Most Recent Publications
3D optical trapping by a tightly focused circular airy beam
Habib Moradi, Mahmoud Jabbarpour, Daryoush Abdollahpour, and Faegheh Hajizadeh
Optics Letters
Doi: 10.1364/OL.464052Microsphere-coupled optical tweezers
Mohammad Hossein Khosravi, Vahid Shahabadi and Faegheh Hajizadeh
Optics Letters
Doi: 10.1364/OL.431271Escape velocity sorting in optical tweezers system using a home-made piezo mirror
Milad Malekmohammadi, Ehsan A Akhlaghi, Jamal Soltani and Faegheh Hajizadeh
Journal of Optics
Doi: 10.1088/2040-8986/ab7d88Gear-like rotatable optical trapping with radial carpet beams
Jamal Bayat, Faegheh Hajizadeh, Ali Mohammad Khazaei and Saifollah Rasouli
Scientific Reports
Doi: 10.1038/s41598-020-68695-8Efficient optical trapping with cylindrical vector beams
Habib Moradi, Vahid Shahabadi, E. Madadi, Ebrahim Karimi, and Faegheh Hajizadeh
Optics Express
Doi: 10.1364/OE.27.007266Ongoing Projects
Acoustic Tweezers
Mahdi Rameh
In Collaboration with Optical Metrology Group
A well-known non-contact method for microscopic manipulation is optical tweezers. However, recent studies have shown that the potential of microscopic trapping can be expanded by using high-frequency standing sound waves, called acoustic tweezers. Acoustic tweezers are biocompatible and can trap larger particles compared to the optical tweezers while the heat-damaging effect is much less. Here, we characterize acoustic tweezers to trap particles with the few tens of micrometers produced by a homemade acoustic device.
Dual-beam Optical Tweezers
Shanay Zafari , Zahra Akbarpour , Milad Malekmohammadi
A dual-beam optical tweezers setup consists of two focused laser beams that could be used to trap two different objects or to trap a large particle like a suspended cell in 3D. Two traps could move independently in solution and this makes it possible to probe the mechanical properties of suspended cells (in 3D). Here, we engaged in developing dual-beam optical tweezers for biological application.
Deep Learning for Microscopy and Optical Tweezers
Javid Farazin
We have begun to use a data-driven approach relying on deep learning to improve the tracking of microscopic particles and the optical tweezers' force measurements using convolutional neural networks.