Study of process parameters and formative mechanism of patterns on a dip-pen nanolithography array using molecular dynamics simulations

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Study of process parameters and formative mechanism of patterns

on a dip-pen nanolithography array using molecular dynamics simulations

Cheng-Da Wu

a

, Te-Hua Fang

a,*

_{, Tsung-Tse Wu}

b

a_{Department of Mechanical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 807, Taiwan} b_{Institute of Mechanical and Electromechanical Engineering, National Formosa University, Yunlin 632, Taiwan}

a r t i c l e i n f o

Article history:

Received 29 September 2011 Received in revised form 12 December 2011 Accepted 18 December 2011 Available online 23 December 2011 Keywords:

Dip-pen nanolithography SAM

Array

a b s t r a c t

The process parameters, pattern transfer mechanism, and pattern characterizations of alkanethiol self-assembled monolayers (SAMs) on a dip-pen nanolithography array are studied using molecular dynamics simulations. The effects of the type of probe tip, distance between probe tips, deposition temperature, probe tip velocity, probe tip radius, and humidity are evaluated in terms of molecular transference, alkanethiol meniscus characteristics, surface adsorption energy, number of transferred chains, and pattern characteristics. The simulation results clearly show that the molecular transfer ability of a conical tip array is better than that of a pyramidal tip array. For a conical tip array, the number of transferred chains increases with decreasing distance between tips, whereas for a pyramidal tip array, the number of transferred chains decreases. When the deposition temperature increases, the number of transferred molecules, the size of the pattern deposited on the substrate, and the density of molecular packing signiﬁcantly increase due to an increase in molecular kinetic energy. The number of transferred chains signiﬁcantly decreases with increasing tip velocity. The number of transferred molecules and meniscus size increase with increasing humidity.

1. Introduction

With recent progress in nanotechnology and the development of advanced nanodevices, the direct patterning of versatile organic or inorganic materials on solid substrates has increased in impor-tance. Dip-pen nanolithography (DPN)[1]has been proven to be a useful tool for the direct writing of diverse nanopatterns on substrates. In DPN, an atomic force microscope (AFM) tip is used to deliver desired molecules, such as self-assembled monolayers (SAMs)[1], proteins[2,3], polymers[4], and inorganic materials

[5,6], to the surface via a solvent meniscus, which naturally forms in the ambient atmosphere. The tip is used as a nanoscale pen, allowing high-resolution patterning with a number of molecular inks on a variety of substrates[7e11]. Several molecular inks can be deposited or aligned on a substrate by the tip because AFM can control the position of deposition. DPN with a single probe tip can arbitrarily create patterns with high-resolution and registration, but its throughput is limited[12,13]. Recently, two-dimensional DPN has emerged as a viable and robust large-area patterning method while maintaining DPN’s nanoscale feature sizes[14,15]. A

similar technique called polymer pen lithography (PPL), which uses a tip array, is widely used [16]. Rather than using hard silicon cantilevers, as in DPN, PPL uses tips made from the elastomer polydimethylsiloxane (PDMS). Arrays containing many thousands of polymer pens have been formed using conventional photolithography.

Understanding the effects of process parameters on the trans-port and adsorption of ink molecules in the DPN process is essential to developing and fully controlling DPN. Giam et al.[17] experi-mentally conﬁrmed a model in which ink deposition rates are governed by ink surface coverage. However, most fundamental properties are extremely difﬁcult to obtain from experiments because molecules are quickly transported to the substrate (in less than 1.5 ns) before feature growth. Therefore, a molecular-level model that considers the complex physical and chemical interac-tions between molecules is required. Molecular dynamics (MD) simulations are a powerful atomic modeling technique for studying material behavior and atomic/molecular interactions at the nano-meter scale. We have recently reported the detailed formation and physical mechanisms in the DPN process using an MD simulation

[18]and found that molecular transfer ability strongly depends on temperature. Ahn[19]and Heo et al.[20,21]studied the effect of molecule-substrate binding energy in the DPN process. They found that increasing the molecule-substrate binding energy increases

* Corresponding author. Tel.: þ886 7 3814526 5336. E-mail address:fang.tehua@msa.hinet.net(T.-H. Fang).

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Polymer

j o u rn a l h o m e p a g e : w w w . e l s e v ie r . c o m / l o c a t e / p o l y m e r

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the molecular deposition rate and makes the monolayer well-ordered.

In the present study, terminal linear alkanethiols of the generic formula (CH3(CH2)15SH, HDT), a prototypical molecule in DPN, are

deposited on a substrate. The effects of the type of tip, distance between tips, deposition temperature, tip velocity, tip radius, and humidity on the DPN array are systematically investigated. The deposition results are evaluated in terms of molecular trajectories, surface adsorption energy, number of adsorbed chains, and pattern formation.

2. Methodology

Fig. 1(a) and (b) show simple schematics of array deposition in the DPN process and an MD model, respectively. The model consists of three silicon (Si) probe tips, a gold (Au) substrate, and HDT molecules adsorbed on the tips. The tips were assumed to be a rigid body to simplify the DPN array analysis. The Au substrate consisted of a perfect face-centered cubic (FCC) single crystal with a length, width, and height of 22.4, 6.9, and 2.3 nm, respectively. 297 HDT molecules were adsorbed on each tip and underwent an MD equilibrium run of 300 ps in order to achieve energy relaxation. In the simulation, the tips have a common constant unit displacement of 2 105_{nm per time-step moving along the Z-axis to deposit the}

SAM pattern and pull-off from a substrate. The time-step unit was 1015s. A three-dimensional system was simulated in the½110, ½100, and ½101 directions (X-, Y-, and Z-axes, respectively). A periodic boundary condition was applied to the X- and Y-axes of the Au substrate to simulate a large system by modeling a small part

that is far away from the edge. Twoﬁxed layers of Au atoms were imposed beneath the substrate to constrain the whole system in the vertical direction. Before the DPN simulation started, the distance between the tips (including the HDT molecules) and the substrate was set to 1.2 nm for all tested cases. The tips were then indented to a given depth. The whole system was simulated at temperatures of 200e500 K.

The alkylthiol chain description presented by Hautman and Klein[22]is used in this study. The CH2and CH3groups were treated

as a single spherical molecule to simplify the model to 17 united molecules per chain. Because the bonds undergo distortion and the chain length decreases under high compression, the Hautman and Klein model was modiﬁed to correct the potential functions to allow for bond stretching and the 12-3 form for the surface potential (interactions of CH2eAu substrate and CH3eAu substrate), as

mentioned in Ref.[23]. The bond-bending terms were modeled using a harmonic potential. The torsional terms were assumed to have a RyckaerteBellemans dihedral potential form, which is a power series expansion of the dihedral angle[22]. The intermo-lecular interaction and intramointermo-lecular non-bonding interaction for atoms separated by more than three bonds along a chain were represented by the Lennard-Jones potential. The Lennard-Jones potential function was also employed to describe the phys-isorption interaction between the tip and HDT molecules[24]. To describe molecule transfer, Luedtke et al.[25]modeled the SeAu interaction as a Morse potential function (S atoms and Au substrate have chemisorption interaction) and_{ﬁtted the} parame-ters to experimentally obtained binding energies. Morse potential is used here to describe the interaction among Au atoms. The potential

Fig. 1. (a) Schematic illustration of the array deposition of the DPN process and (b) an MD model (the tip array comprises three probe tips of the same type of tip). C.-D. Wu et al. / Polymer 53 (2012) 857e863

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4. Conclusion

MD simulation was used to investigate the process parameters of DPN arrays, including the type of tip, distance between tips, deposition temperature, tip velocity, tip radius, and humidity. The following conclusions were obtained:

(1) The molecular transfer ability of the conical tip array is better than that for the pyramidal tip array.

(2) The number of transferred chains increases with decreasing distance between tips for the conical tip array, whereas it decreases for the pyramidal tip array.

(3) When the deposition temperature is increased, the number of transferred molecules, the size of the pattern deposited on the substrate, and the density of molecular packing signiﬁcantly increase.

(4) The number of transferred chains increases with decreasing tip velocity.

(5) The meniscus size increases when water molecules are added, which promotes molecular transfer.

Acknowledgment

This work was supported by the National Science Council of Taiwan under grants 2628-E-151-003-MY3 and NSC-100-2221-E-151-018-MY3.

References

[1] Piner RD, Zhu J, Xu F, Hong S, Mirkin CA. Science 1999;203:661e3. [2] Lee KB, Park SJ, Mirkin CA, Smith JC, Mrksich M. Science 2002;295:

1702e5.

[3] Elena B, Rocio MD, Daniel RM, Anabel L, Daniel M. Adv Mater 2010;22: 352e5.

[4] Noy A, Miller AE, Klare JE, Weeks BL, Woods BW, DeYoreo JJ. Nano Lett 2002; 2:109e12.

[5] Su M, Liu X, Li SY, Dravid VP, Mirkin CA. J Am Chem Soc 2002;124: 1560e1.

[6] Liu X, Fu L, Hong S, Dravid VP, Mirkin CA. Adv Mater 2002;14:231e4. [7] Mirkin CA. ACS Nano 2007;1:79e83.

[8] Fang TH, Chang WJ, Wu CD. Microelectron Eng 2008;85:223e6.

[9] Fang TH, Chang WY, Lin SJ, Fang CN. J Colloid Interface Sci 2010;345: 19e26.

[10] Nafday OA, Vaughn MW, Weeks BL. J Chem Phys 2006;125:144703. [11] Cho Y, Ivanisevic A. Langmuir 2006;22:8670e4.

[12] Kramer S, Fuierer RR, Gorman CB. Chem Rev 2003;103:4367e418. [13] Maoz R, Cohen SR, Sagiv J. Adv Mater 1999;11:55e61.

[14] Haaheim J, Val V, Bussan J, Rozhok S, Jang JW, Fragala J, et al. Scanning 2010; 32:49e59.

[15] Bullen D, Chung SW, Wang X, Zou J, Mirkin CA, Liu C. Appl Phys Lett 2004; 84(5):789e91.

[16] Huo F, Zheng Z, Zheng G, Giam LR, Zhang H, Mirkin CA. Science 2008;321: 1658e60.

[17] Giam LR, Wang Y, Mirkin CA. J Phys Chem A 2009;113:3779e82. [18] Wu CD, Fang TH, Lin JF. Langmuir 2010;26:3237e41.

[19] Ahn Y, Hong S, Jang J. J Phys Chem B 2006;110:4270e3.

[20] Heo DM, Yang M, Hwang S, Jang J. J Phys Chem C 2008;112:8791e6. [21] Heo DM, Yang M, Hwang S, Kim H, Saha LC, Jang J. J Phys Chem C 2009;113:

13813e8.

[22] Hautman J, Klein ML. J Chem Phys 1989;91:4994e5001. [23] Tupper KJ, Brenner DW. Langmuir 1994;10:2335e8. [24] Sung IH, Kim DE. Appl Phys A 2005;81:109e14.

[25] Luedtke WD, Landman U. J Phys Chem B 1998;102:6566e72.

[26] Haile JM. Molecular dynamics simulation: elementary methods. New York: Wiley; 1992.

[27] Rozhok S, Piner R, Mirkin CA. J Phys Chem B 2003;107:751e7.

[28] Sanedrin RG, Amro NA, Rendlen J, Nelson M. Nanotechnology 2010;21: 115302e8.

[29] Jang J, Schatz GC, Ratner MA. J Chem Phys 2002;116:3875e86. [30] Schwartz PV. Langmuir 2002;18:4041e6.

[31] Sheehan PE, Whitman LJ. Phys Rev Lett 2002;88(15):156104. Fig. 11. Snapshots of the transfer process of the ink molecules of the DPN array with

the effect of water molecules at the (a) indentation and (b) pull-off stages.

Fig. 12. Adsorption energy versus time with the effect of water molecules.