Technological watch
New tool allows unprecedented modeling of magnetic nanoparticles
Researchers at North Carolina State University have developed a new computational tool that allows users to conduct simulations of multi-functional magnetic nanoparticles in unprecedented detail. The advance paves the way for new work aimed at developing magnetic nanoparticles for use in applications from drug delivery to sensor technologies.
Many applications of MNPs require an understanding of how the nanoparticles will behave in complex environments, such as using MNPs to deliver a specific protein or drug molecule to targeted cancer-affected cell using external magnetic fields. In these cases, it is important to be able to accurately model how MNPs will respond to different chemical environments. . Previous computational modeling techniques that looked at MNPs were unable to account for all of the chemical interactions MNPs experience in a given colloidal or biological environment, instead focusing primarily on physical interactions.
“Those chemical interactions can play an important role in the functionality of the MNPs and how they respond to their environment,” says Akhlak Ul-Mahmood, first author of the paper and a Ph.D. student at NC State. “And detailed computational modeling of MNPs is important because models offer an efficient path for us to engineer MNPs for specific applications. That’s why we’ve developed a method that accounts for all of these interactions and created open-source software that the materials science community can use to implement it.”
To demonstrate the accuracy of the new tool, the researchers focused on oleic acid ligand-functionalized magnetite nanoparticles, which have already been studied and are well-understood.
“We found that our tool’s predictions of the behavior and properties of these nanoparticles was consistent with what we know about these nanoparticles based on experimental observation,” Mahmood says.
For more information: North Carolina State University
Subject Classifications
Materials Processing and Treatment
Materials Properties and Performance
Materials Testing and Evaluation
Nonmetallic Engineering Materials
Email a friend
Many applications of MNPs require an understanding of how the nanoparticles will behave in complex environments, such as using MNPs to deliver a specific protein or drug molecule to targeted cancer-affected cell using external magnetic fields. In these cases, it is important to be able to accurately model how MNPs will respond to different chemical environments. . Previous computational modeling techniques that looked at MNPs were unable to account for all of the chemical interactions MNPs experience in a given colloidal or biological environment, instead focusing primarily on physical interactions.
“Those chemical interactions can play an important role in the functionality of the MNPs and how they respond to their environment,” says Akhlak Ul-Mahmood, first author of the paper and a Ph.D. student at NC State. “And detailed computational modeling of MNPs is important because models offer an efficient path for us to engineer MNPs for specific applications. That’s why we’ve developed a method that accounts for all of these interactions and created open-source software that the materials science community can use to implement it.”
To demonstrate the accuracy of the new tool, the researchers focused on oleic acid ligand-functionalized magnetite nanoparticles, which have already been studied and are well-understood.
“We found that our tool’s predictions of the behavior and properties of these nanoparticles was consistent with what we know about these nanoparticles based on experimental observation,” Mahmood says.
For more information: North Carolina State University
Subject Classifications
Materials Processing and Treatment
Materials Properties and Performance
Materials Testing and Evaluation
Nonmetallic Engineering Materials
Email a friend
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.
