Fuel Processing Technology最新文献_第5页

Techno-economic assessment of biomass-to-liquid fuel production via chemical looping in comparison to conventional pathways 与传统途径相比，通过化学循环对生物质制液体燃料生产的技术经济评估

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-20 DOI: 10.1016/j.fuproc.2025.108341

Krutarth Pandit, Ishani Karki Kudva, Shekhar G. Shinde, Christian Boose, Liang-Shih Fan

Rising liquid fuel demand is increasing CO₂ emissions, making renewable biomass technologies vital for a low-carbon future. This study presents a chemical looping-based biomass conversion process integrated with Fischer-Tropsch synthesis (CLFT) for liquid fuel production and evaluates its techno-economic performance against two established biomass-based pathways: biomass gasification to liquid fuels (GFT) and biomass pyrolysis to liquid fuels (PHP). A minimum fuel selling price (MFSP) analysis, conducted using a discounted cash flow approach, estimates MFSP values of $3.59/GGE for CLFT, $5.26/GGE for GFT, and $4.54/GGE for PHP. The energy efficiencies of CLFT, GFT, and PHP are at 37.7 %, 37.3 %, and 46.4 %, respectively, while their carbon conversion efficiencies are 32.3 %, 30.5 %, and 40.4 %. Sensitivity analyses reveal that feedstock cost exerts the greatest influence on MFSP, followed by the internal rate of return and capital expenditures. Additionally, a 50 % increase in plant capacity (from the baseline 2000 dry tons/day of biomass) results in only an 11 % reduction in MFSP, whereas a 50 % decrease in plant size leads to a 17 % increase in MFSP. These findings highlight CLFT's economic and technical advantages, reinforcing its promise as a cost-effective, sustainable fuel generation alternative.

不断增长的液体燃料需求增加了二氧化碳排放量，使可再生生物质技术对低碳未来至关重要。本研究提出了一种基于化学环的生物质转化过程，结合费托合成（CLFT）用于液体燃料的生产，并针对两种已建立的生物质转化途径：生物质气化制液体燃料（GFT）和生物质热解制液体燃料（PHP），评估了其技术经济性能。使用贴现现金流方法进行的最低燃料销售价格（MFSP）分析估计，CLFT的MFSP值为3.59美元/GGE， GFT为5.26美元/GGE， PHP为4.54美元/GGE。CLFT、GFT和PHP的能源效率分别为37.7%、37.3%和46.4%，而它们的碳转换效率分别为32.3%、30.5%和40.4%。敏感性分析表明，原料成本对MFSP的影响最大，其次是内部收益率和资本支出。此外，植物容量增加50%（以2000干吨/天生物量为基准）只会导致MFSP减少11%，而植物规模减少50%则会导致MFSP增加17%。这些发现突出了CLFT的经济和技术优势，加强了其作为具有成本效益的可持续燃料发电替代品的承诺。

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引用次数: 0

Experimental investigation and machine learning-based estimation of oxyhydrogen (HHO) gas production using KOH electrolyte in a flat plate electrolyser 平板电解槽中KOH电解液产氢氧（HHO）气的实验研究及基于机器学习的估计

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-20 DOI: 10.1016/j.fuproc.2025.108339

Mohammad Amin Adoul , Balaji Subramanian , Naveen Venkatesh Sridharan , Ramin Karim , Ravdeep Kour

Hydrogen gas has gained significant attention as a cleaner alternative to fossil fuels offering a sustainable energy solution. This study explores the production efficiency of oxyhydrogen (HHO) gas using a flat plate electrolyser with potassium hydroxide (KOH) as the electrolyte. Machine learning regression models were employed to estimate hydrogen generation rates and system efficiency based on key operational parameters that includes voltage, current and electrolyte concentration. A set of gradient-boosting algorithms was evaluated utilizing raw experimental data to predict (i) hydrogen output in liters per minute (LPM) and (ii) system efficiency. The results indicate that Categorical Boosting (CatBoost) excelled in forecasting system efficiency (R² = 0.9748, RMSE = 1.6567 on testing data) and predicting HHO gas generation rate (R² = 0.9936, RMSE = 0.0090). The experimental results show that with the increase in KOH concentration there is increase in production of Hydrogen. Maximum efficiency was noted with 0.5 N of KOH with the peak efficiency of 99.8 % because of its optimal conductivity and power consumption. It can also be absorbed that higher concentration such 0.75 N and 1 N have shown significant improvement in hydrogen production. Experimental findings further revealed that moderate operating conditions maximize hydrogen production with efficiency varying as a function of applied current and electrolyte concentration. This study highlights the advantages of integrating machine learning models with electrolysis-based hydrogen production offering a scalable and data-driven approach to optimizing energy efficiency. The results underscore the potential of KOH-based electrolysis for sustainable hydrogen generation and reinforce the role of predictive modeling in enhancing system performance.

氢气作为一种更清洁的化石燃料替代品，提供了一种可持续的能源解决方案，已经引起了人们的极大关注。本研究探讨了以氢氧化钾（KOH）为电解液的平板电解槽生产氢氧（HHO）气体的效率。基于电压、电流和电解质浓度等关键操作参数，采用机器学习回归模型估算氢气生成率和系统效率。利用原始实验数据评估了一组梯度增强算法，以预测(i)每分钟公升（LPM）的氢气输出和（ii）系统效率。结果表明，CatBoost在预测系统效率（R2 = 0.9748, RMSE = 1.6567）和预测HHO产气率（R2 = 0.9936, RMSE = 0.0090）方面表现优异。实验结果表明，随着KOH浓度的增加，制氢量增加。当KOH浓度为0.5 N时，电导率和功耗均达到最佳，效率最高达99.8%。还可以看出，0.75 N和1 N等较高浓度对产氢效果有显著改善。实验结果进一步表明，适度的操作条件下，氢气产量最大，效率随施加电流和电解质浓度的变化而变化。这项研究强调了将机器学习模型与电解制氢相结合的优势，为优化能源效率提供了一种可扩展和数据驱动的方法。研究结果强调了koh电解在可持续制氢方面的潜力，并加强了预测建模在提高系统性能方面的作用。

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引用次数: 0

Co-Zn bimetallic oxide & hydroxyfluoride nanowires: highly active catalyst for catalytic transfer hydrogenation of furfural 钴锌双金属氧化物&羟基氟化物纳米线：用于糠醛催化转移加氢的高活性催化剂

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-19 DOI: 10.1016/j.fuproc.2025.108330

Chenyu Wang , Xiao Tan , Wei Feng , Peijun Ji

Co-Zn bimetallic hydroxyfluoride nanorods (CoZnF) were synthesized at room temperature in an aqueous solution. After calcination at 330 °C in air, CoZnF was partially decomposed to form CoZn bimetallic oxide & hydroxyfluoride (CoZnO&CoZnF) nanowires. The higher electronegativity of fluorine compared to oxygen reduces the valence electron density of oxygen in CoZnF, thereby weakening the metal‑oxygen bonds, and generating abundant oxygen vacancy sites in CoZnO&CoZnF. Electron transfer between cobalt and zinc maintains cobalt in the Co(II) oxidation state. Catalytic results demonstrate the potential of CoZnO&CoZnF for selective hydrogenation of furfural to furfuryl alcohol (FA). Lewis acid-base pairs (Co²⁺/Zn²⁺-O²⁻) and oxygen vacancy sites act as active sites for catalytic transfer hydrogenation (CTH). The nanowire structure and highly accessible active sites enhance catalytic activity. CoZnO&CoZnF exhibits an excellent catalytic activity, achieving 98.1 % yield of furfuryl alcohol (FA) with a selectivity of 99.2 %. Mechanistic insights from ¹HNMR analysis and kinetic studies elucidate the reaction pathway, including activation energy determination.

在室温条件下，在水溶液中合成了Co-Zn双金属羟基氟化物纳米棒。在330℃空气中煅烧后，CoZnF部分分解生成CoZn双金属氧化物羟基氟化物（CoZnO&CoZnF）纳米线。与氧相比，氟的电负性较高，降低了CoZnF中氧的价电子密度，从而削弱了金属-氧键，并在CoZnO&；CoZnF中产生了丰富的氧空位。钴和锌之间的电子转移使钴保持在Co（II）氧化态。催化结果表明，CoZnO&；CoZnF具有选择性加氢糠醛制糠醇（FA）的潜力。Lewis酸碱对（Co2+/Zn2+-O2−）和氧空位是催化转移氢化反应（CTH）的活性位点。纳米线结构和高度可接近的活性位点增强了催化活性。CoZnO&；CoZnF表现出优异的催化活性，糠醇（FA）的收率为98.1%，选择性为99.2%。从1HNMR分析和动力学研究中获得的机理见解阐明了反应途径，包括活化能的测定。

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引用次数: 0

Machine learning-driven modeling framework for steam co-gasification applications 蒸汽共气化应用的机器学习驱动建模框架

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-19 DOI: 10.1016/j.fuproc.2025.108340

Usman Khan Jadoon, Ismael Díaz, Manuel Rodríguez

Steam co-gasification of biomass and plastic waste is a promising route for syngas production and waste valorization. However, accurately predicting syngas composition remains challenging due to inherent complexity and nonlinearity of the process. This study presents a comprehensive comparative analysis between conventional process simulators-based models (Aspen Plus), namely the thermodynamic equilibrium (TEM), restricted thermodynamic (RTM), and kinetic (KM) modeling approaches, and machine learning (ML) models for the prediction of the syngas composition. Using 208 experimental data points compiled from 20 published studies covering various feedstocks and gasification conditions in bubbling fluidized bed gasifiers (BFBG), the performance of the models was evaluated after extensive data preprocessing. Among several ML algorithms evaluated, the neural network (NN) delivered the lowest average root mean square error in syngas mol fraction predictions (0.0174), outperforming RTM (0.0966), KM (0.1378), and TEM (0.1470). To explore input–output relationships beyond interpolation, a conditional generative adversarial network (cGAN) generated synthetic data, which served as the basis for sensitivity and interpretability analyses. The NN, acting as a surrogate model, was paired with SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDP) to quantify the effects and nonlinear interactions of key features on syngas yields providing actionable insights for process optimization.

生物质和塑料垃圾的蒸汽共气化是合成气生产和废物增值的一条很有前途的途径。然而，由于过程固有的复杂性和非线性，准确预测合成气成分仍然具有挑战性。本研究对传统的基于过程模拟器的模型（Aspen Plus），即热力学平衡（TEM）、限制热力学（RTM）和动力学（KM）建模方法，以及用于预测合成气成分的机器学习（ML）模型进行了全面的比较分析。利用从20篇已发表的研究中收集的208个实验数据点，涵盖了鼓泡流化床气化炉（BFBG）的各种原料和气化条件，经过广泛的数据预处理后，对模型的性能进行了评估。在评估的几种ML算法中，神经网络（NN）在合成气摩尔分数预测中的平均均方根误差最低（0.0174），优于RTM（0.0966）、KM（0.1378）和TEM（0.1470）。为了探索插值之外的输入-输出关系，条件生成对抗网络（cGAN）生成了合成数据，作为敏感性和可解释性分析的基础。该神经网络作为代理模型，与SHapley加性解释（SHAP）和部分依赖图（PDP）配对，以量化合成气产量的关键特征的影响和非线性相互作用，为过程优化提供可操作的见解。

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引用次数: 0

Ex-ante life-cycle assessment of biomass-derived hydrogen via fast pyrolysis and sorption enhanced steam reforming: Addressing scale-up uncertainties 通过快速热解和吸附强化蒸汽重整的生物质衍生氢的事前生命周期评估：解决规模扩大的不确定性

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-17 DOI: 10.1016/j.fuproc.2025.108334

Pablo Comendador , Nicolás Martínez-Ramón , Martin Olazar , Gartzen Lopez , Diego Iribarren

Biomass conversion through pyrolysis and sorption enhanced steam reforming (PY-SESR) is a novel alternative for producing hydrogen at bench scale. This study focused on addressing uncertainties linked to its industrial-scale implementation, comparing it to the process without CO₂ capture (PY-SR), and using steam methane reforming (SMR) as benchmark, which is currently the main hydrogen production route. Both PY-SESR and PY-SR scaled-up processes were simulated in Aspen Plus®, based on experimental bench-scale data. Life-cycle assessment based on process simulation-derived inventories showed that the PY-SESR alternative was the only one resulting in renewable hydrogen production according to the European Renewable Energy Directive (RED III) (3 kg_CO₂-eq kg⁻¹_H₂ threshold), attaining net negative emissions (−1.12 kg_CO₂-eq kg⁻¹_H₂). Nevertheless, its higher energy consumption, mainly driven by sorbent calcination and CO₂ pressurization for storage, led to higher environmental burdens with respect to other indicators. Considering fossil resource use, ozone depletion and freshwater eutrophication, PY-SR was found to outperform both PY-SESR and SMR, while SMR performed better in acidification and use of minerals and metals. Monte Carlo simulations and a sensitivity analysis showed that heat demand and electricity consumption highly contributed to PY-SR and PY-SESR variability, as a consequence of the limitations associated to early-stage process scale-up.

通过热解和吸附强化蒸汽重整（PY-SESR）进行生物质转化是一种新的实验规模制氢方法。本研究的重点是解决与工业规模实施相关的不确定性，将其与无二氧化碳捕集（PY-SR）的过程进行比较，并以蒸汽甲烷重整（SMR）为基准，这是目前主要的制氢途径。基于实验规模数据，在Aspen Plus®中模拟了PY-SESR和PY-SR放大过程。基于过程模拟衍生清单的生命周期评估表明，根据欧洲可再生能源指令（RED III）（3 kgCO₂-eq kg - 1H 2阈值），PY-SESR替代方案是唯一产生可再生氢气的替代方案，实现净负排放（- 1.12 kgCO₂-eq kg - 1H 2）。然而，其较高的能耗，主要是由吸附剂煅烧和CO2加压储存驱动，导致其他指标的环境负担较高。考虑化石资源利用、臭氧消耗和淡水富营养化，PY-SR的效果优于PY-SESR和SMR，而SMR在酸化和矿物和金属的利用方面表现更好。蒙特卡罗模拟和敏感性分析表明，由于早期工艺放大的限制，热需求和电力消耗对PY-SR和PY-SESR的变异性有很大贡献。

{"title":"Ex-ante life-cycle assessment of biomass-derived hydrogen via fast pyrolysis and sorption enhanced steam reforming: Addressing scale-up uncertainties","authors":"Pablo Comendador , Nicolás Martínez-Ramón , Martin Olazar , Gartzen Lopez , Diego Iribarren","doi":"10.1016/j.fuproc.2025.108334","DOIUrl":"10.1016/j.fuproc.2025.108334","url":null,"abstract":"<div><div>Biomass conversion through pyrolysis and sorption enhanced steam reforming (PY-SESR) is a novel alternative for producing hydrogen at bench scale. This study focused on addressing uncertainties linked to its industrial-scale implementation, comparing it to the process without CO<sub>2</sub> capture (PY-SR), and using steam methane reforming (SMR) as benchmark, which is currently the main hydrogen production route. Both PY-SESR and PY-SR scaled-up processes were simulated in Aspen Plus®, based on experimental bench-scale data. Life-cycle assessment based on process simulation-derived inventories showed that the PY-SESR alternative was the only one resulting in renewable hydrogen production according to the European Renewable Energy Directive (RED III) (3 kg<sub>CO₂-eq</sub> kg<sup>−1</sup><sub>H₂</sub> threshold), attaining net negative emissions (−1.12 kg<sub>CO₂-eq</sub> kg<sup>−1</sup><sub>H₂</sub>). Nevertheless, its higher energy consumption, mainly driven by sorbent calcination and CO<sub>2</sub> pressurization for storage, led to higher environmental burdens with respect to other indicators. Considering fossil resource use, ozone depletion and freshwater eutrophication, PY-SR was found to outperform both PY-SESR and SMR, while SMR performed better in acidification and use of minerals and metals. Monte Carlo simulations and a sensitivity analysis showed that heat demand and electricity consumption highly contributed to PY-SR and PY-SESR variability, as a consequence of the limitations associated to early-stage process scale-up.</div></div>","PeriodicalId":326,"journal":{"name":"Fuel Processing Technology","volume":"278 ","pages":"Article 108334"},"PeriodicalIF":7.7,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Corrigendum to ‘Profiling the trapped and deactivating species on HZSM-5 zeolite during 1-butene oligomerization’ [Fuel Processing Technology 277 (2025) 108297] “1-丁烯齐聚过程中HZSM-5沸石上捕获和失活物质的分析”[燃料加工技术277(2025)108297]的勘误表

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-17 DOI: 10.1016/j.fuproc.2025.108333

Sepideh Izaddoust , Idoia Hita , Timo Kekäläinen , José Valecillos , Janne Jänis , Pedro Castaño , Eva Epelde

引用次数: 0

Emulsified fuel stabilized by comb-type ternary block copolymers for drag reduction and heat transfer enhancement 用梳型三元嵌段共聚物稳定乳化燃料，以减少阻力和增强传热

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-17 DOI: 10.1016/j.fuproc.2025.108335

Bin Sun , Xiwei Ye , Yongsheng Guo , Shu Yan , Wenjun Fang

Turbulent flow in high-speed hydrocarbon fuels increases engine resistance and pump load, leading to higher power demands and reduced reliability. Current drag reduction agents often worsen heat transfer performance. To overcome the contradiction between drag reduction and heat transfer deterioration, comb-type ternary block copolymers, hexadecyl methacrylate-co-dimethylaminoethyl methacrylate-co-methacrylic acid, have been designed and synthesized through photoinitiated polymerization and used as emulsifiers to prepare emulsified fuels. The emulsions with different compositions of JP-10 to water as 9.5:0.5, 9:1, 8.5:1.5, and 8:2, respectively, were characterized using creaming index analysis, dynamic light scattering and zeta potential measurements, rheological analysis, laser scanning confocal microscopy and polarized optical microscopy measurements, interfacial tension and interfacial film rheology measurements. A significant enhancement in heat sink and heat transfer coefficients of the emulsified fuel compared to pure JP-10 is observed within the temperature range from 100 to 225 °C. Simultaneous enhancements in drag reduction rate and heat transfer coefficient for the emulsified fuel in a distributed flow calorimeter can reach 19.5 % and 6.09 %, respectively. Emulsified fuels show great prospects in improving the stable and highly efficient operation of advanced aircraft.

高速碳氢燃料中的湍流增加了发动机阻力和泵负荷，导致更高的功率需求，降低了可靠性。目前的减阻剂往往恶化传热性能。为克服减阻与传热恶化之间的矛盾，通过光引发聚合，设计合成了梳状三元嵌段共聚物——甲基丙烯酸十六烷基-二甲基氨基乙基-甲基丙烯酸共聚物，并将其用作乳化剂制备乳化燃料。采用成乳指数分析、动态光散射和zeta电位测量、流变学分析、激光扫描共聚焦显微镜和偏振光学显微镜测量、界面张力和界面膜流变学测量等方法，对JP-10与水的配比分别为9.5:0.5、9:1、8.5:1.5和8:2的乳液进行了表征。在100 ~ 225℃的温度范围内，与纯JP-10相比，乳化燃料的热沉系数和传热系数显著增强。同时，乳化燃料在分布式流量量热计中的减阻率和换热系数分别提高了19.5%和6.09%。乳化燃料在提高先进飞机的稳定、高效运行方面具有广阔的应用前景。

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引用次数: 0

Influence of chain length and saturation on carboxylic acid pyrolysis mechanisms 链长和饱和度对羧酸热解机理的影响

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-16 DOI: 10.1016/j.fuproc.2025.108336

Bernardo A. Souto, Justice Asomaning, David C. Bressler

This study investigates radical-driven deoxygenation mechanisms during the non-catalytic pyrolysis of saturated and unsaturated carboxylic acids. Pyrolysis experiments were conducted at 410 °C, between 0.5 and 2 h, using carboxylic acids of varying carbon chain lengths (C6 to C18) and saturation levels, along with ketones. Feedstock conversion and deoxygenation products were quantified using GC–MS/FID for liquids and GC-TCD/FID for gases. Results demonstrated that carboxylic acid chain length significantly influences pyrolysis behavior, with significant differences in deoxygenation pathway linked to acid chain length and saturation level. Decarboxylation was the predominant pathway for short-chain carboxylic acids, whereas long-chain acids showed increased tendency towards decarbonylation. Short-chain saturated carboxylic acids favoured ketonic decarboxylation during the initial stages of pyrolysis, resulting in notable amounts of ketones and carbon dioxide. Subsequent decarbonylation of these ketones contributed to further deoxygenation, generating hydrocarbons and shorter-chain ketones via radical-driven mechanisms. In contrast unsaturated carboxylic acids underwent extensive cracking, which suppressed ketonic decarboxylation and led to reduced overall hydrocarbon yields. Additionally, mixed carboxylic acid feedstocks showed decreased conversion efficiencies, primarily due to limited intermolecular interactions necessary for effective ketonic decarboxylation. This work explores radical-driven, non-catalytic pyrolysis of fatty acids, providing a detailed mechanistic understanding of how chain length and saturation influence reaction pathway. The findings highlight key determinants of product selectivity and deoxygenation efficiency, providing valuable insights for optimizing feedstock compositions in pyrolysis-based sustainable biofuel production.

本研究探讨了饱和和不饱和羧酸非催化热解过程中自由基驱动的脱氧机制。热解实验在410°C， 0.5 ~ 2 h之间进行，使用不同碳链长度（C6 ~ C18）和饱和度的羧酸以及酮类。用GC-MS /FID和GC-TCD/FID分别对液体和气体的原料转化和脱氧产物进行定量。结果表明，羧酸链长度对热解行为有显著影响，羧酸链长度和饱和水平对脱氧途径有显著影响。短链羧酸的主要途径是脱羧，而长链羧酸的脱羧倾向增加。短链饱和羧酸在热解初期有利于酮脱羧，产生大量的酮和二氧化碳。随后这些酮类的脱碳作用促进了进一步脱氧，通过自由基驱动机制生成碳氢化合物和短链酮类。相反，不饱和羧酸发生了广泛的裂解，这抑制了酮脱羧，导致总烃收率降低。此外，混合羧酸原料的转化效率下降，主要是由于有效酮脱羧所必需的分子间相互作用有限。这项工作探索了自由基驱动的脂肪酸非催化热解，提供了链长和饱和度如何影响反应途径的详细机制理解。这些发现突出了产品选择性和脱氧效率的关键决定因素，为优化基于热解的可持续生物燃料生产中的原料组成提供了有价值的见解。

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引用次数: 0

Production of CO2-free hydrogen via catalytic methane decomposition over Ce-promoted Ni/Al2O3 catalysts ce促进的Ni/Al2O3催化剂催化甲烷分解制无co2氢

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-16 DOI: 10.1016/j.fuproc.2025.108338

Byung Sun Yoon , Ki Cheol Kim , Min-Jae Kim , Jae-Rang Youn , Mincheol Kim , Taesung Jung , Sang Goo Jeon , Woohyun Kim , Chang Hyun Ko

Catalytic methane decomposition (CMD) is a promising reaction for CO₂-free hydrogen production, as it generates no CO₂ emissions and produces solid carbon byproducts. However, catalyst deactivation due to carbon accumulation necessitates the development of catalysts with high activity, stability, and high capacity for carbon products. In this study, Ce-promoted Ni/Al₂O₃ catalysts were synthesized with varying Ce loadings to investigate the role of Ce in enhancing catalyst performance. The addition of Ce was found to weaken the interaction between Ni and Al₂O₃, thereby increasing the surface concentration of metallic Ni⁰ and improving catalytic activity. Nevertheless, excessive Ce loading resulted in performance deterioration, primarily due to a significant reduction in mesoporous volume. This loss of physical space limited the growth of carbon products and hindered catalyst effectiveness. The results highlight the need to balance the promotional effects of Ce with the preservation of pore structure to optimize catalyst design for CMD.

催化甲烷分解（CMD）是一种很有前途的无二氧化碳制氢反应，因为它不产生二氧化碳排放，只产生固体碳副产品。然而，由于碳积累导致催化剂失活，需要开发具有高活性、稳定性和高碳产物容量的催化剂。在本研究中，合成了不同Ce负载的Ce促进Ni/Al2O3催化剂，以研究Ce在提高催化剂性能方面的作用。Ce的加入减弱了Ni和Al2O3之间的相互作用，从而提高了金属Ni0的表面浓度，提高了催化活性。然而，过量的Ce载荷导致性能下降，主要是由于介孔体积的显著减少。这种物理空间的损失限制了碳产物的生长，阻碍了催化剂的有效性。研究结果表明，需要平衡Ce的促进作用和保持孔隙结构，以优化CMD催化剂的设计。

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引用次数: 0

Hydrothermal hydrodenitrogenation and hydrodesulfurization over nickel-based catalysts in sub/supercritical water 亚/超临界水中镍基催化剂的水热加氢脱氮和加氢脱硫

IF 7.7 2区工程技术 Q1 CHEMISTRY, APPLIED

Fuel Processing Technology

Pub Date : 2025-09-16 DOI: 10.1016/j.fuproc.2025.108332

Jie Zhang , Hulin Li , Hao Chen , Hong Zhang , Chuang Yang , Haobo Li

As an inherent by-product of the petroleum industry, oily sludge has substantial potential as energy resource due to its high oil content and calorific value. The hydrodenitrogenation/hydrodesulfurization of nitrogen/sulfur compounds quinoline and thiophene in oily sludge at sub/supercritical hydrothermal conditions was studied, along with its catalytic properties and reaction mechanism. The effects of nickel-based catalysts, hydrogen sources, and reaction conditions on hydrodenitrogenation (HDN) of quinoline were examined. A reaction kinetic model for quinoline in supercritical water was developed. An experimental investigation on hydrodesulfurization (HDS) of sulfur-containing thiophene was conducted, and the catalytic properties of nickel-based catalysts for simultaneous HDN and HDS of quinoline and thiophene were evaluated. Within 400–440 °C, ethanol was superior to formic acid as hydrogen source. Ni-Co/γ-Al₂O₃ had the most effective catalytic impact on denitrogenation of quinoline. The conversion efficiency of 5 wt% quinoline reached 94.67 %, while denitrogenation efficiency was 57.08 % at 24 MPa, 440 °C, and 60 min. The hydrogenation and ring-opening steps had significant effects on the overall denitrogenation process. The hydrodesulfurization catalysis from Ni-Mo/γ-Al₂O₃ was the most prominent for thiophene. At 24 MPa, 440 °C, and 60 min, the desulfurization efficiency of thiophene reached 57.34 %. Desulfurization of thiophene mainly followed the hydrogenation route, with thiophene rings being saturated before desulfurization occurred.

含油污泥作为石油工业的固有副产品，因其含油量高、热值高，具有巨大的能源潜力。研究了亚/超临界水热条件下含氮/含硫化合物喹啉和噻吩在含油污泥中的加氢脱氮/加氢脱硫及其催化性能和反应机理。考察了镍基催化剂、氢源和反应条件对喹啉加氢脱氮反应的影响。建立了喹啉在超临界水中的反应动力学模型。对含硫噻吩的加氢脱硫（HDS）进行了实验研究，并评价了镍基催化剂对喹啉和噻吩同时加氢脱硫和加氢脱硫的催化性能。在400 ~ 440℃范围内，乙醇作为氢源优于甲酸。Ni-Co/γ-Al2O3对喹啉脱氮的催化效果最好。在24 MPa、440℃、60 min条件下，5 wt%喹啉的转化率为94.67%，脱氮效率为57.08%。加氢和开环步骤对整个脱氮过程有显著影响。Ni-Mo/γ-Al2O3对噻吩的加氢脱硫催化作用最为显著。在24 MPa、440℃、60 min条件下，噻吩的脱硫效率可达57.34%。噻吩的脱硫主要采用加氢途径，脱硫前噻吩环被饱和。

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引用次数: 0