1711 papers
This paper presents a novel framework integrating Hierarchical Cognitive Neuro Forecasting (HCNFF) and Adaptive Quantum Automation Intelligence (AQAI-Net) to optimize the green synthesis of ZnO-modified Fe₂O₃ nanoparticles and achieve high-accuracy prediction of their photocatalytic and adsorption performance for environmental remediation.
This study demonstrates that sulfur-modified graphene nanosheets (S-GNS) serve as a highly selective and regenerable adsorbent for desulfurizing petroleum, effectively removing aromatic sulfur compounds via synergistic π–π stacking and donor–acceptor interactions in liquid hexane while allowing easy gas-phase regeneration.
This study utilizes machine learning algorithms, specifically a genetic algorithm-optimized support vector regression (GA-SVR) model, to predict and optimize the tensile strength of metal powder/resin composites, identifying key processing parameters that maximize mechanical performance.
This study demonstrates that multi-directional p-alkoxy-substituted resorcin[4]arenes with elongated hydrophobic alkyl chains effectively inhibit carbon steel corrosion in CO₂-saturated saline media, achieving maximum inhibition efficiencies of up to 94.7% for the longest-chain derivatives.
This study reports a highly sensitive electrochemical sensor for moxifloxacin detection based on an α-ZrP/phosphorus-nitrogen co-doped hollow carbon spheres composite, where DFT computations and experimental data reveal that phosphorus doping optimizes pyridinic-N content and adsorption energy to achieve superior sensing performance in real-world samples.
This study demonstrates that immobilizing β-galactosidase on glutaraldehyde-functionalized bentonite clay nanoparticles significantly enhances the enzyme's stability and storage life while increasing galactooligosaccharide production from paneer whey compared to the free enzyme, although further improvements are needed to optimize reusability.
This study demonstrates the synthesis and characterization of a novel sulfo- and amine-functionalized polyvinyl chloride sorbent that effectively removes radioactive iodine from wastewater, achieving a maximum adsorption capacity of 705 mg/g through a process best described by Langmuir isotherm and pseudo-second-order kinetic models.
This paper presents an automated, interpretable workflow that predicts crystal structures from chemical formulas by combining periodic-descriptor-based template retrieval with space-group probability predictions and a stoichiometry-aware substitution engine, significantly improving space-group match rates on benchmark databases.
This study presents a preliminary performance screening of four distinct bimetallic catalysts supported on cubic CeO₂ for CO₂ hydrogenation, identifying CuNi/CeO₂ as the top performer for CO₂ conversion and FeCu/CeO₂ for CO production, while explicitly noting that the results reflect formulation-level trends rather than intrinsic mechanistic effects due to variations in metal composition, ratios, and synthesis routes.
This study demonstrates an integrated and economically viable process for the efficient separation and purification of 2,3-butanediol from complex broths using an optimized isobutanol/potassium phosphate aqueous two-phase extraction system coupled with distillation, achieving over 98% recovery and enabling effective recycling of both solvent and salt.