Nadar Mahajana Sangam S. Vellaichamy Nadar College (also known as SVN College) is an educational institution located at Nagamalai, Madurai, Tamil Nadu, India. It was started in 1965 by Nadar Mahajana Sangam and offers bachelors and master's level degrees. The college is affiliated with Madurai Kamaraj University. It is a co-educational, autonomous and ISO 9001:2008 certified institution and was re-accredited as "A" grade by the National Assessment and Accreditation Council (NAAC), Bangalore on 10 March 2012.
Pb(Zr0.5Ti0.5)O3 ceramic was synthesized by a solid-state reaction method. X-ray diffraction with Rietveld refinement confirmed the coexistence of rhombohedral (R3c) and tetragonal (P4mm) phases at room temperature, consistent with compositions near the morphotropic phase boundary (MPB). Field-emission scanning electron microscopy (FE-SEM) revealed a dense, well-sintered microstructure with an average grain size of 11 µm. Dielectric and piezoelectric characterization demonstrated superior functional properties: a piezoelectric charge coefficient d33 = 515 pC/N, an electromechanical coupling factor kₚ = 62
In this present work, the structural, spectroscopic and biological evaluation studies of 4-[2-(2-Amino-4,7-dihydro-4-oxo-3 H-pyrrolo[2,3-d]pyrimidin-5-yl)ethyl]benzoic acid molecule were carried out. The optimized molecular structure, structural properties, and harmonic vibrational frequencies were calculated based on density functional theory using Gaussian 09 software. The UV-Visible spectra analysis shows an electronic transition associated with the conjugated system of the molecule. Frontier molecular orbitals analysis reveals information about the kinetic stability and bioactivity of the molecule. The chemical reactivity and charge distribution within the molecule were assessed through Mulliken atomic charge distribution analysis. The molecular docking analysis indicates that the title molecule can act as a novel inhibitor of Mesenchymal-Epithelial Transition receptor, responsible for non-small cell lung cancer. Furthermore, the in vitro cytotoxicity study confirmed moderate cytotoxicity against A549 non-small cell lung cancer cell line. The pharmacokinetic and drug-likeness profile of the molecule were also evaluated. Thus, the present study provides the way for the development of effective drugs in the treatment of non-small cell lung cancer.
The multiferroics cerium substituted La0.85Ce0.15FeO3 (LCFO) and zinc substituted La0.65Zn0.35FeO3 (LZFO) have been prepared by high -temperature solid state reaction route and their structures have been analyzed using XRD and Rietveld refinement techniques. MEM derived charge density study shows that LZFO has slightly high charge density as 0.6593 e/Å3 and 0.9108 e/Å3 along the Fe-O1 and La-O1 bonds than LCFO. LZFO contains small grains and particles with size of about 28 nm and 0.85 µm respectively. The band gap for LZFO multiferroic is found low as 2.12 eV. Both samples exhibit an exchange bias effect that causes its magnetic hysteresis curve to move in a negative direction, demonstrating the coexistence of two distinct magnetically ordered domains (AFM and FM). LZFO has low dielectric constant (807) and its ac conductivity is found as high as 2.68 × 10–3 Ω−1 m−1. The values of electric polarization (Pm) and remanent polarization (Pr) are found to be relatively high (Pm = 39.19 µC/cm2 and Pr = 39.02 µC/cm2) for LZFO than LCFO due to high leakage current. So far, no comparative study has been reported in the literature for Ce- doped LaFeO3 and Zn- doped LaFeO3, even for a single composition. In this article, the physical properties of La0.85Ce0.15FeO3 and La0.65Zn0.35FeO3 have been compared and correlated with charge density, which has not yet been explored in the literature. The effects of secondary (impurity) phase on the magnetic and electric properties are also discussed in this work, which were not addressed in our earlier studies.
Artificial intelligence (AI) is revolutionizing materials science by providing advanced tools for microstructural characterization, functional property assessment, and prediction of structure–property relationships. This chapter explores key machine learning and deep learning approaches—including supervised and unsupervised learning, convolutional neural networks (CNNs), graph neural networks (GNNs), transfer learning, and generative models—highlighting their applications in analyzing complex microstructures and predicting material performance. The integration of AI with multi-scale modeling enables seamless connections from atomic to macroscopic behavior, enhancing accuracy and accelerating simulations. Challenges such as data scarcity, interpretability, and generalizability are discussed, alongside strategies for uncertainty quantification and data fusion. Finally, the chapter emphasizes future perspectives toward autonomous materials discovery, where AI-driven closed-loop systems, robotic laboratories, and inverse design frameworks will dramatically accelerate innovation.
The use of herbal antibiotics has increased as a substitute for synthetic ones, which are ineffective against bacteria that are resistant to drugs. The abuse and overuse of synthetic antibiotics is the root cause of a fast-expanding global health catastrophe. Since people first claimed that medicinal plants had therapeutic qualities thousands of years ago, they have been used. These plants include a variety of phytochemical substances, such as phenolics, terpenoids, alkaloids, flavonoids, tannins, and essential oils. Numerous of these substances have shown broad-spectrum antibacterial action. By interfering with the bacterial cell wall and membrane, preventing the production of proteins and nucleic acids, blocking the efflux pump, and blocking quorum-sensing pathways, these phytochemicals have antimicrobial activity that increases bacterial virulence and resistance.
