Traditional building materials have some drawbacks in the construction industry, particularly in terms of greenhouse gas emissions and energy consumption. Biomaterials derived from renewable sources are a promising alternative, significantly reducing the greenhouse effect and enhancing energy efficiency. However, traditional materials still dominate the construction sector, and there is a lack of understanding among some policymakers and developers regarding biomaterials. Here, we review building biomaterials and their policies and life cycle assessment through case studies. Bio-based materials have the potential to reduce over 320,000 tons of carbon dioxide emissions by 2050. They also exhibit advantages like decreasing water absorption by 40%, reducing energy consumption by 8.7%, enhancing acoustic absorption by 6.7%, and improving mechanical properties. We summarize recent advancements in mycelial materials, bioconcrete, natural fibers, and fiber-reinforced composites. We also explore the contributions of nanotechnology and microalgae technology in enhancing biomaterials' thermal insulation and eco-friendliness.

In the high-energy, high-carbon landscape of the construction industry, a detailed and precise life cycle assessment (LCA) is essential. This review examines the role of building information modeling (BIM) software in streamlining the LCA process to enhance efficiency and accuracy. Despite its potential, challenges such as software interoperability and compatibility persist, with no unified standard for choosing BIM-integrated LCA software. Besides, the review explores the capabilities and limitations of various BIM software, LCA tools, and energy consumption tools, and presents characteristics of BIM-LCA integration cases. It critically discusses BIM-LCA integration methods and data exchange techniques, including bill of quantities import, Industry Foundation Classes (IFC) import, BIM viewer usage, direct LCA calculations with BIM plugins, and LCA plugin calculations. Finally, concluding with future perspectives, the study aims to guide the development of advanced LCA tools for better integration with BIM software, addressing a vital need in sustainable construction practices.

The construction industry, being responsible for a large share of global carbon emissions, needs to reduce its high carbon output to meet carbon reduction goals. Artificial intelligence can provide efficient support for carbon emission calculation and prediction. Here, we review the use of artificial intelligence techniques in forecasting, management and real-time monitoring of carbon emissions, focusing on how they are applied, their impacts, and challenges. Compared to traditional methods, the prediction accuracy of artificial intelligence models has increased by 20%. Artificial intelligence-driven systems could reduce carbon emissions by up to 15% through real-time monitoring and adaptive management strategies. Artificial intelligence applications improve energy efficiency in buildings by up to 25%, while reducing operational costs by up to 10%. Artificial intelligence supports the establishment of a digital carbon management system and contributes to the development of the carbon trading market.

Graphene oxide (GO) has been widely used as an additive due to its numerous unique properties. In this study, the compressive strength, flexural strength and elasticity modulus of concrete containing 0.02 wt%, 0.05 wt % and 0.08 wt % GO, and its dry shrinkage performance have been experimentally investigated. After the sample preparation, apparatus for compression test and flexural test were used to test the relevant properties of concrete containing GO. The dial indicators were used to measure the shrinkage of samples. The results indicate that GO can considerably improve the compressive strength, flexural strength, and elasticity modulus of concrete at the concrete age of 28 days by 4.04–12.65%, 3.8–7.38%, and 3.92–10.97%, respectively, which are substantially smaller than the increment at the age of 3 d by 5.02–21.51%, 4.25–13.06%, and 6.07–27.45% under a water-cement ratio of 0.35. It was also found that GO can increase the shrinkage strain of concrete. For example, at the age of 60 days, 0.02 wt%, 0.05 wt% and 0.08 wt% GO can increase the shrinkage strain of ordinary concrete by 1.99%, 5.79% and 7.45% respectively under a water-cement ratio of 0.49. The study has advanced our understanding on mechanical and shrinkage behavior of concrete containing GO.

Humidity change in concrete is the leading cause of concrete shrinkage. Moreover, the moisture diffusion coefficient of concrete is an essential parameter for assessing and predicting the internal moisture content of concrete. However, there is a lack of theoretical construction and experimental studies on the effect of different conditions, especially different constraints, on the moisture diffusion coefficient of concrete. Therefore, the internal humidity, pore structure parameters, and basic mechanical properties of concrete under different strength grades C30, C40, C50, and C60 (C stands for concrete and numbers indicate the strength class of the concrete), curing environments (dry and sealed curing conditions), and constraints were tested in this study. In addition, a calculation model of concrete’s internal humidity and humidity diffusion coefficient was established. The research findings show that the internal humidity of concrete decreased with age due to hydration and drying. External humidity had a significant effect on the moisture change of concrete, and the lower the external humidity, the larger the humidity diffusion coefficient and the faster the internal humidity of concrete decreases. Reinforcement (confinement) changes the pore structure parameters of the concrete, which in turn affects the transport of moisture within the concrete. The higher the reinforcement rate, the larger the pore structure parameters of the concrete, the larger the humidity diffusion coefficient, and the faster the concrete humidity decreases. The method proposed in the study can accurately predict the internal humidity of concrete using the humidity diffusion coefficient. The research results are a reference for preventing concrete shrinkage and cracking in construction.

This paper evaluates the shrinkage performance of concrete under complex internal constraint environments comprising steel plates, studs, and reinforcement to investigate their respective influence laws on the shrinkage performance of concrete. An early shrinkage model of concrete under complex internal constraints was established based on the theory of capillary tension, and the effects of steel plate, nails, and steel reinforcement on the shrinkage performance of concrete were theoretically analyzed. Six sets of concrete-constrained shrinkage tests and pore structure tests were then performed under different internal constraint conditions with the steel plate thickness, reinforcement diameter, and stud-related parameters (stud diameter, height, and spacing) as research variables. The test results demonstrate that the pore structure of concrete increases with the increase in the constraint coefficient, and that the increase in the pore structure will cause a decrease in the capillary pore stress, which is the driving force of concrete shrinkage. Its decrease will inevitably lead to a decrease in concrete shrinkage. By comparing the calculated values of the shrinkage model with the measured values, it is found that the average value of the prediction error is less than 15%, which reveals that the predicted values of shrinkage are in good agreement with the measured values and proves that the model can effectively predict the shrinkage of concrete that is restrained by steel plates, pins, and reinforcing bars.