A detailed investigation of hydrogen bonding interactions in acenaphthylene based polycyclic aromatic hydrocarbons, including the parent C12H8 and cyano substituted derivatives of acenaphthylene (1-, 3-, 4-, and 5-C12H7CN), with proton donors, H2O, HCl, HCN, NH3, and C2H2, has been carried out. These systems have shown various types of hydrogen bonding interactions, such as N⋯H-O, N⋯H-Cl, N⋯H-C and N⋯H-N, where nitrile acts as proton acceptor. Among the proton donors, HCl has shown comparatively stronger hydrogen bonding interaction. Among nitriles, the 1-cyano substituted acenaphthylene has shown comparatively better interaction with H2O, HCl, HCN and C2H2, possibly due to the enhanced electron delocalisation within non-Huckel π-system. To investigate these interactions, we examined geometrical features, complexation energies and changes in the vibrational frequencies. QTAIM was used to calculate the electron density [ρ(rc)] and Laplacian values [∇2ρ(rc)] at bond critical points, which provide information on bond character and bond strength. The results can help to explain the impact of substituents on hydrogen bonding and molecular stability.
This work investigates the role of copper-based hole transport layers (HTLs) in suppressing rear-junction recombination and enhancing carrier selectivity in Sb2Se3 thin-film solar cells (TFSCs). The validated reference device with an efficiency of 10.12% is first established, then Cu2O, CuSbS2, and CuI are introduced as HTLs. The influence of HTLs on device operation is systematically examined through current-voltage (J-V) characteristics, external quantum efficiency (EQE), surface recombination velocity (SRV), spatial recombination profiles, energy band alignment, and impedance spectroscopy (IS). The results reveal that copper-based HTLs form p+-p rear heterojunctions with Sb2Se3, generating built-in electric fields that extend the effective collection region and strongly suppress back surface recombination. Among the investigated materials, CuI provides the most favorable band alignment, combining a little valence band offset (VBO) (ΔEv=-0.2 eV) with a large conduction band offset (CBO) (ΔEc=+1.7 eV), which enables efficient hole extraction and strong minority carrier reflection. This configuration localizes recombination within the thin HTL, reduces sensitivity to high SRV, and significantly increases the recombination resistance (RRec) as confirmed by impedance analysis. As a result, the CuI-containing device exhibits a predicted efficiency of 16.8%, corresponding to an increase of 6.7 percentage points relative to the experimentally reported 10.12% reference device. These findings demonstrate that rear junction band offset engineering and electric field control are key design strategies for high-efficiency Sb2Se3 solar cells.
Air-breathing polymer electrolyte fuel cells (PEFCs) are a simplified alternative to conventional forced-convection PEFC systems, eliminating external air-supply devices to reduce system complexity, weight, and cost, and to minimise parasitic losses. Despite these advantages, their passive configuration poses critical challenges in oxygen mass transport, water management, thermal regulation, and environmental sensitivity. This study presents a comprehensive bibliometric and systematic review of air-breathing PEFC research published between 2000 and 2025. Using the Scopus database and a PRISMA-guided screening framework, 224 relevant documents were analysed through the Bibliometrix package in RStudio and VOSviewer to map publication trends, international collaborations, keyword evolution, and thematic research clusters. The results indicate irregular but sustained growth in research output, with an annual growth rate of 8.67%. Keyword co-occurrence analysis identified major research themes centred on water management, gas diffusion layer optimisation, flow-field design, numerical modelling, thermal diagnostics, and durability enhancement. Emerging niches include piezoelectric-assisted mass transport and advanced membrane materials for high-temperature and miniature systems. The findings highlight that future technological progress depends on improved mass-transport engineering, enhanced membrane stability, optimised passive flow architectures, and integrated stack-level thermal management. For researchers, the study clarifies the field's conceptual evolution and highlights the most critical research gaps. For industry stakeholders, it provides strategic insights into design priorities for compact, reliable hydrogen-powered systems suitable for portable, off-grid, and unmanned aerial vehicle applications.
Copper substitution represents an effective strategy for tuning the electronic properties of phosphate-based materials. In this work, the effect of partial Cu substitution in orthorhombic FePO₄ was investigated using spin-polarized DFT+U calculations combined with semiclassical Boltzmann transport theory. Cu incorporation preserves the structural framework while introducing Cu 3d states near the Fermi level, reducing the band gap from 2.2 eV to 1.5 eV. These additional states increase the density of states near the band edges, suggesting enhanced electronic transport relative to pristine FePO₄. The electronic structure exhibits pronounced anisotropy, as revealed by constant-energy surface analysis, indicating direction-dependent band dispersion and transport behavior. BoltzTraP2 calculations performed within the constant relaxation time approximation (CRTA) predict an electrical conductivity ratio (σ/τ) of approximately 2.4 × 10¹⁹ S m⁻¹ s⁻¹ at 300 K, together with a Seebeck coefficient of −36 μV K⁻¹, consistent with n-type conduction. Because the absolute conductivity scales linearly with the relaxation time, transport properties are discussed in terms of relative trends within the CRTA framework. Overall, Cu substitution significantly modifies the electronic structure of FePO₄ by narrowing the band gap and increasing the density of states near the Fermi level, thereby promoting electronic transport. In addition, the elastic response of both compounds was investigated using a stress–strain approach: Cu substitution induces a pronounced, direction-dependent softening of the phosphate framework, reducing the principal elastic constants (C₁₁, C₂₂, C₃₃) by approximately 36–40% relative to pristine FePO₄. These findings provide insight into the role of Cu doping in tailoring the electronic properties of phosphate cathode materials. However, the present study focuses exclusively on electronic transport descriptors and does not address ionic diffusion or electrochemical interfacial processes, which require dedicated atomistic and kinetic investigations.
Here we study the variation of HCl reaction-medium volume at fixed LiF and MAX loading, with associated changes in reagent ratios and reaction-medium composition for the formation, structural evolution, and supercapacitor performance of Ti3C2Tx MXenes generated from a single Ti3AlC2 MAX phase. Ti3C2Tx MXenes were produced by lithium fluoride (LiF/HCl) based minimally intensive layer delamination (MILD) approach by adjusting the volume of HCl as 20, 30 and 40 mL, while maintaining other parameters such as Ti3AlC2, LiF, molarity of HCl, temperature and etching time constant. X-ray diffraction (XRD) validated the successful Al removal, as seen by the absence of the MAX-phase (104) peak and the shift of the (002) reflection to lower angles. Ti-MX-30 had the highest interlayer spacing, measuring 1.53 nm. Field-emission scanning electron microscopy (FE-SEM) and high-resolution transmission electron microscopy (HR-TEM) showed a gradual transition of compact MAX particles into accordion-like single-to-few-layer MXene structures, whereas energy-dispersive X-ray spectroscopy (EDX) and X-ray photoelectron spectroscopy (XPS) corroborated the substantial depletion of Al and development of Ti-C frameworks ornamented with -O, -OH, and -F terminations. Electrochemical tests in 1 M H2SO4 revealed that Ti-MX-20 had the maximum three-electrode capacitance of 114.97 F g-1 at 5 mV s-1 and 57.29 F g-1 at 0.4 A g-1 confirmed by the prevalent surface-controlled kinetics. A symmetric Ti-MX-20//Ti-MX-20 device showed capacitance of 47.27 F g-1 at 5 mV s-1, 12.29 F g-1 at 0.1 A g-1, energy and power density of 1.092 Wh kg-1 at 40 W kg-1, respectively and 92.21% retention after 1500 cycles suggested reliable MXene-based energy-storage behaviour. These results suggest reaction-medium conditions can be tuned to balancing etching efficiency, interlayer accessibility, surface chemistry and electrochemical durability of Ti3C2Tx MXene electrodes for scalable supercapacitors.
Silicon carbide (SiC) nanoparticles were synthesized by carbothermal reduction of amorphous silica extracted from rice-husk ash with activated carbon at 1500°C for 5 h under flowing argon, using polyvinyl alcohol as a temporary binder. X-ray diffraction showed reflections consistent with cubic 3C-SiC, with a weak feature near 33.6° (2θ); the lattice parameter calculated from the indexed reflections is a = 4.3781(5) Å, and line-profile analysis gives a mean crystallite size of 19.5 ± 3.8 nm with a microstrain of 1.1 × 10-3. FTIR confirmed the Si–C stretching band at 872 cm-1 and also revealed a Si–O–Si band at 1092 cm-1, indicating a residual silica/surface-oxide contribution; the product is therefore described as predominantly single-phase rather than phase-pure. Diffuse-reflectance data, converted using the Kubelka–Munk function and analysed using an indirect Tauc construction, gave an optical band gap of 2.17 eV, narrower than the reported bulk value for 3C-SiC and consistent with defect- and disorder-related tail states. SEM revealed irregular, densely agglomerated clusters of fine grains, with measured feature diameters of approximately 40, 210 and 398 nm in the representative micrographs. Under irradiation from a 300 W UV lamp, the SiC nanoparticles produced 52% methylene blue removal (10 mg L-1, 30 mg catalyst per 50 mL) within 60 min, compared with 14% removal in the catalyst-free photolysis control, and the apparent pseudo-first-order rate constant was 0.0117 ± 0.0006 min-1 (R2 = 0.987). The results demonstrate photocatalytic activity toward methylene blue under UV irradiation, while residual surface oxide, pronounced agglomeration, and possible charge-carrier recombination are identified as factors that may limit performance.
Aqueous ammonium-ion batteries offer a promising platform for safe and sustainable electrochemical energy storage, yet the coupled physicochemical mechanisms governing NH₄⁺ transport, interfacial interactions, and spatial charge-storage behavior remain insufficiently understood. This study presents a physics-based framework for elucidating the role of reversible hydrogen-bond interactions in regulating NH₄⁺ transport, interfacial charge-transfer kinetics, and reaction-field redistribution within porous Co₉S₈/CNT cathodes. The framework couples non-ideal ionic transport, electronic charge conservation, Butler–Volmer kinetics, reversible hydrogen-bond formation and rupture, double-layer charging, phase evolution, and state-dependent porous-electrode properties. The results reveal a nonmonotonic relationship between hydrogen-bond occupation and electrochemical utilization. Moderate and reversible hydrogen bonding redistributes the Faradaic reaction field and increases participation of internal reaction domains, increasing the Reaction Uniformity Index from 0.74 to 0.87 while raising the Microsphere Depth Utilization Factor from 0.47 to 0.58. In contrast, excessive bond occupation reduces the mobile-ion population, intensifies concentration polarization, and promotes localization of electrochemical activity near the outer particle region. CNT connectivity further modulates the coupled transport–reaction behavior by homogenizing electronic conduction and enhancing the accessibility of internal reaction zones, reducing the electrolyte potential drop from 47.0 to 11.9 mV across the investigated connectivity range. Sensitivity and uncertainty analyses identify hydrogen-bond kinetics, ionic transport, accessible bonding-site density, and structural connectivity as strongly coupled governing factors. These findings demonstrate that hydrogen bonding functions as a dynamic kinetic regulator rather than a passive adsorption interaction and provide a mechanistic basis for balancing reversible molecular-ion association, ionic mobility, and spatially distributed electrochemical activity in porous electrode architectures.
Tolvaptan was investigated using an experimentally anchored multiscale computational workflow integrating density functional theory (DFT), time-dependent DFT, molecular docking, membrane molecular dynamics (MD), MM/GBSA, and ADMET prediction. B3LYP/6-311++G(d,p) calculations gave a HOMO–LUMO gap of 2.71 eV and an electrophilicity index of 17.46 eV, while natural bond orbital analysis identified n→π stabilization energies up to 260.0 kJ mol⁻¹. Among the tested TD-DFT models, B3LYP/SMD yielded the calculated λmax closest to the literature-reported methanolic absorption maximum. Re-docking of co-resolved R-tolvaptan into the vasopressin V2 receptor (PDB 9HAP) reproduced the experimental pose with a heavy-atom RMSD of 0.238 Å. AutoDock Vina scores were −8.34 and −8.31 kcal mol⁻¹ for R- and S-tolvaptan, respectively, indicating minimal static score separation. During independent 100-ns membrane MD simulations, both stereoisomers remained associated with the orthosteric pocket, whereas R-tolvaptan showed lower ligand RMSD and RMSF. Mean MM/GBSA estimates were −92.38 ± 6.69 and −81.83 ± 7.69 kcal mol⁻¹ for R and S, respectively. ADMET analysis predicted 93.24% intestinal absorption and a moderate hepatotoxicity risk. The study provides an experimentally referenced cross-scale framework for Tolvaptan and indicates stereochemistry-dependent differences in dynamic accommodation and calculated energetics without establishing experimental V2R enantioselectivity.
A novel pharmaceutical cocrystal composed of nicotinamide (NA) and pentadecanoic acid (PDA) was synthesized and comprehensively characterized through an experimental and computational approach. Single-crystal X-ray diffraction revealed that NA–PDA crystallizes in the triclinic symmetry (P1¯) with two formula units per unit cell (Z = 2). The structure is stabilized by a hydrogen bonding lattice involving N–H···O and O–H∙∙∙O interactions between the carboxamide group of NA and the carboxylic acid group of PDA. Hirshfeld surface analysis quantified the intermolecular contacts, revealing that H···H interactions dominate with 73.7% contribution, followed by H∙∙∙O/O∙∙∙H (14.3%) and C∙∙∙H/H∙∙∙C (5.6%) contacts, reflecting the balanced hydrophilic-hydrophobic character of the cocrystal. Crystal void analysis demonstrated a void percentage of 10.91%, with asphericity (0.913) and globularity (0.233) indices indicating anisotropic void geometry typical of layered structures containing long aliphatic chains. Energy‑framework calculations showed that the cocrystal is stabilized by electrostatic hydrogen bonding on the NA component and dispersive chain packing on the PDA component. Vibrational spectroscopy combined with periodic density functional theory (DFT) calculations provided detailed assignment of normal modes. The experimental infrared and Raman spectra showed excellent correlation with DFT-calculated vibrational frequencies. Powder X‑ray diffraction combined and Rietveld refinement confirmed the phase purity of the bulk material, and thermal analysis revealed melting at 84 °C followed by a single decomposition step above 170 °C. Antibacterial assays revealed that NA–PDA exhibits enhanced activity against both Gram-positive (S. aureus, S. pneumoniae) and Gram-negative (E. coli, K. pneumoniae) bacteria compared to pure components, with preferential efficacy toward Gram-positive strains. In silico ADME predictions indicated favorable pharmacokinetic properties including high gastrointestinal absorption and appropriate lipophilicity. These results demonstrate that the NA–PDA cocrystal represents a promising pharmaceutical material with favorable physicochemical profile and preliminary antibacterial activity arising from supramolecular assembly.
The Wnt/β-catenin signaling pathway is one of the most frequently dysregulated pathways in human malignancies and plays an important role in tumor proliferation, metastasis, stemness, and therapy resistance, particularly in triple-negative breast cancer (TNBC). Persistent activation of β-catenin signaling contributes to aggressive tumor phenotypes and poor clinical outcomes, making β-catenin an attractive therapeutic target. However, direct inhibition of β-catenin remains challenging because the protein lacks catalytic domains and possesses broad protein–protein interaction interfaces that are difficult to target using conventional small molecules. Recent studies have identified cryptic allosteric pockets within β-catenin that may serve as alternative sites for therapeutic modulation. In the present study, α-mangostin, a xanthone compound isolated from mangosteen rind (Garcinia mangostana L.), was structurally modified through benzoylation to generate derivatives with improved binding potential toward the allosteric region of β-catenin. A total of eighty-one benzoylated α-mangostin derivatives were designed and evaluated using an integrated computational strategy consisting of allosteric site prediction, pharmacophore modeling, molecular docking, molecular dynamics simulations, and binding free-energy analysis. Molecular docking at the PASSer-predicted allosteric pocket demonstrated that several derivatives, particularly amb-14, amb-12, amb-11, amb-25, and amb-74, exhibited stronger binding affinities and favorable interaction profiles compared with the parent compound. Pharmacophore modeling using LigandScout confirmed the importance of hydrophobic contacts and hydrogen-bond interactions with critical residues, including Arg431 and Glu437. Furthermore, 200-ns molecular dynamics simulations revealed stable ligand–protein complexes with reduced flexibility in the armadillo repeat domain associated with transcriptional coactivator binding. MM-PBSA and MM-GBSA calculations supported the energetic stability of the selected complexes. ADMET prediction analysis indicated favorable pharmacokinetic properties, including high intestinal absorption, low blood–brain barrier permeability, minimal cytochrome P450 inhibition liability, and acceptable toxicity profiles, although potential hepatotoxicity requires further evaluation. Collectively, these findings suggest that benzoylated α-mangostin derivatives represent promising scaffolds for allosteric β-catenin inhibitors targeting Wnt/β-catenin-driven cancers.
Schistosoma japonicum causes zoonotic schistosomiasis, which remains a public health concern in endemic regions and underscores the need for novel antischistosomal agents with well-defined molecular targets. This study evaluated bioactive compounds from Bischofia javanica for their interactions with glutathione S-transferase (GST) using molecular docking, clustering-based binding analysis, and molecular dynamics simulations. The predicted binding modes were evaluated in relation to two structurally relevant ligand-recognition regions corresponding to the canonical glutathione-binding site and the Praziquantel-associated allosteric region at the dimer interface. Integration of ligand affinity, binding stability, and residue-level interaction patterns across these regions identified Epifriedelanyl acetate and Friedelin as the leading compounds. Epifriedelanyl acetate exhibited the strongest overall binding profile and more favorable binding energetics than praziquantel. Its interactions were predominantly concentrated within the allosteric region with limited extension toward the catalytic-proximal environment. Friedelin also exhibited favorable and stable binding forming a compact interaction network within the same praziquantel-associated region, although its binding energetics were slightly less favorable than those of the control. Per-residue energy decomposition and native contact occupancy confirmed persistent interactions within the allosteric region whereas principal component analysis revealed broader conformational redistribution for Epifriedelanyl acetate and a more localized response for Friedelin without disrupting the global GST fold. Overall, these findings support Epifriedelanyl acetate and Friedelin as promising GST-targeting antischistosomal candidates that may modulate GST predominantly through an allosteric mechanism.
Underground hydrogen storage (UHS) in depleted reservoirs and saline aquifers represents a pivotal solution for large-scale energy storage and grid stabilization. A key parameter controlling multiphase flow, capillary trapping, and sealing efficiency in UHS systems is the interfacial tension (IFT) between injected gas mixtures and formation fluids. Given the high cost and complexity of experimental IFT measurements under reservoir conditions, predictive modeling offers a practical alternative. This study introduces a comprehensive framework for estimating IFT as a function of thermodynamic and compositional variables, including temperature, pressure, salinity, and the molar fractions of CO₂, CH₄, and H₂. Data preprocessing incorporated a robust outlier detection scheme using the ±2σ criterion to ensure dataset integrity. Eight predictive models spanning traditional, ensemble, and deep learning architectures were developed and validated via 5-fold cross-validation. Performance was assessed using R², MSE, and AARE%. Results highlight the superiority of tree-based ensemble methods, with AdaBoost and Random Forest achieving test R² values of 0.943 and 0.942, respectively, alongside low error rates (MSE=6.65 and 7.37; AARE%=2.72 and 2.83). While the Decision Tree achieved the highest training accuracy (R²=0.979), its generalization was weaker (MSE=9.06), underscoring the ensembles’ robustness. Deep learning models such as CNN demonstrated moderate predictive strength (test R²=0.730), whereas KNN suffered severe overfitting (test R²=0.410). SVR and MLP-ANN also showed limited generalization compared to ensemble methods. To enhance interpretability, SHapley Additive exPlanations (SHAP) were applied, revealing the relative importance of salinity, temperature, pressure, and gas composition in shaping IFT. The proposed framework, particularly the AdaBoost and Random Forest pipelines, provides an accurate, interpretable, and computationally efficient tool for predicting IFT under diverse reservoir conditions, thereby supporting the secure design and optimization of underground hydrogen storage projects.
Triple-negative breast cancer (TNBC) requires safer nanotherapeutics that preferentially eliminate malignant cells while limiting normal-cell toxicity. Here, extracellular metabolites of the marine actinomycete Streptomonospora arabica VSM-25 were used to synthesize selenium nanoparticles (SA-SeNPs), followed by chitosan functionalization to generate pH-responsive CS@SA-SeNPs. Spectroscopic, physicochemical, and microscopic analyses confirmed nanoparticle formation and surface coating. Chitosan increased the mean SEM particle size from 63 to 97 nm (DLS hydrodynamic size: 90 to 122 d nm) and reversed the zeta potential from −28 to +32 mV. Across pH 3–9, particle size increased from 80 to 159 nm, while zeta potential and the stability index decreased from +55 to +16 mV and from 323.5 to 37.2, respectively (r = −0.978, p = 0.0001), demonstrating greater colloidal stability under acidic conditions. CS@SA-SeNPs were more potent than SA-SeNPs against MDA-MB-231 TNBC cells (IC₅₀: 40.83 vs 53.31 µg/mL) and less toxic to HEK293 cells (IC₅₀: 260.08 vs 192.77 µg/mL), yielding a selectivity index of 6.36 and therapeutic index of 11.46. In MDA-MB-231 cells, treatment produced concentration-dependent ROS accumulation (∼485%), mitochondrial membrane depolarization (<10% residual potential), apoptotic-body formation (∼97 per 100 cells), and caspase-3 activation (∼4.3-fold) at 80 µg/mL. PCA attributed 98.1% of the response variance to PC1, supporting ROS-associated mitochondrial apoptosis. Zebrafish embryos exposed to CS@SA-SeNPs had higher No Observed Effect Level (NOEL) and Lowest Observed Effect Level (LOEL) values (275 and 280 µg/mL) than those exposed to SA-SeNPs (150 and 160 µg/mL). Collectively, chitosan functionalization improved the pH-dependent stability, TNBC selectivity, and preliminary in vivo biosafety of metabolite-mediated SeNPs, supporting further validation in mammalian tumor models.
The present work introduces a facile, reductant-free polyol route for synthesizing highly stable, cetyltrimethylammonium bromide (CTAB)-stabilized silver nanoparticles (AgNPs) by leveraging glycerol as an integrated solvent and reducing agent. Comparative analysis against ethylene glycol and propylene glycol established the superior performance of glycerol, which is attributed to its favorable oxidation thermodynamics, enhanced chelation capacity, and balanced fluid dynamics. This unique chemical profile enhanced both reductive kinetics and supramolecular stabilization, ensuring the formation of well-dispersed spherical AgNPs with an average diameter of 9.7 nm, in sharp contrast to the macroscopic precipitates produced by the simple diols. Directly addressing the limitations of traditional polyol synthesis, this study introduces a purification-free platform where the resulting colloids are used immediately as potent antimicrobial agents against S. aureus and E. coli. The novelty of this approach stems from the synergistic stabilization afforded by glycerol’s high-density hydroxyl network, which prevents the aggregation typically seen in lower-density polyols. Furthermore, the scope is extended to environmental catalysis via the selective reduction of 4-nitrophenol. By integrating Langmuir-Hinshelwood kinetic modeling with rigorous thermodynamic analysis, this work establishes a predictive framework for the surface-mediated reduction of nitro-pollutants, positioning the glycerol-based synthesis as a scalable and highly efficient alternative for high-performance nanomedicine and industrial catalysis.
The present study focuses on the magneto-thermal transportation response of Carreau–Yasuda nanofluid flow of Fe3O4–blood through a porous tumor boundary under impulsive magnetic and thermal stimulation. The mathematical model incorporates nonlinear rheology, Darcy–Forchheimer porous resistance, thermal radiation, buoyancy, viscous dissipation, and blood-perfusion effects, while the magnetic field is introduced through an impulsive magnetic boundary condition representing external magnetic stimulation at the tumor interface. The governing nonlinear partial differential equations are solved numerically by the finite difference method (FDM). In addition, an artificial neural network (ANN) model using the Levenberg–Marquardt (LM) back-propagation algorithm is used to predict and validate the velocity and temperature distributions, and the influence of significant governing parameters are analyzed in detail. Thermal analysis shows that the blood perfusion and viscous dissipation parameters have a significant impact on the increase of the temperature field, whereas the increase in the radiation and nanoparticle volume fraction parameters increases the thermal diffusion and decreases the thermal accumulation in the wall region. The accuracy and robustness of the proposed intelligent computational framework are further verified by the excellent agreement between the ANN predictions and the FDM solutions, with regression coefficient values very close to unity and very small mean squared errors. The present study offers important physical insights into the transport of nonlinear magnetic nanoparticles, the enhancement of local hyperthermia, and in vivo thermal regulation in porous biological tissues.
Carbon dots (CDs) are among the most structurally complex nanomaterials, exhibiting heterogeneous architectures, nonlinear formation pathways, and multifunctional properties that challenge conventional structure–property paradigms. These complexities have stimulated increasing interest in machine learning (ML) as a tool for modeling synthesis–property relationships and accelerating materials development. However, predictive accuracy alone is insufficient for advancing scientific understanding when the underlying mechanisms remain unclear. This review examines the emerging role of explainable machine learning (XML) in CD research, highlighting its transition from a predictive framework to a knowledge-extraction approach capable of revealing hidden relationships within complex materials datasets. We discuss the structural heterogeneity of CDs, the nonlinear nature of their formation pathways, and the limitations of current characterization methods that hinder reliable interpretation of functional behavior. Recent studies employing explainable and interpretable ML techniques are analyzed to assess their contributions to understanding synthesis–property relationships, resolving structural ambiguities, and guiding application-oriented design. Current challenges related to data quality, descriptor representation, model reliability, and causal interpretation are also evaluated. Finally, future directions involving causal inference, physics-informed learning, and autonomous discovery platforms are discussed as key pathways toward transforming CD research from empirical optimization to a predictive and scientifically interpretable discipline.
Metal–organic frameworks (MOFs) have attracted considerable interest because of their tunable porosity and versatile adsorption properties. In this study, zeolitic imidazolate framework-8 (ZIF-8) was synthesized under mild conditions at various Hmim/Zn molar ratios and investigated as a carrier for termite pheromones. Structural characterization by X-ray diffraction, scanning electron microscopy, and dynamic light scattering confirmed the successful formation of nanoscale ZIF-8, with ZIF-8-8M exhibiting the average particle size (∼296.2 nm). Thermogravimetric analysis suggested that n-butyl-n-butyrate (PBB) could be incorporated into ZIF-8 with an estimated adsorption amount of ∼23%, whereas 2-methyl-1-butanol (PMB) showed negligible adsorption. Density functional theory calculations revealed that PBB interacts more strongly with ZIF-8 than with solvent molecules, providing a thermodynamic driving force for adsorption, whereas stronger PMB–solvent interactions hinder its incorporation into the framework. These findings demonstrate that competitive interactions among guest molecules, solvents, and MOF frameworks govern adsorption behavior and potential release characteristics. The present study provides mechanistic insights into pheromone–MOF interactions and highlights the potential of MOF-based carriers for environmental and cultural heritage applications.
β Silicon carbide/polypropylene nanocomposites containing 1–10 wt% SiC were investigated to establish the relationships among filler morphology, crystalline structure, dielectric, and thermal degradation behavior. SEM observations revealed that the synthesized SiC possesses a heterogeneous multiscale morphology comprising spherical and agglomerated particles, flakes, rods, needles, and crystallite-decorated nanotube-like structures. EDS detected 54.65 wt% Si, 42.76 wt% C, and 2.59 wt% O, with the minor O contribution attributed to native surface oxidation. XRD confirmed crystalline cubic β-SiC, with the dominant (111) reflection at 2θ ≈ 35.35° and an average crystallite size of 44.22 nm, whereas all composites retained the monoclinic α-PP phase without detectable secondary crystalline phases. The crystallite size of the composites varied non-monotonically with SiC loading, reaching 51.32 nm by the Debye–Scherrer method at 2 wt% SiC and 44.38 nm by Williamson–Hall analysis at 7 wt% SiC. The corresponding microstrain increased from 0.25 × 10⁻³ at 3 wt% to 0.66 × 10⁻³ at 7 wt%, indicating enhanced interfacial lattice distortion. Dielectric measurements over 20–100 °C showed that the response of the composites was governed by Maxwell–Wagner–Sillars interfacial polarization, charge trapping, and thermally activated hopping and tunneling. All SiC/PP composites maintained tan δ below 0.1, while the 5–7 wt% compositions provided the most favorable balance between enhanced AC conductivity and low dielectric loss. Thermogravimetric analysis showed that PP degradation remained predominantly a single-stage process. At SiC contents of 3 wt% and above, the characteristic degradation temperatures increased relative to pure PP, with the 10 wt% composite exhibiting T5%, T10%, and T50% values of 686.35, 701.15, and 761.15 K, respectively, compared with 655.50, 672.89, and 721.00 K for pure PP. Coats–Redfern analysis demonstrated that the 7 wt% SiC/PP composite had the highest kinetic stability, with activation energies of 200.09 kJ mol⁻¹ at α = 0.2 and 234.81 kJ mol⁻¹ at α = 0.5, compared with 142.63 and 175.84 kJ mol⁻¹ for pure PP. The relatively narrow variation in ΔG indicates that SiC primarily modifies the degradation kinetics rather than the overall thermodynamic feasibility. These results identify 7 wt% SiC as the optimum composition for combined dielectric and kinetic performance, while 10 wt% SiC provides the greatest improvement in characteristic thermal degradation temperatures.
Electrochemical energy technologies are showing immense promise to play a pivotal role in future energy and environmental sustainability. However, the electrochemical reactions involved in these processes are complex and sluggish. Electrocatalysts are thus employed to enhance their kinetics; specifically, those with atomically dispersed metal sites are exhibiting great potential in terms of activity and selectivity. Electrocatalysts with atomically dispersed iron (Fe) sites (EADFSs) are one capable contender in this emerging class of advanced catalysts. While the activity of EADFSs towards different reactions is often limited, researchers have adopted different strategies to boost performance. The role of the electronic configuration of the active site towards electrocatalysis has long been known. However, the influence of its spin-state, another fundamental parameter of d-block elements (like Fe), has been realised recently. Proper adjustment of the spin-state at the active site has been found to improve its substrate adsorption/desorption, facilitate favourable reaction intermediate formation, and reduce spin-related energy barriers. Understanding the fundamental roles of the spin-state on the activity and stability of EADFSs and its regularization strategies is thus of seminal interest. In this article, we account for the suitability of EADFSs as catalysts in different reactions and the role of Fe spin-states behind their activity and stability. We then discuss the analytical techniques for determining the spin-states of Fe and account for the strategies adopted to regularize the Fe spin-state in EADFSs to enhance their performance. We also discuss the superiority of Fe for spin-state engineering in comparison to other transition metals such as Ni, Co, and Mn. We finally outline some challenges and future perspectives of spin-state engineering in EADFSs to achieve superior performance.
Indium phosphide (InP) quantum dots (QDs) have emerged as promising semiconductor nanomaterials for photocatalytic and solar-energy conversion systems due to their tunable optoelectronic properties and lower toxicity compared with conventional cadmium-based quantum dots. In this review, recent progress in the materials design, photophysical understanding, and device integration of InP quantum dots for solar-driven photocatalytic applications is systematically examined. First, advances in synthetic strategies and surface chemistry engineering are discussed, focusing on precursor chemistry, crystal growth mechanisms, and ligand-mediated surface coordination that govern nanocrystal quality and stability. Next, the electronic structure and photophysical behavior of InP QDs are analyzed, with particular attention to quantum confinement effects, excitonic dynamics, and carrier relaxation pathways that influence light absorption and charge separation processes. The review then critically summarizes reported photocatalytic and energy-conversion applications of InP-based systems, including photocatalytic hydrogen evolution, CO₂ photoreduction, and hybrid semiconductor architectures designed to enhance interfacial charge transfer. Finally, challenges associated with device integration, large-scale synthesis, environmental considerations, and long-term operational stability are discussed. These insights provide a comprehensive perspective on the design principles and technological prospects of InP quantum dot–based materials for efficient and sustainable solar-energy conversion.
