梁强， 刘姝， 李小龙， 颜翠平， 林龙沅

西南科技大学 环境与资源学院，固体废物处理与资源化教育部重点实验室， 四川 绵阳 621010

引用格式：

梁强， 刘姝， 李小龙， 等. 对喷式流化床气流磨中活性炭粒径调控及颗粒输运特性［J］. 中国粉体技术， 2027， 33（3）： 1-14.

Liang Qiang， Liu Shu， Li Xiaolong， et al. Particle size regulation and particle transport characteristics of activated carbon in opposed⁃jet fluidized⁃bed jet mills［J］. China Powder Science and Technology， 2027， 33（3）： 1-14.

DOI：10.13732/j.issn.1008-5548.2027.03.014

收稿日期： 2026-06-20， 修回日期： 2026-08-24， 上线日期： 2026-11-网上出版日期:12。

基金项目： 国家自然科学基金项目，编号：52463026；四川省科技计划项目，编号：2024ZHCG0121

第一作者： 梁强（1999—），男，硕士生，研究方向为安全技术。E-mail：18323397489@163.com。

通信作者： 颜翠平（1981—），女，副教授，博士，硕士生导师，研究方向为工业通风与除尘， 大气污染控制技术及装备研究等。E-mail：13795774342@139.com。

摘要： 【目的】 针对植物类超级电容器用活性炭（plant⁃derived activated carbon for supercapacitors， PAC）气流粉碎分级过程中粒径调控和颗粒输运机制，开展对喷式流化床气流磨粉碎分级工艺优化及流场特性分析。【方法】 以生物质基活性炭为原料，系统考察分级轮转速、引风机频率和喷嘴进气压力对成品粒径分布及比表面积的影响；在较优实验工况基础上建立三维数值模型，采用剪切应力输运k-ω湍流模型和离散相模型（discrete phase model，DPM）分析不同分级轮转速下分级区速度场和颗粒浓度分布规律。【结果】 当喷嘴进气压力为0.6 MPa、分级轮转速为7 200 r/min、引风机频率为20 Hz时，所得PAC粒径与比表面积满足国家应用要求，比表面积由876 m²/g增大至1 021.37 m²/g，增幅约为16.59%。分级轮转速由3 000 r/min提高至7 200 r/min，分级轮轴向气流整体呈现上升趋势，叶片周围颗粒分布由局部富集逐渐转变为分级轮外缘连续环状分布，分级区速度场对称性增强；分级轮转速继续提高至8 000 r/min时，过强离心作用使颗粒外缘滞留和回流加剧，不利于稳定出料。【结论】 对喷式流化床气流磨能够在射流粉碎、离心分级和粗颗粒回流的连续耦合作用下实现PAC粒径调控和比表面积提升。

关键词： 活性炭； 流化床； 粒度分布； 粉碎分级； 两相流； 数值模拟； 颗粒过程； 分级轮转速

Abstract

Objective Plant-derived activated carbon for supercapacitors （PAC） requires an appropriate particle size distribution and sufficient specific surface area to ensure slurry dispersion， coating uniformity， and subsequent application performance. In an opposed-jet fluidized-bed jet mill， high-speed jet milling， centrifugal classification， axial conveying， and coarse-particle recirculation occur simultaneously， making it difficult to fully reveal the mechanisms of particle size regulation and particle transport through experiments alone. This study aims to optimize the jet-milling and classification process parameters of PAC by using biomass-based activated carbon as the feedstock， with emphasis on analyzing the effects of classifier wheel speed on airflow structure and particle transport stability in the classification zone.

Methods A staged single-factor experimental method was adopted to investigate the effects of classifier wheel speed， induced-draft fan frequency， and nozzle inlet pressure on the particle size distribution and specific surface area of PAC. D₁₀， D₅₀， D₉₀， and D₁₀₀ were used to characterize the particle size features. The experimental system mainly consisted of two opposed Laval nozzles， a centrifugal classifier wheel， a pleated cartridge dust collector， a product collection device， and a centrifugal induced-draft fan. Based on the relatively optimal experimental conditions， a three-dimensional numerical model of the opposed-jet fluidized-bed jet mill was established using ANSYS Fluent. The shear-stress-transport （SST） k-ω turbulence model was used to describe the continuous gas phase， and the discrete phase model （DPM） was used to track particle motion and concentration distribution. In the numerical simulation， the nozzle inlet pressure and outlet diameter were fixed at 0.6 MPa and 3 mm， respectively. The classifier wheel speeds were set to 3 000， 4 800， 6 000， 7 200， and 8 000 r/min， and the particle size range was set to 0.217-27.7 μm. Velocity streamlines， cross-sectional streamlines， axial and tangential velocity distribution， and DPM particle concentration fields were analyzed to characterize the coupling between centrifugal classification and axial conveying.

Results and Discussion Classifier wheel speed had the most significant effect on coarse-particle retention and recirculation for further milling. Increasing the classifier wheel speed generally reduced D₁₀， D₅₀， D₉₀， and D₁₀₀， although the benefit of further increasing the speed for particle refinement gradually diminished at high speeds. Increasing the induced-draft fan frequency strengthened axial suction and particle conveying， but excessively strong negative-pressure suction shortened the effective residence time of particles in the milling and classification zones， causing some insufficiently milled coarse particles to enter the collection system prematurely. The effect of nozzle inlet pressure on medium and coarse particle fractions was non-monotonic. At low to intermediate pressures， increased gas flow rate and axial drag enhanced particle transport， while the jet energy was still insufficient for complete deagglomeration and breakage. At higher pressures， relative velocity， collision intensity， and shear increased， and particle deagglomeration and breakage gradually became dominant. Under the relatively optimal operating conditions of 0.6 MPa nozzle inlet pressure， 3 mm nozzle outlet diameter， 7 200 r/min classifier wheel speed， and 20 Hz induced-draft fan frequency， the D₁₀， D₅₀， and D₉₀ of the obtained PAC were 2.39， 6.42， and 16.75 μm， respectively. Its specific surface area increased from 876 m²/g of the raw material to 1 021.37 m²/g， representing an increase of approximately 16.6%. This indicated that jet milling and classification promoted particle refinement， aggregate deagglomeration， and exposure of effective surface area. Numerical simulation results showed that classifier wheel speed substantially altered the flow-field structure in the classification zone. At 3 000 and 4 800 r/min， pronounced streamline deflection， local backflow， and axial-velocity fluctuations occurred near the classifier inlet and the transition between the milling and classification zones， indicating insufficient upward-flow induction at low speeds and unstable particle transport. When the speed increased to 6 000 r/min， streamline continuity improved and circumferential flow became better developed. At 7 200 r/min， the flow formed a relatively continuous spiral upward structure from the milling zone to the classification zone. The circumferential streamlines around the classifier wheel became more complete， the axial velocity increased steadily， and the tangential velocity distribution was comparatively uniform. These characteristics indicated favorable coordination between centrifugal classification and axial conveying. DPM particle concentration results further showed that， with increasing wheel speed， particle distribution evolved from local enrichment to circumferential enrichment and then to a continuous annular concentration band. At 7 200 r/min， particles formed a continuous annular distribution at the outer edge of the classifier wheel and were transported relatively uniformly along the blade passages， suggesting stable feeding， classification， and fine-particle discharge. When the speed was further increased to 8 000 r/min， excessive tangential centrifugal effect drove high-concentration particles toward the wheel rim and near-wall regions， while the particle concentration in the central region decreased. Particle retention， backflow， and circulating load therefore increased， showing that simply increasing the classifier wheel speed could not continuously improve classification performance.

Conclusion Stable PAC milling and classification in an opposed-jet fluidized-bed jet mill are governed by the coordinated action of jet milling， centrifugal classification， and axial airflow conveying rather than by any single operating parameter. An appropriate classifier wheel speed provides sufficient centrifugal action to retain coarse particles while maintaining stable transport of fine particles toward the interior of the classifier wheel and the outlet. Excessively high speed shifts the balance toward centrifugal retention， suppressing the passage of fine particles， and aggravates particle accumulation and recirculation near the wheel rim. The agreement between experimental results and CFD-DPM simulation results shows that a dynamic balance between centrifugal classification capacity and axial conveying capacity is essential for improving the stability of PAC particle size regulation and the classification performance of fine powder. These findings provide a theoretical basis for optimizing the operating parameters of opposed-jet fluidized-bed jet mills and for the continuous PAC preparation.

Keywords： activated carbon； fluidized bed； particle size distribution； milling and classification； two-phase flow； numerical simulation； particle processing； classifier wheel speed

参考文献（References）

［1］Hu Xiaohong， Liu Xiaojing， Li Bo， et al. Research progress on nickel-based materials in supercapacitors：a review of electrode materials and device properties［J］.Small，026，22（8）：e12830.

［2］Anjana P M， Aminabhavi T M. Supercapattery： energy storage devices combining functionalities of battery electrodes and supercapacitor electrodes［J］.Journal of Energy Storage，2025，134：118265.

［3］Simon P， Gogotsi Y. Materials for electrochemical capacitors［J］.Nature Materials，2008，7（11）：845-854.

［4］Radhakrishnan K， Kumar A. Advances and challenges in biomass-derived supercapacitors［J］.Renewable and Sustainable Energy Reviews，2026，229：116624.

［5］Abimana C， Bello A， Machunda R， et al. Understanding the factors influencing the properties of biomass-derived porous carbon and their impacts on electrical double-layer capacitor electrodes：a comprehensive review［J］.Journal of Renewable Energy，2024，2024：1343256.

［6］GB/T 37386—2019 超级电容器用活性炭［S］.

GB/T 37386—2019 Activated carbon for supercapacitor ［S］.

［7］Rennie A J R， Martins V L， Smith R M， et al. Influence of particle size distribution on the performance of ionic liquid-based electrochemical double layer capacitors［J］. Scientific Reports， 2016， 6： 22062.

［8］Kong Mengran， Tian Xiao， Wang Yu， et al. Effects of rotational speed of the classifying wheel during jet milling on magnetic properties and thermal stability of sintered Nd-Fe-B magnets［J］. Journal of Magnetism and Magnetic Materials， 2024， 606： 172382.

［9］Wang Lidong， Li Xiaoqiang， Gao Fei， et al. Effects of jet milling pretreatment and esterification with octenyl succinic anhydride on physicochemical properties of corn starch［J］. Foods， 2022， 11（18）： 2893.

［10］Xu Zhonghui， Hu Dan， An Ran， et al. Preparation of superfine and semi-hydrated flue gas desulfurization gypsum powder by a superheated steam powdered jet mill and its application to produce cement pastes［J］. Case Studies in Construction Materials， 2022， 17： e01549.

［11］Zhang Quanchao， Huang Dajian， Zhang Xiaopeng， et al. Improving the properties of metakaolin/fly ash composite geopolymers with ultrafine fly ash ground by steam-jet mill［J］. Construction and Building Materials， 2023， 387： 131673.

［12］顾毅楠， 吴永泽， 俞建峰， 等. 涡流空气分级机补气结构设计及流场仿真［J］. 中国粉体技术， 2024， 30（5）： 158-170.

Gu Yinan， Wu Yongze， Yu Jianfeng， et al. Air supply structure design and flow field simulation of turbo air classifier［J］. China Powder Science and Technology， 2024， 30（5）： 158-170.

［13］Bagherzadeh A， Darbandi M， Barezban M B. Numerical simulation of particle separation in a two-phase flow passing through a vortex-based air classifier using Eulerian-Lagrangian DDPM approach［J］. Powder Technology， 2024， 445： 120036.

［14］Wang Zhiyuan， Yang Huandi， Sun Zhanpeng， et al. Structure optimization of rotor cage blades for turbo air classifier based on entropy production analysis［J］. Advanced Powder Technology， 2023， 34（8）： 104103.

［15］Liu Kerun， Yu Yuan. Establishment of particle motion model and study of particle volume fraction distribution in the turbo air classifier based on DSMC［J］. Powder Technology， 2025， 449： 120371.

［16］Varaksin A Y， Ryzhkov S V. Mathematical modeling of gas-solid two-phase flows： problems， achievements and perspectives ：a review［J］. Mathematics， 2023， 11（15）： 3290.

［17］Zhou Youhang， Zou Xin， Ma Zhuxi， et al. Numerical simulation study of a pusher feed classifier based on RNG-DPM method［J］. Processes， 2024， 12（6）： 1151.

［18］Sun Zhanpeng， Liang Longlong， Liu Chunyu， et al. CFD simulation and performance optimization of a new horizontal turbo air classifier［J］. Advanced Powder Technology， 2021， 32（4）： 977-986.

［19］Yang Xiaolian， Xi Te， Qin Yebo， et al. Computational fluid dynamics-discrete phase method simulations in process engineering： a review of recent progress［J］. Applied Sciences， 2024， 14（9）： 3856.

［20］Huang Shenglong， Yin Xixi， Wang Huan， et al. Improving the energy conversion efficiency between airflow and particles in fluidized bed opposed jet mill via a composite nozzle： experiments and simulations［J］. Chemical Engineering Journal， 2025， 512： 162486.

［21］Menter F R. Two-equation eddy-viscosity turbulence models for engineering applications［J］. American Institute of Aeronautics and Astronautics Journal， 1994， 32（8）： 1598-1605.

［22］Shooshtari S H R， Walther J H， Wen C. Combination of genetic algorithm and CFD modelling to develop a new model for reliable prediction of normal shock wave in supersonic flows contributing to carbon capture［J］. Separation and Purification Technology， 2023， 309： 122878.

［23］Hamaidia W， Yahiaoui T， Sellam M. CFD investigation of supersonic two parallel expansions nozzles［J］. Advances in Space Research， 2025， 75（2）： 2378-2390.

［24］Zhao B， Su Y， Zhang J. Simulation of gas flow pattern and separation efficiency in cyclone with conventional single and spiral double inlet configuration［J］. Chemical Engineering Research and Design， 2006， 84（12）： 1158-1165.

［25］Muschelknautz E. Die berechnung von zyklonabscheidern für gase［J］. Chemie Ingenieur Technik， 1972， 44（1/2）： 63-71.

［26］Shen Lingling， Jiang Xiao， Liu Xuedong， et al. Research on the grinding process of superhard particles in the fluidized bed opposed jet mill based on the CFD-DEM methodology［J］. Minerals， 2024， 14（4）： 437.

［27］Huang Long， Yuan Jiale， Pan Miao， et al. CFD simulation and parameter optimization of the internal flow field of a disturbed air cyclone centrifugal classifier［J］. Separation and Purification Technology， 2023， 307： 122760.