Magnetothermal energy dissipation in magnetic nanoparticles requires efficient heat generation under alternating magnetic fields (AMFs), yet the mechanistic relationship between magnetic anisotropy, interparticle dipolar interactions, and heating performance remains insufficiently defined. In this study, Fe3O4 and CoFe2O4 nanoparticles were synthesized via co-precipitation and systematically characterized to isolate the role of magnetic anisotropy in governing magnetothermal behavior. Field-emission scanning electron microscopy (FESEM) confirmed comparable mean particle sizes (41 nm), while X-ray diffraction (XRD) indicated crystallite sizes of 14 nm, consistent with the formation of spinel ferrite phases in both systems. Vibrating sample magnetometry (VSM) revealed similar saturation magnetization values (64 emu.g−1) but significantly different coercive fields (Hc ≈ 15 Oe for Fe3O4 and ≈ 400 Oe for CoFe2O4), providing a controlled basis for anisotropy-driven comparison. First-order reversal curve (FORC) analysis resolved distinct magnetic phase characteristics: Fe3O4 exhibited predominantly single-domain behavior with a narrow interaction field distribution (IFD ≈ 250 Oe) and a minor superparamagnetic fraction (10
Trace element imbalances are implicated in cancer pathophysiology, yet data from Iraq, a country with distinct environmental and industrial exposures, remain scarce. The stomach plays a central role in trace element absorption through its acidic environment and digestive processes, and gastric cancer disrupts this function, potentially altering systemic trace element homeostasis. This study measured serum zinc (Zn), copper (Cu), and lead (Pb) concentrations in gastric cancer patients and evaluated their diagnostic potential with gender-stratified analysis. A case-control study was conducted in Najaf, Iraq (2022–2024), enrolling 100 gastric cancer patients and 100 age-matched healthy controls (50 males and 50 females per group). Serum Zn and Cu were quantified by flame atomic absorption spectrometry (FAAS); Pb was measured by graphite furnace AAS (GFAAS). Independent samples t-tests compared group differences, and receiver operating characteristic (ROC) analysis assessed diagnostic accuracy. Female patients showed significantly lower serum Zn (100.43 ± 64.25 vs. 818.31 ± 130.26 ppb, p < 0.001) and higher Cu (1466.87 ± 568.69 vs. 977.79 ± 249.30 ppb, p < 0.001) compared to healthy controls. Male patients showed significantly lower Cu (89.50 ± 15.50 vs. 173.14 ± 98.94 ppb, p < 0.001), while Zn did not differ significantly (p = 0.394). Serum Pb was elevated in both sexes (females: 40.31 ± 9.43 vs. 11.98 ± 2.68 ppb; males: 44.79 ± 10.33 vs. 12.38 ± 2.68 ppb; both p < 0.001). ROC analysis showed Pb to be the strongest discriminator in both sexes (AUC = 0.989), while Zn was a strong discriminator in females (AUC = 0.994) but poor in males (AUC = 0.396). Serum Pb showed consistent elevation across both sexes and strong diagnostic accuracy, suggesting its potential as a cancer-associated biomarker in this population. Gender-specific differences in Zn and Cu underscore the role of sex as a biological modifier in trace element metabolism during gastric cancer. Larger multicenter studies with comprehensive environmental and dietary data are warranted.
The growing resistance of the pathogenic bacteria to traditional antibiotics has provoked a strong demand of the new antimicrobial materials. Silver nanoparticles (AgNPs) have emerged as potent candidates due to their broad-spectrum antibacterial activity and tunable physicochemical properties. This study presents a systematic research on how the reaction parameters affect the formation, structure and antibacterial behavior of silver nanoparticles (AgNPs) prepared through a straightforward chemical reduction method. Five AgNP formulations (S1–S5) were prepared by varying reaction temperature and time, using sodium dodecyl sulfate (SDS) as a stabilizer and hydrazine hydrate as a reducing agent. UV–visible spectroscopy and XRD analyses were performed for all synthesized samples to examine the effect of synthesis conditions on the optical and structural evolution of AgNPs. The optimized sample (S4, 70 °C, 60 min) was subjected to comprehensive microstructural and surface characterization through SEM, TEM, EDS, and FTIR analyses to establish a clear structure–property relationship. The UV–Vis spectra exhibited distinct surface plasmon resonance (SPR) bands in the range of 395–420 nm, red-shifting systematically with increasing reaction temperature and time, confirming particle growth and enhanced crystallinity. XRD analysis revealed the formation of highly crystalline face-centered cubic (FCC) silver with increasing phase purity under optimized conditions. SEM and TEM imaging of the optimized sample revealed spherical nanoparticles in the range of 60–75 nm, while EDS confirmed compositional purity and uniform spatial distribution of silver. Antibacterial evaluation against Escherichia coli and Staphylococcus aureus revealed that AgNPs prepared at 70 °C for 60 min exhibited the highest efficiency, with minimum inhibitory concentrations (MICs) of 25 µg/mL and 50 µg/mL, respectively. A weak DPPH radical scavenging activity was also observed, reflecting moderate antioxidant potential. The findings demonstrate that the increased crystallinity and homogeneous microstructure of the AgNPs are the direct factors determining their antibacterial effectiveness. This enhanced performance is attributed to improved Ag⁺ ion release and stronger interaction of well-crystallized, uniformly shaped nanoparticles with bacterial cell walls, resulting in more effective disruption of cellular integrity. Overall, this study establishes a direct correlation between synthesis parameters, structural evolution, and biological performance, providing a reliable framework for the rational design of functional AgNPs.
The influence of tuning ultrasound-assisted extraction (UAE) parameters together with in-process ZnO nanoparticle (NP) incorporation on the extraction yield and temperature-dependent rheology of Stevia glycosides was investigated. Compared with maceration and microwave-assisted extraction (MAE), UAE recovered a broader chemical profile (Stevioside, Rebaudioside A, Caryophyllene oxide, Benzaldehyde) and yielded higher recoveries (CRD/CRD-factorial). Rheology exhibited robust shear-thinning across 20-35 degrees C and 1-100 rpm: for 2-6 % w/v extracts, viscosity ranged from 0.029 -> 0.005 Pa.s (Day 1) and 0.032 -> 0.005 Pa.s (Day 28) with increasing shear rate and temperature. Flow behavior was quantified using power-law fits (n < 1; k, n reported). Antimicrobial assays showed concentration-dependent inhibition halos up to 30.0 +/- 1.6 mm (Staphylococcus aureus) and 24.0 +/- 1.5 mm (Escherichia coli), with MIC/MLC as low as 7.5/15.0 mu L.mL(-1) for Candida albicans. FE-SEM revealed flower-like ZnO morphologies; ZnO (0.1-1.0 % w/v) increased low-shear viscosity yet preserved shear-thinning, consistent with NP-matrix interactions. Unlike prior studies that optimized UAE or characterized nanofluids separately, the present work co-varies UAE parameters with in-process ZnO addition and quantifies time-resolved rheology (Day 1 vs. Day 14/28) via power-law fits, thereby linking cavitation, yield, and process-relevant viscosity for scale-up.
This study presents a novel four-stage hybrid framework that integrates machine learning, multi-objective optimization, and multi-criteria decision-making to enhance the thermal management of lithium-ion batteries (LIBs) using a liquid-PCM hybrid cooling system. Addressing a key limitation in existing research, the fragmented treatment of modeling, optimization, and decision-making, this work unifies these components into a cohesive, decision-oriented framework. A GA-optimized multilayer perceptron neural network is first developed to predict thermal-hydraulic responses from design parameters, achieving high accuracy (R > 0.985) and excellent generalizability via cross-validation. For optimization, a novel multi-objective artificial vultures optimization (MOAVOA) is benchmarked against MOPSO, with MOPSO outperforming in Pareto front density, diversity, and convergence. Key trade-offs reveal that PCM thicknesses of 7-8.9 mm, channel widths of 8-8.99 mm, and inlet velocities >0.410 m/s yield optimal thermal performance. The final decision-making stage uses the weighted Tchebycheff method to extract twelve actionable design scenarios aligned with varied operational priorities. This integrated framework enables context-specific, robust engineering decisions across sectors such as electric vehicles and consumer electronics, contributing to the development of safer, more efficient, and sustainable battery technologies.
