Auxetic cementitious cellular composites (ACCCs) offer high deformability that is attractive for mechanical energy harvesting when integrated with flexible piezoelectric materials. However, the intrinsic brittleness of cement-based materials and the complex coupling between auxetic geometry and damage evolution hinder the efficient design of ACCC energy harvesters. This study proposes a novel learning-driven design framework that, for the first time, integrates a physics-based energy harvesting model with Bayesian Optimization (BO) to directly optimize the recoverable hinge-like strain capacity of ACCCs for enhanced electrical output. The optimization maximizes the voltage generated by piezoelectric materials bonded at hinge regions, while using constraints to prevent splitting failure and non-auxetic behavior under compression. The energy harvesting model combines the concrete damage plasticity (CDP) model for pre-compression damage with a secondary elastic model for cyclic loading, enabling prediction of recoverable strain in generalized ACCC geometries. The learning-driven approach proved far more efficient than random generation in identifying optimal ACCC configurations. Experimental validation of the optimized design achieved a peak-to-peak voltage of nearly 15.0 V per cycle, about 2.7 times higher than a reference design. This study provides a learning-driven approach to designing enhanced compliant auxetic cementitious energy harvesters for smart infrastructure applications.

The use of Additive Manufacturing (AM) to create reinforcements for cementitious composites has become a popular research topic in recent years. One illustrative example is the integration of 3D-printed auxetic reinforcements into cementitious matrices, which exhibit superior energy absorption due to their negative Poisson's ratio. This presents the opportunity to tailor the Poisson's ratio of reinforcements to align with local stress distributions and enhance structural efficiency. In this study, Tailored Poisson's Ratio-reinforcements (TPR) were proposed, characterized by a linear gradient of Poisson's ratios along the height of the reinforcement to accommodate varying stress profiles within beams. Specifically, the top chords of TPR exhibit negative Poisson's ratios (auxetic), undergoing lateral contraction under compression and providing confinement to the surrounded matrix. Conversely, the bottom chords possess positive Poisson's ratios, contributing to lateral contraction under tension. These lateral deformations cause a shift in the principal stress state of the confined matrix, extending the loading path in stress space and actively delaying failure. Three novel Tailored Poisson's Ratio-reinforced Cementitious Composite (TPRCC) designs are developed and tested under four-point bending in this study. Experimental recordings indicate increases in load capacity and toughness of up to 191% and 6900% with respect to plain mortar, respectively.

Anisotropy in 3D-printed concrete structures has persistently raised concerns regarding structural integrity and safety. In this study, an architected 3D printing strategy, “stitching”, was proposed to mitigate anisotropy in 3D-printed Engineered Cementitious Composites (ECC). This approach integrates the direction-dependent tensile resistance of extruded ECC, the mechanical interlocking between three-dimensional layers, and a deliberately engineered interwoven interface system. As a result, the out-of-plane direction of the printed structure can be self-reinforced without external reinforcements. Four-point bending tests demonstrated that the “stitching” pattern induced multi-cracking and flexural-hardening behavior in the out-of-plane direction, boosting its energy dissipation to 343 % of the reference “parallel” printing and achieving 48.6 % of cast ECC. Additionally, micro-CT scanning and acoustic emission tests further validated the controlled crack propagation enabled by the engineered interface architecture. The proposed strategy has been proven to substantially alleviate anisotropy and enhance structural integrity.

The microstructure of cement paste determines the overall performance of concrete and therefore obtaining the microstructure is an essential step in concrete studies. Traditional methods to obtain the microstructure, such as scanning electron microscopy (SEM) and X-ray computed tomography (XCT), are time-consuming and expensive. Herein we propose using Denoising Diffusion Probabilistic Models (DDPM) to synthesize realistic microstructures of cement paste. A DDPM with a U-Net architecture is employed to generate high-fidelity microstructure images that closely resemble those derived from SEM. The synthesized images are subjected to comprehensive image analysis, phase segmentation, and micromechanical analysis to validate their accuracy. Findings demonstrate that DDPM-generated microstructures not only visually match the original microstructures but also exhibit similar greyscale statistics, phase assemblage, phase connectivity, and micromechanical properties. This approach offers a cost-effective and efficient alternative for generating microstructure data, facilitating advanced multiscale computational studies of cement paste properties.

Self-healing concrete, with its ability to autonomously repair damages, holds promise in enhancing its structural durability and resilience. Research on self-healing concrete in the past decade has advanced in understanding the mechanisms behind healing, exploring various healing agents, and assessing their effectiveness in concrete structures. However, the full potential of self-healing concrete remains untapped unless its effects are effectively integrated into the design practices of reinforced concrete structures. Realizing this challenge, this paper synthesizes the current research progress and discusses the possibilities to consider self-healing into design codes. The focus was placed on two specific benefits of applying self-healing concrete: one centered on durability and the other on mechanical performance. Specifically, the effect of self-healing on impeding chloride penetration into cracked reinforced concrete was discussed first. Modifications of parameters in existing predictive models based on different types of healing approaches were recommended. Furthermore, the possible impact of the self-healing capacity in mitigating the stiffness reduction of concrete was also discussed. Equations that can describe the stiffness regained due to healing action are presented. In each part of the case study, limitations and challenges still hindering standardization and wider application in the construction field are discussed.

Due to the gradual diffusion of CO₂ under natural exposure, areas with varied degrees of carbonation exist at different depths from the surface of slag-rich cement paste. While extensive research has been dedicated to investigating the fully carbonated zone as identified by phenolphthalein spray, the transitional zone, located between the fully carbonated and the uncarbonated regions, has received comparatively less attention. This study thus aims to address this research gap by exploring its microstructural, micromechanical, and mineralogical properties. The results reveal that carbonation-induced damage extends beyond the fully carbonated zone as identified by phenolphthalein. Particularly in the transitional area close to the carbonated zone, nanoindentations results reveal that micromechanical properties of this area are even lower to that of the fully carbonated zone. In addition, mineralogical investigation suggest that the depth of carbonation stays within the range where slag-containing blends loses its green coloration. By comparing specimens with different slag composition, it was found that the depth of this faded green area can be an important indicator to assess the carbonation resistance of slag-containing blends.

Additive manufacturing (AM) has revolutionized the fabrication of complex geometries, enabling efficient material use and innovative applications across sectors such as biomedical, automotive, and aerospace. A significant development is the emergence of 3D-printed lattice structures (LSs), which combine lightweight design with tailored mechanical properties, making them highly suitable for civil engineering applications, including bridge elements, façade systems, and reinforcement of concrete structures. Recent research has increasingly explored the integration of LSs into cementitious composites, though findings remain diverse and primarily experimental. This paper provides a comprehensive review of lattice structures in cement-based materials, examining both their classifications–by dimensionality (2D vs. 3D) and configuration (cellular vs random)–and their role in enhancing ductility, reducing weight, and improving overall performance. It also surveys materials commonly used in 3D printing, such as polymers (PLA, PEEK, ABS), ceramics, and composites, along with relevant printing techniques. Evidence demonstrates that LSs significantly improve the mechanical behavior of cementitious composites, transforming failure modes from brittle to ductile and increasing energy absorption. These findings highlight the potential of 3D-printed lattices as effective reinforcements, offering promising pathways for advancing structural performance in construction.

This study evaluates the performance of damaged concrete beams retrofitted with a purpose-designed mechanochromic composite, which provides structural reinforcement and visual feedback for structural health monitoring (SHM). The retrofitting process utilizes externally bonded reinforcement (EBR) on pre-damaged concrete prisms. The mechanochromic composite, a thin-ply hybrid material made of unidirectional ultra-high modulus (UHM) carbon/epoxy and S-glass/epoxy layers, changes color to indicate structural overload when the UHM carbon layer fractures due to excessive strain. Eighteen concrete specimens were prepared and subjected to four-point bending tests, assessing various combinations of damaged, undamaged, retrofitted, and non-retrofitted configurations. Results showed that the mechanochromic composite functions effectively as both a passive visual sensor and reinforcement. For instance, a 5 % crack depth reduced load-bearing capacity by 30 %, however, retrofitting with the mechanochromic composite improved load-bearing capacity by up to 208 % compared to undamaged beams. The study further discusses the effects of different damage levels on load-bearing capacity through flexural strength, load-displacement curves, and failure modes.

Auxetic cementitious cellular composites (ACCCs) exhibit hinge-type recoverable deformation during auxetic behavior phase, a rare pseudo-elastic property in cementitious materials. However, their low load-bearing capacity during this phase restricts their use in high-load applications. This study developed ACCCs using strain-hardening cementitious composites (SHCCs) with short (SHCC-SS) and long (SHCC-LS) softening tails, fabricated by additive manufacturing-assisted casting. Uniaxial compression tests employing Digital Image Correlation (DIC) evaluated their compressive behavior, peak strength, Poisson's ratio variation, and energy dissipation. Cyclic tests after pre-compression assessed their recoverable deformation resilience, with fiber bridging at joint cracks examined using digital optical microscope. Results were compared to a reference using fiber-reinforced cementitious materials with strain softening (SS). Compared to the reference (SS), ACCCs using SHCC mixtures exhibit superior load-bearing capacity and stable auxetic behavior under compression. After self-contact, they maintain a negative Poisson's ratio up to a considerably high compressive strain, preventing splitting failure and preserving structural integrity. This is because incorporating SHCC enables greater joint rotation by promoting multiple cracks with strain hardening, which delays primary crack formation and reduces its opening. During cyclic tests, P1-shaped ACCCs with SHCC-LS and SHCC-SS enhance the elasticity modulus of recoverable deformation by 4.8 and 3.0 times, respectively, compared to SS. SHCC-LS outperforms SHCC-SS in compressive resilience due to its prolonged softening tail, which improves fiber bridging in primary cracks and increases rotational stiffness in hinge joints. SHCC mixtures with initial strain hardening and extended softening enable scalable design of advanced auxetic cementitious materials across various load levels.