrete service life by factors of ۱۰ or more.

کلیدواژه ها:

Self-healing Concrete ، Polymer-modified Concrete ، Corrosion inhibitors ، release kinetics ، service life prediction