Study On Nanomechanical Properties Of Transitional And Non-transitional Chalcogenides

In recent years,the unique layered structure and electrical properties of graphene have made it the focus of research at home and abroad.Because graphene is a zero bandgap material,it greatly limits its application in optics and electricity.With the rapid development of graphene research and the continuous innovation of material preparation technology,the research process of other related materials with similar two-dimensional layered structure features has been greatly promoted.In laboratory research,mechanical peeling is the most common and most convenient method for preparing two-dimensional materials.However,due to the strong randomness of mechanical peeling,small peeling of the peeling layer and uneven thickness,it is necessary to further improve the peeling technology and the stripping method.After the second stripping,further identification of the thickness of the two-dimensional material is also an urgent problem to be solved.The use of instrument identification is relatively complicated and expensive,so it is necessary to develop a method for quickly and accurately identifying the number of layers of the two-dimensional material.Among the many outstanding properties of two-dimensional materials,the mechanical properties of two-dimensional materials play an important role in manufacturing,integration and devices and their potential applications.And the coupling between mechanical and other physical properties?thermal,electrical,optical?makes sense for exploring new applications.Therefore,this paper proposes a machine learning solution from the improvement of stripping technology and the identification of different two-dimensional material thickness on different substrates,and in the exploration of the emerging two-dimensional material mechanical properties,using the substrate-free suspension method for indium selenide Materials are studied,the specific contents are as follows:1.In the traditional mechanical stripping process,the plasma cleaning machine is added to clean the substrate and the sample is transferred to the substrate to perform constant temperature heating and the exhaust pressure control film has two key steps,such as internal and external pressure difference,which greatly improves the stripping efficiency and the thin layer rate of the sample.Taking the transition metal chalcogenide MoS₂ and the non-transition metal InSe as an example,adding a plasma cleaner to clean the substrate facilitates removal of gas molecules adsorbed on the surface of the substrate,and the heating and cooling process facilitates the removal of air between the sample and the substrate to increase the sample and the substrate Contact area to improve the quality of peeling.The results show that the improved stripping method significantly increases the stripped sample area as well as the thin layer rate.The improved method has a significant improvement in the success rate of the peeling transition and the non-transition metal compound,and can be further extended to other two-dimensional materials,so that the range of the stripping object is greatly increased,which is conducive to the further development and research of other two-dimensional materials.2.In the traditional method of identifying two-dimensional?2D?materials,we develop a machine learning method based on k-means clustering and nearest neighbor algorithm test?k-NN?,through Red-Green-Blue RGB values to Classify and identify the thickness of different 2D materials.First,based on the Fresnel's law of reflection model,we successfully established the layer number and base thickness of the two-dimensional material,optical wavelength,optical contrast?Optical Contrast-OC?,RGB and optical color difference?Tole Color Difference-TCD?.Based on the relationship between RGB values,A machine learning method based on k-means clustering and k-NN nearest neighbor algorithm is developed.Graphene and MoS₂ are used as examples on SiO₂/Si substrates.This method can quickly and accurately identify the thickness of two-dimensional materials in thin layers,and avoids the damage of samples and the use of expensive instruments.It is suitable for various 2D materials and The substrate lays the foundation for the identification of other 2D materials and provides a new idea for 2D material identification.3.The mechanical properties of different layers of indium selenide?InSe?in the emerging two-dimensional material were studied experimentally,and the Young's modulus of the material was found to decrease with increasing thickness.We used an atomic force microscopy?AFM?-based suspended baseless method to measure the Young's modulus and fracture strength of the multilayer two-dimensional material InSe?>5 L?to 101.37±17.93GPa and 8.68 GPa,respectively,combined with continuous medium.Volume analysis and finite element calculations fit the experimental curve very well.It is also found that the Young's modulus of InSe decreases with increasing thickness,which we speculate may be due to slight sliding between the layers.Secondly,according to the research results,the two-dimensional InSe is softer than most two-dimensional materials,and its breaking strength is higher than that of carbon fiber,but it is more flexible and is an ideal material for flexible electronic applications.