The increase of antibiotic resistance in bacteria has become a major concern for successful diagnosis and treatment of infectious diseases. Over the past few decades, significant progress has been achieved on the development of nanotechnology‐based medicines for combating multidrug resistance in microorganisms. Among these, metallic nanoparticles (MNPs) hold great promise in addressing this challenge due to their broad‐spectrum and robust antimicrobial properties. This review illustrates the antibacterial activities of MNPs and further elucidates how different factors including synthesis method, size, shape, surface charge, pH, dose, type of capping or stabilizing agents of MNPs, and Gram‐type of the bacteria, impact their antibacterial activities, which are expected to promote the future development of more potent MNP‐based antibacterial agents.

Foodborne disease outbreaks due to bacterial pathogens and their toxins have become a serious concern for global public health and security. Finding novel antibacterial agents with unique mechanisms of action against the current spoilage and foodborne bacterial pathogens is a central strategy to overcome antibiotic resistance. This study examined the antibacterial activities and mechanisms of action of inorganic nanoparticles (NPs) against foodborne bacterial pathogens. The articles written in English were recovered from registers and databases (PubMed, ScienceDirect, Web of Science, Google Scholar, and Directory of Open Access Journals) and other sources (websites, organizations, and citation searching). “Nanoparticles,” “Inorganic Nanoparticles,” “Metal Nanoparticles,” “Metal–Oxide Nanoparticles,” “Antimicrobial Activity,” “Antibacterial Activity,” “Foodborne Bacterial Pathogens,” “Mechanisms of Action,” and “Foodborne Diseases” were the search terms used to retrieve the articles. The PRISMA‐2020 checklist was applied for the article search strategy, article selection, data extraction, and result reporting for the review process. A total of 27 original research articles were included from a total of 3,575 articles obtained from the different search strategies. All studies demonstrated the antibacterial effectiveness of inorganic NPs and highlighted their different mechanisms of action against foodborne bacterial pathogens. In the present study, small‐sized, spherical‐shaped, engineered, capped, low‐dissolution with water, high‐concentration NPs, and in Gram‐negative bacterial types had high antibacterial activity as compared to their counterparts. Cell wall interaction and membrane penetration, reactive oxygen species production, DNA damage, and protein synthesis inhibition were some of the generalized mechanisms recognized in the current study. Therefore, this study recommends the proper use of nontoxic inorganic nanoparticle products for food processing industries to ensure the quality and safety of food while minimizing antibiotic resistance among foodborne bacterial pathogens.

Recently, energy has been a research area due to increasing awareness of its advantages. Energy is essential for all daily activities and helps the mind and body grows; it has the ability to determine the growth of an economy and the development of a country. However, energy has its disadvantages. Nonrenewable energy is energy such as fossil fuel, which is the main cause of air pollutant emissions, such as carbon dioxide, synthetic fluorinated gases, water vapor, and methane gases; and nuclear energy, its wastes are the main cause of air pollutant. They are also the main cause of global warming, human health, climate change, and environmental degradation from the extraction up to use. Nowadays, fossil fuel energy is used in production and use of energy in all sectors of the world. Nuclear energy is the most powerful energy source. Renewable energy, such as solar, wind, hydropower, geothermal, tidal, wave, and hydrogen energy, produces zero greenhouse gas emissions compared to fossil fuels, reducing air pollution and combating climate change, improving public health, mitigating smog and acid rain, and long‐term sustainability. The production and use of this renewable energy has been increasing, but it is not sufficient to meet the demand of all sectors in the world. Hydrogen energy is the future of fossil fuels and nuclear energy, free of CO₂ emissions, and radioactive waste. The hydrogen economy envisions using hydrogen as a clean, versatile, and sustainable energy carrier to replace fossil fuels and reduce greenhouse gas emissions. We must control the impacts of energy first by knowing the types of energy and their impact, and then totally replace nonrenewable energy with renewable energy in the future by increasing the efficiency of renewable energy. To increase the efficiency of energy production, energy storage (storing high amount of energy in a small space) uses nanomaterials and green nanomaterial technologies. International cooperation and policy alignment will be essential for driving global transition to a sustainable energy future. By leveraging Artificial Intelligence (AI) and machine learning (ML), the energy sector becomes more sustainable, efficient, and resilient, supporting the transition toward a low‐carbon future. Harmonizing energy policies, sharing best practices, and aligning climate commitments can facilitate the development of a coordinated approach to addressing energy challenges on a global scale. By incorporating these considerations into energy planning and decision‐making, stakeholders can work toward building a future energy system that is sustainable, resilient, and capable of meeting the energy needs of a rapidly changing world. In this study, a critical review of the type, form, storage, advantages, efficiency, respective, and their impact are reviewed. The amounts of energy produced by each type in different years are discussed.

The main objective of this manuscript is to focus on the computational study of the interplay of spin density wave (SDW) and superconductivity using a two-band model for SrFe_2−xNi_xAs₂. We derived mathematical statements for the superconducting critical temperature, SDW critical temperature, superconductivity order parameter, and the SDW order parameter using the Hamiltonian model and Green’s function formalism for the SrFe_2−xNi_xAs₂ superconductor. A mathematical expression for the dependence of transition temperatures on the SDW order parameter was obtained for SrFe_2−xNi_xAs₂. Using these mathematical statements, transition temperatures versus the SDW order parameter phase diagrams were plotted to show the dependence of the SDW order parameter on transition temperatures. By merging these diagrams, we have depicted the intriguing possibility of the interplay of superconductivity and magnetism for the SrFe_2−xNi_xAs₂ superconductor. Phase diagrams of temperature versus superconducting order parameters and the SDW order parameter were also plotted to show the dependence of order parameters on temperature for the SrFe_2−xNi_xAs₂ superconductor.