scholarly journals Chemical Reactivity Study of Anew of Suggested Chemotherapy Agent Using DFT

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Lekaa Husinsa Khdaim ◽  
Abbas A-Ali Draea
2020 ◽  
Vol 71 (10) ◽  
pp. 28-37
Author(s):  
Widia Sari ◽  
Hardoko Insan Qudus ◽  
Sutopo Hadi

Abstract: Chemical reactivity studies of the organotin(IV) carboxylates diphenyltin(IV) di-4-amino-benzoate (1) and triphenyltin(IV) 4-aminobenzoate (2) were conducted using cyclic voltammetry. Then, their antioxidant activities were tested by the 2,2-diphenyl-1-picrylshydrazyl (DPPH) method. Cyclic voltammetry was used to determine the kinetic constants of compounds 1 and 2 for the forward chemical reaction (kf). The constant values of the chemical reaction rate of 1 and 2 on cyclic voltammogram by experiment were obtained by comparing with the values from digital simulation methods obtained using Polar software 5.8.3. The results demonstrated that the constant value of the rate of the subsequent chemical reaction is a function of the rate of its potential (slope = kf/i); that is, 6.481 and 6.069 1/V for 1 and 2, respectively. The type of chemical reaction mechanism that occurs around the surface of the working electrode follows reaction mechanism of electrochemical reaction is quasi reversible and chemical reaction is irreversible (EqCi). The antioxidant activities of compounds 1 and 2 produced IC50 values of 5.91 and 12.57 ig/mL, respectively. These results indicate that both compounds are active as antioxidants. However, their antioxidant activities were lower than that of ascorbic acid, which has an IC50 value of 0.66 ig/mL.


2017 ◽  
Vol 56 (3) ◽  
Author(s):  
Mayra Avelar ◽  
Ana Martínez

The main goal of this investigation is to study the possible mechanisms of Casiopeinas® as anticancer agents. Electrodonating (χ-) and electroaccepting (χ+) electronegativity were calculated applying Density Functional Theory. Two different anticancer mechanisms of Casiopeínas® are proposed. There might be antiradical molecules preventing the formation of cancer cells or these molecules could reduce the amount of GSH and as a result over-produce free radicals, increasing the oxidative stress which in turn kills the cancer cells.


Author(s):  
A. M. Bradshaw

X-ray photoelectron spectroscopy (XPS or ESCA) was not developed by Siegbahn and co-workers as a surface analytical technique, but rather as a general probe of electronic structure and chemical reactivity. The method is based on the phenomenon of photoionisation: The absorption of monochromatic radiation in the target material (free atoms, molecules, solids or liquids) causes electrons to be injected into the vacuum continuum. Pseudo-monochromatic laboratory light sources (e.g. AlKα) have mostly been used hitherto for this excitation; in recent years synchrotron radiation has become increasingly important. A kinetic energy analysis of the so-called photoelectrons gives rise to a spectrum which consists of a series of lines corresponding to each discrete core and valence level of the system. The measured binding energy, EB, given by EB = hv−EK, where EK is the kineticenergy relative to the vacuum level, may be equated with the orbital energy derived from a Hartree-Fock SCF calculation of the system under consideration (Koopmans theorem).


Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.


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