Abstract

Dynamic micro-bead arrays offer great flexibility and potential as sensing tools in various scientific fields. Here we present a software-oriented approach for fully automated assembly of versatile dynamic micro-bead arrays using multi-beam optical tweezers combined with intelligent control techniques. Four typical examples, including the collision-free sorting of array elements by bead features, are demonstrated in real time. Control algorithms and experimental apparatus for these demonstrations are also described.

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References

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  14. http://www.rubiks.com/
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    [CrossRef] [PubMed]
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  18. N. Otsu, “A threshold selection method from gray-level histograms,” IEEE Trans. Sys., Man, Cybernetics SMC-9, 62–66 (1979).
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2008

2007

C. D. Onal and M. Sitti, “Visual servoing-based autonomous 2-D manipulation of microparticles using a nanoprobe,” IEEE Trans. Contr. Syst. Technol. 15(5), 842–852 (2007).
[CrossRef]

W.-H. Tan and S. Takeuchi, “A trap-and-release integrated microfluidic system for dynamic microarray applications,” Proc. Natl. Acad. Sci. U.S.A. 104(4), 1146–1151 (2007).
[CrossRef] [PubMed]

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

2006

2005

P. Y. Chiou, A. T. Ohta, and M. C. Wu, “Massively parallel manipulation of single cells and microparticles using optical images,” Nature 436(7049), 370–372 (2005).
[CrossRef] [PubMed]

2004

J. M. Tam, I. Biran, and D. R. Walt; “An imaging fiber-based optical tweezer array for microparticle array assembly,” Appl. Phys. Lett. 84(21), 4289–4291 (2004).
[CrossRef]

G. S. Sinclair, P. Jordan, J. Courtial, M. Padgett, J. Cooper, and Z. J. Laczik, “Assembly of 3-dimensional structures using programmable holographic optical tweezers,” Opt. Express 12(22), 5475–5480 (2004).
[CrossRef] [PubMed]

2003

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

D. G. Grier, “A revolution in optical manipulation,” Nature 424(6950), 810–816 (2003).
[CrossRef] [PubMed]

2002

2000

C. Mio and D. W. M. Marr, “Optical trapping for the manipulation of colloidal particles,” Adv. Mater. 12(12), 917–920 (2000).
[CrossRef]

1986

1979

N. Otsu, “A threshold selection method from gray-level histograms,” IEEE Trans. Sys., Man, Cybernetics SMC-9, 62–66 (1979).

Ashkin, A.

Biran, I.

J. M. Tam, I. Biran, and D. R. Walt; “An imaging fiber-based optical tweezer array for microparticle array assembly,” Appl. Phys. Lett. 84(21), 4289–4291 (2004).
[CrossRef]

Bjorkholm, J. E.

Chapin, S. C.

Chiou, P. Y.

P. Y. Chiou, A. T. Ohta, and M. C. Wu, “Massively parallel manipulation of single cells and microparticles using optical images,” Nature 436(7049), 370–372 (2005).
[CrossRef] [PubMed]

Chu, S.

Cooper, J.

Courtial, J.

Curtis, J. E.

J. E. Curtis, B. A. Koss, and D. G. Grier, “Dynamic holographic optical tweezers,” Opt. Commun. 207(1-6), 169–175 (2002).
[CrossRef]

Daria, V. R.

Dufresne, E. R.

Dziedzic, J. M.

Eriksen, R. L.

Germain, V.

Glueckstad, J.

Grier, D. G.

D. G. Grier, “A revolution in optical manipulation,” Nature 424(6950), 810–816 (2003).
[CrossRef] [PubMed]

J. E. Curtis, B. A. Koss, and D. G. Grier, “Dynamic holographic optical tweezers,” Opt. Commun. 207(1-6), 169–175 (2002).
[CrossRef]

Hirano, K.

Y. Tanaka, H. Kawada, K. Hirano, M. Ishikawa, and H. Kitajima, “Automated manipulation of non-spherical micro-objects using optical tweezers combined with image processing techniques,” Opt. Express 16(19), 15115–15122 (2008).
[CrossRef] [PubMed]

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

Ishikawa, M.

Y. Tanaka, H. Kawada, K. Hirano, M. Ishikawa, and H. Kitajima, “Automated manipulation of non-spherical micro-objects using optical tweezers combined with image processing techniques,” Opt. Express 16(19), 15115–15122 (2008).
[CrossRef] [PubMed]

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

Jordan, P.

Kambara, H.

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

Kawada, H.

Kitajima, H.

Kohara, Y.

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

Koss, B. A.

J. E. Curtis, B. A. Koss, and D. G. Grier, “Dynamic holographic optical tweezers,” Opt. Commun. 207(1-6), 169–175 (2002).
[CrossRef]

Laczik, Z. J.

Marr, D. W. M.

C. Mio and D. W. M. Marr, “Optical trapping for the manipulation of colloidal particles,” Adv. Mater. 12(12), 917–920 (2000).
[CrossRef]

Mio, C.

C. Mio and D. W. M. Marr, “Optical trapping for the manipulation of colloidal particles,” Adv. Mater. 12(12), 917–920 (2000).
[CrossRef]

Nagata, H.

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

Noda, H.

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

Ohta, A. T.

P. Y. Chiou, A. T. Ohta, and M. C. Wu, “Massively parallel manipulation of single cells and microparticles using optical images,” Nature 436(7049), 370–372 (2005).
[CrossRef] [PubMed]

Okano, K.

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

Onal, C. D.

C. D. Onal and M. Sitti, “Visual servoing-based autonomous 2-D manipulation of microparticles using a nanoprobe,” IEEE Trans. Contr. Syst. Technol. 15(5), 842–852 (2007).
[CrossRef]

Otsu, N.

N. Otsu, “A threshold selection method from gray-level histograms,” IEEE Trans. Sys., Man, Cybernetics SMC-9, 62–66 (1979).

Padgett, M.

Rodrigo, P. J.

Sinclair, G. S.

Sitti, M.

C. D. Onal and M. Sitti, “Visual servoing-based autonomous 2-D manipulation of microparticles using a nanoprobe,” IEEE Trans. Contr. Syst. Technol. 15(5), 842–852 (2007).
[CrossRef]

Takeuchi, S.

W.-H. Tan and S. Takeuchi, “A trap-and-release integrated microfluidic system for dynamic microarray applications,” Proc. Natl. Acad. Sci. U.S.A. 104(4), 1146–1151 (2007).
[CrossRef] [PubMed]

Tam, J. M.

J. M. Tam, I. Biran, and D. R. Walt; “An imaging fiber-based optical tweezer array for microparticle array assembly,” Appl. Phys. Lett. 84(21), 4289–4291 (2004).
[CrossRef]

Tan, W.-H.

W.-H. Tan and S. Takeuchi, “A trap-and-release integrated microfluidic system for dynamic microarray applications,” Proc. Natl. Acad. Sci. U.S.A. 104(4), 1146–1151 (2007).
[CrossRef] [PubMed]

Tanaka, Y.

Y. Tanaka, H. Kawada, K. Hirano, M. Ishikawa, and H. Kitajima, “Automated manipulation of non-spherical micro-objects using optical tweezers combined with image processing techniques,” Opt. Express 16(19), 15115–15122 (2008).
[CrossRef] [PubMed]

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

Walt, D. R.

J. M. Tam, I. Biran, and D. R. Walt; “An imaging fiber-based optical tweezer array for microparticle array assembly,” Appl. Phys. Lett. 84(21), 4289–4291 (2004).
[CrossRef]

Wu, M. C.

P. Y. Chiou, A. T. Ohta, and M. C. Wu, “Massively parallel manipulation of single cells and microparticles using optical images,” Nature 436(7049), 370–372 (2005).
[CrossRef] [PubMed]

Adv. Mater.

C. Mio and D. W. M. Marr, “Optical trapping for the manipulation of colloidal particles,” Adv. Mater. 12(12), 917–920 (2000).
[CrossRef]

Anal. Chem.

H. Noda, Y. Kohara, K. Okano, and H. Kambara, “Automated bead alignment apparatus using a single bead capturing technique for fabrication of a miniaturized bead-based DNA probe array,” Anal. Chem. 75(13), 3250–3255 (2003).
[CrossRef] [PubMed]

Appl. Phys. Lett.

J. M. Tam, I. Biran, and D. R. Walt; “An imaging fiber-based optical tweezer array for microparticle array assembly,” Appl. Phys. Lett. 84(21), 4289–4291 (2004).
[CrossRef]

Electron. Lett.

Y. Tanaka, K. Hirano, H. Nagata, and M. Ishikawa, “Real-time three-dimensional orientation control of non-spherical micro-objects using laser trapping,” Electron. Lett. 43(7), 412–414 (2007).
[CrossRef]

IEEE Trans. Contr. Syst. Technol.

C. D. Onal and M. Sitti, “Visual servoing-based autonomous 2-D manipulation of microparticles using a nanoprobe,” IEEE Trans. Contr. Syst. Technol. 15(5), 842–852 (2007).
[CrossRef]

IEEE Trans. Sys., Man, Cybernetics

N. Otsu, “A threshold selection method from gray-level histograms,” IEEE Trans. Sys., Man, Cybernetics SMC-9, 62–66 (1979).

Nature

D. G. Grier, “A revolution in optical manipulation,” Nature 424(6950), 810–816 (2003).
[CrossRef] [PubMed]

P. Y. Chiou, A. T. Ohta, and M. C. Wu, “Massively parallel manipulation of single cells and microparticles using optical images,” Nature 436(7049), 370–372 (2005).
[CrossRef] [PubMed]

Opt. Commun.

J. E. Curtis, B. A. Koss, and D. G. Grier, “Dynamic holographic optical tweezers,” Opt. Commun. 207(1-6), 169–175 (2002).
[CrossRef]

Opt. Express

Opt. Lett.

Proc. Natl. Acad. Sci. U.S.A.

W.-H. Tan and S. Takeuchi, “A trap-and-release integrated microfluidic system for dynamic microarray applications,” Proc. Natl. Acad. Sci. U.S.A. 104(4), 1146–1151 (2007).
[CrossRef] [PubMed]

Other

D. H. Ballard, and C. M. Brown, Computer Vision (Prentice-Hall, 1982), Chap. 3–4.

J. Chen, Group Representation Theory for Physicists (World Scientific, 1989), Chap. 1.

Y. Tanaka, H. Kawada, K. Hirano, M. Ishikawa, and H. Kitajima, Japan patent 2008–101060 (April, 9, 2008).

http://www.rubiks.com/

A. Murakami, Y. Tanaka, and Y. Kinouch, “Laser manipulation system for automatic control of microscopic particles,” in Proceedings of the 4th Asian Control Conference, Singapore, 25–27 Sept. 2002, pp.414–419.

Supplementary Material (4)

» Media 1: MOV (1740 KB)     
» Media 2: MOV (1860 KB)     
» Media 3: MOV (1435 KB)     
» Media 4: MOV (1485 KB)     

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Figures (8)

Fig. 1
Fig. 1

A new software-oriented approach to assemble a dynamic micro-bead array using multi-beam optical tweezers combined with intelligent control techniques. Labeled beads dispersed in pipetted liquid on a cover glass are automatically trapped, assembled, and sorted to act as a versatile dynamic microarray.

Fig. 2
Fig. 2

Assignment of sixteen destinations and collisionless trajectories for (a): negligible bead size, (b): non-negligible bead size compared with grid size.

Fig. 3
Fig. 3

Sorting method using the collision-free cyclic shifts. (b): Cyclic shift of six beads, (c): that of upper four beads, and (d): that of lower four beads, for the elements of a 3×2 array. (e): A 4×3 array is divided into two 2×3 arrays.

Fig. 4
Fig. 4

Optical and control system configurations for handling an array in a two-and-half-dimensional (2.5D) working space. Multi-beam optical tweezers, which is generated by a time-sharing synchronized scanning (T3S) approach, can be controlled with a PC-controlled 2-axis steering mirror and a lens mounted on a PC-controlled linear stage. Commands by a control algorithm or a PC’s 3-button-mouse determine the position and orientation of the assembled array which can be located in 2.5D space.

Fig. 5
Fig. 5

(Media 1) Video frame sequence of the fully automated assembly of a 4×4 array. Computer vision detects all beads in an image, and sixteen beads nearest to the center position are trapped simultaneously (figure (b)). The sixteen beads are simultaneously transported along the collisionless paths (figure (a), (c)) to form the 4×4 array (figure (d)). Subsequent operations such as shrinking (figure (e)) and rotating (figure (f)) of the array are also demonstrated. The accompanying movie is in real time, not accelerated.

Fig. 6
Fig. 6

(Media 2) Video frame sequence of a fully automated assembly of a 6×6 array using three sets of T3S optical tweezers. The 36 beads are simultaneously transported along the collisionless paths based on the proposed algorithm to form the 6×6 array. Subsequent operations such as shrinking (figure (b)) and translating the Z-axis of the 2×6 arrays (figure (c)) are also demonstrated. The accompanying movie is in real time, not accelerated.

Fig. 7
Fig. 7

(Media 3) Video frame sequence of a fully automated assembly of a dyed beads array. Ri: red beads, Yi: yellow beads, and Bi: blue beads. Computer vision detects all bead positions in an image, and three-color pairs nearest to the center position are trapped and transported simultaneously to form a colored 3×2 array (figure (a), (b)). Subsequent sorting procedure (figure (b)-(e)) proceeds automatically using knowledge data based on group theory in order to rearrange the order of colors like a traffic light. The accompanying movie is in real time, not accelerated.

Fig. 8
Fig. 8

(Media 4) Video frame sequence of a fully automated assembly and sorting of a 3×3 array consisting of silica beads with different sizes. The detected nine beads are trapped, and transported along the collisionless paths, simultaneously, to form a 3×3 array (figure (a), (b)). Subsequent cyclic shift of four beads (CS4: figure (c), (d), (e), (g), (h), (i), (k)) and six beads (CS6: figure (f), (j)) are executed successively using knowledge data based on group theory to sort the array elements by size. The accompanying movie is in real time, not accelerated.

Equations (15)

Equations on this page are rendered with MathJax. Learn more.

y d N ( i 1 ) + 1 = = y d N ( i 1 ) + N < y d N i + 1 = = y d N i + N , i [ 1 , M 1 ] ,
x d N ( i 1 ) + 1 < x d N ( i 1 ) + 2 < < x d N ( i 1 ) + N , i [ 1 , M 1 ] .
y i N ( i 1 ) + 1 y i N ( i 1 ) + N y i N i + 1 y i N i + N , i [ 1 , M 1 ] ,
x i N ( i 1 ) + 1 x i N ( i 1 ) + 2 x i N ( i 1 ) + N , i [ 1 , M 1 ] ,
max ( y i N ( i 1 ) + 1 , , y i N ( i 1 ) + N ) min ( y i N i + 1 , , y i N i + N ) , i [ 1 , M 1 ] .
δ p k = [ δ x k , δ y k ] T = ( p d k p i k ) / n ,
n max | p d k p i k r k | , k = 1 , , M N ,
P ( t s + 1 ) = P ( t s + τ ) = P ( t s ) + δ P , s = 0 , , n 1 ,
x t s i = x i i + ( x d i x i i ) t s n = x i i ( 1 t s n ) + x d i n t s     < x i j ( 1 t s n ) + x d j n t s = x i j + ( x d j x i j ) t s n = x t s j   for  i < j ,
x t s N ( i 1 ) + 1 < x t s N ( i 1 ) + 2 < < x t s N ( i 1 ) + N , i [ 1 , M 1 ] ,
max ( y t s N ( i 1 ) + 1 , , y t s N ( i 1 ) + N ) < min ( y t s N i + 1 , , y t s N i + N ) , i [ 1 , M 1 ] ,
P ( t s + 1 ) = P ( t s + τ ) = P ( t s ) + δ m P , s = 0 , , 2 n + c s t o p 1 ,
δ m p k = { Step 1:  [ 0 , 0 ] T i f   c o l l i s i o n   o c c u r s   i n   n e x t   t i m e s t e p   o r y t s k = y d k , o t h e r w i s e   [ 0 , δ y k ] T until   y t s k = y t s-1 k , k [ 1 , M N ] , Step 2:   [ δ x k , 0 ] T     for   s = c s t e p 1 , c s t e p 1 + 1 , , c s t e p 1 + n 1 , Step 3:   [ 0 , 0 ] T i f   t h e   d e s t i n a t i o n   i s   r e a c h e d , o t h e r w i s e   [ 0 , δ y k ] T     for   s = c s t e p 1 + n , , 2 n + c s t o p 1 ,
L i 2 D max N ,
( G 1 G 2 G 3 G 4 G 5 G 6 B B 2 B 3 B 4     B 5     B 6 ) ,

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