https://www.ijnc.ir/ International Journal of New Chemistry en daily 1 Tue, 01 Apr 2025 00:00:00 +0330 Tue, 01 Apr 2025 00:00:00 +0330 https://www.ijnc.ir/article_722059.html Quantum entanglement is a fundamental phenomenon in quantum mechanics, playing a crucial role in advanced technologies such as quantum computing, quantum communication, and cryptography. This study explores the entanglement properties of two prominent multipartite quantum states, the GHZ (Greenberger-Horne-Zeilinger) state and the W state, using MATLAB for simulation and analysis. The GHZ state is characterized by perfect correlations among particles but is highly sensitive to particle loss, whereas the W state exhibits a distributed entanglement structure, maintaining partial entanglement even when a particle is lost. To analyze these states, key entropic measures, including von Neumann entropy and Tsallis-2 entropy, were employed to quantify the purity and entanglement of the quantum states. The results show that both states are pure, with von Neumann and Tsallis-2 entropy values close to zero, and exhibit maximal entanglement as confirmed by concurrence metrics. Additionally, a continuous transition between GHZ and W states was simulated to observe dynamic changes in entanglement, revealing significant reductions during intermediate states. This study demonstrates the effectiveness of MATLAB in evaluating multipartite entanglement and highlights the unique properties of GHZ and W states, providing valuable insights for the development of robust quantum technologies. https://www.ijnc.ir/article_722263.html As a medium spectrum macrolide antibiotic, erythromycin is widely utilized in veterinary medicine to treat a wide range of infections. A coacervative extraction method was designed and optimized for the extraction of erythromycin residues prior to their liquid chromatographic analysis. The proposed approach was based on a water-induced coacervative extraction. Erythromycin was reacted with β-cyclodextrin to form a complex. The ERY-β-CD complex improved the stability of erythromycin in acidic environment. Capric acid in THF as a surfactant molecule was responsible for vesicle formation. Also, a Central Composite Design as a chemometric method was applied to perform a multivariate optimization of the impacts of five different parameters on the extraction efficiency of the proposed approach. After optimizing the method, the parameters were successfully used to determine erythromycin residues in edible meat. The linear range and limit of detection were 60-480 µg Kg-1 and 27.20 µg Kg-1, respectively and the RSD was lower than 5.4 %. https://www.ijnc.ir/article_722671.html This study explores the extraction of oleoresin from the rhizome of ginger (Zingiber officinale) using supercritical carbon dioxide (SC-CO₂) extraction and Soxhlet extraction techniques. Key operational parameters for SC-CO₂ extraction, including pressure (10–20 MPa), temperature (35–45 °C), and flow rate (10–16 g min⁻¹), were optimized to evaluate their influence on extraction yield, radical scavenging activity, and total phenolic content. A Box–Behnken design was employed for experimental design and analysis. Regression analysis confirmed that the experimental data conformed well to both linear and second-order polynomial models. The SC-CO₂ method achieved a maximum oleoresin yield of 6.47 ± 0.07%, significantly higher than the 3.19 ± 0.22% obtained using Soxhlet extraction. The antioxidant potential of the extracts, determined through 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, revealed values of 50.70 ± 0.52% for SC-CO₂ extraction and 88.50 ± 0.18% for Soxhlet extraction. The total phenolic content, quantified via the Folin–Ciocalteu method, was 103.24 ± 1.58% for SC-CO₂ extracts under optimal conditions, compared to 31.10 ± 0.28% for Soxhlet extracts. https://www.ijnc.ir/article_722763.html Molecular modeling is a crucial aspect of modern chemistry, enabling researchers to simulate and analyze molecular structures and interactions at an atomic level. This review paper explores various algorithmic approaches in molecular modeling, emphasizing the contributions of computer engineering to enhance computational efficiency and accuracy. We begin by discussing foundational algorithms, including molecular dynamics and Monte Carlo simulations, and their evolution over time. The integration of advanced techniques such as machine learning and artificial intelligence is highlighted, showcasing how these innovations facilitate predictive modeling and data-driven insights in chemical research. Furthermore, we examine the role of high-performance computing and parallel processing in accelerating complex simulations, enabling the exploration of larger systems and longer time scales. Challenges such as computational resource limitations and algorithm scalability are also addressed, alongside potential solutions derived from recent advancements in computer engineering. Ultimately, this review aims to bridge the gap between computer engineering and molecular modeling, providing a comprehensive overview of how algorithmic innovations are reshaping the landscape of computational chemistry. https://www.ijnc.ir/article_722829.html The exploration of emotions has long been a central theme in both psychology and neuroscience, yet the intricate neurochemical processes underpinning these multifaceted experiences remain a captivating subject of study. This review paper, titled "The Neurochemical Basis of Emotions: Bridging Psychology and Chemistry," endeavors to synthesize current research findings from both fields, offering an integrative perspective that highlights the intersection of psychological theories and neurochemical mechanisms. We delve into the roles of key neurotransmitters such as serotonin, dopamine, norepinephrine, and GABA in modulating emotional states, examining how imbalances and interactions among these chemicals can influence mood disorders and behavioral responses. Furthermore, the paper discusses the impact of hormones like cortisol and oxytocin on emotional regulation, emphasizing their contribution to stress responses and social bonding. By bridging the gap between psychological constructs and biochemical pathways, this review aims to provide a comprehensive understanding of how emotions are generated and expressed in the human brain. The paper also explores emerging research methodologies, such as neuroimaging and pharmacological interventions, that are advancing our knowledge of emotional processes. Ultimately, this synthesis seeks to foster a deeper appreciation of the complex neurochemical foundations of emotions, paving the way for innovative therapeutic approaches in mental health care and enhancing interdisciplinary collaboration between psychology and chemistry. https://www.ijnc.ir/article_722918.html Reactive oxygen species (ROS) are important factors to carcinogenesis, serving as both initiators and promoters of tumor growth. Superoxide dismutases (SODs), a kind of antioxidant enzyme, regulate ROS levels by converting superoxide anions into hydrogen peroxide. While SODs have generally served protective roles, current research has revealed a paradoxical involvement in cancer cell survival and resistance to treatment. This review presents a complete overview of current understanding about SOD inhibitors and their potential as cancer chemopreventive medicines, with a focus on processes, molecular targets, and treatment methods. Eighteen references are mentioned to lay a solid basis for future study in this promising field of cancer. https://www.ijnc.ir/article_723437.html The mammalian target of rapamycin (mTOR) pathway, which is critical for regulating cellular processes such as growth, metabolism, and survival, plays an important role in cancer development when dysregulated. mTOR inhibitors, notably rapamycin and its variants, have emerged as promising possibilities for cancer treatment and chemoprevention. This study focuses on the chemical characteristics of mTOR inhibitors and their potential utility in cancer chemoprevention. We investigate mTOR's function in cancer, assess the chemical structures of first- and second-generation mTOR inhibitors, describe their mode of action, and review preclinical and clinical data. In addition, we look at novel natural product-based inhibitors, dual inhibitors that target both PI3K and mTOR, and the hurdles of bringing these inhibitors to clinical usage.