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Simulation-Driven Insights into the Role of Ammonium-Amine Additives in Perovskite Solar Cells
Our research investigates how ammonium- and amine-based additives differently affect the efficiency and stability of inverted perovskite solar cells (PVSCs). Using density functional theory (DFT) simulations, we reveal why phenethylamine (PEA) outperforms phenethylammonium iodide (PEA+) in enhancing PVSC performance and durability.
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Advanced Copper-Based Electrocatalysts for Efficient Nitrate Reduction to Ammonia
Our research explores how different support materials enhance the efficiency and selectivity of copper-based electrocatalysts for converting nitrate to ammonia. By developing and studying copper catalysts supported by ceria/carbon, zirconia/carbon, and pure carbon, we identified key factors that influence catalytic performance.
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Innovative Catalytic System for Reductive Amination of Furfural and Furfurylamine
Our collaborative research introduces an efficient catalytic system for producing difurfurylamine (DiFAM), a chemical used in pharmaceuticals and polymers. We developed a novel methoxide and MIL-53-NH2(Al)-derived Ru catalyst, significantly improving the production process. Using density functional theory (DFT), we explored the reaction mechanism, providing deeper insights into its efficiency.
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Enhanced QM/MM Simulations for Accurate Modeling of Adsorption and Catalysis in Zr-Based MOFs
Our research advances hybrid quantum mechanics/molecular mechanics (QM/MM) simulations for accurately modeling adsorption and catalytic reactions in zirconium-based metal-organic frameworks (Zr-MOFs). These materials are crucial for gas storage, separation, and catalysis.
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Biomass-Derived Furan Oligomers Show Promise for Next-Generation Electrochromic Devices
Our research introduces a novel electrochromic material made from biomass, offering sustainable solutions for smart windows and energy-efficient displays. The study focuses on a trifuran oligomer, synthesized via a one-pot reaction, which shows excellent color-changing properties, transitioning from light yellow to red with high efficiency. Advanced computational methods, including density functional theory (DFT), were used to reveal the molecular mechanisms driving these electrochromic behaviors.
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Machine Learning and DFT Unlock New Insights into Cerium Oxide Catalysts
Our research introduces a deep learning approach combined with infrared (IR) spectroscopy and density functional theory (DFT) to analyze the surface properties of cerium oxide (CeO2) catalysts. By using IR spectra, we developed a model that quickly predicts CeO2 surface structures, offering a faster and more efficient method than traditional techniques. This work provides valuable insights for optimizing catalyst design and performance in environmental and redox reactions.
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Fast Water Transport Mechanism Unveiled in UTSA-280 Metal-Organic Framework
Our research uncovers a novel water transport mechanism in the UTSA-280 metal-organic framework (MOF), featuring a unique knock-off mechanism that allows incoming water molecules to displace coordinated ones for efficient mass transfer. This pseudo-three-dimensional transport has important implications for membrane-based separation technologies, especially in water purification and ethanol separation.
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Mixed-Linker Strategy Improves Structural Stability of Metal-Organic Framework Membranes for Gas Separation
Our study employed computational optimization to introduce a mixed-linker strategy that enhances the structural stability of CAU-10-based metal-organic framework (MOF) membranes. By replacing pyridine-3,5-dicarboxylate (PDC) with benzene-1,3-dicarboxylate (BDC), we significantly improved membrane performance. This approach effectively addresses the structural flexibility issue, making MOF membranes more suitable for industrial CO2/CH4 separations.
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Automating Reaction Kinetics with Arkane – A New Tool for Chemical Kinetics and Thermochemistry
This project is about Arkane, an open-source tool that automates complex chemical kinetic and thermodynamic calculations. The software streamlines critical processes essential for understanding chemical reactions. Developed by an international team, Arkane enhances the efficiency and accessibility of computational analysis in the field.
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Automating Reaction Kinetics with Arkane – A New Tool for Chemical Kinetics and Thermochemistry
This research explores an innovative method for converting biomass-derived furfural (FAL) into tetrahydrofurfuryl alcohol (THFA) using Ni-supported catalysts with sodium borohydride (NaBH4) as a hydrogen source. The computational analysis highlights the efficiency and cost-effectiveness of this approach, making it a promising alternative for producing THFA.
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