Lebedev Alexander A, Davydov Sergey Yu, Eliseyev Ilya A, Roenkov Alexander D, Avdeev Oleg, Lebedev Sergey P, Makarov Yurii, Puzyk Mikhail, Klotchenko Sergey, Usikov Alexander S
Solid State Electronic Department, Ioffe Institute, St. Petersburg 194021, Russia.
Solid State Physics Department, Ioffe Institute, St. Petersburg 194021, Russia.
Materials (Basel). 2021 Jan 27;14(3):590. doi: 10.3390/ma14030590.
This work is devoted to the development and optimization of the parameters of graphene-based sensors. The graphene films used in the present study were grown on semi-insulating 6H-SiC substrates by thermal decomposition of SiC at the temperature of ~1700 °C. The results of measurements by Auger and Raman spectroscopies confirmed the presence of single-layer graphene on the silicon carbide surface. Model approach to the theory of adsorption on epitaxial graphene is presented. It is demonstrated that the Green-function method in conjunction with the simple substrate models permit one to obtain analytical results for the charge transfer between adsorbed molecules and substrate. The sensor structure was formed on the graphene film by laser. Initially, a simpler gas sensor was made. The sensors developed in this study demonstrated sensitivity to the NO concentration at the level of 1-0.01 ppb. The results obtained in the course of development and the results of testing of the graphene-based sensor for detection of protein molecules are also presented. The biosensor was fabricated by the technology previously developed for the gas sensor. The working capacity of the biosensor was tested with an immunochemical system constituted by fluorescein and monoclonal antibodies (mAbs) binding this dye.
这项工作致力于基于石墨烯的传感器的参数开发和优化。本研究中使用的石墨烯薄膜是通过在约1700℃的温度下对SiC进行热分解而在半绝缘6H-SiC衬底上生长的。俄歇光谱和拉曼光谱的测量结果证实了碳化硅表面存在单层石墨烯。提出了外延石墨烯吸附理论的模型方法。结果表明,格林函数方法与简单的衬底模型相结合,可以得到吸附分子与衬底之间电荷转移的解析结果。通过激光在石墨烯薄膜上形成传感器结构。最初,制作了一个更简单的气体传感器。本研究开发的传感器对1-0.01 ppb水平的NO浓度表现出灵敏度。还展示了在开发过程中获得的结果以及基于石墨烯的蛋白质分子检测传感器的测试结果。生物传感器是通过先前为气体传感器开发的技术制造的。使用由荧光素和结合该染料的单克隆抗体(mAb)组成的免疫化学系统对生物传感器的工作能力进行了测试。