With the ongoing expansion of global housing and infrastructure, cement as an essential component of concrete is projected to reach a global demand of 468 million tonnes by 2050, contributing approximately 6%-7% of total CO₂ emissions. Reducing carbon emissions in cement and concrete production is thus critical for achieving carbon neutrality goals. In the central and western regions of China, a growing demand for large infrastructure projects such as dams, tunnels, and mountain bridges increasingly relies on the use of mass concrete. However, a great heat release from cement hydration with a low thermal conductivity leads to internal heat accumulation and significant temperature differentials. These thermal gradients increase cracking risk and compromise long-term durability. Conventional strategies like low-heat cement, mineral admixtures, and chemical retarders are adopted to mitigate early hydration heat. Nevertheless, these approaches are limited due to high production costs, reduced strength, or insufficient control over heat evolution rate. Recently, carbon capture, utilization, and storage (CCUS) technologies, particularly semi-dry carbonation, show a promising potential for reducing carbon emissions and regulating hydration heat, especially for high-alkaline materials. In this study, semi-dry carbonation pretreatment was applied to Portland cement, forming a surface layer of CaCO₃ that serves as a physical barrier to suppress early hydration. The effect of semi-dry carbonation on the hydration behavior and microstructure was investigated. The results could provide some insights into applying CCUS technology for hydration heat control in cement-based materials.

A P·I 42.5 Portland cement (Fushun Cement Co., Ltd., China) was used. Semi-dry carbonation was performed in a NELD-CA070 carbonation chamber using simulated kiln gas containing 20% CO₂ at a RH of (70% ± 5%) and a temperature of (20 ± 2) ℃. The cement was loosely spread in trays and carbonated for 2, 4 h, or 8 h, respectively, under manually stirring for every 30 min. The resulting samples were designated as C2, C4, and C8, respectively, while the uncarbonated sample was labeled as C0. All the samples were dried at 40 ℃ for 24 h after carbonation.

Cement pastes were prepared at a water-to-cement ratio of 0.4 and cured under standard conditions (i.e., 20 ± 1 ℃, 95 ± 5% RH). For the determination of compressive strength, cube specimens (40 × 40 × 40 mm) were tested at 1, 3, 7 d, and 28 d, respectively. For the microstructural analysis, fresh pastes were cast in sealed vials, demolded after 24 h, immersed in water, and cured until the specified age. Hydration was stopped by solvent exchange with isopropanol, followed by vacuum drying and grinding to a fine powder with the particle size below 80 μm.

The early hydration heat evolution was measured by isothermal calorimetry (TAM Air). The phase composition was determined by isothermal calorimetry, thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The pore solution alkalinity was assessed through pH measurement and elemental analysis by inductively coupled plasma optical emission spectrometry (ICP-OES). The pore structure was characterized by mercury intrusion porosimetry (MIP), and the microstructure was determined by scanning electron microscopy (SEM).

The semi-dry carbonation alters the phase composition and microstructure of cement. The TG analysis shows a weakened gypsum decomposition peak and an intensified CaCO₃ decomposition, indicating that gypsum participates in carbonation. The mild carbonation (i.e., 2-4 h) increases CH content due to enhanced pre-hydration. CO₂ sequestration reaches 1.60%, 2.27%, and 3.62% after 2, 4 h, and 8 h, corresponding to 3.62%, 5.16%, and 8.23% CaCO₃ formation, respectively. As carbonation progresses, C₃S, C₂S, C₃A, C₄AF, and gypsum decrease, while calcite and amorphous silica increase, driven by reactions with CO₂ and moisture. The FTIR spectra show strengthened C—O stretching (1410 cm^-1), weakened H₂O peaks (3527 cm^-1), and intensified SO₄^2- bands (1124 cm^-1 and 1197 cm^-1), indicating interactions among gypsum, CO₂, and alkali oxides. The SEM images reveal roughened clinker surfaces caused by the deposition of carbonation products such as calcite and silica gel.

The semi-dry carbonation significantly reduces early compressive strength, with 1-d reductions of 31.2%, 77.5%, and 89.6% after 2, 4 h, and 8 h, respectively. However, this effect diminishes over time, with less than 5.4% strength loss at 28 d. Carbonation extends the induction period and reduces hydration heat, lowering cumulative heat by 67.2% at 10 h. Early hydration degrees and chemically bound water also decrease, corresponding to reduced CH content and early strength. Despite this, hydration products at < 400 ℃ are largely unaffected, having the minimal difference in 28-d strength. Early-age pore solution alkalinity declines significantly. In the C8 group, Na⁺ and K⁺ concentrations at 1 d are reduced by 60% and 40.7%, and the pH value is decreased from 13.52 to 13.18. At 28 d, the pH value becomes 13.5, indicating no risk to reinforcement passivation. At this age, total porosity increases slightly from 21.1% to 22.8%, with a minor rise in capillary and gel pores. The SEM images and MIP analyses confirm similarly dense microstructures across all the samples, indicating that the calcite layer is eventually penetrated and has no adverse long-term effect.

This study showed that emi-dry carbonation could alter the phase composition and microstructure of Portland cement. After 2-h, 4-h, and 8 h-carbonation, CO₂ sequestration increased to 1.60%, 2.27%, and 3.62%, respectively, accompanied by a reduction in clinker minerals and gypsum and formation of amorphous silica and calcite layers on cement particle surfaces. These calcite layers could effectively suppress early hydration by reducing the contact area between water and reactive clinker phases. As a result, cumulative heat release at 3 d was decreased by 14.7%, 35.1%, and 58.1%, respectively, leading to a lower early compressive strength, a pore solution alkalinity, and a looser microstructure. However, the long-term effect was limited. At 28 d, the continuous formation of hydration products penetrated the calcite layer, and hydration degree and product quantity were reduced by less than 7%, and the compressive strength, pH value, and porosity were altered by no more than 5.4%, 0.1, and 8.1%, respectively.

The sulfate source in calcium sulfoaluminate (CSA) cement is an important factor that determines its hydration characteristics, and the properties of CSA cement can be controlled via adjusting the molar ratio of calcium sulfate to ye'elimite (generally referred to as the "M-value"). Sulphosilicate cement is a novel cementitious material developed via incorporating ternesite (C₅S₂$) and free-calcium sulfate (f-C$) into the mineral composition of CSA cement. The calculation of the M-value must comprehensively account for their contents in the clinker due to the presence of SO₃ in C₅S₂$ and f-C$. This study optimized the conventional calculation formula for the M-value and systematically investigated its influence on the compressive strength and expansion behavior of sulphosilicate cement. In addition, the mechanism underlying the effect of anhydrite dosage on cement hydration was also elucidated through the evolution of hydration products.

In this experiment, sulphosilicate clinker was synthesized with limestone, fly ash, phosphogypsum, and bauxite as raw materials. The raw materials were calcined at 1250 ℃ for 1 h, followed by rapid air quenching to obtain the clinker. Five groups of sulphosilicate cement with M-values of 0, 0.9, 1.8, 2.7, and 3.6 were designed. Mortar specimens were prepared to evaluate compressive strength and expansion rate, while paste specimens were prepared for analyzing hydration product characteristics at specific ages. The hydration heat release was measured by an isothermal calorimeter. The phase compositions and microstructure of the hydration products were analyzed by X-ray diffractometer, thermal behavior analyzer and field-emission environmental scanning electron microscope. The pore structure was performed by a mercury intrusion porosimeter.

Among the various sulphoaluminate cement groups, the M_1.8 specimen demonstrates the maximum compressive strength of 43.9 MPa after 3-d hydration. As hydration progresses, the compressive strength of the M_2.7 and M_3.6 groups shows a significant growth, with the M_3.6 group reaching 56.7 MPa at 14 d. However, the M_3.6 specimen exhibits a notable strength retrogression, which, is decreased by 4.3 MPa, after 28-d hydration. In contrast, the compressive strength of the M_0.9 group increases markedly from 14 d to 28 d, with an improvement of 12.3 MPa.

For specimens with the M-value below 1, the early hydration products at 3 d are dominated by AFm phases with insufficient AFt content, resulting in an initial shrinkage. As hydration progresses, the dissolution of SO₃ from anhydrite and C₅S₂$ promotes AFt formation, leading to a measurable expansion after 7 d. At low M-values, AFt contributes to pore refinement, while the reaction of C₅S₂$ and C₂S in later stages generates C-(A)-S-H gel and stratlingite (C₂ASH₈), refining the microstructure of hydration products and enhancing long-term strength. In contrast, specimens with higher M-values (i.e., 1.8, 2.7, and 3.6) exhibit expansion as early as 3 d. Increased anhydrite content and prolonged hydration amplify the crystallographic stress exerted by AFt crystals on the surrounding matrix, causing coarsening of pores, and elevated total porosity, and resulting in strength retrogression during 14-28 d of curing.

This study was to propose a formula for calculating the gypsum coefficient M-value in sulphosilicate cement, i.e., C_G= 0.13 × M × (Y - A×2.24 - T×1.27)/S_g, establishing the relationship between gypsum dosage and cement performance, while elucidating the influence of M-values on the mechanical properties and hydration mechanisms. The experimental results demonstrated that within the optimal M-range of 0.9-1.8, cement could achieve continuous strength development for all curing ages. Higher M-values (2.7-3.6) enhanced mid-term strength but induced strength regression at 28 d. Increasing M-values effectively suppressed early-age shrinkage and induced progressive expansion, and expansion rates were positively correlated to M-values at all hydration stages. Hydration products primarily consisted of AFt, AH₃, and C-(A)-S-H gel. At M₀ and M_0.9, AFm phases formed during early hydration, followed by C₂ASH₈ in later stages. Conversely, M-values of ≥1.8 accelerated C₄A₃$ hydration but inhibited both C₅S₂$ dissolution and C₂ASH₈ formation. Microstructurally, M_0.9 specimens exhibited pore refinement and reduced porosity through gel-phase densification, enhancing strength development, whereas M_3.6 samples suffered from coarse pore proliferation due to excessive anhydrite content promoting oversized AFt crystals, ultimately degrading 28-d strength. At the M-value of 0.9-1.8, the system achieved balanced high strength and minimal volumetric deformation, making it suitable for general engineering applications. Elevating the M-value to 1.8-2.7 induced a controlled expansion behavior, enabling targeted use in shrinkage compensation scenarios. However, at the M value of 3.6, delayed strength retrogression and microstructural deterioration could occur, thus establishing 3.6 as a critical upper limit for M-values.

As a type of energy-saving and environmental protection building system, steel structure building is widely used in engineering construction in recent years, and its fire protection measures are particularly important. At present, the commonly used fire retardant coatings are mainly divided into two categories, i.e., organic intumescent and inorganic non-intumescent coatings. Although organic intumescent coatings exhibit a good fire resistance in the initial stage, their duration of protection is relatively short, and they may release toxic and corrosive gases during combustion, posing certain safety risks. In contrast, inorganic non-intumescent fireproof coatings have advantages such as high thermal resistance, strong durability, good wear resistance, and low cost, making them considered as an ideal fire protection material for steel structures. However, some issues such as insufficient adhesion and poor overall durability seriously limit its widespread application in practical engineering. Magnesium phosphate cement (MPC) is regarded as a fireproof material with an application potential due to its high strength, high-temperature resistance and excellent interfacial bonding performance with steel. However, the conventional raw material for MPC like dead-burned magnesia has a high density and carbon emissions, which is unfavorable for its green and sustainable development. To address the above issues, this study was to select a low-grade natural brucite powder as a complete substitute for dead-burned magnesia to prepare magnesium phosphate cement, and optimize the physical, mechanical, and fire insulation properties of brucite-based magnesium phosphate steel structure fireproof coatings (BMPC) via introducing modified expanded perlite.

The raw materials for the preparation of BMPC included natural brucite powder, ammonium dihydrogen phosphate, analytical grade borax, and expanded perlite. Expanded perlite was divided into two types, i.e., untreated (EP) and water absorption pretreatment (HEP) according to different treatment methods. Under the condition of fixed process parameters (i.e., M/P mass ratio of 2.5, borax content of 15%, water-cement ratio of 0.17, and expanded perlite content of 0-20% of the total mass of brucite powder and ammonium dihydrogen phosphate), the BMPC slurry was prepared.

The dry density and surface drying time of the BMPC coating under natural curing conditions were tested in accordance with the standard GB 14907—2018. The compressive strength and adhesive strength tests were conducted on the specimens after 3-d, 7-d and 28-d curing, respectively. The thermal conductivity of BMPC was determined by a transient plane source method. The fire resistance limit was tested according to the standard GB/T 9978.1—2008. The internal pore structure of BMPC samples was analyzed by an industrial computed tomography system, and its microstructure was analyzed by field emission scanning electron microscopy. The phase change of BMPC coating before and after fire test was analyzed by X-ray diffractometry, and its thermal stability in the range of 30-1000 ℃ was analyzed by thermogravimetric analysis.

The expanded perlite (HEP) after water absorption treatment has a more open pore structure and a higher surface roughness rather than the untreated expanded perlite (EP). In the BMPC system, the HEP has a relatively small effect on the mechanical properties, especially under low density conditions, it can still maintain high compressive strength and adhesive strength. At the HEP content of 20%, the microporous structure inside the material significantly reduces the thermal conductivity and thermal diffusion coefficient. This is mainly since the HEP acts as a low thermal conductivity filler, and the air layer retained in its pores (i.e., thermal conductivity of 0.026 W/(m·K)) effectively blocks heat transfer. Also, the introduction of HEP optimizes the pore structure, reduces the proportion of large pores, makes the heat conduction path more complex, delays the diffusion process of heat into the substrate, and significantly slows down the flame propagation rate and thermal decomposition process. The results of fire resistance test and pore structure show that the porosity of BMPC-HEP sample is higher than that of the control group, and the standard deviation of pore fluctuation increases from 4.0% to 5.1%, indicating that HEP forms a lightweight porous structure at a high temperature, further improving the thermal insulation performance and thermal stability of the material. The addition of HEP has a significant effect on the microstructure of BMPC at a high temperature. Some struvite and unreacted raw materials absorb a large amount of heat during pyrolysis, which plays a role in delaying temperature rise and enhancing thermal buffering, and provides an important support for the thermal insulation protection mechanism of fire retardant coatings.

The expanded perlite after water absorption treatment had little effect on the mechanical properties of BMPC system. When the density reduced from 1062 kg/m³ to 647 kg/m³, the 28-d compressive strength and adhesive strength were only reduced by 26.5% and 17.7%, respectively. At the content of HEP of 20%, the thermal conductivity and thermal diffusivity of BMPC were 49.3% and 44.0% lower than those of BMPC without HEP, respectively. The significant improvement of this thermal performance could be mainly attributed to the fact that HEP itself had low density and low thermal diffusion characteristics, effectively slowing down the heat transfer rate in the process of temperature change, and thereby improving the thermal insulation performance of the material. The fire resistance limit of BMPC-HEP system reached 206 min, which was significantly better than that of the control sample. Its excellent fire resistance was mainly attributed to the synergistic effect of porous structure, low thermal conductivity filler and microstructure stability at a high temperature, indicating that it could have a promising application potential in the field of fire retardant coatings for steel structures.

The low alkalinity makes super-sulfate cement (SSC) vulnerable to being carbonated by CO₂. In this paper, we investigated two magnesium slags, i.e., MSⅠ (the proportion of β-C₂S is higher) and MSⅡ (the proportion of γ-C₂S is higher), and analyzed the impact of CO₂ concentration (i.e., 3% and 20%, in volume) on the SSC from the perspectives of hydration and carbonation. The results show that the addition of MSⅠ (with the higher proportion of β-C₂S) to SSC has a negative impact on the hydration and carbonation resistance due to β-C₂S with a stronger hydration activity, suppressing the hydration of SSC itself and lowering the hydration degree of SSC, reducing the amount of hydrates and further deteriorating the strength and structure development of SSC. The addition of MSⅡ (with the higher proportion of γ-C₂S) has the hydration reaction, and maintains the relative content of hydrates after carbonation and compressive strength increase. This is due to the fact that γ-C₂S significantly enhances the carbonization resistance of SSC.

The binder consisted of blast furnace slag (BFS), desulfurization gypsum (DGP), red mud (RM), magnesium slag (MSⅠ (with the higher proportion of β-C₂S) and MSⅡ (with the higher proportion of γ-C₂S), and calcium hydroxide. The BFS substitution levels (i.e., 10% and 20%) by MSⅠ and MSⅡ magnesium slag were investigated. The mineral compositions of used magnesium slags were analyzed by X-ray diffraction (XRD). The prepared pastes were cast in the cubic molds with dimensions of 40 mm × 40 mm × 40 mm. After de-molding, the hardened samples were sealed and cured at 25 ℃. After being cured for 28 d, the carbonation test was conducted at different CO₂ concentrations (i.e., 3% and 20%) and a relative humidity of 70%. At the carbonation age of 7, 14 d, and 28 d, the compressive strength, phase composition, and carbonation depth of SCC with and without carbonation were determined by strength test, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and phenolphthalein color test. The microscopic morphologies of SSC before and after carbonation were also analyzed by scanning electron microscopy (SEM). Besides, the early-hydration performance of fresh SSC pastes with MSⅠ and MSⅡ was evaluated via setting time and isothermal calorimetry tests.

In the hydration stage, the MSⅠ significantly inhibits the hydration rate of SSC. The MSⅠadversely affects the setting time and delays the reaction of SSC. This is because β-C₂S can inhibit the hydration of BFS and reduce the hydration degree of SSC, leading to reduced compressive strength, amounts of hydrates (i.e., ettringite and Calcium aluminum silicate hydrates), and increased carbonation depth after carbonation. The porous and loose microstructures via the SEM images also validate an adverse effect due to the MSⅠ (with the higher proportion of β-C₂S). Also, the addition of MSⅡ does not disrupt the hydration process of SSC and ensure the integrity of hydration phase matrix structure. Meanwhile, a high carbonization activity allows it to react with CO₂ to generate more CaCO₃ and a dense matrix structure, which enhances the carbonation resistance and compressive strength of SSC.

Different types of magnesium slag had different effects on the setting time, reaction rate, and amounts of SSC hydrates. Specifically, the MSⅠ with a higher proportion of β-C₂S and a small amount of Ca(OH)₂ could extend the setting time of SSC, decelerate the hydration rate of the matrix, and markedly reduce the quantity of hydrates. In contrast, the MSⅡ with a high γ-C₂S proportion had a negligible impact on the hydration process of SSC. Furthermore, the XRD patterns and TG results indicated that compared with MSⅡ, the incorporation of MSⅠ hindered the dissolution of gypsum and reduced the generation amount of hydration products, thus decreasing the compressive strength.

Under carbonation environments of different concentrations, the carbonation of calcium silicate in both types of magnesium slags enhanced the compressive strength of magnesium-doped slag-based SSC after carbonation to different extents. Compared with the control group, after 28-d carbonation, SSC doped with MSⅠ exhibited a carbonation depth, which was nearly twice greater than that of the control group (16.3 mm), while the content of hydration products post-carbonation was lower than that of the control group. Conversely, MSⅡ, which was abundant in γ-C₂S, demonstrated a superior protective effect on SSC during the carbonation process. After 28-d carbonation, the carbonation depth was only 6 mm, approximately 20% less than that of the control group. In addition, the content of hydration products post-carbonation remained consistent with the control group, and the strength after carbonation increased significantly.

For the compressive strength of carbonated SSC, the incorporation of slag containing various types of calcium and magnesium silicates could enhance the anti-carbonation performance of magnesium-doped slag SSC to different extents. However, compared to the MSⅡ containing γ-C₂S with a lower hydration activity and the MSⅠ with β-C₂S with a higher hydration activity, the reaction rate of SSC could be reduced. Before the carbonation, only a loose structure with a limited amount of C-A-S-H gel appeared. Conversely, the MSⅡ exhibited a higher proportion of γ-C₂S, which could have a low hydration activity and a high carbonation reactivity. This characteristic minimally affected the reaction rate of SSC, thereby ensuring that SSC doped with the MSⅡ demonstrated an excellent anti-carbonation performance in a carbonation environment. After the carbonation, there was a significant increase in matrix strength, and the microstructure became notably denser.

The predicted models consisting of empirical models, classical models, code-oriented models, theoretical aging models and machine learning algorithms prediction are summarized. The conventional prediction models, such as ACI 209 and CEB-FIP MC90, rely on regression-based equations, but struggle to account for the complexity of recycled aggregate concrete (RAC). The theoretical models like B3/B4 incorporate aging theory, but still require a recalibration for RAC, such as introducing residual mortar coefficients. These models have limitations, including narrow parameter coverage (3-5 factors), reliance on linear assumptions, and poor long-term prediction accuracy (R²~0.7). In contrast, machine learning (ML) models (e.g., XGBoost, CNN, LGBM) achieve significantly a higher performance, with R² > 0.95, compared to 0.6-0.8 for the conventional models. The XGBoost demonstrates the optimum accuracy (i.e., R²=0.989, RMSE=0.117). The ML key advantages include handling nonlinear interactions among 10+ parameters (e.g., the SHAP analysis) and improving stability through CNN's residual encoder. However, some challenges remain, such as high data dependency (requiring 23 300+ samples), overfitting risks, and limited interpretability, due to their "black-box" nature.

This review highlights the complexities of creep in RAC and proposes key strategies for optimization and innovation. Material optimization can be achieved via controlling residual mortar (<20%), incorporating supplementary cementitious materials (SCMs) like 30% GGBS, and adopting CO₂ curing to mitigate creep. Multiscale modeling, combining molecular dynamics with FEM, can simulate interfacial transition zone (ITZ) effects. Machine learning (ML) advancements should focus on expanding databases to include load history, environmental cycles, and admixtures, while hybrid models (e.g., physics-informed neural networks) can enhance both accuracy and interpretability. Sustainable solutions like bio-chemical ITZ self-healing and digital twins for lifecycle prediction offer promising future directions. Overall, integrating ML-enhanced, data-driven approaches enable safer, large-scale RAC applications, supporting greener construction practices.

As the second largest global carbon dioxide emission source, the cement industry contributes approximately 8% of total anthropogenic carbon emissions. Under the "dual-carbon" strategic framework, developing novel low-carbon cementitious materials emerges as a research priority in civil engineering. Alkali-activated cementitious materials (AACM) are regarded as a promising alternative to conventional Portland cement due to their advantages of eliminating high-temperature calcination and utilizing industrial solid wastes. However, the existing research predominantly focuses on material performance optimization, while the definition of their "low-carbon" attributes remains limited to raw material substitution, lacking a systematic life cycle carbon emission accounting framework. No scientific evaluation methods or quantitative models are established to assess carbon footprint disparities among different activator systems (i.e., carbonate, hydroxide, and silicate). Furthermore, red mud-a massive solid waste generated by the alumina industry with global annual emissions exceeding 150 million tons exhibits natural compatibility with alkali-activated systems due to its high alkali metal content. Nevertheless, the existing studies predominantly emphasize its reactivity activation, while neglecting the development of integrated low-carbon processing technologies. Establishing systematic carbon accounting methodologies and elucidating the coupling mechanisms among activators, carbon emissions, and mechanical properties become critical scientific challenges for advancing the engineering applications of alkali-activated materials.

In the AACM production framework, the study defined a "cradle-to-gate" system boundary spanning from raw material acquisition to final product formation. This boundary was divided into three distinct phases, i.e., raw material acquisition stage (Am), encompasses processes such as raw material production, mining, and extraction, and raw material transportation stage (At). Accounts for carbon emissions generate during the transportation of all required raw materials. Production stage (Ap) includes operational steps such as drying, homogenization, grinding, storage, and packaging. The investigation specifically employed red mud as an intrinsic alkali source, focusing on elucidating the influence patterns of both red mud and external alkalis (i.e., Na₂CO₃, NaOH, and Na₂O·2SiO₂) on the carbon emissions of AACM. Response surface methodology (RSM) with the Box-Behnken design was employed to optimize mix parameters (i.e., Na₂CO₃ dosage, red mud content, and cement content), conducting multi-factor interaction analysis with dual objectives, i.e., 28-d compressive strength and carbon emissions.

To compare the life cycle carbon emissions of AACM production in the same production line with industrial solid waste (i.e., red mud), granulated blast furnace slag, and ordinary Portland cement clinker as precursors, as well as Na₂CO₃, NaOH, and Na₂O·2SiO₂ as activators and to design low-carbon AACM, the following parameters were established. For the raw material transportation phase, heavy-duty diesel trucks (46-ton payload) with a carbon emission factor of 0.057 kg CO₂/(t·km) were selected, assuming a default transportation distance of 1000 km. For the production phase, the carbon emissions from drying red mud and granulated blast furnace slag were estimated based on electricity consumption of drying equipment and exhaust fans. The field data indicated that drying granulated blast furnace slag with 10%-13% moisture content required approximately 11.5 kW·h per ton of wet material. For high-moisture red mud drying (using a Φ3 m×28 m rotary dryer with 2.45-4.20 r/min rotation speed and 3.5% slope), the energy consumption reached 35.0 kW·h per ton of wet material (data from Shanghai Bai Ao Heng New Materials Co., Ltd., China). Carbon emissions from material batching, grinding, and homogenization processes were estimated using reference power consumption data (i.e., ≈33 kW·h per ton of cement) from a plant of Southwest Cement Co., Ltd., China. The average carbon emission factor of China's regional power grids was adopted as 0.5366 kg CO₂/(kW·h) (2022 national average electricity CO₂ emission factor).

This study proposes a life cycle carbon footprint accounting model for AACM production, reveals the synergistic regulation mechanism of activator types and mix proportions on the material low-carbon characteristics and mechanical performance through response surface methodology-based optimization design and establishes a cradle-to-gate carbon footprint accounting system covering raw material acquisition, transportation, and production stages. The contribution weights of red mud-based AACM precursors and activator types to carbon emissions are quantified, providing a quantitative basis for evaluating low-carbon cementitious materials. As an endogenous alkali source, red mud can effectively reduce the dosage of external activators. Coupled with the low-carbon characteristics of Na₂CO₃ (carbon emission factor: 0.79 t CO₂/t), this significantly reduces the system's carbon emissions. At a red mud content of ≤50% and a cement clinker dosage of ≤10%, the material's carbon emissions can reduce to below 280 kg CO₂ per ton of AACM, validating a feasibility of the synergistic pathway of solid waste recycling-low-carbon process. The low-carbon design based on the RSM demonstrates that in the optimal mix proportion of the red mud-slag system (with 5.54% Na₂CO₃ dosage, 35.56% red mud, 57.22% slag, and 7.22% cement), the cementitious material achieves a 28-d compressive strength of 58.5 MPa and a carbon emission of 228 kg CO₂ per ton of AACM. This system exhibits both high strength and low-carbon characteristics, with performance comparable to Portland cement P·O 42.5R. In this mix proportion, red mud with a high alkali content provides abundant endogenous alkali to the system, reducing reliance on exogenous alkali. The amorphous phase structure of blast furnace slag endows it with a high alkali reactivity, enabling a rapid release of Ca²⁺ and SiO₄^4- under Na₂CO₃ activation to promote gel formation and enhance strength. The hydration of minerals such as C₃S and C₂S in cement generates additional Ca(OH)₂, further elevating the pH value of the system. This accelerates the depolymerization of slag vitreous phases and enhances the compactness of the matrix interfacial transition zone, thereby ensuring the mechanical performance of the AACM.

This study could pioneer the integration of red mud's intrinsic alkali properties with low-carbon activators, proposing a holistic "low-carbon design-carbon accounting-performance optimization" methodology. The framework provided a theoretical support for industrial applications of alkali-activated materials, offering dual benefits, i.e., large-scale red mud consumption in the alumina industry and a technical pathway for achieving the "dual carbon" goals in construction materials.

It is critical for large-scale energy storage to develop sodium-ion batteries (SIBs) due to their cost-effectiveness and abundant sodium resources. However, some challenges like sluggish kinetics from large Na⁺ radii and poor structural stability of electrode materials hinder their practical application. Transition metal sulfides (TMS) like SnS, NiS, and FeS exhibit high theoretical capacities, but suffer from some intrinsic drawbacks (i.e., low conductivity and severe volume expansion during cycling). To address these limitations, this study was to propose a novel strategy, i.e., designing a mixed-metal sulfide composite of (NiS/Cu₂(Fe,Co,Ni)SnS₄/CNT) with heterointerfaces and multi-metal synergy. The integration of Fe, Co, Ni, Cu, and Sn could enhance electronic/ionic transport, mitigate volume changes, and leverage catalytic effects of transition metals. Carbon nanotube (CNT) were introduced to further improve conductivity and structural integrity. This mixed-metal sulfide composite exhibited the excellent performance at a ultra-high current density.

The composite was synthesized via a co-precipitation method and a subsequent high-temperature sulfidation. For NiS/Cu₂(Fe,Co,Ni)SnS₄/CNT, stoichiometric amounts of FeSO₄, CoSO₄, NiSO₄, CuSO₄, and SnSO₄ were dissolved and co-precipitated with NaOH. The CNT slurry was ultrasonically dispersed and incorporated into the precursor. After sulfidation with thioacetamide in N₂ at 500 ℃, the final product was obtained. NiS/CNT (control sample) followed the similar process using only NiSO₄. The crystallinity, morphology, and elemental states of the samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). To evaluate their kinetics, rate capability and cycling stability, CR2032 half-cells assembled with Na metal counter electrodes were tested by cyclic voltammetry (CV), constant-current charge/discharge test, galvanostatic intermittent titration (GITT) and electrochemical impedance spectroscopy (EIS), respectively.

The results show that the complex consists of Cu₂(Fe,Co,Ni)SnS₄ and NiS biphasic phases, and the heterogeneous interfaces exist, which are confirmed by high-resolution transmission electron microscopy (HRTEM). The built-in electric field at the heterogeneous interface accelerates the charge transfer, and the multimetal synergy (Fe/Co/Ni/Cu/Sn) provides abundant catalytic sites and reduces the Na⁺ diffusion barrier (i.e., 32% reduction in the diffusion barrier according to density-functional theory calculations). The three-dimensional conductive network constructed by the CNTs inhibits the volume expansion efficiently (i.e., the thickness of the electrodes increases by only 37.9% after cycling, which is significantly lower than that of the NiS/CNT). For the electrochemical performance, NiS/Cu₂(Fe, Co, Ni)SnS₄/CNT exhibits an excellent high rate charge/discharge performance and a long cycle stability, and still maintains a discharge specific capacity of 626 mA·h·g^-1 after 1000 cycles at a current density of 5 A·g^-1, and 399 mA·h·g^-1 after 8000 cycles at an ultra-high current density of 20 A·g^-1. Capacitive-dominated storage and enhanced Na⁺ diffusivity outperform monometallic NiS/CNT. The TEM images and CV indicate a reversible phase transition between sulfide and Na₂S, thus validating the reaction mechanism.

The built-in electric field formed by the heterogeneous interface and the synergistic effect of polymetallic cations could enhance the ion and charge transfer rate, and the reduction of polymetallic ions to metal monomers facilitated the ion and electron transport during the charging and discharging process, effectively suppressing the polysulfide shuttling phenomenon, thus decreasing the polarization of the battery. The introduction of carbon nanotubes provided electron transport paths, which further enhanced the structural stability of the material. This study could have a great potential of mixed metal sulfides for application in anode materials for sodium-ion batteries.

Energy, environment and industrial production are interconnected with the rapid development of the industrialization process, conventional fossil fuels are close to exhaustion, and the environment on which mankind depends for survival is seriously damaged. The development of efficient, clean and sustainable energy conversion and storage technology is thus an important research direction in scientific community. In this paper, in-situ Ni-doped CoMoO₄ electrode materials were synthesized on acidified pretreated nickel foam with nickel chloride formed on hydrochloric acid pretreated nickel foam as a reactive nickel source. The capacitive properties of in-situ Ni-doped CoMoO₄ electrode materials synthesized at different hydrothermal reaction temperatures were investigated.

In this work, 1 mmol Co(NO₃)₂·6H₂O and 1 mmol Na₂MoO₄·2H₂O were dissolved in 60 mL of deionized water (DI) and stirred for 30 min, and then the conventionally cleaned nickel foams and four pieces of acidified pretreated nickel foams were immersed into five beakers of the solutions above, respectively. The solutions were then transferred into a hydrothermal high-pressure reactor lined with polytetrafluoroethylene. The reactor was kept in an oven at different temperatures (i.e., 180, 120, 150, 180 ℃, and 200 ℃) for 12 h, respectively. The nickel foam was removed from the cooled reactor, washed and dried in a vacuum oven at 60 ℃ for 12 h. The synthesized materials were labeled as CoMoO₄ (3.6 mg), Ni-CoMoO₄-120 (3.93 mg), Ni-CoMoO₄-150 (3.46 mg), Ni-CoMoO₄-180 (4.88 mg), and Ni-CoMoO₄-200 (7.54 mg), respectively.

The XRD pattern of CoMoO₄ shows that the diffraction peaks at 13.1°, 23.3°, 26.4°, 27.3°, 33.7°, 36.6°, 38.9°, 41.7°, 47.4°, and 54.5° correspond to the crystal planes (001), (021), (002), (112) , (222) , (400), (040), (422), (222), (421), and (440), respectively, of CoMoO₄ (JCPDS 21-0868), indicating the effective synthesis of CoMoO₄. However, CoMoO₄ electrode material synthesized by in-situ Ni doping shows an overall shift of the XRD diffraction peak to the left. The SEM images show that compared to the undoped CoMoO₄, Ni-doped CoMoO₄ nanosheets at different reaction temperatures are uniformly nucleated and grown on the surface of Ni foam due to Ni ions provided by the nickel foam as a crystallization core, and there is almost no pore space between the nanosheets. The nanosheets are stacked together with mutual reliance and supported. The results of specific surface area measurements indicate that in-situ Ni-doped CoMoO₄ has the maximum specific surface area at a hydrothermal temperature of 180 ℃. The results of CV and GCD tests show that the optimum specific capacitance of Ni-doped CoMoO₄ electrode material can be obtained at 180 ℃.

In-situ Ni-doped CoMoO₄ electrode materials were synthesized on acidified pretreated nickel foam by a hydrothermal method. The morphology of Ni-doped CoMoO₄ electrode materials was controlled via modulating the hydrothermal temperatures (i.e., 120, 150, 180 ℃, and 200 ℃), in turn modulating the capacitive properties of CoMoO₄ electrode materials. Compared to undoped CoMoO₄, Ni-doped CoMoO₄ nanosheets with different reaction temperatures uniformly nucleated and grew on the surface of nickel foam due to Ni ions provided by nickel foam as a crystallization core, and the pores between nanosheets became smaller. The nanosheets rely on each other to stack together and support. Ni-CoMoO₄ was less prone to some problems like structural collapse and volume deformation when subjected to long-cycle charging and discharging, showing a better cycling performance. The optimum capacitance performance of Ni-doped CoMoO₄ could be obtained at 180 ℃, with a high specific capacitance of 4680 mF·cm^-2 at 5 mA·cm^-2. The capacitance retention of the ASC device after 10 000 cycles was 96%.

Cadmium magnesium telluride (CdMgTe), as a group II-VI CdTe-based compound semiconductor, can be used in room-temperature radiation detection. However, CdMgTe crystals grown by melt methods often exhibit major defects like vacancies, dislocations, twins, and inclusions, severely impacting the crystal quality and detector performance. Some studies show that selenium (Se) can significantly reduce harmful defects like sub-boundary networks and Te inclusions in CdTe-based crystals, enhancing the crystal quality through its favorable segregation coefficient and intense solid-solution hardening effect. Therefore, in this paper, Se was introduced into CdMgTe crystals via vapor phase diffusion as an advanced annealing strategy to enhance the both crystal quality and detector performance. In addition, the effect of annealing time on the crystal defects, microhardness, optical and electrical properties, and detector performance was also investigated.

The annealing source was a high-purity Se (7N), and the slices with the dimensions of 5 mm×5 mm×2 mm were selected from an In-doped CdMgTe ingot grown by a modified vertical Bridgman method under Cd excess condition. Prior to annealing, the slices were mechanically polished with an MgO suspension and then treated with a 2% Br₂-MeOH solution to eliminate scratches and any damaged layers. The slices and the source were positioned at opposite ends of a quartz annealing device, with quartz crucibles evacuated to a pressure of 10^-5 Pa. The annealing temperature of both slice and source was selected at 773 K. Effect of annealing time on CdMgTe crystal properties was investigated at different holding time (i.e., 30, 60, 120 h, and 240 h). CdMgTe planar room-temperature radiation detectors were fabricated via evaporating Au electrodes onto the both sides of the annealed crystals.

CdMgTe crystals before and after annealing in Se atmosphere were characterized by near-infrared spectrometry (NIR), X-ray photoelectron spectroscopy (XPS), infrared transmission microscopy (IRTM), field emission scanning electron microscopy (FESEM), infrared (IR) spectrometry, Raman spectrometry, and current-voltage (I-V) measurement. Room-temperature radiation detectors were prepared by evaporation of Au electrodes on both sides of CdMgTe crystals. The carrier mobility was determined by a time-of-flight (TOF) technology. The energy spectrum of the detectors was acquired by an ORTEC measurement system with uncollimated ²⁴¹Am α particles with an energy of 5.48 MeV as an irradiation source.

The band gap of the as-grown crystal is 1.505 eV, and annealing in Se atmosphere does not prevent the volatilization of Cd in CdMgTe crystals or reduce Te inclusions. After annealing, the maximum increase of the band gap is 0.042 eV. Se interacts with CdMgTe matrix via diffusion and chemisorption, forming chemical bonds that effectively result in the partial substitution of Se for Te., The solution strengthening effect of Se is more pronounced than that of Mg as the annealing time increases, causing that the microhardness initially decreases and then increases, which is lower than that of the as-grown crystal. The IR transmittance of the crystal after 120 h annealing is 63.6%, which approaches the theoretical value of 65%, thus satisfying a criterion for high-quality crystals. The peak intensity of A₁(Te) is basically unchanged based on the Raman spectra. However, an increase in the peak intensity of TO(CdTe) and a decrease in that of LO(CdTe) indicate that the lattice integrity in the annealed crystal is compromised.

CdMgTe crystal obtained under optimal annealing conditions is fabricated into an Au/CdMgTe/Au planar structure for the room-temperature radiation detector. TOF measurements show a remarkable increase in electron mobility (μ_e), up to 344.47 cm²/(V·s). ²⁴¹Am α particle source with an energy of 5.48 MeV is used for detector energy spectrum testing. The optimal CdMgTe detector exhibits the performance with an energy resolution of 17.2% and a carrier mobility lifetime product (μτ)_e of 1.32×10^-4 cm²/V. Annealing in a Se atmosphere can thus offer an effective approach to enhance the quality of CdTe-based crystals.

An advanced annealing strategy was adopted for enhancing the quality of CdMgTe single crystals for room-temperature radiation detectors. After annealing, a decrease in Cd content along with an increase in Mg content resulted in an expanded band gap. The microhardness and the IR transmittance of the crystals firstly decreased and then increased, and the resistivity gradually decreased as the annealing time increased, thus improving the crystal quality. The optimum condition of Se atmosphere annealing was at 773 K for 120 h. The optimal performance of the detector was an electron mobility (μ_e) of 344.47 cm²/(V·s), an energy resolution of 17.2%, and a (μτ)_e product of 1.32×10^-4 cm²/V for ²⁴¹Am α particles with an energy of 5.48 MeV.

Lithium-ion batteries are widely used in electric vehicles due to their high energy density and environmental compatibility, but their safety and endurance are limited by liquid-state electrolytes. Solid-state electrolytes have attracted recent attention for their high safety and energy density, but their research faces some challenges. Artificial intelligence technologies, such as machine learning, can accelerate the discovery and optimization of solid-state electrolyte materials. However, extracting synthesis information from literature is time-consuming and prone to errors. Large language models (LLMs) become popular in the field of natural language processing. This paper was to propose the use of LLMs to automatically extract solid-state electrolyte synthesis information from literature via building datasets to train and fine-tune models.

The process of extracting synthesis information for solid-state electrolytes included five parts, i.e., literature downloading, parsing and processing, paragraph classification, information extraction, and synthesis process visualization. Initially, the downloaded XML documents were parsed to extract all paragraphs under the headings of "Experimental" or "Method". A classification dataset was constructed using these paragraphs, with the training set used to train and fine-tune a Bayesian model, a BERT model, and three different LLMs. The test set was used to evaluate the classification performance of different models. Three LLMs are fine-tuned using a dataset previously built for the extraction of synthesis information in inorganic catalysts, enabling them to complete the task of extracting synthesis information for solid-state electrolytes, outputting four parts of contents, i.e., product, raw materials, methods, and steps, and testing and evaluating with the synthesis paragraphs filtered by the classification models.

The NB model slightly underperforms the other models in terms of precision, recall, and F1 score. This may be attributed to the pre-training of LLMs and BERT on extensive text data and their fine-tuning on paragraph classification data, endowing them with strong language comprehension abilities. The comparable overall performance of the 3B and 8B models may be attributed to the 3B model being derived from the 8B model through pruning and knowledge distillation, resulting in similar performance characteristics. The classification task in this paper is limited to the classification of solid-state electrolyte synthesis paragraphs and the training and testing data are relatively scarce, the superior performance of the 7B model does not imply that it is always superior to other models. The comparison between the 3B and 8B models demonstrates that in certain scenarios, smaller-parameter models can outperform their larger-parameter counterparts. Therefore, it is not always necessary to pursue models with more parameters. Instead, reasonable choices should be made based on the specific requirements of the task. In misclassifications, there is a higher incidence of predicting label 0 as 1, which may be due to the inclusion of descriptions of electrode preparation and battery assembly in paragraphs about non-solid electrolytes, involving the use of electrolytes, leading to the model to misjudge these paragraphs as solid-state electrolyte paragraphs. To further enhance the classification performance of LLMs, the way prompts the construction of the dataset that can be adjusted to allow LLMs to better understand the subtle differences between different paragraphs.

The three LLMs perform exceptionally well in the task of extracting synthesis information for solid-state electrolytes, demonstrating that the combination of pre-training and fine-tuning can fully leverage the text understanding and instruction following capabilities of large models, making them competent for the crucial task of extracting important information from the synthesis process of solid-state electrolytes. Moreover, the fine-tuning dataset used originates from the field of inorganic catalysts and shows excellent performance in the field of solid-state electrolytes, indicating a great generalization ability of large models. They learn the ability to extract structured information from unstructured text, rather than just extracting information about fixed materials and synthesis processes. The extraction effects of the 3B, 7B, and 8B models are comparable, indicating that the size of the model is not a sole factor determining performance. The design and training strategies of the models are equally important.

In the paragraph classification task, LLMs and BERT, benefiting from their pre-training on large-scale text data and fine-tuning for specific classification tasks, demonstrated classification performance that surpassed that of Bayesian models. Among the LLMs of different sizes, the 3B model, derived from the 8B model through pruning and knowledge distillation, showed similar classification effectiveness to the 8B model. The 7B model achieved an F1 score exceeding 0.9, thus highlighting its superior performance in handling such tasks.

In the synthesis information extraction task, LLMs were fine-tuned using a dataset of inorganic catalyst synthesis information. The results showed that the F1 scores of all three models exceeded 0.9, demonstrating great generalization capabilities of LLMs. This indicated that LLMs could learn the ability to extract structured information from unstructured text, rather than just extracting information about fixed materials and synthesis processes. The extraction performance of the 3B model was slightly better than that of the 7B and 8B models, thus indicating that the number of parameters could not be a sole factor determining performance. The design and training strategies of the models could be equally important.