The research includes the synthesis and identification of the mixed ligands complexes of M 2 Ions in general composition ,[M(Leu) 2 (SMX)] Where L leucine (C 6 H 13 NO 2 )symbolized (LeuH) as a primary ligand and Sulfamethoxazole C 10 H 11 N 3 O 3 S) symbolized (SMX)) as a secondary ligand . The ligands and the metal chlorides were brought in to reaction at room temperature in(v/v) ethanol /water as solvent containing NaOH. The reaction required the following [(metal: 2(Na Leu --): (SMX )] molar ratios with M(II) ions, Were M (  Mn ( II),Co (II),Ni(II),Cu( II),Zn (II),Cd(II)and Hg( The UV Vis and magnetic moment data revealed an octahedral geometry around M(II), The conductivity data show a non electrolytic nature of the complexes . The

The research includes the synthesis and identification of the mixed ligands complexes of M+2ions in general composition[M(Asn)2(SMX)] Where L- Aspargine (C4H8N2O3)symbolized (AsnH) as a primary ligand and Sulfamethoxazole(C10H11N3O3S) symbolized (SMX) as a secondary ligand. The ligands and the metal chlorides were brought in to reaction at room temperature in(v/v) ethanol /water as solvent containing NaOH. The reaction required the following [(metal: 2(Na+Asn-): (SMX)] molar ratios with M(II) ions, Where: M(II)=Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II). The UV–Vis and magnetic moment data revealed an octahedral geometry around M(II), The conductivity data show a non-electrolytic nature of the complexes. The antimicrobial a

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine