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

Dibo Xu, Paerhatijiang Tuersun, Shuyuan Li, Meng Wang, Lan Jiang

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Article in Nanomaterials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Dibo XuXinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.

Paerhatijiang TuersunXinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.

Shuyuan LiXinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.

Meng WangXinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.

Lan JiangXinjiang Key Laboratory for Luminescence Minerals and Optical Functional Materials, School of Physics and Electronic Engineering, Xinjiang Normal University, Urumqi 830054, China.

Funding

Natural Science Foundation of Xinjiang Uygur Autonomous Region 2021D01A116Outstanding Young Talent Program of Xinjiang Normal University XJNUQB2022-18

6 · The paper itself

Abstract

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.

Indexed as

discrete dipole approximationgraphics processing unitslight absorptionlight scatteringPython package

Identifiers

PMID40214545

DOI10.3390/nano15070500

PMCPMC11990789

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LicenceCC BY

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