The challenge of tackling atmospheric pollutants and the demand for low-carbon environmental technologies have imposed urgent requirements on the control of CO and NOx pollutants. Synergistic catalytic treatment is regarded as the most ideal emission reduction technique, with the difficulty lying in simultaneously enhancing catalytic activity and resolving competitive adsorption. In this work, the Cu component was incorporated into the CeTiO2 catalyst. The optimized Cu-2/CeTiO2 catalyst achieved over 90% conversion for both CO and NOx across a broad temperature range of 225-325 degrees C. Characterization and theoretical calculations demonstrated that Cu doping decreased the valence state of Ce and Ti sites, thereby enhancing lattice oxygen activation and migration ability. The increased CO adsorption also contributed to the elevated CO oxidation activity. The broadening of the simultaneous removal temperature range was achieved by eliminating competitive adsorption of reactants. Specifically, the competitive adsorption between NH3 and CO was mitigated after Cu doping. NO was primarily adsorbed at the Ce and Ti sites, while Cu was engineered as the CO capture site. This substantially reduced the competitive adsorption between the two reaction atmospheres, enabling simultaneous removal of both pollutants. This research offers a reliable approach and catalyst construction strategy for the simultaneous removal of CO and NOx, thereby advancing the development of pollution reduction and carbon mitigation technologies.

Granular shear flow refers to a granular flow characterized by a velocity gradient. In this flow, particles move in a simple shear pattern. However, the fundamental mechanisms responsible for the fragmentation of wet agglomerates within granular shear flow are not yet fully understood. This study uses the discrete element method (DEM) combined with liquid bridge and drag force models to analyze the fragmentation behavior of wet agglomerates in granular shear flows. The drag force model is first validated against experimental terminal velocity data. The research then explores how shear rate, liquid content, and solid volume fraction in granular shear flows affect agglomerate fragmentation. Using fractal theory, the study examines changes in the gyration radius and fractal dimension of the largest fragments. A regime map is developed by integrating the dimensionless number (17s) with liquid content to predict fragmentation behavior. The key results include the identification of three fragmentation stages-erosion, deformation, and fragmentation-with deformation marked by an increase in gyration radius ratio and a decrease in fractal dimension, indicating structural breakdown. Higher shear rates and increased solid volume fractions promote fragmentation, which reduces the average liquid bridge force and the coordination number of agglomerates. Conversely, higher liquid content enhances shear resistance, thereby suppressing breakage. Finally, fragmentation is categorized into deformation, mild fragmentation, and complete fragmentation regimes based on the total fragmentation index. The ratio of granular shear flow intensity to the cohesive force of agglomerates (17s), along with the liquid content, serves as a predictive parameter in the regime map.

Oxy-fuel circulating fluidized bed (CFB) technology demonstrates significant potential for efficient carbon capture; however, its pilot-scale investigations entail substantial costs. To reduce time and costs associated with pilot-scale testing, this study presents an efficient methodology that integrates numerical simulation with machine learning for fast prediction and parameter optimization. First, a computational fluid dynamics (CFD) model for a MWth-scale CFB oxy-fuel combustor was developed based on the multiphase particle-in-cell (MP-PIC) method. The model was validated using experimental data from the MWth-scale facility, and the simulation results elucidated the distribution and evolution of key parameters governing gas-solid flow, heat transfer, and reaction processes in the furnace. Then, by integrating numerical simulation and design of experiment, a database of 120 operating conditions of oxy-fuel CFB combustion characteristics was constructed for training and testing of a neural network model. The key parameters predicted by the neural network are in good agreement with those predicted by CFD model. Correlation analysis of variables indicates that the biomass blending ratio is negatively correlated with furnace temperature and CO2 concentration, while positively correlated with NO emissions. Finally, a genetic algorithm of multi-objective optimization was performed to maximize CO2 concentration and minimize pollutant emissions, resulting in a set of optimal solutions. The combined CFD simulation and machine learning method developed in this study aids engineers in fast assessment and optimization of oxy-fuel CFB combustion.

Interfacial oxygen migration from support to noble metal active sites, termed reverse oxygen spillover, represents a critical metal-support interaction influencing the performance of Pt/TiO2 catalysts. In this study, we uncover a size effect of Pt particles on reverse oxygen spillover in Pt/Sn0.2Ti0.8O2 catalysts via a combination of in situ characterizations with ab initio molecular dynamics simulations. Among single-atom Pt, nanocluster Pt, and nanocrystal Pt, nanocluster Pt exhibits the most pronounced reverse oxygen spillover and thus achieves the highest turnover frequency in CO oxidation. The most pronounced reverse oxygen spillover is mainly due to the strongest electron transfer to the interfacial lattice oxygen triggered by CO adsorption with moderate adsorption energy. In contrast, CO adsorption on single-atom Pt is too strong to initiate reverse oxygen spillover, while on nanocrystal Pt, it leads to a weakening of the interaction between Pt sites and the support, thus hinders the reverse oxygen spillover. This study clarifies the relationship between Pt particle size and reverse oxygen spillover effects, furnishing a theoretical basis for designing noble metal catalysts with excellent activity.

Electrocatalytic conversion of carbon dioxide (CO2) into high-value chemicals or fuels is a key approach to simultaneously optimize carbon cycling and energy conversion, providing significant environmental and energetic benefits. Copper-based catalysts, because of their unique selectivity toward multi‑carbon (C2+) products, have become preferred electrode materials for electrocatalytic CO2 reduction reactions (CO2RR). However, during electrochemical polarization, they tend to undergo valence state changes and structural rearrangements, resulting in a decline in catalytic activity and limited long-term stability, which greatly restricts their practical use. To overcome those drawbacks, this study promoted the formation of CuCr2O4/CuO heterojunction by Cr doping during the synthesis of CuO. The strong interactions at the heterojunction interface trapped oxygen atoms within the catalyst, preventing the loss of lattice oxygen as well as stabilizing copper valence states. The heterostructure altered the interface electronic configuration to lower charge transfer resistance and reduced CC coupling energy barriers. The results demonstrated that the as-prepared CuCr2O4/CuO catalyst exhibited excellent CO2RR performance, achieving a C2+ product selectivity of 50.1% at a potential of -0.95 V (vs. RHE), which significantly surpassed that of the undoped CuO catalyst. Additionally, detailed X-ray photoelectron spectroscopy (XPS) analysis before and after the reaction confirmed that the elemental composition and copper valence state of the catalyst remained relatively stable during electrochemical polarization, verifying the integrity of the heterojunction structure and the long-term stability of the catalyst. The 'oxygen-locking effect' proposed in this study offers a new approach for designing highly selective and stable copper-based CO2RR catalysts.

The relatively low surface area commonly observed in usual high-entropy oxides (HEOs) constitutes a primary limitation for their efficient deployment in heterogeneous catalysis, severely constraining active site accessibility and mass transport dynamics. Herein, a silica-templated self-supporting strategy coupled with alkaline etching is proposed to synthesize mesoporous single-phase CuCoNiZnAl HEOs. By nanocasting multicomponent (Cu, Co, Ni, Zn, Al) nitrates into a SiO2 matrix followed by hydrogen reduction and NaOH leaching, a series of HEOs with high surface areas (161-212 m2/g) were fabricated, thereby increasing the exposure of accessible active sites. Surprisingly, abundant dual cation-anion vacancies (i.e., mixed metal cation vacancies and oxygen vacancy) were simultaneously generated, which collectively activate exposed active sites through electronic charge redistribution. This restructuring is directly demonstrated by XPS/EXAFS analyses with a conclusion: Cu, Ni, and Co species shift from electron-rich states to electron-deficient states, while Zn and Al species conversely transform from high-valent to low-valent configurations. Consequently, the optimized CuCoNiZnAl HEOs demonstrate significantly enhanced catalytic efficiency in both CO2 hydrogenation and CO oxidation. This modular synthesis strategy-combining self-supporting architecture with controlled alkaline etching-enables the design of diverse mesoporous HEOs with abundant vacancies, offering a versatile platform tailored for multifunctional catalytic applications.

Ammonia has attracted growing attention as a carbon-free fuel and hydrogen carrier for low-emission combustion applications. In this study, a detailed kinetic mechanism for ammonia combustion is developed through the integration of density functional theory (DFT) calculations and kinetic modeling. Thermochemical data and transition state parameters for key elementary reactions are obtained using high-level quantum chemical calculations, and reaction rate constants are determined based on transition state theory and RRKM/master equation methods. These DFT-calculated kinetic parameters are incorporated into the base mechanism, resulting in an updated mechanism composing 33 species and 223 reactions. The refined mechanism is validated against experimental data of ignition delay times and laminar flame speeds across a broad range of pressures, equivalence ratios, and oxygen concentrations. The model accurately reproduces the mole fraction profiles of NO and NSO under jet-stirred reactor (JSR) oxidation conditions. Rate of production analysis indicates that the intermediates, especially HNO and NHS, dominate the NO generation pathway. The model reliably predicts the variation of the temperature dependence coefficient with equivalence ratio, exhibiting a distinct minimum near stoichiometric conditions and higher sensitivity for both lean and rich mixtures. This study establishes a highfidelity kinetic framework for simulating ammonia combustion and offers a theoretical basis for the development of efficient, low-emission ammonia fuel systems.

This research investigates the interaction between particle agglomeration, liquid evaporation, and fluidization dynamics within a top-spray fluidized bed. The study employs a coupled CFD-DEM approach that integrates a liquid bridge force model alongside a simplified model for the transition from liquid bridges to solid bridges during evaporation. The results reveal that the region of rapid moisture evaporation is predominantly situated near the bed wall. Initially, particles located in the upper-middle region of the bed are entrained into the spray zone due to bubble-induced elutriation. These particles subsequently descend into the near-wall region, characterized by elevated evaporation rates. The interaction of bridging forces among particles leads to region-specific fluidization behaviors: particles in the central region primarily experience fluidization and agglomerate disintegration, while those near the wall exhibit localized recirculation that facilitates agglomeration. The granulation process proceeds in a staged manner, with larger agglomerates gradually settling at the bottom of the bed, while individual particles and smaller agglomerates continue circulating until a more uniform agglomerate size distribution is achieved. Notably smaller agglomerates serve as nuclei for the formation of larger agglomerates. Furthermore, an increased spray rate extends the residence time of particles within the agglomeration region, thereby enhancing the liquid bridge forces and allowing sufficient time for the transition from liquid to solid bridges. This mechanism ultimately enhances the overall degree of agglomeration within the fluidized bed.

Ammonia is a chemical energy storage carrier with great potential, and its use as a fuel is expected to promote the large-scale application of renewable energy. Fluidized beds, characterized by their high specific heat capacity and potential use of catalyst particles, offer advantages that facilitate ammonia ignition and stable combustion. However, combustion characteristics of ammonia in fluidized beds and effects of operating parameters remain unclear. In this study, a high-temperature fluidized bed setup is constructed to investigate the combustion characteristics of ammonia. The effects of equivalence ratio, oxygen volume fraction, and initial bed temperature on temperature distribution, emissions of nitrogen monoxide (NO), ammonia conversion rate and ammonia slip concentration are examined. The differences between premixed and diffusion combustion are also compared. The results indicate that under fuel-lean combustion, NO emissions are relatively high, while under fuel-rich combustion, NO emissions decrease, bed temperature drops and ammonia conversion rate decrease, ammonia slip concentration increases accordingly. Both bed temperature and NO emissions rise with increasing oxygen volume fraction. As initial bed temperature decreases, the region with the highest bed temperature after stable combustion shifts closer to the freeboard. For diffusion combustion, at a constant total ammonia input, an increase in oxygen volume fraction leads to reduced unburned ammonia. Under identical gas input parameters, there are no significant differences in bed temperature, NO emissions and ammonia conversion rate between diffusion and premixed combustion. This suggests that combustion of ammonia in a fluidized bed is not significantly affected by whether combustion is premixed or diffusive for the current experimental setup and operating parameters.

Real-time monitoring of particle size distribution (PSD) in fluidized bed granulation remains a significant challenge due to the complex coupling between particle growth and multiphase flow dynamics, alongside a lack of robust non-invasive techniques. In this work, a physics-informed acoustic inversion framework is developed to enable real-time PSD characterization based on passive acoustic emission (AE) signals. Wavelet packet transform extracts frequency-domain energy features, which are linked to particle size through collision-induced acoustic responses. A constrained least-squares approach is then implemented to decouple multi-component contributions and reconstruct PSD evolution. To overcome signal instability caused by wall-sticking-a key limitation in practical systems-an intermittent spray strategy is introduced to stabilize acoustic signals and improve reproducibility. The proposed approach achieves reliable PSD prediction during the drying stage, with an average relative error of 22.13%. The remaining errors are mainly associated with trace component identification (mass fraction <5%) and severe deposition-induced signal distortion. Importantly, this method captures the attenuation of fluidization dynamics during particle growth, providing real-time quantitative feedback for process control. This work establishes a non-invasive and mechanism-informed monitoring strategy, offering a practical pathway toward intelligent control of fluidized bed granulation processes.

Improving the thermodynamic efficiency of liquefied natural gas (LNG) production remains a priority for reducing the carbon footprint of the energy transition. We establish an integrated data-driven framework synthesizing exact geometric topology with physics-informed thermo-hydraulic modeling to optimize the eco-design of spiral wound heat exchangers (SWHE). A unit-weighted numerical model resolves the radial heterogeneity of hydraulic impedance, while a hybrid computational fluid dynamics and artificial neural network (CFD-ANN) surrogate predicts shell-side heat transfer, capturing non-linear falling film behaviors driven by centrifugal forces. Systematic multi-objective optimization via the non-dominated sorting genetic algorithm II (NSGA-II) reveals that the global minimum curvature governs the conflict between resource efficiency (equipment compactness and material footprint) and energy dissipation (hydraulic pressure drop and pumping power). We demonstrate the curvature effect, showing that enhancing heat transfer through secondary flows incurs a severe hydraulic penalty. Traversing the Pareto frontier from the most energy-efficient to the most compact design results in a 50-fold increase in pressure drop, quantifying the energy-material nexus. This framework transforms SWHE development into a predictive design methodology, providing tailored solutions for the critical physical conditions of diverse facilities, from space-constrained offshore floating liquefied natural gas (FLNG) platforms to onshore baseload terminals.

Based on a novel carbonation-regeneration CO2 capture experiment, this study conducts the three-dimensional CFD simulation for CO2 capture by potassium-based solid sorbents. By the integration of gas-solid multiphase flow dynamics, thermal energy transfer mechanisms, and chemical reactions, a comprehensive CFD model of CO2 capture by potassium-based solid sorbents is established under the Eulerian-Eulerian framework. An in-depth analysis is conducted on the gas-solid flow configuration, temperature distribution pattern, and species concentration profile. Finally, the effects of operating parameters of the carbonator on aggregate variables (solid circulation rate and CO2 capture efficiency) are analyzed. Results indicate that the sorbent circulation rate and CO2 capture efficiency can be affected by adjusting the central gas velocity, flue gas velocity, and static bed height in the carbonator. These findings offer valuable insights for optimizing CO2 capture performance. Combined with the experimental study, the CFD simulation in this study enables a better understanding for CO2 capture by solid sorbent containing potassium.

Direct air capture (DAC) is an important route toward negative carbon emissions. Because atmospheric CO2 is present at an ultralow concentration and always coexists with water vapor, the interfacial interaction between CO2 and H2O plays a key role in capture performance. As a common support for alkali-metal-based composite adsorbents, ZrO2 has good thermal stability and abundant surface acid-base sites, yet its interfacial response to CO2 under humid conditions remains unclear. In this work, first-principles calculations were employed to systematically investigate the adsorption behavior and interfacial mechanisms of single CO2, single H2O, and CO2+nH2O (n = 1∼4) on the ZrO2(001) surface. The results show that isolated H2O preferentially adsorbs at the 5-coordinated Zr site through stable chemisorption, whereas isolated CO2 exhibits a weak adsorption energy of only 0.45 eV at its optimal site, indicating the limited intrinsic CO2 capture ability of pristine ZrO2(001). After introducing H2O, both the co-adsorption energy and interaction energy become negative, demonstrating a synergistic effect, which becomes much more pronounced when n > 2. Under low-water conditions, H2O mainly stabilizes CO2 indirectly through local electrostatic regulation, hydrogen bonding, and weak intermolecular interactions. When n > 2, the multi-water network further improves orbital matching between the O atoms of CO2 and surface Zr sites and strengthens direct bonding. Excited-state spectra and electron-hole analyses further show that multiple water molecules not only modify interfacial interactions but also alter the dominant electronic transition characteristics. This work reveals the intrinsic mechanism of cooperative CO2/H2O adsorption on ZrO2 at the atomic and electronic scales, providing a theoretical basis for understanding the adsorption behavior at interfaces of DAC-related oxides.

Particle size distribution (PSD) within fluidized beds significantly influences operating efficiency and product quality. However, the complex dynamics of particle movement-particularly the interactions among particles of varying sizes-pose significant challenges for PSD monitoring. Therefore, an accurate, real-time, and noninvasive measurement method is essential. This study proposes an innovative PSD measurement method that integrates an acoustic emission (AE) system with a wavelet packet transform (WPT) algorithm. Based on the principle of energy superposition, the energy distribution across various frequency bands, specific energy, and total energy of AE signals were used to establish a system of equations relating to the mass fractions of particles of different sizes. This system was subsequently solved using the least squares method (LSM) combined with physical constraints. Experimental results demonstrate that this new method performs well in estimating the mass fractions of multi-size particles with total masses ranging from 100 to 280 g and particle sizes between 100 and 800 & micro;m. The model achieved a mean absolute error of 1.97 % points, with the majority of relative errors falling below 15%. As a non-intrusive and real-time monitoring technique, this method holds significant potential for process optimization and quality control in industrial particulate processes, such as granulation and coating.

Owing to its low material cost and high energy density, the calcium looping (CaL) process, based on the reversible reaction between CaCO3 and CaO, has emerged as a promising solution to address the dispatchability challenges of concentrated solar power (CSP) systems. This study employs an exergy-economic analysis approach to evaluate the energy conversion efficiency and commercial feasibility of a novel CSP-CaL dual-cycle coupled system. A combined exergy-economic analysis was conducted to uncover the energy transfer mechanisms and assess the economic feasibility of the system. Exergy analysis shows that 58 % of the total input exergy is converted to effective work, with 42 % lost mainly due to irreversible losses in the reactor module (calciner/ carbonator), heat exchanger network (39 %), and process waste heat (3 %). Sensitivity analysis indicates that air flow rate, solid conversion rate, and carbonation conditions significantly influence system efficiency. Moderately increasing these parameters improves power generation and storage performance but decreases the system's economic performance. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) was used to perform multi-objective optimization of the highly sensitive parameters within the system. The results identified three main operation regions: the high-efficiency-prioritized region (global system efficiency of 42.26 %, power generation cost of $0.114/kWh, and discharge efficiency of 49.16 %), the cost-constrained region (system efficiency of 34.14 %, power generation cost of $0.095/kWh, and discharge efficiency of 35.08 %), and the balanced region (which aims to balance efficiency and cost to meet diverse operational needs). This study provides a theoretical framework and decision support for engineering applications of CaL-based energy storage systems.

In alkali metal carbonate-based direct air capture (DAC), water vapor is a key carbonation reactant but may simultaneously slow kinetics via competitive adsorption and interfacial mass transfer limitations. Leveraging the K2CO3/ZrO2-TiO2 composite DAC adsorbent system, this work probes the fundamental role of Ti-doped ZrO2 in interfacial H2O adsorption/activation to elucidate the microscopic origins of the doping-enhanced CO2 capture performance. Comprehensive characterization (BET, XRD, SEM, TEM-EDS, XPS, FTIR, EPR, DVS, and contact angle measurements) establishes a clear correlation between Ti-doping induced defect evolution and enhanced hydrophilicity. First-principles calculations on pristine and Ti-doped ZrO2 (001) slabs were conducted to identify the optimal H2O adsorption sites. The interfacial bonding mechanism is unraveled by combining weak interaction analysis, charge transfer, excited state transitions, PDOS/COHP and frontier-orbital reconstruction, along with quantified oxygen vacancy formation energies and transition state barriers for H2O dissociation into surface hydroxyls. The results show that Ti doping synergistically promotes interfacial H2O polarization and dissociation by inducing electronic structure rearrangement and facilitating oxygen vacancy formation, offering transferable guidelines for dopant regulation and defect engineering.

Hydrolysis catalysts for carbonyl sulfide (COS) removal from blast furnace gas still confront the challenges of inadequate low-temperature activity and limited durability, primarily due to inefficient H2O activation and competitive COS/H2O adsorption. Herein, we developed morphology-engineered Al2O3 catalysts (nanorod, nanoblock and nanoparticle) via controlled precursors modulation in hydrothermal synthesis, with further potassium (K) doping creating supplementary active sites. Structural characterizations (NMR and in-situ DRIFTS) illustrated that the nanorod catalyst possessed the highest ratio of terminal -OH and the best H2O activation efficiency, which was maintained after the load of K. Theoretical calculations verified terminal -OH promoted H2O adsorption and decreased the reaction energy barrier of H2O dissociation. Furthermore, dual-site engineering (K/Al-OH) mitigated adsorption competition through selective molecular anchoring- H2O preferentially bound to -OH sites while COS interacted with K centers. The optimized K0.1Al2O3-NR catalysts achieved more than 95 % COS conversion at 75 degrees C (WHSV = 12 0000 cm- 3g- 1h- 1), maintaining more than 80 % COS conversion under 5 H2O. This dual-site strategy surpassed the low activity caused by competitive adsorption during COS hydrolysis, thereby advancing the progress of blast furnace gas treatment.

Ammonia (NH3)/coal co-combustion has attracted increasing interest as a viable route for ammonia utilization in existing coal-fired systems; however, the chemical interaction between NH3 and coal volatiles during devolatilization remains poorly resolved. In this work, a detailed kinetic mechanism for NH3/coal-volatile co-combustion comprising 173 species and 2036 elementary reactions is developed and validated against laminar flame speeds of NH3, CH4, H2, and representative mixed fuels over a wide range of conditions. Numerical simulations are conducted to analyze the flame characteristics of NH3/coal-volatiles. With increasing NH3 fraction, the laminar flame speed decreases while the flame thickness increases, accompanied by a downstream shift of the main reaction zone due to reduced reactivity and delayed radical formation. Analysis of nitrogen chemistry indicates that NO formation is primarily controlled by NHx oxidation pathways involving HNO intermediates, whereas NO reduction is governed by NHx-mediated reactions. Reaction pathway analysis further reveals that HCN acts as a key intermediate linking carbon- and nitrogen-containing reaction networks, enabling strong coupling between volatile oxidation and NH3 conversion. The present mechanism provides a mechanistic framework for interpreting flame structure evolution and nitrogen conversion in NH3/coal-volatile co-combustion and establishes a robust kinetic basis for predictive modeling of ammonia-based co-firing systems.

The phenomenon of particle agglomeration in a liquid-containing fluidized bed is closely associated with the interactions between gas and solid phases, as well as the evaporation of the liquid component. This study performs an experimental investigation to examine the interactions among particle growth, fluidization behavior, and droplet evaporation within a continuous top-spray fluidized bed system. The research indicates that increased drying air temperatures generate severe drying conditions that promote the conversion of liquid bridges to solid bridges between particles. This conversion significantly decreases the nucleation time and encourages a more consistent distribution of agglomerate sizes. Additionally, a rise in the spraying rate and binder viscosity, strengthen the cohesive forces among particles, resulting in the development of larger agglomerates. The evaporation of the liquid binder exhibits a substantial correlation with the behavior of bubbles within the bed, which in turn affects particle growth and the chaotic dynamics of the fluidized bed system. The process of particle growth is delineated into two separate phases: nucleation growth and shell growth. Notably, the duration of nucleation growth phase exceeds that of the shell growth phase. Ultimately, a regime map has been developed to evaluate the feasibility of the spray granulation process concerning fluidization and drying parameters. The findings suggest that excessively low fluidization numbers, coupled with inadequate drying conditions, could lead to the failure of the liquid-containing fluidization process.