Schiff bases are pivotal motifs in materials science and medicinal chemistry; their properties are governed by electronic structure. Density Functional Theory (DFT) provides a powerful framework for elucidating structure-property relationships in such systems, offering insights into reactivity, stability, and optoelectronic characteristics that are often difficult to probe experimentally. In this work, a novel phenylalanine-derived Schiff base, N-(4-isopropylbenzylidene)-2-phenylethanamine (IP), which incorporates an electron-donating isopropyl group to modulate electronic and optical properties, was synthesized and characterized. The compound is synthesized via a solvent-free mechanochemical approach and characterized using FT-IR, UV-Vis, and NMR spectroscopy, and elemental analysis. A detailed DFT study was conducted at the B3LYP/6-31G(d,p) level to optimize geometry, compute vibrational frequencies, NMR chemical shifts, electronic transitions, and global/local reactivity descriptors. Topological analysis was performed within the Quantum Theory of Atoms in Molecules (QTAIM) framework. Natural bond orbital (NBO) analysis was employed to investigate intramolecular charge transfer. The DFT-calculated spectroscopic data show excellent agreement with experimental results, validating the chosen computational model. The molecule exhibits a high HOMO-LUMO energy gap (5.112 eV), indicating significant kinetic stability. NBO analysis revealed strong hyperconjugative interactions, particularly pi(C = C) -> pi*(C = C) delocalization within aromatic systems, with stabilization energies up to 22.59 kcal mol-1. The first hyperpolarizability (beta tot = 562.71 & times; 10-33 esu) suggests potential nonlinear optical activity. Fukui function and Molecular Electrostatic Potential (MEP) analyses identified the imine nitrogen and specific carbon atoms as nucleophilic and electrophilic sites, respectively. This study successfully demonstrates the synergistic use of experiment and DFT to fully characterize a novel Schiff base and underscores its potential in optoelectronic and bioactive applications.
Metal-oxide nanocomposites have emerged as a versatile class of materials whose combined physicochemical characteristics are superior to those limitations of individual metal oxides. These hybrid materials demonstrate increased surface activity, synergistic electrical interactions, and improved structural stability properties which are crucial for next-generation energy, environmental, and sensing technologies by combining two or more nanoscale oxides into a nanocomposite. In this work, a nanocomposite SnO2/NiO was synthesized through co-precipitation method to achieve uniform particle dispersion and intimate interfacial contact between the constituent oxides. The successful creation of nanoscale domains with average crystallite sizes of 13.9 nm is confirmed by thorough structural analysis. The functional groups are identified using FTIR. Its morphology was described using SEM and HRTEM, and the elemental investigations was done using Energy Dispersive X-rays (EDAX) and XPS. The synthesized SnO2/NiO nanocomposite exhibited higher specific capacitance of 550 Fg−1 at 1 Ag−1. The material showed 90.25
The growing demand for sustainable and biodegradable materials in biomedical applications motivates this study on biodegradable poly (lactic acid) (PLA) nanocomposites reinforced with cellulose nanofibres (CNFs) derived from Agave sisalana. The nanocomposites were fabricated via solvent casting. SEM analysis confirmed uniform dispersion of CNFs and enhanced interfacial bonding with the PLA matrix. XRD results indicated an increase in the crystalline regions of PLA due to CNF incorporation, contributing to improved mechanical strength and thermal stability, which are critical for biomedical implants. Thermal degradation studies showed a 19 degrees C increase in degradation temperature compared to plain PLA, indicating enhanced heat resistance. Mechanical testing revealed a 48.4 % increase in tensile strength and a 66.1% increase in Young's modulus relative to plain PLA, demonstrating the reinforcing effectiveness of CNFs. Chemical degradation tests showed accelerated hydrolytic and environmental degradation of the nanocomposites compared to plain PLA, beneficial for controlled biodegradation. Additionally, antimicrobial activity improved with increasing CNF content against common pathogens. Hemolytic and MTT assays confirmed good biocompatibility at 3 wt% CNF loading, highlighting the potential of these nanocomposites for safe biomedical applications.
In recent years, digital communication captured massive attention among people, and it plays a significant role in various streams such as banking, healthcare departments, industries, information technologies, and more. At present, all data transfers are transmitted through the internet, which requires a high level of security to transfer the original message until it reaches the destination. Cryptography and Steganography are the two important functionalities that ensure data security over open internet sources. Steganography is the procedure that deals with hiding secret text, audio, and video within massive data. It is found to be a useful source as well as it paves the way for secured communication between two groups to hide the information. However, existing methods are not capable enough to provide efficient results and key creation frequently depend on predictable, deterministic techniques, which might not fully account for anomalies or inefficiencies in the key selection procedure. Hence, proposed method introduces effective key generation using an Optimized Genetic Algorithm (OGA) as it produces complex keys along with Enhanced Rivest-Shamir-Adleman (RSA) encryption and Enhanced RSA decryption algorithm. Enhanced Discrete Wavelet Transform (E-DWT) is employed for the compression and decompression process, and Improvised Lifting Wavelet Transform (I-LWT) is used for the data embedding process. The Genetic algorithm with the Rabin Miller Primality test (RMPT) is mainly proposed for the complex key generation process with secured communication. The private and public keys are generated using an optimized genetic algorithm. Performance metrics are employed to evaluate and analyse the capability of the proposed method considering the Peak signal noise ratio (PSNR), Single to noise ratio (SNR), and Mean Squared Error (MSE) metrics. The proposed model resulted in of MSE rate of 0.00000000042036 and an SNR value of 99.98 %.
In this paper, we introduce a new class of closed sets called the generalization of generalizedstar generalized closed sets (briefly (gg)& lowast;g-closed sets) in topological spaces. And, we scrutinized some of theircharacterization and its relationship along other closed sets
