By Prashant K Jain1, Nahil Sobh1, Jeremy Smith, AbderRahman N Sobh1, Sarah White, Jacob Faucheaux, John Feser1

1. University of Illinois at Urbana-Champaign

Calculate scattering and absorption of light by targets with arbitrary geometries and complex refractive index.

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Version 2.0 - published on 13 Apr 2016

doi:10.4231/D3NV99C0Q cite this

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This tool is useful for calculating the plasmonic properties of nanostructures and composites containing dielectric heterostructures. Spectra (absorption and scattering) and electrical (near) fields can be readily calculated using classical electrodynamics. This tool is useful for people building bio-sensors based on refractive index sensing and plasmonic coupling, as well as people who wish to compute fields for SERS or other field enhanced spectroscopies.

Through the use of Discrete Dipole Approximation (this tool uses DDSCAT version 7.3) users are able to study absorption, scattering, and electric fields around arrays of nanostructures, including nanobio systems, with varied properties. This tool provides a platform for allowing user-input for the DDSCAT (Discrete Dipole Scattering) software package through an interactive interface. There are a number of geometries supported within this tool including: rectangular prism, anisotropic ellipsoid, ellipsoid, concentric ellipsoids, isotropic cylinder, isotropic cylinder with hemispherical end-caps, cylinder with unixial anisotropic dielectric tensor.


The way that an electromagnetic field interacts with small metallic nanoparticles can be very surprising and yield great insights into the particle itself. This phenomenon can be observed on the macro scale – the precise way a halo forms around a solar eclipse, the combination of colors in a rainbow that forms after a rain storm or emerges from a spray hose on a sunny day, or even the changing colors of the sky at sunset. Each of these physical consequences of light scattering can tell us a great deal about the underlying systems. Light scattering has been used to make gains in biological understanding, study entire galaxies and even understand light itself.


SPR uses light to detect biological material
Biomedical Diagnostics Institute (

SERS is another popular detection method
Prof. Liu (UIUC)

Some of the interesting properties of light (e.g. evanescent fields, light extinction, scattering, absorption, and others) can be leveraged for medical and engineering applications. Surface Plasmon Resonance (SPR), Surface Enhanced Raman Spectroscopy (SERS), are two examples of high impact bionanotechnology in the field of medicine. In order to harness the full power of these phenomena, however, scientists need to understand the interactions of light with nanoparticles at very small length scales.

This principle can be extended and applied in a rigorous laboratory setting to attain very detailed information regarding a variety of particles. Scientists have used light and more generally electromagnetic radiation to study everything from cells and soybeans to planets and stars. As we’ve mentioned, however, this ability to use light as a scientific tool is dependent on our understanding of the interaction between light (and electromagnetic radiation in general) with particles.

Many scientists have worked to understand the behavior of electromagnetic radiation. In the nineteenth century, however, a Scottish physicist, James Clerk Maxwell, developed a mathematical description of the behavior of electric and magnetic fields. This set of partial differential equations, known as Maxwell’s equations, is an approximation of electrodynamic behavior, which nonetheless has formed the foundation for the field since their creation. Many phenomena can be predicted and explained by these equations. Many more, however, cannot. Maxwell’s equations are well characterized and excellent approximations for very common and simple shapes such as spheres and infinite cylinders. For a more general class of geometries, however, exact solutions are not known.

Non-standard geometries are critical for optimizing nanobio systems
Myroshchenko et. al.

Scientists, of course, are still interested in these non-common geometries. New ways, such as using numerical methods, have arisen to meet the challenge of determining the interaction of electromagnetic radiation with particles arranged in uncommon ways. Mie scattering, for example, has been developed to describe scattering by particles that are larger than a wavelength. Conversely, Rayleigh scattering was developed to understand scattering smaller than a wavelength.

Another very powerful method is known as Discrete Dipole Approximation (DDA). Here, the target is discretized into a collection of dipoles, or polarizable points. This method then uses various algorithms to solve the equations for how the incoming beam interacts with each of the dipoles individually. The resulting data can be used to compute scattering and absorption properties of the target. This method relies on the assumption that the dielectric properties (and hence the interaction between the particle and incoming beam) are directly related to the polarizability of dipoles.

An Example "Target" of DDA

Once the target is converted to a collection of dipoles, the scattering problem can be solved exactly for each dipole. Note that the calculation of interaction with many individual dipoles means that this method lends itself well to parallel processing.

A popular software package for conducting DDA calculations is called DDSCAT. DDSCAT allows for the computation of scattering properties with arbitrary shapes and geometries, and provide graphs of light extinction, absorption, and scattering properties. Using software like DDSCAT, scientists can determine properties of, as mentioned before, everything from space dust to red blood cells (RBCs).

Substrate for SPR studies
Prof. Fainman (UCSD)

The simulation methods can be used to not only understand properties of these systems but design diagnostic platforms as well. A very exciting area of research involves Surface Plasmon Resonance (SPR), which deals with the changing properties of scattering based on the ordering of gold nanoparticles on some surface. This technology can be used to determine the presence and concentrations of certain proteins in solution or find detect very small quantities of other substances. DDSCAT can be used to design the surface and optimize it for maximal sensitivity. In astrochemistry, scientists can use telescope imaging data and use DDSCAT to find geometries of space targets that most closely match the data in order to determine the most probable geometry.

Clearly, light scattering has been and will be a primary target of research relevant to a variety of fields. Many methods, tools, and approaches exist to conduct light scattering studies. Here, we present an implementation of a popular tool, DDSCAT, which may be used with another tool, DDACONVERT, to determine the light scattering properties of a variety of irregular particles and targets. Please see the instructions file to learn more about using this tool


Other Light Scattering Software


Sponsored by

NanoBio Node, University of Illinois Champaign-Urbana


Google Code page for DDSCAT

  • "Discrete Dipole Approximation." Wikipedia. Wikimedia Foundation, 27 Oct. 2013. Web. 27 Jan. 2014. (link)
  • Draine, Bruce T., and Piotr J. Flatau. "Discrete-dipole Approximation for Scattering Calculations." Journal of the Optical Society of America A 11.4 (1994): 1491. Web. (pdf)
  • Draine, Bruce T., and Piotr J. Flatau. User Guide for the Discrete Dipole Approximation Code DDSCAT 7.2. N.p., 2012. Web. (pdf)
  • Jain, Prashant K., Kyeong Seok Lee, Ivan H. El-Sayed, and Mostafa A. El-Sayed. "Calculated Absorption and Scattering Properties of Gold Nanoparticles of Different Size, Shape, and Composition: Applications in Biological Imaging and Biomedicine." The Journal of Physical Chemistry B 110.14 (2006): 7238-248. Web. (pdf)
  • Jain, Prashant K. "Plasmons in assembled metal nanostructures: radiative and nonradiative properties, near-field coupling and its universal scaling behavior." (2008). (pdf)


Copper plasmonics and catalysis: role of electron–phonon interactions in dephasing localized surface plasmons

Qi-C. Sun,   Yuchen Ding,   Samuel M. Goodman,   Hans H. Funke and   Prashant Nagpal

Nanoscale, 2014,6, 12450-12457
DOI: 10.1039/C4NR04719B
Received 16 Aug 2014, Accepted 15 Sep 2014
First published online 17 Sep 2014



Regioselective Plasmonic Coupling in Metamolecular Analogs of Benzene Derivatives

Aiqin Fang , Sarah White , Prashant K. Jain *, and Francis P. Zamborini *

† Department of Chemistry, University of Louisville, Louisville, Kentucky 40292, United States
‡ Department of Chemistry, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
Nano Lett., 2015, 15 (1), pp 542–548
DOI: 10.1021/nl503960s
Publication Date (Web): December 16, 2014
Copyright © 2014 American Chemical Society


One-to-One Correlation between Structure and Optical Response in a Heterogeneous Distribution of Plasmonic Constructs

Aiqin Fang, Sarah L. White, Rafael A. Masitas, Francis P. Zamborini*, and Prashant K. Jain*

† Department of Chemistry, University of Louisville, Louisville, Kentucky 40292, United States
‡ Department of Chemistry, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
J. Phys. Chem. C, Article ASAP
DOI: 10.1021/acs.jpcc.5b09292
Publication Date (Web): September 28, 2015
Copyright © 2015 American Chemical Society

Cite this work

Researchers should cite this work as follows:

  • Draine, B.T., & Flatau, P.J. 1994, "Discrete dipole approximation for scattering calculations", J. Opt. Soc. Am. A, 11, 1491-1499

    Draine, B.T., & Flatau, P.J. 2012, "User Guide to the Discrete Dipole Approximation Code DDSCAT 7.2"

    Draine, B.T., & Flatau, P.J., "Discrete-dipole approximation for periodic targets: theory and tests", J. Opt. Soc. Am. A, 25, 2593-2703 (2008)

    Flatau, P.J., & Draine, B.T., "Fast near-field calculations in the discrete dipole approximation for regular rectilinear grids", Optics Express, 20, 1247-1252 (2012)

  • Prashant K Jain; Nahil Sobh; Jeremy Smith; AbderRahman N Sobh; Sarah White; Jacob Faucheaux; John Feser (2016), "nanoDDSCAT," (DOI: 10.4231/D3NV99C0Q).

    BibTex | EndNote


  1. nano/bio
  2. Discrete Dipole Approximation
  3. DDA
  5. Discrete Dipole Scattering
  6. Illinois
  7. scattering
  8. scattering nanoprobes
  9. Mie Scattering
  10. Simulation
  11. NanoBio Node
  12. nanoBIO tools
  13. nano/bio
  14. Mie Scattering
  15. NanoBio Node
  16. nanoBIO tools
  17. scattering
  18. scattering nanoprobes
  19. Simulation