The human nature of curiosity, wonder, and ingenuity date back to the age of humankind. In parallel with our history of civilization, interest in scientific approaches to unravel mechanisms underlying natural phenomena has been developing. Recent years have witnessed unprecedented growth in research in the area of pharmaceuticals and medicine. The optimism that nanotechnology (NT) applied to medicine and drugs is taking serious steps to bring about significant advances in diagnosing, treating, and preventing disease—a shift from fantasy to reality. The growing interest in the future medical applications of NT leads to the emergence of a new field for nanomaterials (NMs) and biomedicine. In recent years, NMs have emerged as essential game players in modern medicine, with clinical applications ranging from contrast agents in imaging to carriers for drug and gene delivery into tumors. Indeed, there are instances where nanoparticles (NPs) enable analyses and therapies that cannot be performed otherwise. However, NPs also bring unique environmental and societal challenges, particularly concerning toxicity. Thus, clinical applications of NPs should be revisited, and a deep understanding of the effects of NPs from the pathophysiologic basis of a disease may bring more sophisticated diagnostic opportunities and yield more effective therapies and preventive features. Correspondingly, this review highlights the significant contributions of NPs to modern medicine and drug delivery systems. This study also attempted to glimpse the future impact of NT in medicine and pharmaceuticals.

Quantum dots (QDs) with unique properties have been widely employed for energy, environmental, and health care applications. Green natural resources, because of their renewability, sustainability, abundance, low cost, and environmental-friendliness, can be utilized for the synthesis of diverse nanoarchitectures. This critical review highlights the recent advancements in the greener and sustainable synthesis of carbon, graphene and metal-based QDs, as well as their significant environmental applications such as photocatalytic hydrogen production, degradation of hazardous contaminants/pollutants and reduction of CO₂, with emphasis on the important challenges and future perspectives.

In recent years, new developments in controlling greenhouse gas emissions have been implemented to address the global climate conservation concern. Indeed, the earth's average temperature is being increased mainly due to burning fossil fuels, explicitly releasing high amounts of CO₂ into the atmosphere. Therefore, effective capture techniques are needed to reduce the concentration of CO₂. In this regard, metal organic frameworks (MOFs) have been known as the promising materials for CO₂ adsorption. Hence, study on the impact of the adsorption conditions along with the MOFs structural properties on their ability in the CO₂ adsorption will open new doors for their further application in CO₂ separation technologies as well. However, the high cost of the corresponding experimental study together with the instrument's error, render the use of computational methods quite beneficial. Therefore, the present study proposes a Gaussian process regression model with four kernel functions to estimate the CO₂ adsorption in terms of pressure, temperature, pore volume, and surface area of MOFs. In doing so, 506 CO₂ uptake values in the literature have been collected and assessed. The proposed GPR models performed very well in which the exponential kernel function, was shown as the best predictive tool with R² value of 1. Also, the sensitivity analysis was employed to investigate the effectiveness of input variables on the CO₂ adsorption, through which it was determined that pressure is the most determining parameter. As the main result, the accurate estimate of CO₂ adsorption by different MOFs is obtained by briefly employing the artificial intelligence concept tools.