Transmission Electron Microscopic and X-ray Diffraction Based Study of Crystallographic Bibliography Demonstrated on Silver, Copper and Titanium Nanocrystals: State of the Art Statical Review
Md. Khalid Hossain Shishir, Sumaiya Islam Sadia, Shanawaz Ahmed, Allah Rakha Aidid, Md. Masud Rana, Md. Mehedi Hasan, Sazal Kumar, Raton Kumar Bishwas, Md. Ashraful Alam
Asian Journal of Applied Chemistry Research · pp. 1–19 · Published 14 May 2024
10.9734/ajacr/2024/v15i3287Abstract
This statistical review compares the crystallographic structures of functional nanocrystals composed of silver (Ag), copper (Cu) and titanium (Ti) using transmission electron microscopy (TEM) and X-ray diffraction (XRD) analyses. TEM provides high-resolution imaging to directly visualize individual nanoparticles' size, internal shape and crystallinity. Statistical analysis quantifies variations in lattice parameters, crystal structure, size distributions, phase compositions, lattice strains, preferred orientation and lattice volume of these three crystalline nanomaterials. The review highlights the complementary roles of TEM and XRD in comprehensive Ag, Cu and Ti nanocrystalline materials characterization. The crystallographic functional parameters of Ag were 2θ= 38.1° (111), 44.3° (200) and 64.4° (220); for Cu crystal 43.3° (111), 50.4° (200), 74.1° (220), 89.9° (311) and 95.1° (222) and 35.1° (100), 38.4° (002), 40.2° (101), 53.0° (102), 63.0° (103), 70.7° (110), 76.2° (112), 82.3° (201) demonstrated for Ti nanocrystals. The crystallographic predominant plane or Miller indices were also revealed by selected area electron diffraction (SAED) on TEM. The FCC structure of Ag and Cu is shown in larger lattice volumes compared to the HCP structure of Ti and prefer oriented. The degree of crystallinity of Ti, Cu and Ag nanocrystalline materials was observed at 90.0%, 98.0% and 100.0% respectively. This quantitative comparison provides valuable insights into the structural property relationships in these nanocrystals, enabling rational design strategies for optimizing their performance in various functional applications.
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