Huaqing Xie

Perovskite oxides show excellent catalytic performance for thermochemical CO₂ splitting, with A/B-site cation substitution further enhancing redox activity. While traditional first-principles methods are computationally expensive, machine learning (ML) provides an efficient approach to perovskite optimization. In this paper, machine learning is employed to investigate and predict the performance of perovskite catalysts in CO₂ decomposition reactions. Based on 227 perovskite compositions (A₁A₂)(B₁B₂)O₃ curated from experimental literature, a total of five ML models are used, including Decision Tree, Bagging, Random Forest, Extra Trees, and Gradient Boosting Regression (GBR). The Random Forest model performed best. After hyperparameter optimization, the Random Forest model achieved an R² of 0.910 and an MAE of 41.528 on an independent test set. SHAP analysis indicated that the thermal reduction temperature (T₁) and the B1-site stoichiometric fraction (C_b₁) are the most influential features governing the predicted CO yield. A higher CO yield is predicted when C_b₁ ranges from 0.6 to 0.8, and T₁ exceeds 1300 °C. This behavior can be attributed to the enhanced formation of oxygen vacancies at elevated temperatures and the optimized electronic structure induced by appropriate B-site stoichiometry.

Conventional ammonia production via the Haber–Bosch process is energy-intensive and carbon-heavy. Emerging biomass-based approaches offer a sustainable alternative but often lack rigorous system-level analysis based on actual reaction kinetics. This study presents a novel integrated process coupling biomass pyrolysis/gasification with Chemical Looping Ammonia Generation (CLAG) and waste heat recovery. Unlike previous models relying on simplified assumptions, this simulation incorporates experimental kinetic data for both N-absorption and N-desorption stages to ensure high fidelity. The system’s energy and mass flows were rigorously evaluated using Aspen Plus. Results indicate that the gasification stage is optimal at an O₂/biomass molar ratio of 0.2 and 750 °C. In the CLAG unit, a higher N-absorption temperature (1600 °C) and α-Al₂O₃/C ratio (3:3) significantly enhance ammonia yield. Under these optimal conditions, the system achieves a remarkably low energy consumption of 10.12 GJ/t-NH₃ and specific CO₂ emissions of 3.2 t/t-NH₃—a reduction of over 60% compared to traditional coal-based routes. The integration of waste heat recovery is identified as a critical factor in minimizing net energy input. This work validates the feasibility of the biomass-based CLAG process as a low-carbon, energy-efficient pathway for sustainable ammonia synthesis.

The study conducted isothermal tests for biochar-based N-absorption reaction in Chemical Looping Ammonia Generation to investigate the factors affecting biochar conversion, the kinetic model, and the reaction mechanism. The results show that the N₂ gas flows had little effect on biochar conversion. Raising the reaction temperature and the molar ratio of α-Al₂O₃ to C enhanced the conversion of biochar. When the N₂ flow rate was set to 200 mL/min, the reaction temperature to 1600 °C, and the α-Al₂O₃/C molar ratio to 3:3, the biochar conversion reached its peak at 95.45%. After evaluating several kinetic models, the D₁ diffusion model was found to provide the closest match to the biochar conversion. The activation energy decreased from 241.91 kJ/mol at a 1:3 α-Al₂O₃/C molar ratio to 146.77 kJ/mol at a 3:3 ratio with an increasing α-Al₂O₃/C molar ratio. The biochar’s high specific surface area and abundant pore structure facilitated a rapid reaction between carbon and oxygen on the carbon surface. Additionally, the diffusion of oxygen produced during the decomposition of α-Al₂O₃ became the limiting factor in the N-absorption reaction.

In this paper, a novel process for synergistic carbon in situ capture and the utilization of blast furnace gas is proposed to produce CO via chemical looping. Through thermodynamic analysis, this process was studied in terms of the carbon fixation rate, CO yield, in situ CO₂ utilization rate, CH₄ conversion rate and energy consumption. It provides valuable insights for achieving efficient CO₂ capture and in situ conversion. FeO and CaO are used as the oxygen carrier and the carbon carrier, respectively. Under the conditions of reaction temperature of 400 °C, pressure of 1 bar and FeO/CO ratio of 1, the carbon capture rate of blast furnace gas can reach more than 99%. In the carbon release reactor, the CO yield is lower than that in the original blast furnace gas (BFG) if no reduction gas is involved. Therefore, methane is introduced as a reducing gas to increase CO yield. When the reaction temperature is increased to 1000 °C, the pressure level is reduced to 0.01 bar and the CH₄/C ratio is 1:1 (methane to carbon), the CO yield is four times that of the initial blast furnace gas. Under the optimal conditions, the energy consumption of the system is 0.2 MJ/kg, which is much lower than that of the traditional process. This paper verifies the feasibility of the new process from the perspective of thermodynamics.

Iron and steel are regarded as the foundation for national development, but their processing consumes huge amounts of fossil fuel and produces large amounts of carbon dioxide gas, which is not conducive to the sustainable development of society

Converter blowing limestone powder making slag steelmaking process has the advantages of low carbon and high efficiency, and can realize the resource utilization of CO₂ in the metallurgical process, which is in line with the development direction of green metallurgy. Based on a thermogravimetric-differential thermal analyzer, the kinetic mechanism of decomposition of small limestone at steelmaking temperatures was investigated by a modified double extrapolation method. The results showed that with a higher rate of heating, limestone decomposition lagged, and decomposition temperature increased. Furthermore, the smaller the limestone particle size, the lower the activation energy of decomposition. Compared with N₂, air, and O₂, small limestone powder used for converter blowing could complete more rapid decomposition, and the time required for decomposition shortened by about 1/3, although the decomposition temperature increased in the CO₂. The limestone decomposition rate increased and then decreased at low to high CO₂ partial pressures. With a limiting link, the inhibition was more significant under high CO₂ partial pressure, but the reaction can be fully completed by 1000 °C. The decomposition type modeled was stochastic nucleation and subsequent growth. As the partial pressure of CO₂ increased from 25% to 100%, the number of reaction stages, n, increased.