Dynamic simulation and modeling of the motion modes produced during the 3D controlled manipulation of biological micro/nanoparticles based on the AFM

Saraee, M. B.; Korayem, M. H.

doi:10.1016/j.jtbi.2015.04.021

Cited by 13 publications

(6 citation statements)

References 18 publications

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“…Mirowski et al [38] provided the magnetic field gradient by magnetic probe to sort out magnetic particles on an microfluidic platform with an array of magnetic trap elements and the particle size was 1 µm in diameter. Currently, the common methods used for the manipulation of single nanoscale objects by AFM are pushing, rolling, cutting, drilling and dissecting [7][8][9]. Also, the main methods are pushing and sliding of the particle along a linear path.…”

Section: Resultsmentioning

confidence: 99%

“…Due to the high resolution of atomic force microscope (AFM), it is a proper tool for the imaging and manipulation of nano objects [5,6]. Korayem and Saraee et al [7][8][9] modeled and simulated the pushing and sliding of nanoparticles by AFM for biological sample separation and positioning. Hsieh et al [10] utilized the AFM tip to push the gold nanorods, demonstrating that it can be used for the building of blocks in nano-fabrication.…”

Section: Introductionmentioning

confidence: 99%

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Mechanical manipulation of magnetic nanoparticles by magnetic force microscopy

Liu

Zhang

et al. 2017

Journal of Magnetism and Magnetic Materials

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mechanical manipulation of magnetic nanoparticles by magnetic force microscopy

Liu

Zhang

et al. 2017

Journal of Magnetism and Magnetic Materials

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“…Finally, the governing dynamic equations for the center of mass of the probe tip and the forces exerted in three directions are obtained as follows [36]:…”

Section: Rabinovich Surface Roughness Model and Its Developmentmentioning

confidence: 99%

“…The equations related to the critical sliding and rolling forces in the 3D manipulation process are as follows [36]: Figure 6 illustrates the modeling algorithm for the manipulation of a cylindrical biological nanoparticle on a rough substrate. Once the ultimate force exerted on a nanoparticle overcomes the critical sliding or rolling force, the manipulation process begins and the nanoparticle is displaced on the rough substrate until it reaches the target position.…”

Section: Rabinovich Surface Roughness Model and Its Developmentmentioning

confidence: 99%

Dynamic modeling and simulation of 3D manipulation on rough surfaces based on developed adhesion models

Saraee

Korayem

2016

Int J Adv Manuf Technol

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Since surface roughness greatly influences the force of adhesion between two bodies, the dynamic behavior of different biological micro/nanoparticles on rough surfaces during 3D manipulation operations has been studied in this paper by employing the atomic force microscope (AFM). In this regard, the force of adhesion between two surfaces has been simultaneously investigated on the basis of two important approaches. First, the interactions between two surfaces have been evaluated based on the available contact mechanics theories, and depending on the type of biological nanoparticle studied in this research, an appropriate model has been presented. Then, the common adhesion models of Rumpf and Rabinovich have been modified based on the Van der Waals force and with regard to the cylindrical geometry of the nanoparticles. Finally, based on the Schwartz method, by developing the adhesion model based on the two approaches mentioned above, the adhesion force between cylindrical biological nanoparticles and rough surfaces has been extracted for the first time. The dynamic behavior of nanoparticles in 3D manipulation on a rough substrate has been modeled and then simulated and analyzed. The simulation results indicate that, by increasing the asperity radius, the critical force needed to manipulate a nanoparticle increases. Also, in contrast to the sliding mode, the critical force of movement in the rolling mode diminishes with the increase of nanoparticle radius. The experimental results obtained from the topography of glass and silica substrates indicate that the Rumpf model underestimates the adhesion force relative to the Rabinovich model.

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“…Image sensing at a small scale is essential in many fields, such as for the MEMS device defect detection [ 1 , 2 ], precise manipulation [ 3 , 4 , 5 ], micromaterial characterization [ 6 , 7 ] and so on. In these tasks, a microscope is usually required to enlarge the micro object to observe the details clearly.…”

Section: Introductionmentioning

confidence: 99%

Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

Shen

Wan

Zhang

et al. 2015

Sensors

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Image sensing at a small scale is essentially important in many fields, including microsample observation, defect inspection, material characterization and so on. However, nowadays, multi-directional micro object imaging is still very challenging due to the limited field of view (FOV) of microscopes. This paper reports a novel approach for multi-directional image sensing in microscopes by developing a rotatable robot. First, a robot with endless rotation ability is designed and integrated with the microscope. Then, the micro object is aligned to the rotation axis of the robot automatically based on the proposed forward-backward alignment strategy. After that, multi-directional images of the sample can be obtained by rotating the robot within one revolution under the microscope. To demonstrate the versatility of this approach, we view various types of micro samples from multiple directions in both optical microscopy and scanning electron microscopy, and panoramic images of the samples are processed as well. The proposed method paves a new way for the microscopy image sensing, and we believe it could have significant impact in many fields, especially for sample detection, manipulation and characterization at a small scale.

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Dynamic simulation and modeling of the motion modes produced during the 3D controlled manipulation of biological micro/nanoparticles based on the AFM

Cited by 13 publications

References 18 publications

Mechanical manipulation of magnetic nanoparticles by magnetic force microscopy

Mechanical manipulation of magnetic nanoparticles by magnetic force microscopy

Dynamic modeling and simulation of 3D manipulation on rough surfaces based on developed adhesion models

Multidirectional Image Sensing for Microscopy Based on a Rotatable Robot

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