A metal-free microwave-induced carbon cloth discharge technology for efficient degradation of Rhodamine B.

This study investigated the effects of different drying methods, including freeze drying, oven drying, shade drying, and microwave drying (360, 600, and 900W), on the volatile profile, total phenolic content (TPC), and color characteristics of wild-grown Thymus praecox subsp. skorpilii. Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) analysis identified 26 volatile compounds in the fresh sample, with α-pinene, 3-octanone, limonene, and β-caryophyllene as the predominant constituents. Drying induced pronounced shifts in volatile composition, characterized by an overall increase in isoprenoid compounds and a reduction in fatty acid derivatives, alongside the emergence of compounds such as nonanal and hexadecane. Increasing microwave power led to a decrease in monoterpenes and an increase in sesquiterpenes. TPC (19.5-40.21mg gallic acid equivalent [GAE]/g), and color parameters were also significantly affected (p<0.05), with freeze drying and high-power microwave drying showing improved phenolic retention and color preservation compared to oven and shade drying. Overall, the results indicate that drying influences multiple quality attributes in a method-dependent manner, with variations in processing conditions leading to distinct compositional outcomes. These findings highlight the importance of aligning drying conditions with specific quality targets when processing wild thyme. PRACTICAL APPLICATIONS: This study establishes a practical framework for selecting drying strategies in wild thyme (Thymus praecox subsp. skorpilii) by linking processing conditions to changes in volatile composition, color, and phenolic content. The results demonstrate that drying induces method-dependent transformations rather than uniform quality changes. Accordingly, drying methods should be chosen on the basis of the targeted product profile together with processing efficiency, enabling more tailored production of high-quality dried thyme.

ABSTRACT The purpose of this study is to examine the influence of microwave-assisted thermal treatment of spent biomass, Saccharomyces cerevisiae from invertase production, on the removal of methylene blue from wastewater. Functional group, surface morphology, and textural properties, of thermally treated yeast cells (TSAC) and untreated yeast cells (NSAC) were evaluated using FTIR and SEM. The effect of microwave power and irradiation time on the treatment of yeast cells was assessed in terms of biosorption (%). The maximum biosorption capacities of NSAC and TSAC were 7.19 and 11.17 mg/g, respectively. TSAC demonstrated superior regeneration potential over multiple biosorption cycles, retaining more than 80% of its initial biosorption efficiency after three consecutive runs, indicating its suitability for repeated wastewater treatment. Mechanistic insights suggest that microwave-induced surface restructuring and enhanced exposure of functional groups contribute to the improved biosorption capacity of TSAC. SEM analysis revealed the increased surface roughness, formation of cavities and pores as well as micro-cracks that can potentially facilitate the approach of MB molecules to their binding sites on the biosorbent surfaces. This valorisation of spent yeast biomass supports circular economy principles by converting enzyme production waste into an effective biosorbent for toxic pollutant removal.

Low permeability of China’s coal reservoirs and the high adsorption capacity of coalbed methane represent core constraints on coalbed methane extraction. Microwave heating technology has enhanced recovery rates in low-permeability reservoirs. However, existing studies typically simplify coal’s dielectric constant as a fixed value and adopt a single-point heating injection pattern. This study proposes a novel coalbed methane enhancement technique, based on directional drilling and continuous tubing technology, enabling large-scale coal seam heating. A fully coupled electromagnetic-thermal-fluid-solid model, incorporating the actual temperature-dependent dielectric properties of coal seams, was established. This model simulates and thoroughly investigates the enhancement and migration patterns of coalbed methane under varying microwave power levels. Results show microwave heating significantly promotes methane desorption and enhances reservoir permeability. 1600 W heating for 120 days, the effective desorption radius exceeded 3.6 m, with maximum permeability increases near the wellbore reaching 18.4%. Under 2400 W microwave irradiation, cumulative gas production reached 5781.5 m3, 15.7% higher than the 4996.3 m3 produced under the non-microwave heating. Due to excessively high power may cause overheating, 1600 W was determined as the optimal power level, balancing efficiency and safety. The study provides both theoretical foundations and practical strategies for optimizing microwave-enhanced coalbed methane recovery rates.

This study investigated the extraction of Elettaria cardamomum seed essential oil (EO) using microwave and ultrasound-assisted extraction techniques and evaluated its repellency activity against S. oryzae. Three extraction methods were evaluated: conventional hydrodistillation (HD), microwave-assisted hydrodistillation (MAHD), and ultrasonic pretreatment combined with microwave-assisted hydrodistillation (US+MAHD). Extraction conditions for MAHD were optimized using a Box-Behnken Design (BBD) and Response Surface Methodology (RSM) considering three factors: microwave time (min), microwave power (W), and solid-to-liquid ratio (g/mL). The developed quadratic model was significant (p < 0.05) showed a high coefficient of determination (R2 = 0.9933). The optimal extraction conditions predicted by the model were 15 min extraction time, 600 W microwave power, and a 1:6 solid–liquid ratio, with a predicted EO yield of 4.487%. Experimental validation under optimized conditions produced an EO yield of 4.5469 ± 0.0603%, confirming the adequacy and reliability of the model. US+MAHD achieved the highest EO yield (5.42%) with a shorter extraction time than HD. Major compounds identified by GC-MS were α-terpinyl acetate (35.13%), 1,8-cineole (33.43%), trans-sabinene hydrate acetate (8.38%), and linalool (6.94%). The EO exhibited complete repellency against Sitophilus oryzae at 1 μL/cm2 for 3 h. These findings demonstrate that RSM effectively optimized the MAHD process and that US+MAHD improved extraction efficiency while preserving the characteristic oxygenated monoterpene profile of the EO. Further studies are required to evaluate the stability and effectiveness of the EO under practical storage conditions.

Nanocellulose from passion fruit peel for starch-xanthan gum films and cherry tomato coatings.

NiO-shelled Ni-core (NiO@Ni) composites with tunable NiO/Ni ratios, in the presence or absence of conductive carbon supports, are widely recognized as low-cost and earth-abundant bifunctional electrocatalysts for overall water splitting. However, their practical performance remains constrained by sluggish formation of catalytically active γ-NiOOH phase and uncontrolled distribution of active sites. Herein, we report a highly efficient bifunctional electrocatalyst consisting of NiO@Ni with an optimized bulk NiO/Ni ratio anchored on biowaste-derived porous graphitic carbon (PGC), denoted as PGC-NiO@Ni, synthesized via a single-step microwave (MW)-induced N2 plasma-assisted disproportionation strategy. During this process, Ni salts undergo simultaneous oxidation and reduction to NiO and metallic Ni, respectively, with the NiO/Ni ratio regulated by MW irradiation time, power, and precursor stoichiometry. The optimized NiO/Ni ratio (0.75) enhances population and spatial distribution of active sites, while the conductive PGC support functions as an efficient electronic sink that mitigates surface charge accumulation on semiconducting NiO, thereby promoting rapid and unimpeded γ-NiOOH formation. Consequently, it delivers 195mV at 100mA cm-2 for the oxygen evolution reaction (OER) and 244mV at 100mA cm-2 for the hydrogen evolution reaction (HER), while a two-electrode electrolyzer operates at 1.50V with 165h stability and 98% Faradaic efficiency.

In narrow conductors, electron-electron collisions can create a viscous fluid state, allowing conductivity beyond ballistic transport into the superballistic regime. Point contacts made from ultrahigh-mobility two-dimensional electron gas serve as a platform to study this effect. Under microwave irradiation, edge magnetoplasmons in point contacts are excited and strongly influence electron dynamics. This study uses photoconductivity signals - changes from microwave exposure - to investigate superballistic electron flow, confirmed by size-dependent photoconductivity, magnetic field effects, and microwave power analysis. At low magnetic fields, weak microwaves lead to positive photoconductivity due to superballistic flow, while strong radiation causes negative photoconductivity because of enhanced phonon scattering.

Phytofabricated Silver Nanoparticles from Origanum majorana: Anti-Pathogenic Activity and Biocompatibility Evaluation.

Case study on steam-assisted solvent-free microwave extraction of black pepper essential oil: Comparative performance, kinetics, and process intensification against microwave hydrodistillation

The effect of microwave power on physicochemical properties of adlay seed starch after high-temperature storage

Microwave-assisted vacuum drying (MVD) is an emerging technology suitable for producing healthy snack foods, such as cheese snacks. This study aimed to produce a low-fat, low-salt, crunchy cheese snack using MVD. Low-fat, low-salt cheese slices were dried under seven different combinations of microwave power (5%-15%), vacuum level (220-300Torr), and drying time (6.5-11min), selected through preliminary trials. The resulting snacks were characterized by their physical properties and volatile compound profile. The results revealed significant differences in moisture content, water activity, bulk density, and volumetric/surface/cross-sectional expansion among the samples. Samples produced under high vacuum and long process time conditions exhibited the most favorable overall characteristics, including the lowest moisture, water activity, and density, alongside the highest volume expansion. These samples also showed a darker color and a superior crispy texture (higher fracturability with lower hardness, springiness, and chewiness). Twelve volatile compounds, with a profile limited by the low-fat content of the cheese, were detected. The TOPSIS analysis identified the sample produced under high vacuum conditions (dried at 10% power, 220Torr, 10min) as optimal. PRACTICAL APPLICATIONS: This study provides a roadmap for producing crunchy, low-fat, and low-salt cheese snacks using microwave vacuum drying. For food manufacturers, the identified optimal conditions offer a process guideline to develop a healthier snack alternative with an appealing texture and color. The systematic TOPSIS-based evaluation method can be adopted for quality control and product development decisions. For consumers, the resulting product aligns with growing demand for nutritious, reduced-sodium convenience foods.

Microwave drying (MWD) is a promising technique for dehydrating agricultural products due to its rapid volumetric heating, high energy efficiency, and superior preservation of product quality. However, the complex and nonlinear nature of microwave–material interactions, along with the spatial and temporal variability of dielectric properties, presents significant challenges for process modeling, control, and optimization. Traditional mathematical models often fall short in capturing these dynamics, which limits their use in adaptive or real-time process regulation. The goal of this review is to provide a comprehensive synthesis of artificial intelligence (AI) techniques applied to the microwave drying of agricultural products, focusing on predictive modeling, intelligent control, and optimization through a bibliometric analysis that covers literature from 2014 to 2024. Techniques such as artificial neural networks (ANNs), support vector machines (SVMs), adaptive neuro-fuzzy inference systems (ANFIS), and evolutionary algorithms are assessed for their effectiveness in modeling drying kinetics, predicting quality attributes, and supporting closed-loop control. Recent advancements in hybrid and ensemble models, real-time sensor integration, and multi-objective optimization are also examined. The review highlights current limitations in AI-based drying systems, including data scarcity, overfitting, poor model interpretability, and limited real-time deployment. It proposes strategic future directions, such as the adoption of explainable AI, digital twin frameworks, embedded edge computing, and sensor fusion for autonomous control. This work highlights the transformative potential of AI in developing intelligent, scalable, and energy-efficient MWD systems that align with the goals of Industry 4.0 and sustainable food engineering. • AI methods predict microwave drying behavior more effectively than classical models. • ANNs are widely used to model drying rates and moisture ratios from microwave parameters. • Hybrid AI models improve optimization of microwave power and temperature settings. • AI-driven control systems use sensor feedback and machine learning to adjust drying. • AI enables multi-objective optimization of energy use, time, and product quality.

Carbon dots (CDs) are versatile fluorescent nanomaterials with tunable optical properties and biocompatibility. Here, we report a rapid, sustainable microwave-assisted synthesis of nitrogen and sulfur co-doped red-emissive carbon dots (N,S-CFCDs) from alkaline-pretreated coconut fibers, a renewable carbon source. The synthesis was completed in 5min at 90°C under 300W microwave power, achieving a high yield of ∼85%. Nitrogen and sulfur codoping effectively tuned the optical properties, shifting emission from blue in undoped CDs to intense red in N,S-CFCDs. TEM, FTIR, XPS, Raman, and UV-Vis analyses confirmed uniformly distributed nanoparticles (∼5nm) with partially graphitized cores and N,S-enriched surface functionalities, resulting in strong red photoluminescence (λ_em ≈ 680nm), a quantum yield of ∼19%, and excellent aqueous stability. Leveraging these properties, N,S-CFCDs were employed as label-free fluorescent probes for creatinine detection, exhibiting concentration-dependent quenching with a low detection limit of 0.12nM, excellent linearity, and high selectivity against interfering biomolecules. Analytical performance in human serum, urine, and artificial cerebrospinal fluid showed recoveries of 95%-99.8%. This work demonstrates a sustainable strategy for converting biomass waste into high-value red-emissive nanoprobes, uniquely integrating synergistic N,S co-doping and green analytical validation to develop a high-performance platform for bioimaging, diagnostics, and environmental sensing.

This study investigates the microwave-assisted catalytic pyrolysis of polyetherimide (PEI). Activated carbon (AC), petroleum coke, graphite, silicon carbide, and AC-supported oxides (Fe₃O₄, Fe₂O₃, Al₂O₃, and ZnO) were chosen as microwave absorbers and/or catalysts to determine the impact of microwave absorber/catalyst type on the decomposition. Experiments were conducted at a microwave power of 400 W, which corresponded to an average bulk temperature of 400 °C, for 10 min in an argon atmosphere. No PEI remained intact after the treatments and the products were in the gas, liquid, wax, and solid phases, with the gas phase being the dominant fraction. Decomposition with the AC–Fe₃O₄ catalyst resulted in the highest gas yield and hydrogen production of up to 20 mmol g⁻¹ PEI, corresponding to 76% of the hydrogen content of PEI. Decomposition without metal oxides produced more wax, whereas metal oxides shifted the product distribution toward gases and/or aromatic condensates (notably toluene), depending on the oxide. The catalysts were deactivated by carbon deposition, degradation of the carbon support and/or reduction of metal oxide species. These results demonstrate that microwave-assisted catalytic pyrolysis of PEI enables hydrogen generation and the recovery of aromatic hydrocarbons (e.g., toluene, styrene, and naphthalene), highlighting its potential as a chemical recycling route for high-performance thermoplastics. • Microwave-assisted PEI decomposition achieved complete polymer conversion. • AC–Fe₃O₄ combined microwave absorption with high H₂ yield from PEI. • Catalyst choice controlled H₂ and aromatic recovery from PEI decomposition.

To study MEMS power detection chips more accurately, a thermo-electromechanical coupling model is proposed in this work. The fringing capacitance is included in the model, further refining the expression for the parallel-plate capacitance. Moreover, the squeeze-film damping and thermoelastic damping are considered in the second-order differential equation to study the cantilever vibration. It is found that the squeeze-film damping is the dominant damping of the system, and the cantilever beam exhibits linear expansion with increasing temperature. A dual-channel microwave detection chip is fabricated and measured, and the return loss reaches its minimum of −66.46 dB at 9 GHz, indicating optimal impedance matching at the central frequency. Moreover, the measured sensitivity is approximately 65.6 fF/W. Critically, the measured resonant frequency of the cantilever beam is 115.7 kHz, which is orders of magnitude lower than the input signal frequency. This large separation ensures that the sensor operates in a stable, non-resonant regime, thereby guaranteeing linearity and reliability. These findings demonstrate the excellent microwave performance of the power sensor fabricated in this work, providing valuable insights for optimizing the design of MEMS microwave power detection chips.

Here we report a successful synthesis of fluorescent carbon dots derived from salak (Salacca zalacca) peel waste via an eco-friendly microwave-assisted approach. The synthesis was conducted in aqueous medium at a microwave power of 450 W for only 9 minutes, demonstrating a significant reduction in energy consumption and reaction time compared to conventional hydrothermal approaches. The as-prepared CDs were characterized by UV-Vis absorption spectroscopy and Fourier-transform infrared (FTIR) spectroscopy. The UV-Vis spectroscopy revealed characteristic absorption peaks at 206 nm and 285 nm, attributed to π→π* transitions of aromatic C=C bonds and n→π* transitions of C=O groups, respectively, and FTIR analysis confirmed the presence of hydroxyl, carbonyl, and carboxyl functional groups on the CD surface. Photoluminescence (PL) spectroscopy used in Fe(III) sensing showing the fluorescence intensity of the CDs decreased significantly in the presence of Fe(III) ions. The CDs exhibited strong and selective fluorescence quenching in the presence of Fe(III) ions 1 μM . These findings highlight the potential of salak peel waste as a low-cost, eco-friendly precursor for the fabrication of functional nanomaterials with promising application in fluorometric heavy metal ion sensing.

Olive leaves are abundant in phenolic compounds; however, they tend to be underutilized because of their agricultural waste status. This study aimed to optimize the extraction of total phenolic compounds (TPC) from Olea europaea L. leaves collected from Edremit, Balıkesir, Türkiye, and dried by microwave. The Lewis model (r > 0.98) was determined to be the most appropriate to represent the drying kinetics of the olive leaves. The Box–Behnken design was used to evaluate the effect of microwave drying (180–450 W), extraction time (1–3 h), and ethanol concentration (0–50% v/v) on the extraction of the phenolic compounds. The optimal parameters for maximizing the extraction of the phenolic compounds were 183.61 W microwave power, 48.69% ethanol concentration, and 2 h 58 min extraction time, yielding 42.57 mg GAE/g dry leaf of total phenolic compounds that was also experimentally validated. The oleuropein content and antioxidant activity of the extract obtained under optimum conditions were analyzed.

This study investigated the influence of microwave (MW) on signal enhancement, shot-to-shot repeatability of emission signals, and parameters of laser-induced plasma (LIP) of soil samples. A neodymium-doped yttrium aluminum garnet (Nd:YAG) laser working at its fundamental wavelength, with energy ranging from 40 to 260 mJ was utilized in conjunction with MW power varying from 400 to 1200 W to generate plasma. The plasma emissions were recorded and analyzed with a spectrometer (LIBS 2500 Plus, Ocean Optics) at varying detector gate delay (DGD) up to 5 µs. At optimized laser energy of 140 mJ and MW power of 1.2 kW, the emission signal intensities and the signal-to-noise ratio (SNR) were enhanced by up to seven-fold and nine-fold, respectively, compared to conventional LIBS. Furthermore, MW coupling with plasma significantly improved LIBS repeatability by reducing the relative standard deviation (RSD) of emission line intensities from 38% to 11% and from 18% to 4%, for Mg and Si, respectively. Additionally, the MW-assisted LIBS also decreased shot-to-shot fluctuations in plasma temperature (Te) from 15% to 6%, and in electron density (Ne) from 14% to 7%. These improvements in sensitivity and stability due to MW-assisted LIBS pave the way for future quantitative analysis and the detection of trace elemental contaminants in soil at low concentration levels (e.g., ppm), which is a critical application in environmental monitoring.

A new integrated extraction strategy was established by combining natural solvent systems (NADES), microwave-assisted extraction, and machine learning techniques for optimizing the extraction of bioactive compounds from fermented watermelon rind. The results showed that solid-state fermentation significantly improved extraction rates, compared to non-fermented controls. The fermentation pretreatment comparison was conducted under identical extraction conditions, with non-fermented watermelon rind serving as the internal control. Machine learning models optimized using Bayesian optimization were developed to describe and predict three important response variables: TPC, TFC, and antioxidant activity, as functions of four extraction variables (microwave power, temperature, time, and solid-liquid ratio). The ensemble models showed outstanding predictive capabilities with test R² values of 0.9147, 0.9088, and 0.9252 for TFC, TPC, and DPPH activity, respectively, with very low overfitting (ΔR² < 0.06). Importance analysis of the features showed temperature as the most important parameter in the extraction of bioactive compounds (importance: 0.842-0.885), followed by solid-liquid ratio. Simultaneous optimization using the validated models showed the optimal extraction conditions to be 62.5°C, 27.7min, 300W, and 30mg/mL, predicting values of 1.656mg CE/g (TFC), 19.80mg GAE/g (TPC), and 71.27% (DPPH activity). Solid-state fermentation enhanced extraction yields, increasing total phenolics (16.9 to 19.1mg GAE/g), flavonoids (0.61 to 0.74mg CE/g), and DPPH activity (66% to 75%). The developed ensemble models showed high accuracy (R² = 0.91-0.93; RMSE = 0.0812mg/g, 0.51mg/g, and 0.74%). Experimental validation results have confirmed the high accuracy of the model with relative errors of less than 3% for all responses. The combination of fermentation pretreatment, green extraction, and machine learning indicates promise for sustainable valorization of agricultural waste resources as sources of bioactive compounds for nutraceutical applications.