This study examines the effects of three polymer binders—polyvinyl alcohol (PVA), polyethylene glycol (PEG), and polyacrylic acid (PAA) on the mechanical properties and dry–wet cycle corrosion resistance of cement mortar at different dosages (1–4%). Mechanical testing combined with scanning electron microscopy (SEM) and molecular dynamics (MD) simulations was conducted to validate the experimental findings and reveal the underlying mechanisms. Results show that polymers reduce early-age strength but improve flexural performance, and at low dosage, enhance compressive strength. PVA and PAA exhibited a pronounced improvement in mechanical strength while PVA and PEG showed a significant improvement in wet cycle corrosion resistance. SEM observations indicated that polymers encapsulate cement particles, enhancing interfacial bonding while partially inhibiting hydration. MD simulations revealed that PVA and PAA interact with Ca²⁺ via Ca-O coordination, while PEG primarily forms hydrogen bonds, resulting in distinct water-binding capacities (PEG > PVA > PAA). These interactions explain the enhanced mechanism of mechanical and dry–wet cycle resistance properties. This work combined experimental and molecular-level validation to clarify how polymer–matrix and polymer–water interactions govern mechanical and durability, respectively. The findings provide theoretical and practical guidance for designing advanced polymer binders with tailored interfacial adhesion and water absorption properties to improve cementitious materials.

To promote the sustainable utilization of agricultural solid waste, this study proposes a novel approach for reinforcing soft clay using a peanut ash (PA)–cement composite stabilizer. The unconfined compressive strength (UCS) of pure cement and PA–cement composite systems was tested at curing ages of 3, 7, and 28 days, while the durability of the stabilized clay was evaluated through dry–wet cycling. Given that PA is rich in pozzolanic components, its addition may influence the hydration process of cement. Therefore, hydration heat analysis was conducted to examine the early hydration behavior, and XRD and TG analyses were employed to identify the composition and quantity of hydration products. SEM observations were further used to characterize the microstructural evolution of the stabilized matrix. By integrating mechanical and microstructural analyses, the solidification mechanism of the PA–cement stabilizer was elucidated. Mechanical test results indicate that the reinforcing effect increases with the stabilizer dosage. Pure cement exhibited superior strength at 3 days; however, after 7 days, specimens incorporating 5% PA showed higher strength than those stabilized solely with cement. At 28 days, the UCS of the 15% cement + 5% PA specimen reached 3.12 MPa, 11.03% higher than that of the 20% cement specimen and comparable to the 25% cement specimen (3.15 MPa). After five dry–wet cycles, the strength reduction of the 15% cement + 5% PA specimen was 22.76%, compared to 31.31% for the 20% cement specimen, indicating improved durability. Microscopic analyses reveal that PA reduces hydration heat and does not participate in early hydration, leading to lower early strength. However, its pozzolanic reactivity contributes to secondary hydration at later stages, promoting the formation of additional C-S-H gel and ettringite. These hydration products fill the inter-lamellar pores of the clay and increase matrix density. Conversely, excessive PA content (≥10%) exerts a dilution effect, reducing the amount of hydration products and weakening the mechanical performance. Overall, the use of an appropriate PA dosage in combination with cement enhances both strength and durability while reducing cement consumption, providing an effective pathway for the high-value utilization of agricultural solid waste resources.

Additive manufacturing enables the fabrication of complex geometries and structures that are difficult to attain by conventional methods. However, many printable materials exhibit inherent trade-offs among their performance properties. Traditional material design, often relying on intuition-driven and inefficient trial-and-error approaches, frequently fails to identify optimal formulations. In this study, we propose a machine learning-assisted framework to efficiently refine the composition of 3D-printable calcium sulphoaluminate (CSA) cement composites with a balanced trade-off among thixotropy, mechanical strength, and shape stability. Our approach integrates a multi-objective optimization algorithm with a data-driven surrogate model to intelligently propose new mix proportions, thereby reducing the number of required experiments. Starting from seven primary formulations and 28 initial experimental samples, the method identified 23 improved mix proportions after only 20 algorithm iterations. The workflow demonstrates how optimization-assisted formulation refinement can accelerate the search for better-performing materials and is potentially adaptable to other material design challenges.