The urgent need for sustainable water treatment solutions has driven global scientific efforts toward developing novel materials. Biochar, a low-cost material produced from biomass waste, represents a promising and versatile adsorbent class. In this study, acid-treated peanut shell biochar (PS-BC) was synthesized and evaluated for the removal of the methyl orange (MO) dye from aqueous solution. Characterization via Fourier Transform Infrared Spectroscopy (FT-IR) confirmed the presence of carbonaceous groups, such as C=O, C-O, C=C and derived phosphoric groups, such as P=O. Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDS) revealed a mesoporous and macroporous structure, while X-ray Diffraction (XRD) indicated a predominantly amorphous material containing amorphous SiO₂ phases. The adsorption was followed by monitoring 464 nm band of MO in UV-Vis spectroscopy, and the adsorbent achieved a maximum removal of above 89% of MO within a 60-minute experiment. The adsorption kinetics were analysed in pseudo-first and pseudo-second models, which the adsorption was described better by the pseudo-first-order model. Also, adsorption isotherms (Langmuir, Freundlich and Temkin) were studied, and the equilibrium data closely fit the Langmuir isotherm model, pointing to monolayer adsorption onto a homogeneous surface. The FT-IR analysis of post-adsorbed PS-BC confirmed bands associated to MO, such as N=N, SO₃^- and change in aromatic C=C, indicating the possible adsorption pathways. These results confirm the successful application of the acid-treated PS-BC as an efficient and eco-friendly adsorbent for organic pollutant removal from water.

In response to the growing demand for sustainable technologies for wastewater treatment, this study reports the green synthesis of Ag?O-doped TiO? nanoparticles using Salix babylonica bark extract as a natural reducing and stabilizing agent. Although several plant extracts have been explored for the green synthesis of photocatalysts, the use of Salix babylonica biomass for the simultaneous synthesis and Ag?O doping of TiO? nanoparticles remains scarcely investigated. The proposed synthesis route eliminates the need for hazardous chemicals and provides an environmentally friendly alternative for the production of photocatalytic materials. The synthesized samples, containing 0, 0.5, and 1 wt% Ag?O, were characterized by thermogravimetric analysis (TGA), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and UV–Vis spectroscopy. The results confirmed the formation of predominantly anatase-phase TiO? and the successful incorporation of silver species without altering the crystalline structure of the oxide matrix. Ag incorporation promoted changes in the morphological and optical properties of TiO?, favoring improved charge separation and enhanced light utilization. Photocatalytic activity was evaluated through the degradation of methylene blue under irradiation. The Ag?O-doped samples exhibited superior performance compared with undoped TiO?, with the 1 wt% Ag?O sample showing the highest degradation efficiency. This improvement is attributed to the formation of Ag?O/TiO? heterojunctions, which facilitate electron–hole separation and increase the generation of reactive oxygen species responsible for pollutant degradation. Overall, the results demonstrate that the proposed green synthesis strategy is a simple, low-cost, and sustainable approach for producing efficient photocatalysts with potential application in environmental remediation and wastewater treatment.

Cutting force is a key indicator that reflects the mechanical interaction between the cutting tool and the workpiece during machining. It directly influences energy consumption, tool wear, process stability, and machined surface quality. As modern manufacturing increasingly demands efficient, flexible, and sustainable production systems, the development of adaptive, real-time, and cost-effective cutting force measurement technologies has become essential. Previous review studies have primarily focused on cutting force modelling and commercial dynamometer systems, while limited attention has been given to the integration of low-cost sensors, microcontrollers, Internet of Things (IoT) technologies, and smart manufacturing applications. This review aims to evaluate recent developments in sensor- and microcontroller-based cutting force measurement systems and their potential integration within Industry 4.0 environments. The review synthesizes more than 230 references, primarily published between 2020 and 2026, together with selected earlier studies that provide important theoretical and technological foundations. Four main aspects are discussed: (1) theoretical foundations of cutting force, (2) sensor technologies and measurement system architectures, (3) modelling and data analysis methods, and (4) challenges and future development trends. The findings indicate that load cell and strain gauge sensors provide economical and practical solutions for long-term monitoring, whereas piezoelectric sensors remain the preferred option for high-frequency dynamic measurements due to their superior sensitivity and bandwidth. Furthermore, the integration of microcontrollers, IoT connectivity, machine learning, and digital twin technologies is accelerating the development of intelligent machining systems for smart and sustainable manufacturing.