Mechanochemical activation stands out as an eco-friendly and cost-effective solid-state technique for the synthesis of a variety of materials. Due to its simplicity and robustness, high-energy ball milling has become an efficient and greener alternative to improve physicochemical properties of solids, including an increase in Specific Surface Area (S_BET), ion mobility, oxygen vacancies, metal–support interactions and even the formation of new polymorphic structures, due to the accumulation of surface and structural defects and high pressure and temperature locally achieved.

In this work, Cu/TiO₂ catalysts were prepared by several high-energy ball milling strategies (dry milling and semi-wet milling) using different copper reagents and compared with a sample synthesized by a conventional impregnation method. Crystal structures were identified by means of X-ray Diffraction (XRD), including anatase, rutile, high-pressure TiO₂ (II), and W species due to mill vial erosion under some conditions. Specific Surface Area (S_BET) values were calculated from N₂ physisorption (BET method), indicating a correlation between the energy supplied to the powder and the milling conditions. Moreover, Scanning Electron Microscopy (SEM) showed the distinctive morphologies achieved, while a semi-quantification of present elements could be performed using Electron Diffraction Spectroscopy (EDS). Catalysts obtained through this green and one-pot process could be suitable for a variety of reactions, including CO₂ hydrogenation and glycerol hydrogenolysis.

Carbon monoxide (CO) is a colorless, odorless, and toxic gas that requires effective detection due to health risks upon exposure. Carbon dots (CDs), due to their size and surface properties, are used in gas sensing applications especially when functionalized through heteroatom doping. In this study, N-doped carbon dots derived from water hyacinth were synthesized through ultrasound-assisted solvothermal carbonization. A Box–Behnken design under Response Surface Methodology was employed to obtain optimal synthesis conditions for maximum quantum yield, with optimal parameters identified as 177°C, 6.25 hours, and 2.62 g dopant amount achieving a quantum yield of 20.15%. UV–vis and PL analysis confirmed nitrogen doping with peaks at 272 nm and 394 nm, corresponding to electron transitions, and stable excitation-independent emission at 483 nm, respectively. FTIR analysis confirmed surface functional groups such as O–H, N–H, C–H, C–N, and C–OH. FESEM-EDX analysis revealed spherical to quasi-spherical morphology with size ranging between 8 to 55 nm and confirmed the presence of carbon, nitrogen, and oxygen. Gas sensing was performed in a fabricated setup comprising a sealed chamber, CO and N₂ cylinders, and temperature and mass-flow controllers and were regulated at the set parameters. Results showed that the N-doped water hyacinth CDs exhibited higher gas response than undoped CDs in all tested concentrations and temperatures, attributed to improved charge transfer and increased active adsorption sites from doping. Statistical analysis also confirmed that CO concentration and temperature had significant and independent effects on sensor performance. This study demonstrated the potential of N-doped CDs in CO sensing at lower concentrations.

1,3-Thiazole derivatives are of considerable interest in pharmacy, medicine, and agriculture as potential biologically active compounds. In this work, we report for the first time a convenient and efficient method for the synthesis of N-amidoalkylated derivatives of 2-amino-1,3-thiazole. The starting N-(2,2,2-trichloro-1-thioureidoethyl)carboxamides readily react with α-bromoacetophenone in ethanol at 20 °C in the presence of equimolar triethylamine, which serves to neutralize the released hydrogen bromide. Under these conditions, the desired N-amidoalkylated 1,3-thiazole derivatives were obtained in 68–75 % yields. Attempts to perform the counter-synthesis by direct amidoalkylation of 4-phenylthiazol-2-amine resulted in severe tarring of the reaction mass and did not lead to product isolation. The structures of the synthesized compounds were confirmed by ¹H and ¹³C NMR spectroscopy. In the ¹H NMR spectra, two characteristic doublet signals of the NH protons were observed at 9.25–8.39 ppm, while the CH signals of the thiazole and alkylamide fragments appeared at 7.24–7.19 ppm and 7.03–6.84 ppm, respectively. The ¹³C NMR spectra exhibited diagnostic signals of C=O (≈167 ppm), CCl₃ (≈102 ppm), and CH (≈71 ppm) carbons, as well as three thiazole carbon signals at ≈166, 149, and 103 ppm. The structure of compound 3a was unambiguously confirmed by single-crystal X-ray diffraction analysis, which revealed its nearly coplanar molecular geometry and a hydrogen-bonded chain motif along the [001] direction, stabilized by bifurcated N–H…O interactions.

Freshwater scarcity motivates membranes that simultaneously deliver high water flux and near‑complete salt rejection. Here we use all‑atom molecular dynamics (MD) to investigate pressure‑driven desalination across monolayer graphene containing sub‑nanometer pores with controlled edge chemistry. We systematically vary pore diameter (0.5–1.0 nm), geometry, and functionalization (H, OH, COOH) to map the flux–selectivity trade‑off and identify design windows for optimal performance. Simulations of saline feed solutions (monovalent and divalent salts) quantify water permeability from steady‑state volumetric flux and ion rejection from translocation statistics. Free‑energy profiles (potential of mean force) and hydration analyses reveal the mechanisms governing selectivity: ions experience a large dehydration penalty at constrictions, which is modulated by edge polarity and charge; in contrast, water benefits from low interfacial friction and the atomically thin transport length of graphene. We find that pores near the dehydration threshold (~0.7–0.9 nm) with mild polar functionalization maximize selectivity while maintaining high throughput, whereas strongly charged edges enhance ion exclusion but reduce flux due to increased water structuring. Mechanical responses under transmembrane pressure confirm pore stability within the operating range. The results provide quantitative guidelines for tailoring pore size and chemistry to achieve near‑complete salt rejection with high permeability, and they clarify when graphene outperforms thicker polymeric membranes. These insights support the rational design of next‑generation, two‑dimensional desalination membranes and suggest experimental targets for scalable fabrication.

The hard-rock mining industry faces persistent challenges of deep-level extraction, volatile commodity markets, and rising expectations for worker safety and environmental stewardship. These pressures have accelerated interest in “smart mining”, which entails the integration of emerging technologies (ETs) such as advanced sensing, autonomous equipment, robotics, artificial intelligence, digital twins, wearable technologies and real-time analytics. These technologies are designed to transform and revolutionise the conventional method of locating, mining and processing ore bodies. This paper critically examines the strategic benefits of technology uptake in deep-level hard-rock operations, demonstrating how smart mining enhances safety, productivity, and sustainability while strengthening long-term competitiveness. The study employed a structured, closed-ended questionnaire survey administered to highly experienced mining professionals in the South African hard-rock mining sector. The retrieved data were subjected to descriptive analysis. Findings revealed that reduced human exposure to hazardous environments, safety promotion, improved productivity, enhanced robust data analysis, easy data transfer, and optimised scheduling processes are the top benefits of adopting ETs. Therefore, the transition to smart mining presents a compelling strategy for deep-level hard-rock operations seeking to balance productivity imperatives with worker welfare and environmental responsibility. Hence, the South African experience underscores the broader global potential of emerging mining technologies to deliver safer workplaces, enhanced resource efficiency, and sustainable growth for the sector.

This study explores the chemical composition and anti-inflammatory potential of the essential oil extracted from the aerial parts of Satureja calamintha, a medicinal and aromatic plant belonging to the Lamiaceae family. The essential oil was analyzed by gas chromatography (GC) and gas chromatography–mass spectrometry (GC-MS), which led to the identification of twenty compounds, representing 96.7% of the total oil. The composition was dominated by oxygenated monoterpenes (74%) and, to a lesser extent, by hydrocarbon monoterpenes (7.4%) and sesquiterpenes (9.52%). Pulegone was identified as the major constituent (50%), followed by iso-menthone, β-caryophyllene, menthol, and cubebol.

To better understand the contribution of pulegone to the biological activity of the oil, a pulegone-rich fraction (F2) was obtained through column chromatography and subsequently characterized by GC-MS. This fraction contained pulegone as the predominant compound (80%), along with E-β-caryophyllene and pipertenone oxide. Anti-inflammatory activity was assessed using the heat-induced albumin denaturation method. The enriched fraction exhibited a significantly higher inhibitory effect (IC₅₀ = 0.128 mg/mL) compared to the crude oil (IC₅₀ = 0.86 mg/mL), suggesting antagonistic interactions in the unfractionated oil. Furthermore, combination studies with diclofenac sodium revealed a pronounced synergistic effect. Notably, the pulegone-rich fraction combined with diclofenac displayed enhanced activity (IC₅₀ = 0.085 mg/mL), more than twice as effective as diclofenac alone (IC₅₀ = 0.194 mg/mL). Additionally, hemolysis assays conducted on human red blood cells indicated a low cytotoxic potential for both the crude essential oil and the F2 fraction, supporting their potential as safe and effective natural anti-inflammatory agents.

The production of green hydrogen through water splitting is considered to be one of the most environmentally friendly and practical solutions to address the global energy crisis and mitigate the greenhouse effect. A primary challenge in the field concerns the development of efficient, stable, and cost-effective electrocatalysts capable of facilitating both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER), particularly in alkaline media. In this study, Co-P alloy coatings with different P contents were deposited on the copper (Cu) surface using a straightforward and sustainable electroless metal deposition technique. The morphology, structure, and composition of the Co-P coatings were analysed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Furthermore, the catalytic activity of the coatings for HER and OER in 1 M KOH was investigated using linear sweep voltammetry (LSV) and chrono-techniques. The Co-P coating with 11 wt% P exhibited the lowest overpotential of 98.9 mV for the HER to achieve a current density of 10 mA cm^-2, thereby demonstrating superior performance compared to the Co-P coatings with 8, 5, 1.6, and 0.4 wt% P. Conversely, the Co-P coating with 8 wt% P exhibited the lowest overpotential of 378 mV for the OER to achieve the same current density of 10 mA cm^-2, in contrast to the coatings with 5, 11, 1.6 and 0.4 wt% P. These high-performance, P-tuned Co–P coatings demonstrate considerable potential for sustainable hydrogen production and scalable renewable energy storage applications.

Acknowledgement

This research was funded by a grant (No. P-MIP-23-467) from the Research Council of Lithuania.

Introduction: Heat exchangers used in high-temperature environments require lightweight designs with high thermal resistance and efficiency. This study numerically investigates the thermal performance of a multi-channel compact cross-flow heat exchanger, focusing on geometric configurations and material selection.

Methods: Simulations were performed under steady-state conditions to reflect the operating conditions in typical micro gas turbine recuperators. The model featured a total mass flow rate of 0.01 kg/s, with hot air at 1223 K and cold air at 453 K. Five geometric configurations (baseline, conical flow diffuser, ramped ribs, semi-circular bumps, and turbulence promoters) and two materials (stainless steel and graphene-reinforced alumina ceramic composite) were compared.

Results: The implementation of these designs resulted in a 30.8% increase in efficiency for steel heat exchangers and a 33.4% increase for ceramic composite heat exchangers. A material change from steel to ceramic in the baseline geometry yielded an 11.3% effectiveness increase. However, geometric enhancements proved more impactful, with effectiveness increasing exponentially for both materials from baseline to the most complex geometry. This highlights geometric optimization as the primary driver of performance gains. Additionally, the ceramic material's 50% lighter weight offers advantages in weight-constrained applications.

Conclusion: These findings confirm that significant performance improvements in compact heat exchangers are achievable through geometric optimization and advanced materials. Geometric augmentations substantially boosted thermal effectiveness, with gains predominantly linked to geometric optimization. This study suggests that optimized flow channels and integrated internal features, facilitated by additive manufacturing, will be crucial for future high-performance heat exchanger designs.

Local air quality conditions depend on local and regional climatic conditions, source contribution, emission strength of individual pollutant precursors, and the trajectory of air masses, with effects being more conspicuous in urbanized areas with complex terrain pattern, thus induces a need to develop a reliable data-analytic model to capture the realistic associations between emission changes, meteorological conditions and surrounding chemistry processes of the investigated spatial region. Using available emission database, modeled meteorological outputs and raw pollutant attributes of Hong Kong, a new Hybrid Statistical-Dynamic Model was developed by taking advantages of both statistical and deterministic features, and was applied into retrieving historical pollution profile and forecasting next-day surface pollutant concentrations.

By considering the contribution ratio of local to regional pollutant and emission sources, influence of background source and regional meteorological conditions, the categorization of outputs from a coupled regional meteorological and chemistry model was performed, and was adopted to parametrize the equations of a statistical Generalized Additive Model (GAM) within the framework. The established model was shown capable in retrieving temporal patterns of short-term PM_2.5, PM₁₀ and NO₂ concentrations in Hong Kong, but suffered from underestimation during pollution episodes. Thus, bias-adjustment techniques like Hybrid Forecast and Kalman Filter were applied into complementing such statistical deficiency with the aid of observational datasets, and the effectiveness of these techniques were validated by categorical assessments and common statistical metrics. The development of this hybrid model opens new windows in projecting scenario-based pollutant changes, and providing project-based opportunities for acquiring reasonable pollution forecasts.

Harnessing renewable energy offers the most promising path toward sustainable power generation and advancing to a low-carbon future. The importance of harvesting sustainable energy emerged in the late 19th century and has steadily evolved into a global priority today. In this context China stands at the forefront as the world’s leading powerhouse in renewable energy production, while Bahrain remains the smallest contributor. This highlights the urgent need for sustainable power. Therefore, stronger energy policies need to be adopted for promoting and encouraging clean energy production across the globe. Also incremental innovations are essential to support low-power devices. One such advancement is proposed in this paper, where the solar energy is harvested by a thermoelectric generator (TEG), which converts heat into a stable DC voltage. Further, the stable DC voltage is fed to a novel topology of multilevel inverter to produce AC voltage across the load with minimum harmonic presence. The design is carried out in a way that the inverter setup looks compact with low cost, enabling efficiency for low-voltage AC applications. In continuation with this, the design is modeled in MATLAB, and the performance of the TEG with inverter is studied for resistive and impedance loads. From the study, it is found that the TEG with inverter performs better, and it is suitable for applications that need minimum voltages.