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In this paper, Jr .NiFe 2 O 4 nanoparticles (NPs) were synthesized first time using the leaves extract of Juglans regia via a straightforward process. The physio and phytochemical analysis of plant confirm the presence of macromolecules which function as bio-reductant and stabilize the nanoparticles. The Jr .NiFe 2 O 4 NPs were characterized by UV–visible, FTIR spectroscopy, PXRD pattern, SEM and TGA/DTA analysis. The nanoparticles proved to be optically active having a value of indirect bandgap of energy in the range of 1.53 eV. The Jr .NiFe 2 O 4 NPs have the ability in scavenging 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH) free radicals and showed 58.01% ± 1.2% scavenging activity at 100 µg/mL concentrations. The photocatalytic degradation study of ciprofloxacin (CIP) and Congo red (CR) reveals that the highest degradation rate was acquired for CIP using pH = 3, at 254 nm, while 85% of removal rate was analysed for CR. The kinetic studies in case of CR removal followed pseudo-first-order model with thermodynamic parameters (∆G° = − 5.87 kJ mol −1  K, ΔH° = 1393.50 kJ mol −1 and ΔS° = 22.537 kJ mol −1  K) with error analysis. Overall, these data recommend an innovative inspiring application of a plant-mediated synthesis of Jr .NiFe 2 O 4 NPs.

Over the decades, as industrialization progressed, energy has been a critical topic for scientists and engineers. Particularly, photovoltaic technology has drawn great attention in the renewable energy industry as an environmentally clean technology for converting sunlight into electricity. However, the complexity of energy chemistry and the need for novel materials to improve solar cell efficiency and cost-effectiveness have led to challenges in establishing rules beyond empirical observations. Machine learning models are being developed to streamline the prediction process and efficiently predict photovoltaic parameters. This paper proposes a novel hybrid-optimized multi-objective predictive model to predict the photovoltaic parameters: open-circuit voltage (Voc), current density (Jsc), fill factor (FF), and power conversion efficiency (PCE). The proposed model is based on Bayesian Optimization (BO) with the ensemble Bootstrap Aggregating (Bagging) decision tree. The proposed model integrates with the Explainable Artificial Intelligence (XAI) using the SHAP (Shapley Additive Explanations) values to introduce feature importance analysis that provides valuable insights into the impact of individual features on prediction outputs. The proposed model, named BO-Bagging, achieves high prediction accuracy, with an average high correlation coefficient of r = 0.92, a coefficient of determination of R 2  = 0.82, and a Mean Square Error (MSE) of 0.00172. In terms of complexity, the BO-Bagging model has a short processing time that is indicated with an average training time of 182.7 s and an average inference time averaging 0.00062 s. Also, the number of predicted observations per second is measured by prediction speed, which results in good prediction accuracy with an average of 2188.4 and model size with an average of 10,740.4 KB. Finally, the proposed model’s primary critical operations across each phase, from training to predicting the final outputs, are represented by 108 floating-point operations per second (FLOPS). All of these results demonstrate the proposed model’s accuracy and high efficiency in intelligent chemical applications.

The use of metal phosphides, particularly aluminum phosphide, poses a significant threat to human safety and results in high mortality rates. This study aimed to determine mortality patterns and predictive factors for acute zinc and aluminum phosphide poisoning cases that were admitted to Menoufia University Poison and Dependence Control Center from 2017 to 2021. Statistical analysis revealed that poisoning was more common among females (59.7%), aged between 10 and 20 years, and from rural regions. Most cases were students, and most poisonings were the result of suicidal intentions (78.6%). A new hybrid model named Bayesian Optimization-Relevance Vector Machine (BO-RVM) was proposed to forecast fatal poisoning. The model achieved an overall accuracy of 97%, with high positive predictive value (PPV) and negative predictive value (NPV) values of 100% and 96%, respectively. The sensitivity was 89.3%, while the specificity was 100%. The F1 score was 94.3%, indicating a good balance between precision and recall. These results suggest that the model performs well in identifying both positive and negative cases. Additionally, the BO-RVM model has a fast and accurate processing time of 379.9595 s, making it a promising tool for various applications. The study underscores the need for public health policies to restrict the availability and use of phosphides in Egypt and adopt effective treatment methods for phosphide-poisoned patients. Clinical suspicion, positive silver nitrate test for phosphine, and analysis of cholinesterase levels are useful in diagnosing metal phosphide poisoning, which can cause various symptoms.

Four new complexes (Ni2+, Cu2+, Ag+, and Hg2+) were prepared from the ligand N-(4-chlorophenyl)-2-(phenylglycyl)hydrazine-1-carbothioamide (H2L). Analytical and spectroscopic techniques were used to clarify the structural composition of the new chelates. In addition, all chelates were tested against bacterial strains and the HepG2 cell line to determine their antiseptic and carcinogenic properties. The Ni(II) complex was preferable to the other chelates. Molecular optimization revealed that H2L had the highest reactivity, followed by Hg-chelate, Ag-chelate, Ni-chelate, and Cu-chelate. Moreover, molecular docking was investigated against two different proteins: the ribosyltransferase enzyme (code: 3GEY) and the EGFR tyrosine kinase receptor (code: 1m17).

New Pb(II), Mn(II), Hg(II), and Zn(II) complexes, derived from 4-(4-chlorophenyl)-1-(2-(phenylamino)acetyl)thiosemicarbazone, were synthesized. The compounds with general formulas, [Pb(H2L)2(OAc)2]ETOH.H2O, [Mn(H2L)(HL)]Cl, [Hg2(H2L)(OH)SO4], and [Zn(H2L)(HL)]Cl, were characterized by physicochemical and theoretical studies. X-ray diffraction studies showed a decrease in the crystalline size of compounds that were exposed to gamma irradiation (γ-irradiation). Thermal studies of the synthesized complexes showed thermal stability of the Mn(II) and Pb(II) complexes after γ-irradiation compared to those before γ–irradiation, while no changes in the Zn(II) and Hg(II) complexes were observed. The optimized geometric structures of the ligand and metal complexes are discussed regarding density functional theory calculations (DFT). The antimicrobial activities of the ligand and metal complexes against several bacterial and fungal stains were screened before and after irradiation. The Hg(II) complex has shown excellent antibacterial activity before and after γ-irradiation. In vitro cytotoxicity screening of the ligand and the Mn(II) and Zn(II) complexes before and after γ-irradiation disclosed that both the ligand and Mn(II) complex exhibited higher activity against human liver (Hep-G2) than Zn(II). Molecular docking was performed on the active site of MK-2 and showed good results.

The sonication method was used to prepare a new set of CuO and CuO/Ag nanocomposites. The particle size was estimated using XRD and HR-TEM while the morphology of the nanoparticles was investigated with SEM. The average particle sizes of CuO and Ag falls in the 29.32–35.80 nm and 35.13–45.95 nm ranges, respectively. XRD declared that CuO has the space groups C 1 c 1 (9) and C 1 2/c 1 (15), while silver has space group F m -3 m (225). XPS analysis indicated the presence of Ag as Ag 0 and Cu as Cu 2+ . Nano-oxide and nanocomposites were used to synthesis CuO and CuO/Ag doped lithium–zinc borosilicate glass. Physical parameters of the glass samples were calculated including density, V m , V o , V m B , OPD, d B - B , n b , and N, R p , and R i depending on Ag and CuO mole fractions. The physical properties of glass indicated an increase in density and an initial expansion in glass structural network with the addition of silver metal due to its larger size followed by a compression as its molar ratio increase due to its higher C no . XRD measurements were reported for the glass samples doped with nanoparticles, proving the amorphous phase. ESR measurements were determined for all glass samples to detect the nature of the doped nanoparticles when incorporated inside a glassy matrix where CuO was found as tetragonal in octahedral sites and silver can be transformed after melting inside the glass matrix into Ag + to form more stable Ag y x + clusters.The fabricated sample of CuAgB-4 with significant nano silver doping (7.32% mol) has the maximum LAc and effective atomic number. Nano silver content increases the γ -RdSg in the lithium–zinc borosilicate glasses.

In the present study, naphthyl acetohydrazide (HL) ligand was prepared and used for the synthesis of new six amorphous transition metal (Co(II), Ni(II), Cu(II), Zn(II), Pb(II), Cd(II)) complexes. All the compounds were characterized by elemental analysis, UV-vis, FT-IR, 1H- and 13C-NMR, and Matrix-Assisted Laser Desorption Ionization (MALDI). The solubilization study was carried out by estimating the interaction between the metal complexes with surfactants viz. sodium stearate (SS) and Cetyltrimethylammonium bromide (CTAB). UV-Visible spectroscopy was employed to determine partitioning and binding parameters, whereas electrical conductivity measurements were employed to estimate critical micellar concentration (CMC), the extent of dissociation, and free energy of micellization. The CT-DNA interaction of synthesized compounds with DNA represents the major groove binding. The synthesized ligand and metal complexes were also tested against bacterial and fungal strains and it has been observed that Cu(II) complex is active against all the strains except Candida albicans, while Cd(II) complex is active against all bacterial and fungal strains except Pseudomonas. Among all compounds, only the Pd(II) complex shows reasonable activity against cervical cancer HeLa cell lines, representing 97% inhibition.

Till now the exact mechanism and effect of biogenic silver nanoparticles on fungus is an indefinable question. To focus on this issue, the first time we prepared hydrothermal assisted thyme coated silver nanoparticles (T/AgNPs) and their toxic effect on Candida isolates were determined. The role of thyme ( Thymus Vulgaris ) in the reduction of silver ions and stabilization of T/AgNPs was estimated by Fourier transforms infrared spectroscopy, structure and size of present silver nanoparticles were detected via atomic force microscopy as well as high-resolution transmission electron microscopy. The biological activity of T/AgNPs was observed against Candida isolates from COVID-19 Patients. Testing of virulence of Candida species using Multiplex PCR. T/AgNPs proved highly effective against Candida albicans , Candida kruzei , Candida glabrata and MIC values ranging from 156.25 to 1,250 μg/mL and MFC values ranging from 312.5 to 5,000 μg/mL. The structural and morphological modifications due to T/AgNPs on Candida albicans were detected by TEM. It was highly observed that when Candida albicans cells were subjected to 50 and 100 μg/mL T/AgNPs, a remarkable change in the cell wall and cell membrane was observed.

The microbial resistance to current antibiotics is increasing day by day, which in turn accelerating the development of new effective drugs. Several studies have proved the high antimicrobial potential of the interaction of several organic ligands with a variety of metal ions. In the present study, a conventional method has been adopted in the synthesis of twelve new heteroleptic complexes of cobalt (II), nickel (II), copper (II) and zinc (II) using three aldimines, namely, (HL1 ((E)-2-((4-chloro-2-hydroxybenzylidene)amino)-3,4-dimethyl-5-phenylcyclopent-2-en-1-one), HL2 ((Z)-3-((4-chlorobenzylidene)amino)-4-hydroxy-5-nitrobenzenesulfonic acid) HL3 (2,2′-((1,2-phenylenebis(azaneylylidene))bis(methaneylylidene))diphenol)) as primary ligands, while phenyl glycine was the secondary ligand. The synthesized compounds were characterized by UV-vis, IR and multinuclear (1H and 13C) NMR spectroscopy, elemental analysis, and electrical conductance. The IR study revealed the coordination of the aldimine derivatives with the -OH and N atom of imine moiety. In contrary to this, the phenyl glycine coordinated to the metal ions via oxygen of carboxylate and nitrogen of the amino group. The spectroscopic analysis unveiled the tetrahedral geometry of the synthesized metal (II) complexes, except for ligand HL3 which exhibited octahedral geometry. The synthesized compounds generally showed antibacterial activity for all microbes, except Ni (II) complexes lacking sensitivity. Furthermore, to access the bioavailability, the synthesized complexes were screened for their solubilization in the micellar media of sodium lauryl sulphate. The metal complex–surfactant interaction was revealed by UV-vis spectroscopy and electrical conductivity measurements.

Sixteen fuberidazole derivatives as potential new anticancer bioreductive prodrugs were prepared and characterized. The in vitro anticancer potential was examined to explore their cytotoxic properties by employing apoptosis, DNA damage, and proliferation tests on chosen hypoxic cancer cells. Eight substances (Compound 5a, 5c, 5d, 5e, 5g, 5h, 5i, and 5m ) showed promising cytotoxicity values compared to the standard control. The potential of compounds was also examined through in silico studies (against human serum albumin ), including chem-informatics, to understand the structure-activity relationship (SAR), pharmacochemical strength, and the mode of interactions responsible for their action. The DFT calculations revealed that only the 5b compound showed the lowest ΔET (2.29 eV) while 5 i showed relatively highest βtot (69.89 x 10–31 esu), highest αave (3.18 x 10–23 esu), and dipole moment (6.49 Debye). This study presents a novel class of fuberidazole derivatives with selectivity toward hypoxic cancer cells.