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CPDDA: A Python Package for Discrete Dipole Approximation Accelerated by CuPy

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Vydáno v:Nanomaterials vol. 15, no. 7 (2025), p. 500
Hlavní autor: Xu, Dibo
Další autoři: Tuersun, Paerhatijiang, Li, Shuyuan, Wang, Meng, Jiang, Lan
Vydáno:
MDPI AG
Témata:
Chaumet
Dielectric properties
Optical properties
Parallel processing
Light scattering
Atmospheric optics
Iterative methods
Fast Fourier transformations
Approximation
Numerical analysis
Zinc oxide
Materials selection
Refractivity
Numerical methods
Linear algebra
Gold
Fourier transforms
Simulation
Optics
Electromagnetic absorption
Graphics processing units
Absorption
Dipoles
Mie scattering
Electric fields
Nanorods
Methods
Light
Mathematical models
Object oriented programming
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Abstrakt:Discrete Dipole Approximation (DDA) is a rapidly developing numerical method in recent years. DDA has found wide application in many research fields including plasmonics and atmospheric optics. Currently, few DDA packages based on Python have been reported. In this work, a Python package called CPDDA is developed. It can be used to simulate the light-scattering and -absorption properties of arbitrarily shaped particles. CPDDA uses object-oriented programming, offers high flexibility and extensibility, and provides a comprehensive database of refractive indices. The package uses the biconjugate gradient method and fast Fourier transform for program acceleration and memory optimization, and it uses parallel computation with graphics processing units to enhance program performance. The accuracy and performance of CPDDA were demonstrated by comparison with Mie theory, the MATLAB package MPDDA, and the Python package pyGDM2. Finally, CPDDA was used to simulate the variations in light-absorption and -scattering properties of ZnO@Au core-shell nanorods based on the particle size. CPDDA is useful for calculating light-scattering and -absorption properties of small particles and selecting materials with excellent optical properties.
ISSN:2079-4991
DOI:10.3390/nano15070500
Zdroj:Materials Science Database