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Comparative analysis of Modified Johnson-Cook model and Artificial Neural Network for flow stress prediction in BN-reinforced AZ80 magnesium composite.
J Phys Condens Matter
January 2025
University of Science and Technology Beijing, No. 30, Xueyuan Road, Haidian District, Beijing, 100083, CHINA.
Boron nitride (BN), renowned for its exceptional optoelectrical properties, mechanical robustness, and thermal stability, has emerged as a promising two-dimensional (2D) material. Reinforcing AZ80 magnesium alloy with BN can significantly enhance its mechanical properties. To investigate and predict this enhancement during hot deformation, we introduce two independent modeling approaches a modified Johnson-Cook (J-C) constitutive model and an Artificial Neural Network (ANN).
View Article and Find Full Text PDFDirect Synthesis of Topology-Controlled BODIPY and CO2-Based Zirconium Metal-Organic Frameworks for Efficient Photocatalytic CO2 Reduction.
Angew Chem Int Ed Engl
January 2025
National University of Singapore, Department of Chemical and Biomolecular Engineering, 4 Engineering Drive 4, National University of Singapore, 117585, Singapore, SINGAPORE.
Boron dipyrromethene (BODIPY)-based zirconium metal-organic frameworks (Zr-MOFs) possess strong light-harvesting capabilities and great potential for artificial photosynthesis without the use of sacrificial reagents. However, their direct preparation has not yet been achieved due to challenges in synthesizing suitable ligands. Herein, we reported the first successful direct synthesis of BODIPY-based Zr-MOFs, utilizing CO₂ as a feedstock.
View Article and Find Full Text PDFEnhancing Rashba Spin-Splitting Strength by Orbital Hybridization.
ACS Nano
December 2024
Department of Materials Science and Engineering, National University of Singapore, Singapore117575, Singapore.
Article Synopsis
- A Rashba spin-splitting state allows for charge-spin interconversion through the interplay of inversion symmetry breaking (ISB) and spin-orbit coupling (SOC), which is key for developing efficient spintronic devices.
- The study demonstrates that introducing orbital hybridization at the h-BN/CoPt interface increases the spin-splitting strength, enhancing the Rashba effect and spin-orbit torque (SOT) efficiency.
- Results indicate significant improvements in switching efficiency and lower current thresholds, suggesting potential for advanced energy-efficient spintronic technologies.
Large Scale Raman Spectrum Calculations in Defective 2D Materials using Deep Learning.
J Phys Condens Matter
December 2024
Département de physique et Institut Courtois, Université de Montréal, C.P. 6128, succursale Centre-ville, Montreal, Quebec, H3C 3J7, CANADA.
We introduce a machine learning prediction workflow to study the impact of defects on the Raman response of 2D materials. By combining the use of machine-learned interatomic potentials, the Raman-active $\Gamma$-weighted density of states method and splitting configurations in independant patches, we are able to reach simulation sizes in the tens of thousands of atoms, with diagonalization now being the main bottleneck of the simulation. We apply the method to two systems, isotopic graphene and defective hexagonal boron nitride, and compare our predicted Raman response to experimental results, with good agreement.
View Article and Find Full Text PDFGradient polaritonic surface with space-variant switchable light-matter interactions in 2D moiré superlattices.
Sci Adv
December 2024
College of Physics, Sichuan University, Chengdu, Sichuan 610064, China.
Polaritons in two-dimensional (2D) materials provide unique opportunities for controlling light at nanoscales. Tailoring these polaritons via gradient polaritonic surfaces with space-variant response can enable versatile light-matter interaction platforms with advanced functionalities. However, experimental progress has been hampered by the optical losses and poor light confinement of conventionally used artificial nanostructures.
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