NH₃ has emerged as a promising candidate for low-carbon gas turbines, with NO_x emission issues being mitigated by air-staged combustion. However, the role of fuel/air mixing quality (represented by unmixedness) in NO_x formation in NH₃ systems remains poorly explored. In this study, the characteristics of NO_x formation under the effects of unmixedness have been numerically investigated using an NH₃/CH₄ fired air-staged model combustor consisting of perfectly stirred reactors (PSRs) and plug flow reactors (PFRs), employing the 84-species, 703-reaction Tian mechanism under H/J heavy duty gas turbine conditions. It was found that a primary-stage equivalence ratio of 1.2–1.5 corresponds to a low NO_x formation region under perfectly mixed fuel and air conditions. In this region, a relatively low NO_x formation is achieved when the unmixedness is less than 0.12 and NO_x formation exhibits low sensitivity to fuel/air unmixedness. Based on these findings and the fact that the air-staged combustion loses its advantage in reducing NO_x emissions when the unmixedness exceeds 0.12 across all equivalence ratios, recommended mixing quality thresholds for different equivalence ratios are proposed to guide combustor design and operation optimization. A parametric study of chemical reaction pathways at different unmixedness levels in the two stages demonstrates that NO_x is mainly formed in the main combustion zone of the secondary stage via the HNO pathway, which results in NO_x formation rising to thousand ppm when unmixedness exceeds 0.3, although NO_x reduction through NHi and N₂O pathways partially offsets contributions from the HNO and thermal NO_x pathways. To leverage the NO_x reduction potential of the NHi and N₂O pathways, the residence time in both stages should be carefully adjusted to help suppress NO_x to as low as 48 ppm. The results of this study are important for engineering applications, providing guidance for the design of NH₃ fired combustors aimed at significantly reducing NO_x formation.

This study employs the method of embedding voltage leads within three cells of an electrolysis stack to investigate the quantitative impact of the electrolysis cells and their interfaces on overall stack performance. A 900-h stability test was conducted at a constant temperature of 750 °C with a current density of 500 mA/cm² and 60 vol.% (volume fraction) water steam content. The results indicate the electrolysis voltage of the stack increased by 0.213 V, while the voltage across the three cells increased by 0.268 V. Post-mortem analysis reveals changes in the three-phase boundary (TPB) and porosity of the Ni-YSZ electrodes across different cells. These structural changes explain the variations in both ohmic resistance and polarization resistance. In contrast, the voltage drop across the current-collecting interface between the interconnect and the cell decreases by 0.055 V, accounting for 25.82% of the total stack degradation. Improved interface contact helps inhibit stack degradation. Future work will further investigate the stability of stack components and their interfaces, aiming to optimize stack design.

The substitution of traditional fossil fuels with renewable energy sources is a crucial endeavor for achieving carbon neutrality targets. However, the intermittency of solar, wind, and other renewables poses significant challenges to the power grid. Power-to-X (P2X) technologies play an essential role in enabling the efficient consumption of renewable energy. High-temperature solid oxide electrolysis cells (SOECs) to convert CO₂ offer a promising method for CO₂ conversion, allowing renewable electricity to be stored in chemical form and facilitating the resourceful utilization of carbon resources. In this paper, the mechanism of CO₂ reduction through SOECs is reviewed, two pathways for converting CO₂ to chemicals via SOECs are summarized, and the current markets and manufacturers of SOECs are elucidated. Based on this discussion and analysis, the main challenges and development directions for the large-scale application of SOECs in CO₂ conversion are further proposed.

Aqueous zinc-ion batteries (AZIBs) have emerged as promising candidates for next-generation energy storage systems due to their inherent safety, cost-effectiveness, and high theoretical capacity. However, their practical application remains constrained by limited cycling stability and sluggish ion diffusion kinetics, particularly under high mass loading conditions. These limitations are primarily attributed to the restricted ion transport pathways within the electrode structure and structural degradation caused by repeated zinc-ion insertion and extraction in highly loaded electrodes. To address these challenges, formamide (FA)-inserted VOPO₄ (FA-VOPO₄) nanosheet cathodes were designed with expanded interlayer spacing (9.3 Å), where FA molecules partially replace interlayer water, thereby enhancing both structural stability and ion transport pathways. This unique structural modification, supported by synergistic hydrogen bonding between FA and residual water, significantly improves Zn²⁺ diffusion kinetics and charge transfer properties, as confirmed by electrochemical tests and theoretical analysis. Consequently, FA-VOPO₄ electrodes delivered a remarkable volumetric capacity of 733 mAh/cm³ at 40 mA/g, approximately 8 times higher than that of the VOPO₄·2H₂O electrode, and retained 82.1% of their capacity after 1000 cycles at 1 A/g with a mass loading of 10 mg/cm². Even at a high mass loading of 20 mg/cm² (4.4 mAh/cm²), the FA-VOPO₄ cathode maintained a volumetric capacity of 535 mAh/cm³. These findings provide valuable insights into electrode design strategies for high-performance AZIBs, contributing to the development of safer, more efficient energy storage technologies with potential applications in grid storage and portable electronics.

Thermal runaway presents a significant challenge for large-scale application of lithium-ion batteries (LIBs), often leading to the release of flammable, explosive, and toxic gases. In this study, porous flowerlike cerium dioxide microspheres (FL-CeO₂) were investigated to eliminate hydrogen fluoride (HF) gas generated during thermal runaway. A dedicated test device and method were developed for this purpose. The FL-CeO₂ was synthesized via a hydrothermal method and coated onto nickel foam to fabricate a gas filter. During thermal runaway of a 5 Ah lithium iron phosphate (LiFePO₄) battery, the filter—loaded with 1.2 g CeO₂—achieved an instantaneous HF removal rate of up to 82.24% within approximately 40–50 s. X-ray photoelectron spectroscopy (XPS) results indicate that F⁻ ions replace O²⁻ ions in the CeO₂ lattice. Additionally, the potential for reusability of the CeO₂ microspheres was evaluated through multiple HF adsorption and desorption cycles. After 10 cycles, the regenerated CeO₂ microspheres retained a HF adsorption rate of 76.11%, demonstrating promising reusability.

A just energy transition (JET) to low-carbon fuels, such as green hydrogen, is critical for mitigating climate change. Countries with abundant renewable energy resources are well-positioned to meet the growing global demand for green hydrogen. However, to improve the volumetric energy density and facilitate transport and distribution over long distances, green hydrogen needs to be converted into an energy carrier such as green ammonia. This study conducted a comparative life cycle assessment (LCA) to evaluate the environmental impacts of green ammonia production, with a particular focus on greenhouse gas (GHG) emissions. The boundary of the study was from cradle-to-production gate, and the design was based on a coastal production facility in South Africa, which uses renewable energy to desalinate seawater, produce hydrogen, and synthesise ammonia. The carbon intensity of production was 0.79 kg CO₂-eq per kg of ammonia. However, if co-products of oxygen, argon and excess electricity are sold to market and allocated a portion of GHG emissions, the carbon intensity was 0.28 kg CO₂-eq per kg of ammonia. Further, without the sale of co-products but excluding the embodied emissions of the energy supply system, as defined in the recent international standard (ISO/TS 19870), the carbon intensity was 0.11 kg CO₂-eq per kg of ammonia. Based on the hydrogen content of ammonia, this is equivalent to 0.60 kg CO₂-eq per kg of hydrogen, which is well below the current threshold for certification as a low-carbon fuel. The process contributing most to the overall environmental impacts was electrolysis (68%), with particulate matter (55%) and global warming potential (33%) as the dominant impact categories. This reflects the energy intensity of electrolysis and the carbon intensity of the energy used to manufacture the infrastructure and capital goods required for green ammonia production. These findings support the adoption of green ammonia as a low-carbon fuel to mitigate climate change and help achieve net-zero carbon emissions by 2050. However, achieving this goal requires the rapid decarbonisation of energy supply systems to reduce embodied emissions from manufacturing infrastructure.

With the growing emphasis on sustainable development, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture is increasing. Ionic liquids (ILs), as promising green solvents, offer significant potential but face considerable challenges, particularly in solvent selection. To overcome the limitations of traditional screening methods, machine learning (ML) techniques have recently been applied, offering a more efficient and data-driven approach. This review provides an overview of key ML methods used in solvent screening and compares them with traditional experimental and theoretical techniques. It examines the role of descriptor selection in structure‒property-based methods, such as quantitative structure-activity relationships (QSAR) and quantitative structure‒property relationships (QSPR), which are critical for predicting IL properties. The review also explores the application of these methods to screen IL properties, including toxicity, viscosity, density, and CO₂ solubility. Additionally, it discusses challenges in selecting appropriate models based on data scale and task complexity, integrating physical information for model interpretability, and achieving multi-objective optimization to balance key properties in ionic liquid (IL) design. Finally, it summarizes the achievements, limitations, and prospects of ML applications in ILs research, offering insights into how these methods can advance the development of sustainable ILs.

High entropy alloys (HEAs) have gained significant attention in electrocatalysis research due to their distinctive multi-element composition, intricate electronic structure, and superior properties. By harnessing multi-component synergy, precise electron regulation, and the high-entropy effect, HEA electrocatalysts exhibit remarkable catalytic activity, selectivity, and stability. These materials demonstrate outstanding catalytic performance in a variety of electrocatalytic small molecule reduction reactions, including oxygen reduction (ORR), hydrogen evolution (HER), and CO₂ reduction (CO₂RR), making them promising candidates for clean energy conversion and storage applications, including fuel cells, metal-air batteries, water electrolysis, and CO₂ conversion technologies. This review highlights recent advancements in HEA electrocatalyst research, focusing on their synthesis, characterization, and applications in electrocatalytic small molecule reduction reactions. It also explores the underlying mechanisms of the high-entropy effect, multi-component synergy, and structural design. Finally, it discusses key challenges that remain in the application of HEAs for electrocatalytic small molecule reduction and outlines potential directions for future development in this field.

Developing environmentalyl friendly and energy-efficient CO₂ adsorbents for post-combustion capture is a critical step toward achieving toward carbon neutrality. While aqueous amines and metal oxides have play pivotal roles in CO₂ capture, their application is limited by issues such as secondary pollution and high energy consumption. In contrast, Zn-based metal-organic frameworks (Zn-based MOFs) have emerged as a green alternative, offering low toxicity reduced regeneration temperatures, and high efficiency in both CO₂ adsorption and catalytic conversion into valuable fuels and chemicals. This mini review begins with a general introduction to MOFs in CO₂ capture and conversion, followed by an overview of early studies on Zn-based MOFs for CO₂ capture. It then summarizes recent research advancements in Zn-based MOFs for integrated CO₂ capture and conversion. Finally, it discusses key challenges and future research directions for post-combustion CO₂ capture and conversion using Zn-based MOFs.

Hydrogen is a promising energy carrier that is expected to play a crucial role in helping Canada achieve its net-zero target by 2050. However, reducing the ambiguity in regulatory frameworks is essential to incentivize and facilitate international trade in hydrogen. To this end, regulators must agree on quantification methodologies that consider life cycle boundaries, process descriptions, co-product allocation, conversion constants, and certification units. Several studies have highlighted the importance of life cycle assessment (LCA) as a standardized, relevant method for estimating the carbon footprint associated with hydrogen production and evaluating its environmental sustainability. As such, LCA-based certification schemes could help create a transparent hydrogen market. The aim of this study is to validate the proposed harmonized LCA-based methodology for quantifying hydrogen production’s carbon intensity. This methodology follows a consistent scope and life cycle inventory (LCI) development criteria, alongside a rigorous data quality assessment. The well-to-gate carbon intensities of six hydrogen production pathways are compared, which range from 0.26 to 10.07 kg CO_2e per kg of hydrogen (kg CO_2e/kg H₂), against the hydrogen carbon intensity thresholds established by the Canadian Clean Hydrogen Investment Tax Credit (CHITC). For example, the biomass gasification with carbon capture (CC) pathway demonstrates the lowest carbon intensity, while thermochemical pathways, such as steam methane reforming of natural gas without CC, poses challenges to meeting the maximum CHTIC threshold of 4 kg CO_2e/kg H₂.