Nanoparticle Applications


Drug delivery in cancer treatment and diagnostic tests, medical devices, chemotherapeutic agents.


Medicines for cardiology, osteoporosis and pulmonary, vaccines for most diseases and illnesses, smoking cessation.

Personal care products

Shampoos, sun screen, comestics and dental creams.

Ocular health products

Special ocular liquids and surgical instruments.

Food Industry

Nutritional and managing-obesity products.

Electronics and photovoltaics

Solar panels, semi-conductors, sensors and displays.

Materials Industry

Ceramics, textile, and building materials.

Clustering Analysis of Nanoparticles

Complex networks have been widely used in science and technology because of their ability to represent several systems. One of these systems is found in Biochemistry, in which the synthesis of new nanoparticles is a hot topic. However, the interpretation of experimental results in the search of new nanoparticles poses several challenges. This is due to the characteristics of nanoparticles images and due to their multiple intricate properties; one property of recurrent interest is the agglomeration of particles.

Complex Networks Modeling

Addressing this issue, we proposed a solution based on complex networks to detect and describe nanoparticle agglomerates so to foster easier and more insightful analyses. In this approach, each detected particle in an image corresponds to a vertice and the distances between the particles define a criterion for creating edges. Edges are created if the distance is smaller than a radius of interest. Once this network is set, we calculate several discrete measures able to reveal the most outstanding agglomerates in a nanoparticle image. The following images illustrate our method and tool.



Experimental results using images of Scanning Tunneling Microscopy (STM) of gold nanoparticles demonstrated the effectiveness of the proposed approach over several samples, as reflected by the separability between particles in three usual settings. The results also demonstrated efficacy for both convex and non-convex agglomerates. In the image, edges are created only between vertices separated by a distance smaller than a radius of interest.


Results with NanoImage Analyzer

Illustration of the NanoImage Analyzer. At the left, the original image; in the middle, the complex network according to our method; at the right, the set of nanoparticle agglomerates.


Results with NanoImage Analyzer

A second example, now considering a much denser image with intersecting agglomerates.


How to Run


Please, download the java jar file NanoImage Analyzer (~4MB, Last Update on February 23, 2017 - version 1.8). NanoImage Analyzer works on different systems, including Microsoft Windows, Mac OS X, and Linux-like systems.

Instructions to Run

To run the NanoImage Analyzer:

  • Step 1: In the main window, click on the Menu Open.
  • Step 2: Select the option Load Image (Ctrl+N) to open a nano-scale image; our tool can manage extensions tiff, tif, png, and jpg.
  • Step 3: Once the image was opened, go to the Menu Open again and choose the option Load Data (Ctrl+D). Notice that our tool does not find the position of the particles in an image. Therefore, we assume that you have the center (X,Y) of all particles (an example is shown below). Microscopy devices can capture intrinsic parts of the materials providing the necessary coordinates. Feel free to contact us if you need any help to locate the particles automatically.
  • Step 4: Click on the Button Analyze and results will be shown in the Panel Nanoparticle Characterization. Besides it, you can adjust the network with 3 sliders:
    • (1) the size of particles,
    • (2) the radius to form an agglomerate and,
    • (3) the density of nanoparticle agglomeration.
    •   * If you make any change in the sliders you should click again on the Button Analyze.

  • Step 5 (Optional): You can export the results, including plots, images with nets and description of group particles, by clicking on the main Menu, option Save.

The description of agglomerates, the network visualization, and the group formation are showed in the other panels. In the main window, you can see at the left-bottom the distribution of agglomerated particles, calculated by the frequency of agglomeration.

Image Sample and Format of the Data File

Click to donwload the sample image and its correspondent data file with the coordinates of the nanoparticles.

Image Sample 1

Data Points of Sample 1

The data file has three columns: number of the nanoparticles, coordinates X and Y; they are separated by tabulation. The image below shows the coordinates of the sample1.txt

If you have questions or suggestions, you can send us an email to brunobrandoli gmail com