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Physical Methods for Characterizing Solids
Published in Elaine A. Moore, Lesley E. Smart, Solid State Chemistry, 2020
It is now standard academic practice to deposit final published structures and their data in a crystallographic database, of which there are several: the Cambridge Structural Database, CSD (for small organic and organometallic molecules); the Inorganic Crystal Structure Database, ICSD, the Crystallographic Open Database, COD; CRYSTMET for metals and alloys; the Protein Data Bank, PDB; and the Nucleic Acid Database, NDB. These databases check the deposited structure and its data through their own software to ensure internal consistency.
Large Dataset Electron Diffraction Patterns for the Structural Analysis of Metallic Nanostructures
Published in Alina Bruma, Scanning Transmission Electron Microscopy, 2020
Arturo Ponce, José Luis Reyes-Rodríguez, Eduardo Ortega, Prakash Parajuli, M. Mozammel Hoque, Azdiar A. Gazder
The electron diffraction under the illumination modes previously mentioned have been used extensively to study the structure of materials, to measure the strain, and to compare texture-related information of different size and ranges of materials (Matsui and Tabata 2012). (Sang, Kulovits and Wiezorek 2013) Electron diffraction in TEM has several advantages compared with analogue diffraction methods, neutrons, and x-rays. One important advantage is the use of lenses to produce an image of the analyzed region at subnanometric resolution. In fact, the imaging methods in TEM are directly related to the diffraction, for instance, the diffraction contrast mode can produce bight-field (BF) and dark-field (DF) images. By tilting the specimen and exciting a reflection in the DP, one can reach the two-beam conditions to characterize structural defects such as dislocations, grain boundaries, stacking faults, and precipitations. In this way, electron diffraction combined with the power of magnification of the microscope has the advantage that is not found in other diffraction method. Convectional electron DPs are registered without alteration of the specimen, if the material is not sensitive to be damaged by the high energy of the incident beam. When the sample is stable the electron pattern does not change over time, the electron beam interacts permanently with the specimen and can be considered static because the deflector coils in the column of the microscope do not deflect the beam. Under these conditions, the electron beam is not called “dynamic” if full automation is not performed; therefore, the data collection, indexing, and graphic interpretation must be performed separately. The results are postanalyzed by using the crystallographic database by modeling and simulating the structure using computational tools that finally will be correlated with the experimental data collected. An automatic analysis and data collection are necessary for special requirements of the specimen. The collection of large dataset electron DPs arises from the special requirements of the specimen, such as the reduction of the radiation damage, the analysis of crystals in a polycrystalline material, and the characterization of individual nanoparticles dispersed in a film. A fully reproducible and systematic analysis over wide ranges would require a traceable scanning probe to allow pixel correlation. Over the past years, a combination of software and instrumentation has been developed to fulfill this objective (Darbal et al. 2013; Viladot et al. 2013). These approaches can be divided into three categories: (1) using the microscope lenses, (2) using a spherical-aberration-corrected system (Cs-Corr), and (3) using additional hardware.
Silver nanoparticles decorated graphene oxide nanocomposite for bone regeneration applications
Published in Inorganic and Nano-Metal Chemistry, 2020
Cuilan An, Pan Hao, Huilian Li, Bahman Nasiri-Tabrizi
The morphological features of GO and AgNPs-GO nanocomposite were analyzed with a HITACHI SU8000 Field Emission Scanning Electron Microscope (FESEM) with an accelerating voltage of 5.0 KV. It was equipped with an Energy Dispersive X-ray Spectrometry (EDS) analyzer to assess the elemental composition and also to determine the spatial distribution of elements in the specimens using elemental mapping mode. A High-Resolution Transmission Electron Microscope (HRTEM-FEIG-4020) with an accelerating voltage of 500 KV was also used to assess the structural features of the composite. XRD studies were executed using a PANalytical’s Empyrean using Cu‒Kα (λ = 1.54056°A) at 30 kV and 35 mA over a two-theta range of 10 to 80°, in which the observed XRD profiles were compared with the I the Joint Committee on Powder Diffraction and Standards (JCPDS) crystallographic database. Raman spectroscopy analysis was executed using a Renishaw inVia Raman microscope with 20 mW of 514 nm laser at room temperature. The reaction energy plots for an AgNO3‒GO closed system was also provided to determine the normalized reaction energy of the interface as a function of molar fraction x of the reactants in the system.
Collective variables for the study of crystallisation
Published in Molecular Physics, 2021
Tarak Karmakar, Michele Invernizzi, Valerio Rizzi, Michele Parrinello
The crystal structures of NaCl and CO were taken from the crystallographic database. The unit cells were replicated to generate the supercells using the AVOGADRO software [45]. In the subsequent step, the supercells were minimised and thermally equilibrated in constant temperature simulations. The corresponding liquid phases were obtained by melting the crystal at a temperature higher than their respective melting temperatures and afterward cooling down to the desired value.
Electrochemical corrosion behaviour of Sn–Sb solder alloys: the roles of alloy Sb content and type of intermetallic compound
Published in Corrosion Engineering, Science and Technology, 2021
Marcelino Dias, Nathália C. Verissimo, Natal N. Regone, Emmanuelle S. Freitas, Noé Cheung, Amauri Garcia
The phases forming the microstructures of the Sn–Sb alloys were characterised by X-ray diffraction with Cu-Kα radiation. The resulting XRD patterns (Figure 3), show that the Sn(β) and the SnSb phases constitute the microstructural phases of both the Sn–2wt-%Sb and Sn–5.5wt-%Sb alloys samples, whereas the Sn(β), SnSb and the Sn3Sb2 phases form the microstructure of Sn–10wt-%Sb alloy sample. These XRD patterns were associated with a crystallographic database – the Inorganic Crystal Structure Database–ICSD [25]. In a previous study [17], which confirmed the occurrence of such IMCs despite the contradictions existing in the literature with respect to their compositions. In the present investigation, more detailed diffractogram data were obtained using a detector with higher resolution than that of reference [17], which has been employed with the aim to identifying the presence of the IMCs previously reported in the literature. Figure 3 shows peaks related to the XRD data of α-Sn and β-Sn phases, reported with a cubic and tetragonal crystal structure, respectively. The α-Sn phase shows a Fd-3 ms space group and lattice parameters a = b = c = 6.489 Å [26], while the β-Sn phase shows a I 41 / a m d s space group and lattice parameters a = b = 5.831 Å, and c = 3.182 Å [27]. The β-Sn or (Sn)rt phase is formed by a peritectic reaction described as: L + Sn3Sb2 ↔ (Sn)rt at 243°C giving rise to the (Sn)lt phase or the so-called α-Sn phase through the (Sn)rt ↔ (Sn)lt reaction at 13°C [28]. Although considerable intensity peaks associated with the α-Sn phase in Figure 3(a–c), they are insufficient to assign this phase since only a single peak was detected for each alloy sample. In addition, the samples have not undergone temperatures below 13°C and it is reported that the addition of antimony suppress the (Sn)rt ↔ (Sn)lt transformation [29].