This work introduces a newly synthesized triazole derivative, 5-([(2-furanyl)methyl]-thiomethyl)-4-(naphtha-2-yl)-3-hydroxyl-4H-1,2,4-triazole (FTNT), as an effective corrosion inhibitor for carbon steel A106 G/B in 0.1 M HCl solution. The structure of the novel derivative was confirmed by FTIR, 1 H NMR, and 13 C NMR spectra. Potentiodynamic polarization measurements reveal that FTNT markedly suppresses corrosion, with inhibition efficiency reaching 81.6% at 600 ppm. Thermodynamic analysis indicates spontaneous, physisorption/chemisorption-augmented adsorption of FTNT on the steel surface, best described by the Freundlich isotherm. Atomic force microscopy (AFM) surface examination demonstrated that a protective FTNT coating precipitated on the metal surface. The experimental findings are corroborated by complementary density functional theory calculations at the B3LYP/6-311++G (d, p) level, which demonstrate advantageous electronic properties and adsorption propensity that are correlated with high inhibitory efficiency. The results provide molecular-level insight into the rational design of triazole-based corrosion inhibitors, and FTNT represents a focused, well-characterized inhibitor with practical potential to reduce carbon steel corrosion in acidic settings.
Hydrate dissociation equilibrium conditions for carbon dioxide + methane with water, nitrogen + methane with water and carbon dioxide + nitrogen with water were measured using cryogenic sapphire cell. Measurements were performed in the temperature range of 275.75 K–293.95 K and for pressures ranging from 5 MPa to 25 MPa. The resulting data indicate that as the carbon dioxide concentration is increased in the gas mixture, the gas hydrate equilibrium temperature increases. In contrast, by increasing the nitrogen concentration in the gas mixtures containing methane or carbon dioxide decreased the gas hydrate equilibrium temperatures. Furthermore, the cage occupancies for the carbon dioxide + methane system were evaluated using the Van der Wa
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Ternary semiconductors AB5C8 (A = Cu/Ag, B = In and C = S, Se or Te) have been investigated. The CuIn5S8 and AgIn5S8 have been synthesize in cubic spinel structure with space group (Fd3m), whereas CuIn5Se8, AgIn5Se8, CuIn5Te8 and AgIn5Te8 have tetragonal structures with space group P-42m. The relaxed crystal geometry, electrical properties such as electronic band structure and optoelectronic properties are predicted by using full potential method in this work. For the determination of relaxed crystal geometry, the gradient approximation (PBE-GGA) is used. All the studied compounds are semiconductors based on their band structures in agreement with the experimental results, and their bulk moduli are in the range 35 to 69 GPa. Wide absorption
... Show MoreThe performance quality and searching speed of Block Matching (BM) algorithm are affected by shapes and sizes of the search patterns used in the algorithm. In this paper, Kite Cross Hexagonal Search (KCHS) is proposed. This algorithm uses different search patterns (kite, cross, and hexagonal) to search for the best Motion Vector (MV). In first step, KCHS uses cross search pattern. In second step, it uses one of kite search patterns (up, down, left, or right depending on the first step). In subsequent steps, it uses large/small Hexagonal Search (HS) patterns. This new algorithm is compared with several known fast block matching algorithms. Comparisons are based on search points and Peak Signal to Noise Ratio (PSNR). According to resul
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
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The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ
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