生物质灰对K+和NH4+吸附行为的分子模拟研究OA
Molecular simulation study on adsorption behavior of K⁺ and NH4+ by biomass ash
为揭示生物质灰对铵根离子(NH4+)和钾离子(K⁺)的吸附机制,采用实验表征与分子模拟方法系统分析了灰分中主要矿物组分与两类离子的相互作用机理.通过X射线衍射(XRD)和X射线荧光光谱(XRF)分析确定生物质灰的主要矿物组成为氧化铁(Fe₂O₃)、二氧化硅(SiO₂)、氧化铝(Al₂O₃)、钾长石(KAlSi₃O₈)和钠长石(NaAlSi₃O₈).基于Materials Studio软件,采用Forcite模块进行分子动力学(MD)模拟,采用DMol³模块进行量子化学(DFT)计算.模拟结果显示,静电势分布与径向分布函数(RDF)分析表明,离子主要吸附于矿物表面带负电的氧原子附近,其中钾长石和钠长石的吸附能力较弱.电子密度分布结果表明K⁺吸附以物理吸附为主,而NH4+则可能存在化学吸附行为.相互作用能计算结果显示,K⁺的吸附能力依次为Al2O3>Fe2O3>SiO2,NH4+的吸附能力依次为Fe2O3>Al2O3>SiO2.
To elucidate the adsorption mechanisms of ammonium(NH4+)and potassium(K+)ions by biomass ash,a combined approach of experimental characterization and molecular simulation was employed.X-ray diffraction(XRD)and X-ray fluorescence(XRF)analyses revealed that the primary mineral components of the biomass ash are ferric oxide(Fe2O3),silicon dioxide(SiO2),aluminum oxide(Al2O3),orthoclase(KAlSi3 O8),and albite(NaAlSi3 O8).Based on the Materials Studio software,molecular dynamics simulations were performed using the Forcite module,and quantum chemical calculations were carried out using the DMol3 module.Simulation results indicate that NH4+and K+ions preferentially adsorb near negatively charged oxygen atoms on the mineral surfaces,as revealed by electrostatic potential distributions and radial distribution function(RDF)analysis.Orthoclase and albite exhibit relatively weak adsorption capacity.Electron density distribution results indicate that K+adsorption is primarily physical,while NH4+may exhibit chemical adsorption.Interaction energy calculations indicate that the adsorption affinity of K+follows the order:Al2 O3>Fe2 O3>SiO2,whereas that of NH4+follows:Fe2 O3>Al2 O3>SiO2.
潘朔;顾子扬;冯亚兵;王擎;柏静儒;孟欣;李全杰
东北电力大学能源与动力工程学院,吉林 吉林 132012东北电力大学能源与动力工程学院,吉林 吉林 132012东北电力大学能源与动力工程学院,吉林 吉林 132012东北电力大学能源与动力工程学院,吉林 吉林 132012东北电力大学能源与动力工程学院,吉林 吉林 132012华能吉林发电有限公司,吉林 长春 130012华能吉林发电有限公司,吉林 长春 130012
能源科技
生物质灰分子模拟钾离子铵根离子吸附微尺度
biomass ashmolecular simulationpotassium ionammonium ionadsorptionmicroscale
《化工学报》 2026 (3)
1485-1495,11
中国华能集团有限公司科技项目(HNKJ23-HF54)吉林省科技发展计划项目(20250203007SF)
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