Atom transfer radical polymerization (ATRP) is a kind of controllable reactive radical polymerization method with potential application value. The modification of graphene oxide (GO) by ATRP reaction can effectively control various graft polymer molecules Chain length and graft density, giving GO different functionality, such as good solvent dispersibility, environmental sensitive stimulus responsiveness, biocompatibility, and the like. In this paper, ATRP reaction and GO surface non-covalent bonding ATRP polymer molecular chain were directly initiated from GO surface immobilization initiator. The ATRP reaction modified GO was reviewed, and the process conditions and research methods of ATRP modification reaction were summarized, as well as pointed out the functional characteristics and application prospect of GO functionalized composites.

Water splitting has been one of the potential techniques as a clean and renewable energy resource for the fulfillment of world energy demands. One of the major aspects of this procedure is the exploitation of efficient and inexpensive electrocatalysts due to the fact that the water oxidation procedure is accompanied by a delayed reaction. In this research, ZnO-CoFe₂O₄ nanostructure was successfully synthesized via the green method and green resources from cardamom seeds and ginger peels for oxygen evolution reaction (OER). The modified Glassy carbon electrode (GCE) with ZnO-CoFe₂O₄ is effective for the electrochemical water oxidation interaction since it has sufficient electrical strength and excellent catalytic performance. The creation of rice-like and small granular structures of ZnO-CoFe₂O₄ nano-catalysts was confirmed by characterization methods such as XRD, FESEM, EDS and MAP. According to the achieved results, in the electrolysis of water, with in-cell voltage of 1.40 V and 50 mA cm^–2 for current density in a 0.1 M KOH electrolyte and OER only has 170 mV overpotentials.

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.

The work is devoted to the numerical solution of the initial boundary value problem for the heat equation with a fractional Riesz derivative. Explicit and implicit difference schemes are constructed that approximate the boundary value problem for the heat equation with a fractional Riesz derivative with respect to the coordinate. In the case of an explicit difference scheme, a condition is obtained for the time step at which the difference scheme converges. For an implicit difference scheme, a theorem on unconditional convergence is proved. An example of a numerical calculation using an implicit difference scheme is given. It has been established that when passing to a fractional derivative, the process of heat propagation slows down.

Accurate drug-drug interaction (DDI) prediction is essential to prevent adverse effects, especially with the increased use of multiple medications during the COVID-19 pandemic. Traditional machine learning methods often miss the complex relationships necessary for effective DDI prediction. This study introduces a deep learning-based classification framework to assess adverse effects from interactions between Fluvoxamine and Curcumin. Our model integrates a wide range of drug-related data (e.g., molecular structures, targets, side effects) and synthesizes them into high-level features through a specialized deep neural network (DNN). This approach significantly outperforms traditional classifiers in accuracy, precision, recall, and F1-score. Additionally, our framework enables real-time DDI monitoring, which is particularly valuable in COVID-19 patient care. The model’s success in accurately predicting adverse effects demonstrates the potential of deep learning to enhance drug safety and support personalized medicine, paving the way for safer, data-driven treatment strategies.

ZrO₂ thin film samples were produced by the sol-gel dip coating method. Four different absorbed dose levels (such as ~ 0.4, 0.7, 1.2 and 2.7 Gray-Gy) were applied to ZrO₂ thin films. Hence, the absorbed dose of ZrO₂ thin film was examined as physical dose quantity representing the mean energy imparted to the thin film per unit mass by gamma radiation. Modification of the grain size was performed sensitively by the application of the absorbed dose to the ZrO₂ thin film. Therefore the grain size reached from ~50 nm to 87 nm at the irradiated ZrO₂ thin film. The relationship of the grain size, the contact angle, and the refractive index of the irradiated ZrO₂ thin film was investigated as being an important technical concern. The irradiation process was performed in a hot cell by using a certified solid gamma ray source with 0.018021 Ci as an alternative technique to minimize the utilization of extra toxicological chemical solution. Antireflection and hydrophilic properties of the irradiated ZrO₂ thin film were slightly improved by the modification of the grain size. The details on the optical and structural properties of the ZrO₂ thin film were examined to obtain the optimum high refractive index, self-cleaning and anti-reflective properties.