Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 10, 2026

Testing of Nanoparticle Release from a Composite Containing Nanomaterial Using a Chamber System
04:55

Testing of Nanoparticle Release from a Composite Containing Nanomaterial Using a Chamber System

Published on: November 22, 2016

Computational strategies for predicting the potential risks associated with nanotechnology.

Amanda S Barnard1

  • 1Commonwealth Scientific and Industrial Research Organisation Materials Science and Engineering & Future Manufacturing Flagship Clayton, Victoria, Australia. amanda.barnard@csiro.au

Nanoscale
|July 21, 2010
PubMed
Summary

Addressing potential nano-hazards is crucial for sustainable nanotechnology. This research explores strategies combining theory, simulation, and experiments to predict and prevent risks from nanoparticles entering the ecosystem.

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Impact of nanoparticle morphologies on property prediction using explainable AI.

Nanoscale horizons·2025
Same author

Fractal Characterization of Simulated Metal Nanocatalysts in 3D.

Small science·2025
Same author

Materials "Economatics": Combining Chemical, Financial, Environmental, and Social Factors Using Machine Learning.

ACS nano·2025
Same author

Property Prediction for Complex Compounds Using Structure-Free Mendeleev Encoding and Machine Learning.

Journal of chemical information and modeling·2024
Same author

Classification of battery compounds using structure-free Mendeleev encodings.

Journal of cheminformatics·2024
Same author

Complex Dispersion of Detonation Nanodiamond Revealed by Machine Learning Assisted Cryo-TEM and Coarse-Grained Molecular Dynamics Simulations.

ACS nanoscience Au·2023

Area of Science:

  • Environmental Science
  • Materials Science
  • Risk Assessment

Background:

  • The transition from nanoscience to nanotechnology necessitates addressing potential 'nano-hazards'.
  • Increasing use of nanoparticles in eco-friendly products leads to inevitable environmental release.
  • Understanding nanoparticle hazardous properties and risks is essential.

Purpose of the Study:

  • To discuss strategies for assessing and mitigating nano-hazards.
  • To ensure the sustainable commercialization of nanotechnology.
  • To predict potential risks associated with nanoparticles in the ecosystem.

Main Methods:

  • Combining theoretical approaches, computational simulations, and experimental observations.
  • Developing predictive models for nanoparticle behavior and impact.

Related Experiment Videos

Last Updated: Jun 10, 2026

Testing of Nanoparticle Release from a Composite Containing Nanomaterial Using a Chamber System
04:55

Testing of Nanoparticle Release from a Composite Containing Nanomaterial Using a Chamber System

Published on: November 22, 2016

  • Integrating insights from complementary scientific fields.

    • Main Results:

    • Proposed strategies integrate diverse methodologies for comprehensive risk assessment.
    • Emphasis on the role of theory and computation in predicting nano-hazards.
    • Frameworks for preventative measures are being developed.

    Conclusions:

    • A multidisciplinary approach is vital for managing nano-hazards.
    • Proactive risk assessment is key to sustainable nanotechnology.
    • Integrating theoretical and experimental data enables robust safety predictions.