In this work pyrazolin derivatives were prepared from the diazonium chloride salt of 4-aminobenzoic acid. Azo compounds were prepared from the reaction of an ethanolic solution of sodium acetate and calculated amount of active methylene compound namely, acetyl acetone to obtain the corresponding hydrazono derivative (1). Cyclocondensation reaction of compounds (1) with hydrazine hydrate and phenyl hydrazine in boiling ethanol affording the corresponding pyrazoline-5-one derivatives of 4-aminobenzoic acid (2,3). Then compound (3) was reacted with thionyl chloride to give the corresponding acid chloride derivative(4), followed by conversion into the corresponding acid hydrazide derivative (5) carboxylic acid thiosemicarbazide (11), esters

Nine new compounds of 2-amino-5-chlorobenzothiazole derivatives were synthesized. These new compounds were formed through the reaction of 2-amino-5-chlorobenzothiazole 1 with ethyl chloroacetate and KOH, which gave an ester derivative 2, followed by refluxing compound 2 with hydrazine hydrate to afford hydrazide derivative 3. The reaction of compound 3 with CS₂ and KOH gave 1,3,4-oxadiazole-2-thiol derivative 4, and then the reaction of compound 2 with thiosemicarbazide to produce compound 5  then treated it with 4%NaOH led to ring closure to provide 1,2,4-triazole-3-thiol derivative

Two new organotin(IV) complexes Me2Snesc (C1) and Bu2Snesc (C2) have been synthesised from the reaction of the corresponding organotin(IV) chloride with the Schiff base ligand 3,4-dihydroxybenzaldehyde-4-ethylsemicarbazone (H2esc). The ligand was prepared in two steps. The first step includes the formation of 4-ethylsemicarbazide, which then reacted with 3,4-dihydroxybenzaldehyde to give the title ligand. Complex formation between the organotin(IV) moiety and the anionic form of 3,4-dihydroxybenzaldehy-4-ethylsemicarbazone occurred through the o-dihydroxy positions. The ligand and its complexes were characterised by elemental analysis, FT-IR and NMR (1H, 13C and 119Sn) spectroscopy. Accordingly, the complexes were proposed to have tetrahedr

Objectives: Six different Schiff bases were synthesized from ampicillin and amoxicillin with isatin, 5-bromoisatin, and 5-nitroisatin. Methods: Ampicillin and Amoxicillin are linked directly through their α-amino groups to the acyl side chain with isatin and isatin derivatives by nucleophilic addition using glacial acetic acid as a catalyst. Results: chemical structures of these Schiff bases were confirmed using FTIR, 1H NMR and elemental microanalysis. The antibacterial activity was evaluated by measuring minimum inhibitory concentration (MIC) values and showed various degrees of antibacterial activities when compared with parent drugs. Compounds 1a and 2b, which are the Schiff bases of ampicillin and amoxicillin with isatin, showed very

The purpose of my thesis is to prepare four new ligands (L1-L4) that have been ‎used to prepare a series of metal complexes by reacting them with metal ions:‎ ‎ M=(Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II) ‎ ‎ Where succinyl chloride was used as a raw material for the preparation of ‎bi-dented ligands (L1-L4) by reacting it with potassium thiocyanate as a first ‎step and then reacting with (2-aminobenzothiazole, Benzylamine, 4-‎aminoantipyrine, Sulfamethoxazole) respectively as a second step with the use ‎of dry acetone as a solvent, the chemical formula of the four ligands prepared in ‎succession:‎ N1,N4-bis(benzo[d]thiazol-2-ylcarbamothioyl)succinamide (L1)‎ N1,N4-bis(benzylcarbamothioyl)succinami

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological