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First-principles insights into structure and magnetism in ultra-small tetrahedral iron oxide nanoparticles.

Phys Chem Chem Phys

September 2025

Masaryk University, Faculty of Science, Department of Chemistry, Kotlářská 2, Brno, 611 37, Czech Republic.

Structural and magnetic properties of ultra-small tetrahedron-shaped iron oxide nanoparticles were investigated using density functional theory. Tetrahedral and truncated tetrahedral models were considered in both non-functionalized form and with surfaces passivated by pseudo-hydrogen atoms. The focus on these two morphologies reflects their experimental relevance at this size scale and the feasibility of performing fully relaxed, atomistically resolved first-principles simulations.

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Nanoparticles exhibit unique catalytic properties that are highly dependent on their size and shape, influencing reaction rates, selectivity, and efficiency. Identifying the structural effects that achieve a high catalytic performance is critical to a wide range of applications, from energy conversion to environmental remediation. High-throughput screening (HTS) methods, particularly desorption electrospray ionization mass spectrometry (DESI-MS), offer a powerful approach for rapidly assessing the catalytic performance of nanoparticles with varying sizes and shapes.

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MFeO (M = Co and Mn) nanoparticles were synthesized from coconut coir extract using a microwave-assisted co-precipitation method, representing a green and sustainable approach for ferrite nanomaterial preparation. The physical properties of the samples were characterized using X-ray diffraction, scanning electron microscopy, ultraviolet-visible spectroscopy, photoluminescence, Raman spectroscopy, and vibrating sample magnetometry. Scanning electron micrographs revealed nanoscale morphology with evidence of polymorphism.

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Pd nanocatalysts engineering for direct oxidation methane-to-methanol with 99.7% selectivity.

Nat Commun

August 2025

State Key Laboratory of Tropic Ocean Engineering Materials and Materials Evaluation, School of Marine Science and Engineering, Hainan University, Haikou, China.

Pd catalysts demonstrate remarkable activity and selectivity for the direct oxidation methane-to-methanol (DOMM) under mild conditions. However, understanding the structure-performance relationship is challenging because Pd catalysts used in existing studies have complex polycrystalline structures. In this work, well-defined Pd nanocrystals with controlled morphologies are synthesized and used as model systems to investigate the origins of the observed structure-activity differences.

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Machine Learning Potential Analysis of Structural Transition in Cu and Ag Nanoparticles: From Icosahedral to Face-Centered Cubic.

J Chem Theory Comput

September 2025

Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, c/Martí i Franquès 1-11, 08028 Barcelona, Spain.

A highly accurate high-dimensional neural network potential (HDNNP), trained using more than 180,000 DFT-calculated structures, is used to investigate the structure or realistic Cu-Ag bimetallic particles, as this is the dominant species during the CO reduction process. The structural transition of Cu and Ag nanoparticles of increasing size, ranging from hundreds of atoms to tens of thousands of atoms, has been studied. Global optimization shows that all Cu and Ag nanoparticles containing 100 to 1000 atoms have an icosahedral core.

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