Chemistry, Volume 8, Issue 5 (May 2026) – 15 articles

The catalytic reduction of 4-nitrophenol (4-NP) requires highly efficient and cost-effective materials, making Mn-Ni nanostructures a promising candidate. In this study, Mn-Ni nanoparticles with distinct morphologies (specifically spheres, stars, and core–shell structures) were synthesized by tuning the precursor composition. The structural and optical properties of the synthesized catalysts were characterized via electron microscopy and UV-Vis spectroscopy. Kinetic evaluations of the 4-NP reduction demonstrated that the core–shell architecture yielded the highest catalytic activity, outperforming both the star-shaped and spherical nanoparticles. Furthermore, the high-index facets at the tips of the nanostars appeared to have contributed to enhanced catalytic activity by providing additional active surface sites for the reduction process. Ultimately, this work suggests that structural morphology and interfacial interactions play important roles in determining catalytic performance, rather than absolute surface area, providing valuable insights into the design of future bimetallic catalysts. Full article

This study investigated the application of six machine learning regression algorithms such as Random Forest, CatBoost, K-Nearest Neighbours, XGBoost, LightGBM, and Gradient Boosting, paired with Molecular ACCess System (MACCS) key fingerprints for the quantitative prediction of aromatase (CYP19A1) inhibitory potency, expressed as pIC₅₀. A dataset of 187 compounds was assembled from the ChEMBL database (version 33, Target ID: CHEMBL1978) following by systematic data curation workflow encompassing duplicate removal, pIC₅₀ transformation, and activity-based filtering. Model performance was rigorously evaluated using an 80/20 stratified train/test split, 5-fold cross-validation, and Y-randomisation testing to ensure unbiased assessment of predictive generalisation. Feature selection via CatBoost permutation importance on the held-out test set identified the top 20 predictive MACCS keys from an initial 166-bit space, substantially reducing dimensionality and improving generalisation across all models. Among the algorithms evaluated, CatBoost trained on the top 20 features achieved the strongest test-set performance (R² = 0.693, RMSE = 0.794, MAE = 0.659) with the most stable cross-validation R² (0.062 ± 0.304), outperforming all other algorithms. Y-randomisation testing returned an empirical p-value of <0.01, confirming that model performance reflects genuine structure–activity relationships rather than statistical chance. Permutation importance and SHAP analysis identified nitrogen-containing heterocyclic fragments (MACCS_41, MACCS_145) and halide-bearing substructures (MACCS_109) as the primary structural determinants of aromatase inhibitory potency, consistent with established CYP19A1 pharmacophoric requirements. Application of the model to ten representative plasticizers demonstrated that the refined applicability domain (h* = 0.423) accommodated eight of the ten compounds, enabling reliable potency predictions across phthalate esters and bisphenol analogues. These findings establish a transparent and reproducible QSAR framework for first-tier endocrine disruption risk screening of plasticizers and highlight the importance of permutation-based feature selection and applicability domain assessment in QSAR model development. Full article

As key therapeutic targets for symptomatic treatment of Alzheimer’s disease (AD) according to the cholinergic hypothesis, acetylcholinesterase (AChE; EC 3.1.1.7) and butyrylcholinesterase (BChE; EC 3.1.1.8) have been the subject of numerous studies over decades, leading to large collections of different ligands with corresponding AChE and BChE activity. This vast amount of data provides an ideal basis for the implementation of different machine learning (ML) and deep learning (DL) tools in different steps of the drug discovery process. Mainly applied to identify potential strong inhibitors of AChE and to a lesser extent BChE, many quantitative structure–activity relationship (QSAR) models and other predictive tools have been constructed utilizing different ML algorithms and DL techniques with various success depending on the input data and specific context. Here, we provide an extensive overview of such cases reported in the literature in recent years. Full article

Direct Coal Liquefaction (DCL) is a promising route for converting abundant coal resources into liquid fuels, yet its efficiency remains strongly dependent on catalyst performance. In this work, we present an integrated computational framework combining density functional theory (DFT) calculations with machine learning (ML) to investigate iron–sulfur (FeS) cluster catalysts for DCL. DFT calculations were employed to examine hydrogen-donor dissociation and coal-derived radical hydrogenation on representative FeS clusters. The results indicate that the most favorable catalytic pathways arise from the cooperation between metallic Fe sites (Fe_2) and interfacial Fe sites adjacent to sulfur (Fe_1), while sulfur atoms mainly play an indirect structural and electronic modulation role. Based on these mechanistic insights, a database containing thermodynamic and kinetic data for 636 reactions across 50 FeS cluster models was constructed. This dataset was then used to train three ML classifiers, among which the Random Forest model showed the best performance, reaching accuracies of 80% for H-donor cleavage and 93% for radical hydrogenation on the held-out test sets. SHapley Additive exPlanations (SHAP) analysis further showed that descriptors associated with Fe active-site identity were among the most influential variables in both tasks. Overall, this work provides a mechanistically informed and interpretable computational framework for understanding FeS-catalyzed DCL chemistry and for the preliminary screening of catalyst motifs within the chemical space covered by the present FeS cluster library. Full article

The escalating threat of antibiotic resistance, driven by the persistence of tetracycline in aquatic ecosystems, necessitates the development of advanced remediation platforms with high structural efficiency. In this study, a bimetallic Ag-Fe co-doped ZIF-8 framework was strategically engineered to optimize pore accessibility and surface chemical affinity. The resulting nanocomposite exhibited an ultra-high BET surface area of 1322.64 m²/g and a pore volume of 0.502 cm³/g, while maintaining the characteristic structural integrity of the parent ZIF-8. Adsorption benchmarks demonstrated a superior maximum capacity of 417.97 mg/g at pH 8 under ambient conditions. The sequestration process was found to be governed by pseudo-second-order kinetics, while the Freundlich and intraparticle diffusion models accurately described a multilayer adsorption mechanism occurring across heterogeneous active sites. Furthermore, the Ag-Fe-ZIF-8 maintained its structural stability and performance over three consecutive cycles. These findings highlight the potential of bimetallic ZIF-8 derivatives as robust, high-surface-area platforms for the sustainable removal of pharmaceutical pollutants from wastewater, with an adsorption capacity as high as 417.97 mg/g after 3 h. Full article

In the post-Moore era, large-area manufacturing of high-quality two-dimensional (2D) materials remains a central bottleneck for the industrialization of next-generation microelectronic and optoelectronic devices. Conventional mechanical exfoliation is limited by randomness and small lateral size, whereas chemical vapor deposition inevitably introduces grain boundaries, stress, and interfacial contamination, making it difficult to achieve both high quality and scalability. Metal-assisted exfoliation (MAE) enables controllable exfoliation and nondestructive transfer of large-area, high-quality monolayer 2D materials via precise modulation of metal-2D interfacial interactions dominated by strain-induced decoupling and atomic intercalation. This article systematically outlines the interfacial physical mechanisms and technological evolution of MAE, and highlights its state-of-the-art applications in patterned transfer, high-performance field-effect transistors, and complementary logic circuits, aiming to provide a firm theoretical and technical basis for advancing 2D materials from fundamental research toward practical applications. Full article

The combination of gemcitabine (GEM) and olaparib (OLA) shows promise for treating pancreatic cancer, particularly in patients with mutations in the BRCA genes. This work presents the validation of a straightforward, fast, and sensitive chromatographic method for the simultaneous analysis of GEM and OLA, supporting the development of advanced pharmaceutical formulations that combine the two drugs. The efficient chromatographic separation of GEM and OLA was achieved using a C18 column (250 × 4.6 mm, 5 μm) with a mobile phase composed of acetonitrile and water (50:50, v/v), which eluted isocratically at a flow rate of 0.8 mL/min. Determinations were performed using a PDA detector at 243 nm for both drugs. The retention times for GEM and OLA were approximately 3.3 and 4.3 min, respectively. The method was linear (R² > 0.999), with a regression curve in the concentration range of 0.5 to 10.0 μg/mL, demonstrating sensitivity, precision, and accuracy. The recovery rates of the drugs from the pancreatic tissue were higher than 97.0%. The components of a coated liposomal formulation and the pancreatic tissue did not interfere with the analysis, and both drugs demonstrated a low degradation rate under stressful conditions. In conclusion, the validated method was suitable for quantifying GEM and OLA simultaneously, even in a biological matrix, making it feasible to support the development of advanced pharmaceutical formulations that incorporate both drugs, such as liposomes. Full article

Phosphorus is an indispensable key element in life systems and materials science. Here in this work, several cyanoterphenyl-based phosphinic acid-bridged liquid crystal (LC) dimers of 2(CTOn)P (n = 6, 11) and their methyl esterification derivatives of 2(CTOn)P1E have been synthesized through hydrophosphination reaction followed by Suzuki coupling. The cyanoterphenyl LC dimers of 2(CTOn)P and methyl esterified 2(CTOn)P1E exhibit rich enantiotropic LC mesophases such as nematic (N), smectic A (SmA) and highly ordered smectic E (SmE), rather than the monotropic N or twist bend nematic (N_TB) displayed by the analogous phosphinic acid-bridged cyanobiphenyl LC dimers of 2(CBOn)P as reported previously. The phase transition temperatures of the cyanoterphenyl LC dimers 2(CTOn)P are also significantly higher than those of the cyanobiphenyl series, which is attributed to the larger π-conjugated system of cyanoterphenyl as compared with cyanobiphenyl, resulting in much enhanced π-π stacking interactions. However, the significantly enhanced interactions also make them extremely insoluble; thus, a different two-step synthesis pathway combining hydrophosphination with Suzuki coupling reactions was adopted. It is worth pointing out that by combining multiple characterization techniques, including DEPT 135°, ¹³C NMR, and HR-MS spectra, the definite molecular composition and structure of a byproduct with a third pro-mesogen attached via a branching alkyl spacer has been unambiguously demonstrated, which evidently deepens our understanding of the free radical-mediated hydrophosphination reaction mechanism, thereby providing valuable guidance for diminishing side reactions and achieving well-preparation of the high-purity phosphorus-containing LC dimers. Such phosphinic acid functionalized LC materials are envisioned to bear some unique application prospects. Full article

Developing eco-friendly metal oxide nanoparticles (NPs) with plant-based reducing and stabilizing agents offers a sustainable alternative to traditional chemical methods. Nonetheless, the detailed mechanisms by which phytochemicals influence NPs formation, antimicrobial properties, and cytocompatibility remain poorly understood, especially in systems mediated by Vaccinium. This study aimed to synthesize TiO₂ NPs and ZnO NPs using Vaccinium corymbosum (blueberry) extract, analyze their structural and surface characteristics, assess their antimicrobial effectiveness and cytotoxicity, and explore potential molecular mechanisms through computational docking. ZnO NPs were produced via alkaline precipitation (pH 12) from ZnCl₂, while food-grade TiO₂ was mixed with blueberry extract. A comprehensive characterization was carried out using techniques like X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, transmission and scanning electron microscopy (TEM/SEM), dynamic light scattering (DLS), and high-performance liquid chromatography (HPLC) for polyphenol profiling. The antimicrobial activity was tested against Escherichia coli and Salmonella Typhimurium, and the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined. Cytotoxicity was assessed using Gallus gallus domesticus leukocytes and Artemia salina bioassays, and molecular docking simulations were performed to examine polyphenol interactions with the bacterial DNA gyrase subunit B (GyrB). XRD analysis confirmed the presence of wurtzite ZnO (with a crystallite size of 18.2 nm) and anatase TiO₂ (12.8 nm after functionalization). HPLC identified key polyphenols, including quercetin, cyanidin, malvidin, and cyanidin-3-glucoside, with patterns indicating stronger adsorption onto TiO₂ NPs surfaces. ZnO NPs showed higher antimicrobial effectiveness (>90% inhibition at 2 mg/mL; MIC 0.5–1 mg/mL) compared to TiO₂ (72% inhibition at 16 mg/mL; MIC 8–16 mg/mL). Cytotoxicity results indicated concentration-dependent effects. Molecular docking simulations revealed favorable binding energies (−6.2 to −8.4 kcal/mol) for blueberry polyphenols with GyrB, suggesting potential synergistic antimicrobial effects and ROS production. The study highlights a successful green synthesis of bioactive TiO₂ NPs and ZnO NPs using Vaccinium corymbosum extract, where polyphenol surface functionalization enhances both colloidal stability and biological activity. This comparative research offers mechanistic insights into how polyphenol-coated NPs work and supports the development of eco-friendly antimicrobial oxide nanomaterials. Full article

This study presents an efficient and environmentally friendly route for synthesizing succinic acid derivatives via palladium-catalyzed oxidative dicarbonylation of ethylene, utilizing oxygen as the terminal oxidant. By systematically optimizing reaction parameters—including catalyst composition, solvent volume, gas ratio, temperature, and additives—the turnover number (TON) for dimethyl succinate was significantly enhanced to 10,325. This strategy not only demonstrates the potential of CO and ethylene as simple and abundant C1 and C2 building blocks but also highlights the viability of oxygen as a sustainable oxidant. The developed process offers a promising pathway toward the cost-effective and scalable production of biodegradable materials such as poly(butylene succinate) (PBS), with important implications for advancing green synthesis and enabling an autonomous supply chain in the biodegradable polymer industry. Full article

A series of morpholine-appended 1,8-naphthalimide probes (S1–S5) was developed to investigate the influence of the morpholine moiety on H₂S detection. All probes exhibited characteristic absorption and emission features and responded to H₂S with fluorescence enhancement, although the intensity varied markedly across the series. S2 displayed the highest signal enhancement, while S5 showed minimal response, highlighting the critical role of a two-carbon spacer between the morpholine group and the fluorophore for optimal sensing. Kinetic analysis revealed that S1–S4 followed similar reaction profiles, whereas S5 reacted faster but produced a weaker signal. S2 maintained reliable performance across pH 4–9 and in DMSO-containing media and demonstrated excellent selectivity over common biothiols and other potentially interfering species. These findings provide a clear structure–activity relationship for morpholine-based fluorescent probes and inform the rational design of highly selective H₂S sensors. Full article

This work presents an energy-efficient and simple method for producing luminescent, antibacterial sulfur quantum dots (SQDs). For the first time, polyethyleneimine (PEI)-coated SQDs were synthesized via a mechanochemical technique, utilizing either elemental sulfur or sodium thiosulfate as the sulfur source. The roles of hydrogen peroxide (H₂O₂) as an etching agent and of sodium hydroxide (NaOH) in the PEI-mediated SQD formation were investigated. The as-synthesized SQDs were characterized by UV-visible, Raman, infrared (IR), and photoluminescence (PL) spectroscopy, as well as by transmission electron microscopy (TEM) and atomic force microscopy (AFM). Both TEM and AFM analyses revealed similarly small SQD sizes (average diameter ~3 nm), independent of the sulfur source used. The influence of synthesis conditions on the optical properties, including the photoluminescence quantum yield (QY), was evaluated. SQDs derived from elemental sulfur, PEI, and NaOH exhibited the best water solubility and the strongest photoemission in the 400–550 nm range. Antibacterial activity was assessed against representative Gram-positive and Gram-negative strains, and minimum inhibitory concentration (MIC) values were determined. The PEI-coated SQDs demonstrated antibacterial activity against the Gram-positive bacteria Bacillus subtilis, Staphylococcus aureus, and Staphylococcus epidermidis, which is attributed primarily to the sulfur component. Full article

Despite the extensive literature on microalgal production, most studies focus on controlled laboratory-scale systems, resulting in a critical lack of confidence at industrial scale. This is further compounded by the frequently observed inconsistencies, with only modest increases achieved in operational scale. This work demonstrates the design, construction, and operation of a commercial-scale tubular photobioreactor and associated equipment for the production of algae using CO₂ derived from an industrial nickel refinery. The reactor was demonstrated by growing the species Nannochloropsis gaditana. Biomass concentrations of 1.0 to 1.3 g L⁻¹ were achieved with a productivity of 0.11 g L⁻¹ d⁻¹. Extrapolation to a 300-day production year showed that the reactor was capable of producing 541.2 kg algae and sequestering around 1 tonne of CO₂. A technoeconomic assessment showed that the total plant CAPEX was £583,905 and the OPEX was £98,196. Sales of algae alone showed poor economic performance. However, economic favourability is observed for species that contain phycocyanin pigment and yield a positive net present value within 4 to 7 years based on recovery yield. This work effectively provides reliable process data developed at scale that can be used to formulate business cases for further scale-up and expansion of algal production systems. This moves the technology a step closer to full-scale realisation and the potential for a net-zero, sustainable future. Full article

An effective strategy for significantly enhancing photocatalytic activity of composite materials is to construct heterojunctions. Herein, a series of imidazole-modified heterostructured g-C₃N₄/SnO (CNIS) Z-scheme photocatalysts were prepared by calcination methods, leading to superior photocatalytic performance than pure SnO and imidazole-modified g-C₃N₄. Rhodamine B (Rh B) aqueous solution was taken as the target pollutant, and the result presented that both imidazole modification and the Z-scheme heterojunction construction benefited from significant enhancement in photocatalytic activity. Moreover, it is revealed that electrons were transferred from imidazole-modified g-C₃N₄ to SnO through the interface of the composite by XPS analysis. Under visible light (>420 nm) irradiation, the built-in electric field, band edge bending, and Coulomb interaction work synergistically to drive the recombination of relatively useless electrons and holes in the hybrid. As a result, the residual electrons and holes, which possess enhanced reducibility and oxidizability, endow the composite with exceptional redox capability. This research can not only deepen our comprehension of designing and fabricating innovative Z-scheme heterojunction photocatalysts but also presents an effective approach to tackle environmental pollution issues in the future. Full article

Cyclodepsipeptides constitute a structurally diverse class of natural products composed of amino acid and hydroxy acid residues interconnected through both amide and ester bonds. Among them, xylaroamide A, a cyclic heptadepsipeptide, was recently identified from an endolichenic Xylaria species via a molecular networking-guided discovery approach. Despite xylaroamide A exhibiting intriguing structural features and notable bioactivity potential, its total synthesis has thus far remained unexplored. Herein, we report the first total synthesis of xylaroamide A, achieved through a hybrid solid/solution-phase synthetic approach. The linear precursor was assembled in accordance with the native amino acid sequence via Fmoc-based solid-phase peptide synthesis, incorporating the preassembled ester fragment at a later stage of assembly. Subsequent macrocyclization took place under high-dilution conditions to furnish the target cyclodepsipeptide. The structure of the synthetic product was confirmed by means of optical rotation and NMR and MS spectroscopic analyses, which exhibited good agreement with the reported data for the natural product. This work establishes a reliable and efficient synthetic route to xylaroamide A and provides a foundation for further bioactivity and structure optimization investigations. Full article