3D printed concrete (3DPC) creates opportunities, including a reduction in construction waste and time and increased design freedom. However, because of the differences in the construction technique compared to traditional concrete casting, the structures also perform differently; namely, the micro- and meso-structure and durability are shown to be different. For the 3DP technology to find its way to the market, one needs to be aware of these differences and needs to know how to quantify the above-mentioned properties, as differences in the testing methodologies impose themselves when characterizing printed instead of cast concrete. In this paper, we elaborate on the test methods to investigate the micro- and meso-structure and the durability of 3DPC. We start with a discussion on the micro- and meso-structure of the 3D printed concrete and how it is different from conventional mold-cast concrete. An in-depth discussion of the test methods to assess the durability of 3D printed concrete is outlined. Reported findings related to the two aforementioned properties are discussed. In addition, we report on the technologies proposed to improve the durability performance of 3DPC, and we highlight the remaining challenges and opportunities related to 3DPC.@en

The proper control of the rheological performance of silicate-based alkali-activated slag (AAS) mixtures is problematic, as the conventional superplasticizers become less effective in alkaline media. Nevertheless, several methods have been proposed to improve the workability of silicate-activated AAS, such as by extending the mixing time, and replacing sodium silicate with sodium carbonate activators. However, the underlying fluidizing mechanism is not yet well understood in the literature, which is crucial knowledge to achieve proper rheology control of silicate-activated AAS. In this study, the effects of mixing conditions and activator anionic species on the rheology of silicate-activated AAS concrete have been assessed. The reaction products, particle size and interparticle interactions, as well as the reaction kinetics in AAS, have been further investigated to understand the distinct fluidizing mechanisms. By using a longer mixing time, it was found that the solid particles formed at early ages are broken down into smaller particles, accompanied by a slight increase in the amount of reaction products to improve the fluidity. With the sodium carbonate substitution, the calcium ions dissolved from slag particles are entrapped into calcium carbonate precipitates to slow down the accumulation of C-(A)-S-H phases, leading to a better dynamic flow. However, the interparticle interactions are intensified due to the formation of larger particles and the declined dispersing effect induced by silicate activators.

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To properly control the reaction kinetics and fresh properties evolution in conventional alkali-activated materials (AAMs), a conceptual design of two-stream AAMs has been proposed in this study. This is achieved by dividing the solid and liquid components in AAMs, including blast furnace slag (BFS) and electric arc furnace slag (EFS) precursors, as well as aqueous sodium hydroxide and silicate activators into two separate streams A and B, where a very limited reactivity is expected in individual streams to ensure sufficient workability retention. Moreover, a final-stage intermixing is required to combine individual stream mixtures and trigger the major activation reaction. Fresh and hardened properties of combined mixtures were checked at different stages. The microstructure and reaction products were investigated to understand the strength development. Low dynamic rheological parameters and good workability retention have been detected in all individual stream mixtures, accompanied by limited exothermic heat flows after the initial dissolution confirmed by calorimetry tests. Further, Portland cement (PC) is partially blended into stream A to alter the early stiffening process in combined mixtures and meet various setting demands after intermixing. However, this might lead to a reduction in mechanical properties, associated with the formation of porous microstructures and an increase in the Ca/Si ratio in reaction products. Eventually, the conceptual design is validated in different scenarios including self-compacting and 3D-printing concrete applications.

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Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly correlate the AAC mix design parameters to their performances through an artificial intelligence approach. To be specific, 145 fresh property data and 193 mechanical strength data were collected from laboratory tests on 52 AAC mixtures, which were used as inputs for the machine learning algorithm. Five independent random forest (RF) models were established, which are able to predict fresh and hardened properties (in terms of compressive strength, slump values, static/dynamic yield stress, and plastic viscosity) of AAC with equivalent accuracy reported in the literature. Moreover, an inverse optimization was performed on the RF model obtained to reduce the sodium silicate dosages, which may further mitigate the environmental impact of producing AAC. The present RF model gives practical information on AAC mix design cases.

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