In this study, we report a new epoxy acrylate based shape memory polymer (SMP) fabricated by Liquid crystal display (LCD) Stereolithographic 3D printing. The printed 3D object has a high resolution and high transparency in visible light region. The uniaxial tensile tests showed enhanced tensile toughness and tunable mechanical properties. The fix-recovery and cycle tests indicated high shape recovery properties including high shape recovery rate and excellent cycling stability. In addition, a smart electrical valve actuator was fabricated that can be used in fast heat or electricity responsive electrical circuits. LCD 3D printing provides a low-cost and high efficient way to fabricate fast responsive SMP, which can be used in wide applications in various fields on aerospace engineering, biomedical devices, soft robots and electronic devices.

In this study, a new structure is proposed based on the body-centered cubic (BCC) lattice structure by adding a cubic truss in the center of the BCC structure and denoting it TLC (truss–lattice–cube). The different dimensions of the central cube can notably affect the mechanical properties of the lattice structure. With a fixed length (15 mm) of a unit cell, the optimal size for the central cube is determined to be 5 mm. Quasi-static compressive tests are performed on specimens made of polylactic acid (PLA) using additive manufacturing technology. The deformation characteristics of the new structure are analyzed in detail by experiments and numerical simulations. Compared to the BCC structure, the mechanical properties of the TLC structure were significantly improved. The initial flow stress of the TLC increased by 122% at a strain of 0.1; the specific strength enhanced by 293% at a strain of 0.5; and the specific energy absorption improved by 312% at a strain of 0.6. Printing defects in the lattice structure may remarkably damage its mechanical properties. In this work, incorporation of microcracks into the finite element model allows the simulation to capture the influence of printing defects and significantly improve the predictive accuracy of the simulation.

Elastic modulus, crucial for assessing material stiffness and structural deformation, has recently gained popularity in predictions using data-driven methods. However, research systematically comparing different machine learning models under the same conditions, especially for ultra-high-performance concrete (UHPC), remains limited. In this study, 10 different machine learning models were evaluated for their capacity to predict the elastic modulus of UHPC. The results showed that XGBoost demonstrated the highest accuracy in predictions with large training datasets, followed by KNNs. For smaller training datasets, Decision Tree exhibited the greatest accuracy, while XGBoost was the second-best performing model. Linear regression displayed the lowest accuracy. XGBoost demonstrated the most potential for accurately predicting the elastic modulus of UHPC, particularly when a comprehensive dataset is available for model training. The optimized XGBoost exhibited better predictive performance than fitting equations for different UHPC formulations. The findings of this study provide valuable insights for researchers and engineers working on the data-driven design and characterization of UHPC.

In this study, a new structure is proposed based on the body-centered cubic (BCC) lattice structure: adding a cubic truss in the center of the BCC structure, which is denoted by TLC (Truss-lattice-cube). The different dimensions of the central cube can affect the mechanical properties of the lattice structure notably. With a fixed length (15mm) of a unit cell, the optimal size for the central cube is determined to be 5 mm. Quasi-static compressive tests are performed on specimens made of Polylactic Acid (PLA) using additive manufacturing technology. The deformation characteristics of the new structure is analyzed in detail by experiments and numerical simulations. Compared to the BCC structure, the mechanical properties of the TLC structure are significantly improved. The initial flow stress of the TLC has been increased by 122% at a strain of 0.1; the specific strength has been enhanced by 293% at a strain of 0.5; and the specific energy absorption has been improved by 312% at the strain of 0.6. Printing defects in the lattice structure could deteriorate the mechanical property remarkably. In this work, incorporation of microcracks into the finite element model makes the simulation capture the influence of printing defects and improve the predictive accuracy of simulation significantly.