Search Results (934)

Microwave-driven thermochemical cycles can split water for hydrogen production at temperatures far below those of conventional solar thermochemical routes, yet the responsible physical mechanisms remain unclear and numerical models for the coupled solar-microwave hybrid system are still scarce. Building on previous experimental work, we developed a coupled numerical model that integrates impedance matching, non-thermal enhancement, two-stage Arrhenius kinetics, and energy conservation to systematically investigate the interplay between microwave power, temperature evolution, and reaction progress. The model predictions agree well with experimental data in terms of temperature evolution trends, power threshold ranges, and reaction timescales. The results indicate that, within the present modeling framework, the effective microwave absorption efficiency increases from 1.2% at low temperatures to approximately 14% near 85 °C, with the non-thermal enhancement factor contributing as an empirical parameter. Under pure microwave mode, the required power threshold for reaction initiation is approximately 120 W; the solar-microwave synergistic mode reduces this threshold to about 70 W, a 42% reduction. At an input power of 100 W, the energy conversion efficiency reaches a maximum of 42%. Analysis of the sudden temperature change identifies 85 °C as the critical triggering temperature: below it, the system remains in a low-absorption cold state, while once crossed, a positive feedback mechanism rapidly propels the system into the high-temperature reaction regime. This study provides a numerical modeling framework for describing the coupled solar-microwave thermal behavior of the system and for guiding the optimization of its operational parameters. Since the available measurements cannot independently separate the thermal and non-thermal contributions, the non-thermal enhancement remains an empirically introduced factor rather than an experimentally established physical effect. Full article

This study investigates how non-ideal electromechanical actuation influences the emergence and modulation of complex dynamics in dissipative nonlinear systems. A hybrid four-dimensional model is formulated by coupling a continuous stirred tank reactor (CSTR) with Haldane substrate-inhibition kinetics to a non-ideal electromechanical power source, explicitly accounting for the bidirectional interaction between the mechanical driver and the biochemical process. Numerical simulations and Lyapunov spectrum analysis are employed to characterize the resulting nonlinear dynamics and synchronization properties. The results show that the mechanical subsystem can evolve toward a high-energy chaotic regime with non-ideal rotational velocity pulsations, while the reactor subsystem retains a negative conditional Lyapunov exponent over a broad parameter range despite the presence of global chaos. This dynamical configuration characterizes generalized synchronization, in which the dissipative reactor response becomes functionally constrained by the chaotic mechanical attractor. In addition, the parametric analysis demonstrates that variations in coupling strength can either transmit complex oscillatory behavior or suppress chaos, depending on the operating regime. These findings indicate that aperiodic oscillations in process variables may originate from deterministic electromechanical coupling rather than intrinsic chemical instabilities and highlight the dual role of non-ideal actuation as both a source of nonlinear complexity and a potential mechanism for stabilization and control in hybrid engineering systems. Full article

Conventional anaerobic digestion (AD), despite its proven efficiency in wastewater treatment, faces limitations due to energy requirements and extended hydraulic retention times, with methane yields from waste-activated sludge rarely exceeding 50% of the stoichiometric maximum at retention times of 20 days or more and with the resulting biogas containing 50–75% methane. It also has a constrained capacity for high-grade resource valorization except energy in the form of methane-enriched biogas. This review focuses on bioelectrochemical systems (BES) and hybrid configurations as promising alternatives for sustainable wastewater management. BES mechanisms, including microbial fuel cells (MFC), microbial electrolysis cells (MEC), and microbial electrosynthesis (MES), are analyzed in detail, with emphasis on their capacity to directly convert organic pollutants into electricity or high-value chemicals (hydrogen, acetate) with minimal external energy input. Key advantages include potential electrical energy production, significantly reduced excess sludge production, and high level of waste mineralization. Reported performance reaches power densities of 2203 and 4990 mW/m² for sludge-fed microbial fuel cells and up to 26,680 mW/m² in algae-assisted configurations, chemical oxygen demand (COD) removal of up to 92%, and excess sludge production of 0.09 g/g COD against 0.159 g/g COD for anaerobic digestion treating the same stream. Limitations in terms of scalability and capital costs remain barriers to industrial implementation. Special attention is given to hybrid configurations integrating BES with AD through direct interspecies electron transfer (DIET), which accelerates biodegradation kinetics and enhances resource recovery pathways; compiled MEC-AD data report methane increases of about 3–228% over unpolarized controls, and in a 1.7 L reactor treating alkaline-thermally pretreated waste-activated sludge, the optimum of 0.6 V raised the methane yield from 213.2 ± 9.5 to 308.7 ± 5.9 mL CH₄/g COD removed. These integrated approaches close material and energy cycles, enabling the simultaneous recovery of energy, nutrients (N, P), and bio-chemicals, transforming wastewater treatment plants into zero-waste biorefineries aligned with circular economy principles. Full article

Flocculation is a physicochemical process with critical relevance to industrial and environmental operations, including potable water production, wastewater remediation, mineral processing, papermaking, and food manufacturing. The efficiency of flocculation is determined by the chemical nature, molecular structure, and physicochemical interactions of flocculants with suspended colloidal matter. Conventional synthetic polyacrylamides, available in nonionic, anionic, and cationic forms, function predominantly via electrostatic neutralization, polymer chain bridging, and sweep flocculation induced by precipitated hydroxides. Their high molecular weight, customizable charge density, and cost-effectiveness have consolidated their industrial dominance. However, the inherent resistance of polyacrylamides to biodegradation in combination with its monomer’s toxicity and increasing regulatory pressure have accelerated research toward sustainable alternative materials. Recent developments include functionalized natural polysaccharides (e.g., chitosan, cellulose derivatives, starch esters), bio-based copolymers, and nanoengineered hybrid systems incorporating inorganic domains to enhance colloid destabilization and sedimentation kinetics. This review systematically examines the physicochemical principles underlying flocculation, evaluates the performance parameters and limitations of polyacrylamides, and highlight emerging strategies for sustainable flocculant design. Prospects for the next generation of flocculation technologies are discussed in the context of mechanistic optimization, ecological safety, and compliance with evolving environmental regulations. Full article

Photocatalytic wastewater treatment is a promising technology for degrading persistent organic pollutants; however, its optimization remains challenging because photocatalytic performance depends on complex interactions among catalyst properties, operating conditions, and wastewater composition. Machine learning (ML) has emerged as a powerful tool for accelerating catalyst development, predicting photocatalytic performance, and optimizing process parameters. This review critically analyzes recent studies on ML-assisted photocatalytic wastewater treatment, covering supervised learning, ensemble learning, deep learning, and hybrid optimization approaches for predicting degradation efficiency, reaction kinetics, and catalyst performance. Rather than simply summarizing existing studies, the review compares the strengths, limitations, and applicability of different ML models while evaluating the influence of dataset quality, feature engineering, and validation strategies on predictive reliability. Emerging developments in explainable artificial intelligence, physics-informed machine learning, digital twins, and autonomous catalyst discovery are also discussed. Current challenges, including limited datasets, data heterogeneity, model overfitting, lack of standardized benchmarking, and poor transferability to real wastewater systems, are critically examined. Finally, future perspectives emphasizing standardized datasets, interpretable AI, rigorous model validation, and intelligent catalyst design are proposed. This review provides a practical roadmap for integrating artificial intelligence with photocatalysis to accelerate the development of reliable and sustainable wastewater treatment technologies. Full article

The extensive use of pesticides in modern agriculture has resulted in their persistent accumulation in environmental systems, posing significant risks to ecosystems and human health. Consequently, the development of integrated strategies for the sensitive detection and efficient removal of pesticide residues has become critically important. In this context, fluorescent inorganic–organic hybrid nanoparticles have emerged as versatile platforms owing to their tunable physicochemical properties and distinctive optical behavior. This review provides a comprehensive overview of recent advances in these hybrid nanomaterials for pesticide sensing and remediation. Particular emphasis is placed on the underlying photophysical mechanisms governing detection, including fluorescence quenching, Förster resonance energy transfer (FRET), inner filter effect (IFE), and photoinduced electron transfer (PET). In parallel, the role of interfacial interactions such as hydrogen bonding, electrostatic attraction, and π–π stacking in adsorption processes is critically discussed. Furthermore, these hybrid systems exhibit high adsorption capacities and rapid removal kinetics, enabling efficient pesticide elimination using both adsorption and catalytic degradation pathways. Overall, this review underscores the potential of fluorescent inorganic–organic hybrid nanoparticles as next-generation materials for sustainable environmental monitoring and remediation of pesticide contaminants. Full article

Backgorund/Objectives: Respiratory diseases represent a substantial global health burden and require effective localised pulmonary delivery strategies, particularly for poorly water-soluble therapeutic molecules. Nanoparticle-based drug delivery systems, especially those manufactured using microfluidics, have emerged as promising approaches to overcome pulmonary barriers, enhance local drug retention, and reduce systemic side effects. Among these nanocarriers, solid lipid nanoparticles (SLNs) and solid hybrid nanoparticles (SHNs) combine biocompatibility with controlled release and improved formulation stability. Methods: In this study, SLNs and lipid–chitosan SHNs were developed using microfluidic technology as candidate platforms for pulmonary drug delivery, with Cyclosporine A (CyA) used as a model hydrophobic cyclic peptide. Nanocarriers were produced using 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and cholesterol as lipids, with low-molecular-weight chitosan incorporated to obtain hybrid systems. Physicochemical properties were evaluated using dynamic light scattering (DLS) and ζ potential measurements, while morphology and structural organisation were investigated using transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). Results: The microfluidic approach enabled the production of nanoparticles with controlled sizes below 200 nm, narrow size distributions, and good reproducibility. In addition, the SHNs exhibited a positive surface charge, high encapsulation efficiency (~80%), and good colloidal and thermal stability. In vitro release studies showed an initial burst release followed by sustained CyA release, reaching approximately 94% cumulative release within 6 h. The Korsmeyer–Peppas model was used as the standard kinetic model. No blank nanoparticles were used as controls in the EE and release assay. Conclusions: Overall, these findings support further investigation of microfluidic-produced lipid and hybrid nanoparticles as candidate platforms for pulmonary drug delivery. Full article

Redox-active polymers have become an important component of second-generation electrochemical biosensors, solving the problem of efficient charge transfer between the biological recognition material and the electrode surface. In this review, we discuss the basic design principles, electron transfer mechanisms, and synthesis strategies from the perspective of biosensor applications. Three main classes of redox centers are considered—metal complexes, metallocenes, and organic radicals—as well as polymer matrices, and the factors affecting their stability and operability are discussed. Particular attention is paid to hybrid nanocomposites based on carbon nanotubes, graphene, and metal nanoparticles. The review concludes that despite significant advances in molecular design and the development of nanocomposites, the commercialization of biosensors based on redox polymers is hindered by unresolved issues related to biofouling, metal center instability, and low reproducibility. This emphasizes the need for standardized synthesis and integration of machine learning-based design to achieve a balance between electron transfer kinetics, biocompatibility, and operational properties. Full article

Thermal drying is a critical phase in coffee processing, significantly influencing energy consumption, moisture uniformity, storage stability, and sensory quality. Despite the superior throughput of mechanical dryers over open-sun drying, these systems often operate with limited observability and manual control. This systematic review evaluates the readiness of mechanical coffee drying for Digital Twin (DT) integration. A comprehensive search across Scopus, Web of Science, IEEE Xplore, and ScienceDirect identified 22,859 records. Following multi-stage screening, 58 studies were retained for qualitative synthesis, categorized into a primary coffee-drying corpus and a secondary transferable corpus of methods from related food-processing applications. Findings indicate that while DT-enabling components, such as CFD models, drying-kinetics models, IoT monitoring, and non-destructive sensing, are established, they remain fragmented. No fully implemented and operationally validated DT for mechanical coffee drying was identified. Based on the evidence, a hybrid reduced-order physics-based model integrated with constrained supervisory control represents the most defensible near-term architecture. Future research should prioritize standardized datasets, uncertainty-aware soft sensors, and field validation across diverse dryer topologies and operating conditions. Full article

Background: Patient-specific targeted radionuclide therapy (TRT) requires consideration not only of administered activity but also of the spatial distribution of radiopharmaceutical uptake and radionuclide-specific energy deposition. This study developed a voxel-based computational workplan to compare ¹⁷⁷Lu, ¹⁶¹Tb and ⁹⁰Y, together with hybrid radionuclide models, using patient-specific PSMA PET-derived tumour activity distributions. Methods: PSMA PET/CT data from 20 patients with prostate cancer, comprising 10 ¹⁸F-PSMA and 10 ⁶⁸Ga-PSMA examinations, were processed to obtain 2285 quality-filtered lesions. Radionuclide-specific dose-point kernels (DPKs) were generated in water using OpenGATE and applied to voxel-wise lesion activity distributions to reconstruct absorbed-dose maps. Kernel characteristics were evaluated using radial energy-containment metrics, and ¹⁷⁷Lu, representing ¹⁶¹Tb simulations, was subjected to grid-convergence testing and external comparison with a published DPK. Lesion dosimetry was assessed using Dmean, D90, D95, equivalent uniform dose (EUD) and tumour control probability (TCP), with uncertainty quantified using patient-cluster bootstrap confidence intervals. Kinetic sensitivity and diagnostic tracer subgroup analyses were additionally performed. Results: The study showed that ¹⁶¹Tb produced the highest median lesion-level Dmean, D90, D95 and EUD at 182.79, 136.28, 132.07 and 148.53 Gy, respectively, with a median TCP of 0.981. Corresponding values for ¹⁷⁷Lu were 141.33, 105.42, 102.10 and 114.78 Gy (TCP 0.930), while ⁹⁰Y produced lower local dose metrics but the broadest radial dose distribution, consistent with its longer-range β-particle crossfire. ¹⁶¹Tb remained the highest-ranking radionuclide across the investigated kinetic cases and within both diagnostic tracer subgroups. Hybrid ¹⁶¹Tb/⁹⁰Y kernels provided a controllable compromise between localised energy deposition and extended crossfire; a 70:30 model increased central dose localisation while retaining an R90 and R95 of 6 and 7 mm, respectively. Grid-convergence and published-DPK comparisons supported the numerical adequacy of the kernel methodology. Radionuclide emission characteristics substantially influence the transformation of heterogeneous tumour uptake into spatial absorbed-dose distributions. Within this model, ¹⁶¹Tb provided the strongest overall lesion-level dosimetric performance, whereas the extended range of ⁹⁰Y may offer complementary crossfire for selected bulky or heterogeneous lesions. Conclusions: The findings support phenotype-informed radionuclide comparison and provide a computational basis for investigating hybrid strategies. However, the absolute dose estimates and proposed radionuclide combinations remain model-based and require validation using serial therapeutic imaging, heterogeneous patient-specific dosimetry and normal-organ dose constraints before clinical translation. Full article

To address cathode passivation, performance deterioration, and toxic stress during the removal of hexavalent chromium [Cr(VI)] in biocathode microbial fuel cells (MFCs), this study constructed nanomaterial-hybridized biocathodes to improve electricity generation and Cr(VI) removal in MFCs. Reduced graphene oxide (rGO), nano-iron sulfide (nano-FeS), and rGO/nano-FeS were separately hybridized with biocathodes to systematically investigate the effects of different hybridized biocathodes on the performance of MFCs for Cr(VI)-containing wastewater treatment. The results showed that the FeS group exhibited the best Cr(VI) removal capability, with a maximum removal kinetic constant of 0.184 h⁻¹, which was 3.60 times that of the Control group, and showed the smallest performance decline after three consecutive cycles. Mechanistic analysis indicated that nano-FeS promoted the transformation of Cr(VI) into Cr(III) and Cr(0) through its strong adsorption and reducing capacities; it also enhanced biofilm cell activity and the protein/polysaccharide ratio in extracellular polymeric substances; furthermore, it shaped a multi-taxon-dominated microbial community capable of Cr(VI) tolerance and reduction and enhanced the associated metabolic functions, thereby improving resistance to Cr(VI) stress and effectively alleviating cathode passivation. In contrast, rGO tended to enhance biocathode conductivity and electricity generation in MFCs, with the rGO + FeS group achieving the highest power density output of 51.54 ± 3.62 mW/m², which was 1.22 times that of the Control group, as well as the smallest decline in power density after three consecutive cycles. Overall, nanomaterial hybridization reshaped interfacial electron transfer and microbial stress resistance in biocathodes, enabling efficient Cr(VI) removal and stable electricity generation, and providing a new strategy to construct long-term stable bioelectrochemical systems for heavy metal-containing wastewater treatment. Full article

Polysaccharide-based organic-inorganic hybrid carriers combine renewable polymer matrices with inorganic phases that can modify mechanical integrity, swelling, barrier performance, payload retention, and release behavior. This review critically evaluates alginate as a reference matrix together with chitosan, cellulose/nanocellulose, starch/maltodextrin, pectin, carrageenan, and related polysaccharides, focusing on how matrix chemistry, inorganic-phase properties, interfacial interactions, and fabrication route govern encapsulation efficiency, loading, structural stability, swelling, mechanical and barrier properties, storage retention, and release kinetics. Silica and mesoporous silica, clays and halloysite, layered double hydroxides (LDHs), metal oxides, hydroxyapatite, magnetic particles, and metal-organic frameworks are compared according to their reservoir, reinforcing, diffusion-controlling, responsive, and safety-related functions. Representative quantitative findings illustrate the importance of hybrid architecture; for example, incorporation of LDHs into an alginate matrix reduced erythropoietin release after 108 h from 86% to 24% while increasing mechanical performance by approximately 5–30-fold. In this review, particular attention is given to volatile and bioactive compounds, for which storage retention, oxidation stability, headspace behavior, and application-relevant release are as important as initial encapsulation efficiency. Key challenges, such as long-term stability, standardization of release studies, scalability, safety assessment, and performance in real formulations, are also discussed, together with future directions for sustainable, application-specific hybrid carrier systems. Overall, the review provides a structure-property-application framework for selecting matrix-filler-processing combinations for controlled-release systems. Full article

Most active pharmaceutical ingredients (APIs) reach their target by passive systemic distribution, so the dose required for efficacy at the lesion is set by what healthy tissue can tolerate; conventional dosage forms consequently produce pharmacokinetic profiles that oscillate between toxic peaks and sub-therapeutic troughs. Nanoparticulate carriers (liposomes, lipid nanoparticles, polymeric and inorganic systems, and biomimetic carriers) and hydrogels (natural, synthetic, supramolecular, and microgel-assembled) have emerged as the dominant strategies to address this, increasingly combined as hybrid nanoparticle–hydrogel constructs in which the gel provides locoregional retention and the nanoparticles provide cargo protection, intracellular delivery and stimuli responsiveness. Stimuli-responsive chemistries (pH, redox, enzyme, ROS, hypoxia, temperature, light, magnetic, ultrasound, glucose, and multi-stimuli logic) translate the molecular signatures of a disease into spatiotemporally controlled cargo release. This narrative review consolidates the state of the art (prioritizing 2022–2026) and departs from the conventional carrier-type survey in one respect: the literature is read along an explicit chain—disease cue, sensing chemistry, carrier architecture, release mechanism and kinetics, administration route, and clinical readiness—which exposes a variable that classification by carrier type conceals. Across all three material classes, what governs release behavior is not primarily the carrier chemistry but the identity of the released species (dissolved drug, drug from an embedded nanoparticle, an intact nanoparticle, and a matrix fragment) and the transport step that limits it. This is why power-law exponent analysis developed for dissolved drug fits particulate release poorly, why statistical goodness-of-fit cannot by itself establish a release mechanism, and why carrier class predicts clinical readiness less well than administration route and regulatory product type. Translational hurdles—CMC complexity, regulatory fragmentation, anti-PEG immunogenicity, and the structural mismatch between preclinical promise and clinical efficacy—are critically appraised in light of previously reported <1% delivery efficiency analysis. This review identifies converging strategies that could move stimuli-responsive controlled release from an aspirational outcome to a routine clinical reality. Full article

Phenolic aerogels, owing to their low density, high char yield, large specific surface area, and well-defined three-dimensional topological networks, hold considerable promise for applications in extreme thermal protection and multifunctional material systems. The sol–gel process, a cornerstone methodology for constructing the three-dimensional nanoporous architecture of these materials, critically governs the resulting microstructural topology and macroscopic performance through its reaction kinetics, phase-separation behavior, and drying dynamics. This review systematically surveys recent advances in the sol–gel synthesis of phenolic aerogels, focusing on the polycondensation mechanisms operative under acidic and basic catalytic conditions, nucleation-and-growth kinetics, and strategies for tailoring multiscale pore structures. It further provides a comparative analysis of interfacial regulation mechanisms for capillary-stress elimination across supercritical drying, freeze-drying, and ambient-pressure drying routes. We also dissect the structure–property relationships underpinning Knudsen-effect-mediated gaseous thermal insulation, multi-scale hybrid network toughening, and inorganic phase-transition-induced in situ ceramization for thermal protection, demonstrating the synergistic optimization of thermal insulation, structural load-bearing, and ablation resistance. Finally, we summarise current applications in extreme thermal protection, environmental adsorption, electromagnetic interference shielding, and electrochemical energy storage and highlight future directions towards green, scalable manufacturing and intelligent materials design. Full article

Modern pyrotechnic materials are evolving from conventional fuel–oxidizer mixtures toward function-oriented energetic systems designed for controlled ignition, light emission, gas generation, pressure output and thermal response. This review analyzes recent progress in pyrotechnic materials through oxidizer chemistry, thermal and kinetic behavior, study-normalized performance comparison and bibliometric mapping. Representative oxidizer families, including nitrates, perchlorates, chlorates, metal oxides, hybrid oxide–salt systems, high-nitrogen salts, halogen-oxo oxidizers and coordination nitrate complexes, are compared in terms of chemical role and functional output. Thermal data show that decomposition temperature, heat release and activation energy must be interpreted together, since lower activation energy can indicate either enhanced reactivity or degradation during aging. A study-normalized relative performance factor (RPF) was used to compare performance changes within individual publications. The strongest relative improvements were associated with oxide selection, particle-size reduction, hybrid oxidizer design and coupling of nanothermites with gas-generating components. Bibliometric mapping confirmed a shift toward metal-based energetic materials, nanothermites, gas generators, combustion diagnostics, color systems and pyrotechnic devices. These trends show that oxidizer chemistry, particle architecture and additive function are increasingly selected for defined pressure, gas, light or thermal outputs. Full article