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 Concept Videos

Molecular Models02:00

Molecular Models

43.3K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.3K

You might also read

Related Articles

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

Sort by
Same author

Electronic Polarization Governs Structure-Transport Coupling of Angstrom-Scale Confined Water.

ACS nano·2026
Same author

Hydrogen-bond networks and proton transfer in choline geranate: insights from IR spectroscopy.

Physical chemistry chemical physics : PCCP·2026
Same author

Nanoplastics Can Build Themselves.

The journal of physical chemistry letters·2026
Same author

Good Practices for Simulation Studies Published in <i>The Journal of Physical Chemistry B</i>.

The journal of physical chemistry. B·2026
Same author

CONAN Build: Building Functionalized or Doped Carbon Nanomaterials.

Journal of chemical information and modeling·2026
Same author

Efficiency landscape of bioorthogonal click reactions producing bispecific antibody conjugates.

Cell reports methods·2026

Related Experiment Video

Updated: Jan 7, 2026

Interactive Molecular Model Assembly with 3D Printing
06:15

Interactive Molecular Model Assembly with 3D Printing

Published on: August 13, 2020

10.8K

Building Nanoplastic Models for Molecular Calculations.

Boglárka Szabó1, Paul Zaby2, Leonard Dick2

  • 1Department of Physical Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary.

The Journal of Physical Chemistry. B
|January 5, 2026
PubMed
Summary

Researchers developed a new workflow using simulated annealing and quantum chemistry to create stable nanoplastic structures. This method models polyethylene, polypropylene, polystyrene, and nylon-66, providing valuable data for toxicity and simulation studies.

More Related Videos

3D Printing of Biomolecular Models for Research and Pedagogy
09:17

3D Printing of Biomolecular Models for Research and Pedagogy

Published on: March 13, 2017

24.9K
Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

10.9K

Related Experiment Videos

Last Updated: Jan 7, 2026

Interactive Molecular Model Assembly with 3D Printing
06:15

Interactive Molecular Model Assembly with 3D Printing

Published on: August 13, 2020

10.8K
3D Printing of Biomolecular Models for Research and Pedagogy
09:17

3D Printing of Biomolecular Models for Research and Pedagogy

Published on: March 13, 2017

24.9K
Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

10.9K

Area of Science:

  • Environmental Science
  • Materials Science
  • Computational Chemistry

Background:

  • Molecular simulations are crucial for understanding micro- and nanoplastic toxicity.
  • Modeling nanoplastics requires complex folding of polymer chains, demanding optimized procedures.

Purpose of the Study:

  • To establish a systematic workflow for preparing stable nanoplastic structures using molecular simulations.
  • To provide a reliable method for modeling various plastic types for toxicity assessments.

Main Methods:

  • Utilized simulated annealing with the CHARMM36 force field for initial nanoplastic structure preparation.
  • Performed quantum chemical geometry optimizations using GFN2-xTB, followed by DFT benchmarking.
  • Applied the protocol to polyethylene, polypropylene, polystyrene, and nylon-66.

Main Results:

  • Achieved stable nanoplastic structures with geometries consistent with theoretical and experimental findings.
  • Observed distinct structures for different polymers: crystalline for polyethylene, helical for polypropylene and polystyrene, and hydrogen-bonded for nylon-66.
  • Made optimized nanoplastic structures publicly available in an online repository.

Conclusions:

  • The developed workflow provides a robust method for simulating nanoplastic particles.
  • The generated structures and data will advance research in nanoplastic toxicity and simulation studies.
  • The open-access data repository facilitates further ensemble simulations and community research.