钴
X射线光电子能谱
化学工程
纳米棒
催化作用
化学计量学
热处理
纳米颗粒
离子交换
无机化学
化学
色散(光学)
羟基磷灰石
材料科学
纳米技术
离子
物理化学
有机化学
工程类
物理
光学
复合材料
钙
作者
Corentin Reynaud,Cyril Thomas,Dalil Brouri,Yannick Millot,Antoine Miche,Guylène Costentin
出处
期刊:Catalysis Today
[Elsevier]
日期:2024-03-06
卷期号:432: 114621-114621
被引量:4
标识
DOI:10.1016/j.cattod.2024.114621
摘要
Cobalt deposition in an excess of solution was used to design Co-modified hydroxyapatite materials with various Co loadings and controlled dispersion. It is rationalized how the properties of hydroxyapatite supports (more or less stoichiometric compositions, nanorod or platelet morphologies and crystalline (100) zig-zag termination or non-apatitic hydrated external layer), influence the immobilization processes of Co by operating either with slightly acidic (natural) or basic pH of the suspension media. Four cobalt immobilization mechanisms impacting the final dispersion of Co on hydroxyapatites were identified by combining structural (XRD, 1H and 31P solid-state NMR, UV-Vis, Raman and X-ray fluorescence spectroscopies), surface (XPS) characterizations of Co-modified hydroxyapatites after drying and thermal treatment at 500 °C, and monitoring of the pH and the composition of the supernatant solutions during the Co deposition step. On dried Co-modified crystalline stoichiometric hydroxyapatite nanorods, cobalt is highly dispersed through cationic exchange or strong electrostatic adsorption (SEA) at slightly acidic or basic pH, respectively. After thermal treatment at 500 °C, only cation exchange preserved atomic dispersion of Co(II) ions since Co3O4 nanoparticles were observed on samples for which Co deposition occurred via SEA. On defective hydroxyapatite platelets, cobalt deposited at acidic natural pH could diffuse in an external non-apatitic layer, whereas under basic pH media, this surface layer was hydrolysed, resulting in the formation of a cobalt-substituted hydroxyapatite layer in which only a limited fraction of the surface cobalt species could be probed by XPS.
科研通智能强力驱动
Strongly Powered by AbleSci AI