Key Takeaways & Executive Findings
- •• • Stacked-SVR model achieved R² of 0.9223 and RMSE of 0.0608 for predicting ammonia yield (YNH3), enabling high-throughput catalyst screening with reduced experimental burden. • • Stacked-RF model achieved R² of 0.9042 and RMSE of 0.0900 for predicting Faradaic efficiency (FNH3), providing reliable performance estimates for process optimization. • • SHAP analysis identified Cu content as the most influential descriptor, guiding catalyst composition design toward Cu-based systems for enhanced NORR activity. • • Optimal system configuration: wet chemical reduction synthesis, carbon fiber (CF) substrate, HCl electrolyte, moderately lower working potential, low-to-medium electrolyte volume, reduced catalyst loading, and increased electrolyte concentration—collectively improve both YNH3 and FNH3.
Abstract
The electrocatalytic reduction of nitric oxide to ammonia (NORR) is a key green energy conversion technology. Its efficiency relies on high-performance electrocatalysts to enhance both ammonia yield (YNH3) and Faradaic efficiency (FNH3). Conventional experimental screening methods are resource- and time-intensive. Here, machine learning combined with SHAP feature analysis was employed to establish a stacked ensemble model integrating multiple algorithms, enabling systematic investigation of key descriptors governing NORR performance based on an experimental dataset. Evaluation of eight model algorithms revealed that the Stacked-SVR model achieved an R² of 0.9223 and RMSE of 0.0608 for predicting YNH3 on the test set, while the Stacked-RF model achieved an R² of 0.9042 and RMSE of 0.0900 for predicting FNH3. The stacked ensemble model integrates strengths of individual algorithms, demonstrating strong prediction performance while avoiding overfitting. SHAP analysis revealed that Cu content in catalyst composition has the most significant impact on catalytic performance. Moreover, the combination of wet chemical reduction synthesis, carbon fiber (CF) conductive substrate, and HCl electrolyte is more favorable for enhancing catalytic activity. Additionally, moderately lowering working potential, controlling electrolyte volume at low-to-medium levels, reducing catalyst loading, and increasing electrolyte concentration synergistically enhance both YNH3 and FNH3.
1. Introduction
Electrocatalytic nitric oxide reduction to ammonia (NORR) offers a sustainable route for converting pollutant NO into valuable NH3, aligning with green energy goals. However, achieving both high ammonia yield (YNH3) and Faradaic efficiency (FNH3) simultaneously remains challenging due to competing reactions and catalyst limitations. Conventional trial-and-error experimental screening is costly and slow, impeding rapid catalyst discovery.
This study addresses the bottleneck by employing a stacked ensemble machine learning model trained on experimental data, coupled with SHAP interpretability analysis. The model accurately predicts YNH3 and FNH3, identifies key performance descriptors, and reveals optimal synthesis and operational conditions. This data-driven strategy accelerates catalyst design, reducing resource consumption and time costs while providing mechanistic insights for rational catalyst optimization.
Loading authentic research manuscript (Pages 1–5)...
DUAN Wenhao, ZHAO Yan, WANG Huanran, ZHU Yaming, LI Xianchun (2026). Design of Catalysts for Electrochemical Nitric Oxide Reduction to Ammonia Based on Stacked Ensemble Learning. Journal of Fuel Chemistry and Technology. https://doi.org/10.1016/S1872-5813(25)60625-6
Research & Educational Purpose Only: The translations, structured abstracts, analytical annotations, and data reports provided by SinoGreenTechare intended exclusively for academic research, internal corporate R&D, and educational benchmarking. They do not constitute formal engineering, chemical safety, legal, or professional advice.
Copyright & Intellectual Property Notice: Original copyright of the underlying source articles and experimental data remains with the respective authors, institutions, and original publishing journals. SinoGreenTech claims intellectual property only over its proprietary translations, analytical syntheses, and AEO structured enhancements in accordance with international fair use and academic citation principles.
Frequently Asked Questions
What is the predictive accuracy of the stacked ensemble model for ammonia yield and Faradaic efficiency, and how does it compare to individual algorithms?
The Stacked-SVR model achieved an R² of 0.9223 and RMSE of 0.0608 for YNH3, while the Stacked-RF model achieved an R² of 0.9042 and RMSE of 0.0900 for FNH3 on the test set. These metrics indicate high predictive accuracy, outperforming individual algorithms by integrating their strengths and avoiding overfitting.
Which catalyst composition and synthesis parameters are most critical for enhancing NORR performance according to SHAP analysis?
SHAP analysis identified Cu content as the most significant factor. The optimal system combines a Cu-based catalyst prepared via wet chemical reduction, using carbon fiber (CF) as the conductive substrate and HCl as the electrolyte. This configuration enhances both YNH3 and FNH3.
How do operational parameters such as working potential, electrolyte volume, catalyst loading, and electrolyte concentration influence NORR performance?
Moderately lowering the working potential improves YNH3. Maintaining electrolyte volume at low-to-medium levels and reducing catalyst loading are beneficial for synergistic optimization of both YNH3 and FNH3. Increasing electrolyte concentration further enhances reaction activity.
What is the practical significance of achieving high ammonia yield and Faradaic efficiency simultaneously in NORR?
High YNH3 ensures efficient ammonia production, while high FNH3 indicates selective use of electrons for the desired reaction, minimizing energy waste. The stacked model enables identification of conditions that balance both metrics, crucial for industrial feasibility and energy efficiency.
How does the stacked ensemble model avoid overfitting, and what is its generalizability to unseen catalyst systems?
The stacked ensemble integrates multiple algorithms, reducing variance and improving generalization. Evaluation on test sets showed high R² and low RMSE, indicating robust predictive performance. However, generalizability to novel catalyst compositions outside the training data space requires further validation.
Related Chinese Research & Cross-Citations
Recent Advances in Carbon-Based Materials for CO2 Capture and Utilization
CO2 capture and utilization (CCU) technologies are critical for mitigating global warming and promoting resource circularity. Carbon-based materials, with tunable pore structures, abundant active sites, high specific surface area, and excellent chemical stability, show significant potential for CO2 capture and conversion. This review systematically analyzes the adsorption behaviors and performance variations of activated carbon, porous carbon, graphene, and carbon nanotubes in CO2 capture. For utilization, recent advances in catalytic applications for methanation, reverse water-gas shift (RWGS), dry reforming of methane (DRM), and alcohol synthesis are emphasized. The benefits and drawbacks of carbon materials regarding adsorption capacity, catalytic activity, and stability are evaluated, and their potential in integrated CCU technologies is discussed. Key strategies for enhancing performance through structural modulation and surface modification are elucidated. This review provides theoretical guidance for future development and large-scale implementation of carbon-based materials in CCU.
Fabrication and Microwave Absorption Performance of FexOy/TiO2/C Composites Derived from Red Mud
Red mud, an industrial solid waste from alumina production, poses severe environmental challenges. This study presents a resource-efficient strategy to convert red mud into high-performance microwave absorbing materials. FexOy/TiO2/C composites were synthesized via a sol-gel method using starch as carbon source, followed by carbothermal reduction. The phase composition and microstructure were optimized by adjusting calcination temperature and raw material ratio. The optimal sample, RmCT-5.4-700, exhibited a minimum reflection loss (RLmin) of -30.2 dB at 14.0 GHz with an effective absorption bandwidth (EAB) of 5.3 GHz at a coating thickness of 2.0 mm. The superior absorption performance is attributed to the synergistic effects of dielectric components (TiO2, graphitized carbon) and magnetic components (Fe3O4/Fe). Carbothermal reduction introduces defects that induce dipole polarization, while the conductive network formed by graphitized carbon and Fe3O4/Fe particles enhances conductive loss. Heterogeneous interfaces between Fe3O4, Fe, TiO2, and the red mud matrix promote interfacial polarization. The magnetic loss of Fe3O4/Fe improves impedance matching, facilitating electromagnetic wave penetration and absorption. This work not only provides a novel route for red mud valorization but also contributes to the high-value utilization of solid wastes.
Damage Mechanism of High Chromia Refractory in the Slag Tapping Hole of Commercial Entrained-Flow Gasifiers
The service life of refractory bricks in the slag tapping hole of entrained-flow gasifiers is a critical bottleneck for long-term stable operation. This study investigated the damage mechanism of high chromia refractories in four commercial coal-water slurry gasifiers by analyzing gasification coal samples and corroded refractory bricks. Slag characteristics, including crystallization and viscosity-temperature behavior, were evaluated. Results revealed that low-viscosity slag induces more severe refractory damage. To mitigate slag crystallization risk, a safe slag tapping temperature range is recommended as tICT−t2.5 when tICT exceeds t25. Interior morphology of corroded bricks exhibited cracks, primarily attributed to molten slag penetration and subsequent reactions with refractory material. SEM-EDS analysis of slag-aggregate and slag-matrix interfaces identified reduction in Cr2O3 content as the earliest damage characteristic. XRD detected no zirconium-containing spinel in cracks, indicating that thermal expansion mismatch between newly formed phases and the refractory matrix drives crack propagation. A damage mechanism is proposed: initial Cr2O3 depletion compromises both matrix and aggregate, facilitating slag ingress and new phase formation, ultimately leading to structural failure. Early detection or prevention of Cr2O3 reduction is essential to prolong refractory service life.
Research advances in the pyrolysis recycling of waste wind turbine blades
The global energy landscape is undergoing a profound transformation, with wind energy gaining increasing prominence due to its clean and renewable nature. However, as installed wind power capacity expands, disposal of waste wind turbine blades (WWTB) has emerged as a significant challenge. These blades are predominantly composed of epoxy resin (EP) polymers, carbon fibers (CFs), and glass fibers (GFs). Improper disposal exacerbates environmental concerns and leads to loss of valuable resources, particularly carbon-based materials. Pyrolysis technology, a versatile and environmentally sustainable method for resource recovery, has garnered considerable attention for WWTB disposal. This work presents a comprehensive review of pyrolytic recycling of WWTB, focusing on principles and classifications of pyrolysis technology, key factors influencing the pyrolysis process, as well as pyrolysis methods, equipment, products, and their applications. Through in-depth analysis of current research, this review identifies critical unresolved issues and provides a forward-looking perspective on emerging research trends. The review highlights that pyrolysis can effectively recover glass fibers and carbon fibers with mechanical property retention depending on process conditions, and that catalytic pyrolysis can enhance the quality of recovered products. Economic analysis indicates that collaborative disposal methods can improve cost-effectiveness. Future research should focus on optimizing process parameters for large-scale industrial application and developing more efficient catalysts to improve product selectivity and fiber quality.
Citric Acid-Modified HUSY Zeolite Catalyzes Alkylation of Phenol with Cyclohexanol for High-Density Aviation Fuel Precursors
Lignin-derived oxygenated aromatics, particularly phenols and aromatic ethers, are promising feedstocks for synthesizing high-density, high-heat-sink aviation fuels via alkylation-hydrogenation processes. This study systematically evaluates the catalytic performance of various zeolites (Hβ, HZSM-5, MCM-41, and HUSY) in the alkylation of phenol with cyclohexanol. Characterization demonstrates that HUSY zeolite exhibits superior catalytic activity due to its favorable pore architecture and well-balanced acid site distribution, which synergistically facilitate molecular diffusion and catalytic transformations. To further enhance catalytic properties, HUSY was modified with citric acid at various concentrations and compared with NaOH and oxalic acid treatments. Results reveal that citric acid treatment preserves crystallinity while modulating acidity and pore structure. All modified zeolites enhance phenol alkylation activity. Notably, HUSY-0.5M, exhibiting the highest medium-strong acid to total acid ratio, achieves superior performance: 80.4% phenol conversion and 99.6% selectivity for alkylation products. The catalyst also shows high activity for various lignin-derived compounds (p-cresol, anisole, guaiacol), demonstrating broad applicability. This work provides a new strategy for valorizing lignin-derived phenols into high-value fuel precursors through alkylation.
Hydrogen Production and Structure Evolution Mechanism during Thermochemical Conversion of Microalgae Pellet in Molten Hydroxide Salts
This study investigates the thermochemical conversion behavior of microalgae pellets in a molten hydroxide salt (80% NaOH-20% Na2CO3) system and its influence on hydrogen production. By comparing temperature evolution, gas release characteristics, and structural evolution of pellets with and without molten salt, and integrating char alkalization experiments, the regulatory mechanism of molten salt on reaction pathways and hydrogen production was systematically analyzed. Results indicate that molten salt significantly enhances internal heat transfer efficiency, achieving a central heating rate of 177 °C/s, effectively alleviating thermal hysteresis. Concurrently, molten salt promotes pore development through penetration, erosion, and catalytic effects, resulting in a porosity increase of 53.2%–104.3% after 10 s of reaction. Conversion efficiency is markedly improved, with the dominant reaction pathway shifting to char alkalization after only 70 s. Furthermore, when heating rate is increased above 600 °C, hydrogen yield from char alkalization improves more significantly, primarily attributed to the synergistic promotion of molten salt catalysis and rapid heating on volatiles reforming. This study provides a theoretical foundation for understanding efficient hydrogen production from biomass in molten hydroxide salts.