Search Results (31)

The nucleation and growth mechanisms of copper electrodeposition from Cu(I)-containing-reline, a deep eutectic solvent, were investigated through a combination of electrochemical techniques and surface characterization. Cyclic voltammetry revealed the characteristic nucleation loop associated with an overpotential-driven electrocrystallization process, from which the equilibrium potential of the Cu(I)/Cu(0) redox couple was determined to be −0.35 V vs. a Ag quasi-reference electrode. Experimental potentiostatic current density transients were analyzed using nucleation models capable of accounting for both adsorption and three-dimensional (3D) diffusion-controlled growth, thereby allowing deconvolution of the individual contributions to the overall current response. The kinetic parameters, including the nucleation frequency and the number density of active sites, exhibited an exponential dependence on the applied overpotential, thus indicating enhanced nucleation kinetics at greater driving forces, while determining a Cu(I) diffusion coefficient of (3.39 + 0.09) × 10⁻⁷ cm² s⁻¹. Thermodynamic analysis showed that the Gibbs free energy of the formation of the critical nucleus decreases with increasing overpotential and follows the expected dependence on the inverse square of the overpotential, in agreement with classical nucleation theory. The estimated critical nucleus size was found to be smaller than one atom, suggesting that nucleation occurs at highly active surface sites. Furthermore, an exchange current density of (3 ± 1) μA cm⁻² was estimated for the Cu(I) electrochemical reduction. Scanning electron microscopy revealed a high density of copper nanoparticles (~20 nm) distributed across the electrode surface, along with larger aggregates (~100 nm) formed by coalescence and growth, consistent with a progressive nucleation mechanism. X-ray photoelectron spectroscopy confirmed that the deposits consist exclusively of metallic copper, with no evidence of oxidized species. These results demonstrate that copper electrodeposition in reline is governed by a complex interplay between the thermodynamic driving force, the interfacial kinetics, and mass transport, comprehensively providing fundamental insight into the electrocrystallization processes in deep eutectic solvents. Full article

Background/Objectives: Non-covalent nanocarrier-based systems have become a promising platform as they offer a strategy to improve the efficacy-safety profile of doxorubicin (DOX) without altering its chemical structure. Praised for biocompatibility and rich surface chemistry, nanodiamonds (NDs) have launched as nanocarriers of choice for advanced cancer therapy. By investigating DOX-ND physicochemical interactions, this work advances the structural understanding of a non-covalent potential anticancer system, which has not been quantitatively experimentally explored so far. Methods: To our knowledge, this is among the first studies combining ultraviolet–visible (UV–VIS) spectroscopy with spectral deconvolution to reveal the redistribution of different DOX species in the presence of NDs. Centrifugation-assisted analysis enabled differentiation between hypothetical labile and stable ND/DOX fractions. Adsorption kinetics was studied, and dynamic light scattering (DLS) measured particle size and zeta potential. In vitro screening was performed in non-malignant fibroblasts (MRC-5) and malignant melanoma (HS294T), glioblastoma (U251), and breast cancer (MCF-7) cells to evaluate ND/DOX combinations. Results: Centrifugation analysis revealed heterogeneous ND-DOX binding. Kinetic experiments showed fast multi-stage adsorption kinetics, best described by a bi-exponential decay function and the Weber–Morris model. DLS suggested stable systems with a particle size within 10–80 nm, predominantly around 20 nm, and positive zeta potential. Comparative in vitro screening demonstrated differential cellular responses across cell types, highlighting the relevance of ND/DOX interactions. Conclusions: The findings contribute to elucidating ND-DOX interactions relevant for the design and optimization of drug delivery systems, emphasizing the importance of spectroscopic insights for the design of nanodiamond-based drug delivery systems. Full article

RNA origami enables genetically encoded, single-stranded RNA nanostructures that can self-assemble through co-transcriptional folding and are increasingly deployed as scaffolds for biosensing, synthetic biology, and nanomedicine. A recurring practical bottleneck is scalable, solution-phase readout of whether a designed scaffold has reached its intended base-paired architecture, whether it undergoes slow maturation or kinetic trapping, and how its stability is distributed across motifs. Here, we adapt microfluidic modulation spectroscopy (MMS) as a label-free structural biosensor for RNA folding by exploiting the rich 1760–1600 cm⁻¹ vibrational fingerprints of RNA bases and base pairs. MMS alternates between sample and composition-matched buffer measurements in a microfluidic transmission cell to automatically subtract the solvent background, enabling high-quality spectral measurement from microliter volumes under native solution conditions. Using a six-helix-bundle-with-clasp (6HBC) RNA origami as a model, we established an analysis workflow (baselined second derivative and constrained deconvolution) to quantify paired versus unpaired populations. Thermal ramping resolves multiple unfolding events and yields an unfolding barcode that differs between young and mature ensembles. Importantly, MMS tracks post-transcriptional maturation from a kinetically trapped young conformer toward a more compact, base-paired mature state, consistent with prior cryo-EM/SAXS observations for 6HBC RNA origami. Together, these results position MMS as a rapid, automated, and scalable complement to high-resolution structure determination for engineering dynamic RNA origami biosensors. Full article

Glycidyl azide polymer (GAP)-based polyurethane, a kind of energetic thermoplastic elastomer (ETPE), is a promising binder for advanced solid propellants, but its thermal decomposition involves overlapping competitive reactions that conventional single-step kinetic models cannot characterize accurately, limiting its engineering applications. To address this limitation, a constrained asymmetric Gaussian deconvolution strategy with fixed peak area ratios and shape constraints was developed in this work. This strategy was applied to resolve overlapping reaction rate curves converted from derivative thermogravimetric data of GAP-based ETPEs with 50 wt% GAP content at four heating rates of 5, 10, 15 and 20 K·min⁻¹. The complex decomposition process was successfully split into five stages, assigned to azide cleavage, polyether backbone scission, carbamate cleavage, hydrocarbon product degradation and residue decomposition, with a goodness of fit of R² > 0.998. Apparent activation energies of the five stages were determined through cross-validation by the Friedman and Flynn–Wall–Ozawa methods without prior assumption of reaction mechanisms, following the order of residue decomposition (181.4 ± 1.0 kJ·mol⁻¹) > hydrocarbon product degradation (159.9 ± 1.0 kJ·mol⁻¹) ≈ azide cleavage (156.5 ± 0.6 kJ·mol⁻¹) > backbone scission (135.1 ± 0.7 kJ·mol⁻¹) > carbamate cleavage (111.9 ± 1.1 kJ·mol⁻¹). Pre-exponential factors with lnA₀ values ranging from 22.2 to 34.0 were derived via the kinetic compensation effect. Finally, generalized master plots were employed to compare with classic solid-state reaction models for mechanistic insight, and the Šesták–Berggren model fit three major stages excellently (R² > 0.996) by accounting for synergistic nucleation-growth and phase boundary mechanisms, enabling high-precision kinetic equations. It should be noted that the constrained deconvolution method proposed in this work has general applicability for kinetic analysis of GAP-based ETPEs with different formulations and other complex energetic polymer systems, while the obtained kinetic parameters are composition-specific and only applicable to the corresponding ETPE formulation studied herein. Full article

This study examined the thermal degradation of pulverized Musa sapientum (banana) peel waste through thermogravimetric measurements and thermokinetic modelling. For the first time, it also incorporated backpropagation deep learning to model pyrolysis traces, enabling the prediction and optimization of the process. Physicochemical characterization confirmed the material’s lignocellulosic composition. TGA was performed between 30 and 950 °C at heating rates of 5, 10, 20, and 40 °C min⁻¹, identifying a primary devolatilization range of 190 to 660 °C. The application of a backpropagation machine learning technique to the processed TGA data enabled the estimation of arbitrary constants that accurately captured the characteristic behaviour of the experimental data ($R^2~0.99$). This modelling and simulation approach achieved a significant reduction in training loss—decreasing from 35.9 to 0.07—over 47,688 epochs and 1.4 computational hours. Sensitivity analysis identified degradation temperature as the primary parameter influencing the thermochemical conversion of BP biomass. Furthermore, analyzing deconvoluted DTG traces via Criado master plots revealed that the 3D diffusion model (Jander [D3]) is the most suitable reaction model for the hemicellulose, cellulose, and lignin components, followed by the R2 and R3 geometrical contraction models. The estimated overall activation energy values obtained through the Starink (STK) and Friedman (FR) model-free isoconversional kinetic methods were 82.8 ± 3.3 kJ.mol⁻¹ and 97.6 ± 3.9 kJ.mol⁻¹, respectively. The thermodynamic parameters estimated for the pyrolysis of BP indicate that the formation of activated complexes is endothermic, endergonic, and characterized by reduced disorder, thereby establishing BP as a potential candidate material for bioenergy generation. Full article

This report focuses on the oxalate anion radical (C₂O₄^●−) formed during γ-radiolysis of polycrystalline oxalates: protonated oxalic acid (H₂C₂O₄·2H₂O), caesium oxalate (Cs₂C₂O₄), and potassium oxalate monohydrate (K₂C₂O₄·H₂O). Irradiation at 77 K generates stable radical species, revealed by EPR spectroscopy and supported by DFT calculations. In H₂C₂O₄·2H₂O, the primary axial signal (g_avg = 2.0035) is shown to arise from the structural relaxation of the HC₂O₄∙ radical into the intrinsically stable non-planar (D_2d) conformation, resolving the symmetry conflict with the planar crystal precursor. Numerical deconvolution confirmed the co-existence of this radical with the secondary HCO₂^● species, exhibiting distinct relaxation characteristics. In Cs₂C₂O₄, the broad isotropic signal (g ≈ 2.008) is attributed to the D_2d form. Quantitative analysis proved a sharp, thermodynamically driven structural conversion (D_2d→D_2h) upon annealing above 220 K, where the D₂h conformer (g_avg ≈ 2.011) becomes the dominant species (≈73%). In K₂C₂O₄·H₂O, the C₂O₄^●− radical undergoes rapid decomposition into the CO₂^●− radical (g_avg ≈ 2.0007) due to the kinetic instability of the primary species in that matrix. Our findings underscore the crucial role of computational assistance and quantitative numerical fitting in EPR studies: DFT provided crucial assistance and yielded satisfactory agreement in most cases, while clarifying the structural and kinetic stability governed by the local cationic environment. The stability of the most resistant radical forms persists up to 430 K in the caesium salt. Full article

In this study, thermogravimetric analysis (TGA) was coupled with Fourier-transform infrared (FTIR) spectroscopy to systematically investigate the pyrolysis characteristics and mechanisms of cement fiberboard across varying heating rates. Experimental findings demonstrated that the thermal degradation process occurs in four distinct phases. Overlapping decomposition peaks in DTG curves were successfully resolved using a double-Gaussian deconvolution algorithm. A comprehensive kinetic analysis was conducted by integrating model-free iso-conversional methods (Flynn–Wall–Ozawa and Kissinger–Akahira–Sunose analysis) with a model-fitting technique (Coats–Redfern approximation) to determine the activation energies for each degradation stage. A subsequent FTIR spectroscopic analysis revealed that the evolution of gaseous products follows the sequence CO₂ > H₂O > CH₄. The CO₂ release was found to originate from multiple pathways, including the decomposition of organic components and high-temperature inorganic reactions. Notably, while the heating rate had a negligible impact on product speciation, it exhibited a statistically significant influence on CO₂ emission intensities. Finally, mechanistic interpretations integrating Arrhenius parameters with time-resolved infrared spectral features were proposed for each thermal decomposition stage. Full article

The present study presents a comparative evaluation of two analytical deconvolution models applied to Optically Stimulated Luminescence (OSL) decay curves of zirconia-reinforced lithium silicate (ZLS), a glass-ceramic material with potential applications in accidental dosimetry. ZLS samples were subjected to beta irradiation and measured under Continuous Wave OSL (CW-OSL) protocols. A comparative analysis is conducted between two deconvolution approaches—the General Order Kinetics (GOK) model and a master analytical equation based on the Lambert W function. The results imply that both models yield a linear dose-response behavior of the fast OSL component; however, the Lambert W approach offers simpler fitting with fewer parameters. The abovementioned findings demonstrate the methodological robustness of the Lambert W formalism and also confirm that ZLS is a promising dosimetric material, aligning with the goals of protocol development in material characterization. Full article

This study analyzes the thermal degradation of PVA and PVA/glycerol films in air under varying heating rates. Thermogravimetric analysis (TGA) of pure PVA in both air and inert atmospheres confirmed that oxidative conditions significantly influence degradation, particularly at lower heating rates. For PVA/glycerol films in air, deconvolution of the differential thermogravimetry (DTG) curves during the main degradation stage revealed distinct peaks attributable to the degradation of glycerol, PVA/glycerol complexes, and PVA itself. Isoconversional methods showed that, for pure PVA in air, the apparent activation energy (Ea) increased with conversion, suggesting the simultaneous occurrence of multiple degradation mechanisms, including oxidative reactions, whose contribution changes over the course of the degradation process. In contrast, under an inert atmosphere, Ea remained nearly constant, consistent with degradation proceeding through a single dominant mechanism, or through multiple steps with similar kinetic parameters. For glycerol-plasticized films in air, Ea exhibited reduced dependence on conversion compared with that of pure PVA in air, with values similar to those of pure PVA under inert conditions. These results indicate that glycerol influences the oxidative degradation pathways in PVA films. These findings are relevant to high-temperature processing of PVA-based materials and to the design of thermal treatments—such as sterilization or pyrolysis—where control over degradation mechanisms is essential. Full article

The thermoluminescence (TL) method is one of the most widely used techniques in various studies, including dosimetric applications, dating of archaeological and geological materials, luminescence spectroscopy of certain insulating or semiconducting phosphors, and the detection of ionizing radiation damage. This study examines the TL properties of plagioclase, a feldspar group mineral, focusing on its dose–response behavior, kinetic parameters, and glow curve characteristics. TL measurements of plagioclase samples were carried out with different ionizing radiation doses ranging from 0.1 to 550 Gy. The results show a strong linear dose–response relationship in the 0.3–550 Gy range, with no evidence of saturation or supralinearity. A computerized glow curve deconvolution (CGCD) analysis revealed that the TL glow curve of the mineral consists of five distinct TL peaks with activation energies ranging from 0.842 eV to 0.890 eV and obeying general order kinetics. In addition, an artificial neural network (ANN) model was developed to predict TL glow curves using three optimization algorithms, including Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). Among these, the BR algorithm demonstrated the best performance with an accuracy value of 0.99915, a Mean Absolute Error (MAE) of 2.34 × 10⁻³, and a Mean Squared Error (MSE) of 3.82 × 10⁻⁵, outperforming LM and SCG in in terms of generalization and accuracy. The findings of this study demonstrate the effectiveness of combining TL analysis with ANN-based modelling for accurate dose–response predictions and the improved luminescence characterization of plagioclase, supporting the applications of luminescence studies in radiation dosimetry and geochronology. Full article

Biomolecular adsorption has great significance in medical, environmental, and technological processes. Understanding adsorption equilibrium and binding kinetics is essential for advanced process implementation. This requires identifying intrinsic determinants that predict optimal adsorption properties at bio–hybrid interfaces. Solid-binding peptides (SBPs) have targetable intrinsic properties involving peptide–peptide and peptide–solid interactions, which result in high-affinity material-selective binding. Atomic force microscopy investigations confirmed this complex interplay of multi-step peptide assemblies in a cooperative modus. Yet, most studies report adsorption properties of SBPs using non-cooperative or single-step adsorption models. Using non-cooperative kinetic models for predicting cooperative self-assembly behavior creates an oversimplified view of peptide adsorption, restricting implementing SBPs beyond their current use. To address these limitations and provide insight into surface-level events during self-assembly, a novel method, the Frequency Response Cooperativity model, was developed. This model iteratively fits adsorption data through spectral analysis of several time-dependent kinetic parameters. The model, applied to a widely used gold-binding peptide data obtained using a quartz crystal microbalance with dissipation, verified multi-step assembly. Peak deconvolution of spectral plots revealed distinct differences in the size and distribution of the kinetic rates present during adsorption across the concentrations. This approach provides new fundamental insights into the intricate dynamics of self-assembly of biomolecules on surfaces. Full article

This work focuses on the fabrication and evaluation of a passive wireless sensor for the monitoring of the temperature and corrosion of a metal material at high temperatures. An inductor–capacitor (LC) resonator sensor was fabricated through the screen printing of Ag-based inks on dense polycrystalline Al₂O₃ substrates. The LC design was modeled using the ANSYS HFSS modeling package, with the LC passive wireless sensors operating at frequencies from 70 to 100 MHz. The wireless response of the LC was interrogated and received by a radio frequency signal generator and spectrum analyzer at temperatures from 50 to 800 °C in real time. The corrosion kinetics of the Cu 110 was characterized through thermogravimetric (TGA) analysis and microscopy images, and the oxide thickness growth was then correlated to the wireless sensor signal under isothermal conditions at 800 °C. The results showed that the wireless signal was consistent with the corrosion kinetics and temperature, indicating that these two characteristics can be further deconvoluted in the future. In addition, the sensor also showed a magnitude- and frequency-dependent response to crack/spallation events in the oxide corrosion layer, permitting the in situ wireless identification of these catastrophic events on the metal surface at high temperatures. Full article

Thermogravimetric analysis (TGA) was performed on six samples of pine wood, poplar sawdust and olive residue, and the kinetic parameters were evaluated by using isoconversional models. The hemicellulose, cellulose and lignin contents were also estimated using the Fraser–Suzuki deconvolution method. In addition, a range of thermodynamic parameters and combustion indices was calculated. Significant correlations were found between the kinetic, thermodynamic and combustion parameters. The ignition index showed an inverse relationship with the activation energy, whereas the burnout index correlated with enthalpy values for most samples. Higher heating rates during TGA increased ignition and combustion efficiencies but decreased combustion stability. Differences in behaviour were detected between the olive residues, which had a much higher lignin content (51.2–56.9%), and the woody biomass samples (24.2–29.2%). Moreover, the sample with the highest ash content also exhibited some distinctive characteristics, including the lowest high heating value and ignition index, coupled with the highest activation energy, indicating a less favourable combustion behaviour than the other samples. The particle size of the samples was also found to be critical for both combustion efficiency and safety. Full article

Alkaline sodium hydroxide/sodium silicate-activating high-purity metakaolin geopolymerization is described in terms of metakaolin deconstruction in tetrahedral hydrate silicate [O[Si(OH)₃]]⁻ and aluminate [Al(OH)₄]⁻ ionic precursors followed by their reassembling in linear and branched sialates monomers that randomly copolymerize into an irregular crosslinked aluminosilicate network. The novelty of the approach resides in the concurrent thermo-calorimetric (differential scanning calorimetry, DSC) and rheological (dynamic mechanical analysis, DMA) characterizations of the liquid slurry during the transformation into a gel and a structural glassy solid. Tests were run either in temperature scan (1 °C/min) or isothermal (20 °C, 30 °C, 40 °C) cure conditions. A Gaussian functions deconvolution method has been applied to the DSC multi-peak thermograms to separate the kinetic contributions of the oligomer’s concurrent reactions. DSC thermograms of all tested materials are well-fitted by a combination of three overlapping Gaussian curves that are associated with the initial linear low-molecular-weight (Mw) oligomers (P1) formation, oligomers branching into alumina-rich and silica-rich gels (P2), and inter- and intra-molecular crosslinking (P3). The loss factor has been used to define viscoelastic behavioral zones for each DMA rheo-thermogram operated in the same DSC thermal conditions. Macromolecular evolution and viscoelastic properties have been obtained by pairing the deconvoluted DSC thermograms with the viscoelastic behavioral zones of the DMA rheo-thermograms. Two main chemorheological behaviors have been identified relative to pre- and post-gelation separation of the viscoelastic liquid from the viscoelastic solid. Each comprises three behavioral zones, accounting for the concurrently occurring linear and branching oligomerization, aluminate-rich and silica-rich gel nucleations, crosslinking, and vitrification. A “rubbery plateau” in the loss factor path, observed for all the testing conditions, identifies a large behavioral transition zone dividing the incipient gelling liquid slurry from the material hard setting and vitrification. Full article

Two representative organic-rich mudstones from the Middle Permian (MP) and the Upper Carboniferous (UC) around the Fukang Depression in the Junggar Basin were selected to study and compare the pyrolysis behavior and kinetics. The MP and UC were described as type I and type II kerogen, respectively. The FTIR and XRD results revealed that the MP contains carbonates and different clay minerals compared to the UC. Peak deconvolution was used for the UC to delineate the pyrolysis process to better understand and compare the similarities and differences in the pyrolysis kinetics of the two mudstones. In addition, the Coats-Redfern method was employed to further differentiate the reaction stages based on the differences in the reaction models during pyrolysis. The kinetic results revealed that the activation energy, pre-exponential factors, and reaction models of the two mudstones have some similarities and differences. Combined with the analysis of the pyrolysis volatiles, the UC sample can release more CH₄, CO, CO₂, and aromatic hydrocarbon compounds at high temperatures, indicating that the UC has more oxygen-containing functional groups and aromatics, while the MP has more aliphatics. Through the above studies, the pyrolysis kinetics and mechanism of two organic-rich rocks could be clarified, guiding their development and efficient utilization. Full article