ToF-SIMS study on the cleaning methods of Au surface and their effects on the reproducibility of self-assembled monolayers

ToF-SIMS study on the cleaning methods of Au surface and their effects on the reproducibility of self-assembled monolayers

Applied Surface Science 255 (2008) 1025–1028 Contents lists available at ScienceDirect Applied Surface Science journal homepage: www.elsevier.com/lo...

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Applied Surface Science 255 (2008) 1025–1028

Contents lists available at ScienceDirect

Applied Surface Science journal homepage: www.elsevier.com/locate/apsusc

ToF-SIMS study on the cleaning methods of Au surface and their effects on the reproducibility of self-assembled monolayers Hyegeun Min a,b, Ji-Won Park a,b, Hyun Kyong Shon a, Dae Won Moon a,b, Tae Geol Lee a,b,* a b

Nanobio Fusion Research Center, Korea Research Institute of Standards and Science, Daejeon 305-600, Republic of Korea Department of Nano Surface Science, University of Science and Technology, Daejeon 305-333, Republic of Korea

A R T I C L E I N F O

A B S T R A C T

Article history:

The production of reproducible self-assembled monolayers (SAMs) is essential to many nano(bio)technology applications. To check the effects of different cleaning methods on a reproducible SAMs formation, the cleaning methods were varied and then used for preparing each SAM. The reproducibility of each SAM was examined by ToF-SIMS analysis along with principal component analysis (PCA). Using what we found to be a superior method of cleaning gold surfaces, alkanethiol SAMs with different terminal groups such as 1-dodecanethiol (DDT), 11-mercaptoundecanoic acid (MUA), 11-mercapto-1undecanol (MUD) were reproduced. Our statistical results show that reproducible alkanethiol SAMs on a well-cleaned gold surface can be produced within only a few standard deviation percentages obtained from point-to-point and sample-to-sample spectra. ß 2008 Elsevier B.V. All rights reserved.

Available online 13 May 2008 Keywords: Self-assembled monolayer Reproducibility ToF-SIMS PCA Quantification

1. Introduction Self-assembled monolayers (SAMs) have been enthusiastically received because of their two-dimensional ordered structure and their potential for various modifications of surface characteristics [1,2]. In particular, in the aftermath of Zisman’s concept of selfassembly on a metal surface in 1946 [5], monolayers of alkanethiolates on gold have probably been the most studied SAMs [3,4]. However, although SAMs of alkanethiol reagents are easily formed on a gold surface, the poor reproducibility of SAMs formation has limited the popularity of SAMs-based biochips for industrial and medical applications. This poor reproducibility could be due to any number of experimental factors such as the surface cleaning method, gold deposition method, the substrate for gold, etc. In recent years, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been used extensively to analyze the SAMs surface in order to obtain complex information about the sample composition, surface order, and chemical bonding of the SAMs, as well as to obtain quantitative information [6,7]. Together with the ToF-SIMS analysis, principal component analysis (PCA) has

* Corresponding author at: Nanobio Fusion Research Center, Korea Research Institute of Standards and Science, Daejeon 305-600, Republic of Korea. Tel.: +82 42 868 5129; fax: +82 42 868 5032. E-mail address: [email protected] (T.G. Lee). 0169-4332/$ – see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.apsusc.2008.05.099

been successfully used to decode complex information and to differentiate spectra of each SAM sample from large data sets [8,9]. In the present study, 1-dodecanethiol (DDT), 11-mercaptoundecanoic acid (MUA), and 11-mercapto-1-undecanol (MUD) SAMs were produced on a gold substrate cleaned using different methods, and were investigated by using the ToF-SIMS technique. Using PCA and statistical calculations such as the standard deviation and percentage difference, we were able to show how these different methods, super-piranha, piranha, and ethanol cleaning, affected a reproducible SAM formation. We suggest that the super-piranha cleaning is superior to the piranha cleaning method [10] in terms of removing organic contaminations on a gold surface reproducibly and successfully. The contact angle analysis (CAA) was used to examine the wetting properties of the gold surfaces cleaned by the various methods. 2. Experimental 2.1. Sample preparations The gold substrates were prepared by evaporating a 20 A˚ thick film of Ti and a 400 A˚ thick film of gold onto a Si wafer. Prior to the formation of each SAM, the gold substrates were subject to three kinds of aqueous removal processes for cleaning heavy organic materials. Five pieces of gold substrates were treated by superpiranha cleaning in a solution (1:10:6) 61% HNO3:30% H2O2:95% H2SO4 (v/v/v). Sulfuric acid was added slowly until the solution

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came to a boil. When the boiling stopped, the gold substrates were taken out from the cleaning solution. Another five pieces of gold substrates were cleaned in a piranha solution (1:4) 30% H2O2:98% H2SO4 (v/v) at room temperature for 5 min. (Caution: the superpiranha and piranha solution react violently with most organic materials and must be handled with extreme care.) The gold substrates that had been dipped in the super-piranha and piranha solutions were washed sufficiently with DI water. The other five substrates were sonicated in ethanol solution for 5 min and washed sufficiently with DI water as reference samples. For the formation of a SAM, each gold substrate was immersed in a 2 mM ethanol solution of 98% 1-dodecanethiol (DDT, Aldrich), 11-mercaptoundecanoic acid (MUA, Aldrich), and 11-mercapto-1undecanol (MUD, Aldrich) for 12 h or more. They were then rinsed sequentially with ethanol and dried by nitrogen gas.

was used to investigate the degree of spread-outness of intensities for each molecular ion peak, where Dx is the dispersion and x¯ is an average of variables, xi. In addition, the percentage difference showed the difference of the two intensities for each molecular ion peak in day-to-day spectra and was expressed by

2.2. ToF-SIMS and principal components analysis (PCA)

Contact angle measurements on the gold substrates subject to different cleaning methods were made with a homemade system at 25 8C and 60% (RH). Contact angles were calculated using a drop snake fitting of ImageJ program in the automatic mode and represented an average between the left and right angles. Photographs were taken within 5 s after dropping a DI water droplet of 1 mL on the gold substrates.

ToF-SIMS spectra were obtained by using a ToF-SIMS V instrument (ION-TOF GmbH, Germany) with 25-keV Bi+ primary ions. The primary ion source was operated with an average current of 0.36 pA, a pulse width of 19.5 ns, and a repetition rate of 5 kHz. Negative spectra were acquired on three points with an area of 200 mm  200 mm on every sample, keeping the primary ion dose of 1012 ions cm2. Negative ion spectra were calibrated by using CH, C2H, C4H, Au, Au2, and Au3 peaks. The mass resolution M/DM was more than 9000 between m/z 800 and m/z 1000. A peak list to perform the PCA was made by selecting 96 ions which consisted of C, H, S, and Au atoms from the spectra. A PCA was performed using a PLS_Toolbox (version 3.5, Eigenvector Research, Manson, WA) for MATLAB (version 7.0 MathWorks, Inc., Natick, MA). Each peak was normalized by the summation of selected peaks and the data was mean centered. The PCA was performed by using a total of forty-five spectra (3 groups  5 samples  3 points for each sample) obtained from the three groups for the selected peaks over the mass range of m/z 2–1000. Another data set was obtained at a different date to check for reproducibility. 2.3. Standard deviation percentage and percentage difference ToF-SIMS spectra for each group (i.e. cleaning method) provided the numerical calculations for standard deviation percentage and percentage difference and were used to obtain the measure of reproducibility. The standard deviation percentage defined by pffiffiffiffiffiffiffi Dx  100 ð%Þ x¯

(1)

2jx¯  yj ¯  100 ð%Þ x¯ þ y¯

(2)

where x¯ and y¯ are averages of variables, xi and yi for each day. These mathematical analyses for point-to-point, sample-to-sample spectra, and day-to-day were important means by which homogeneity and reproducibility of SAMs formation were examined. 2.4. Contact angle analysis

3. Results and discussion Fig. 1a shows the scores plot from a PCA of the negative ion spectra of 1-dodecanethiol SAM produced on a gold surface by the three different cleaning methods. The three isolates, ‘superpiranha’, ‘piranha’ and ‘ethanol’ groups, are clearly distinct from each other in the scores plot of principal component (PC) 1 (94.03%) versus PC 2 (5.27%). The super-piranha group is isolated around the score of 0.065 on PC 1, while the other two groups are placed on the positive scores. In the loadings plot on PC 1 (Fig. 1b), the super-piranha group is characterized by specific peaks with negative loadings. It is interesting to note that these negative loadings are molecular ion [M  H] peak of DDT SAM and their gold adducts like AuxSy[M  H]z where x, z = 1, 2, or 3 and y = 0, or 1. In contrast, the major peaks of the positive loadings for the piranha and ethanol groups are the short hydrocarbon fragments containing gold atoms like CkHlSmAun where k, l, m, n = 0, 1, 2, . . .. Graham and Ratner suggested that as the SAM reagents are packed closely and ordered well on a gold substrate, more molecular ion species are emitted by an impact of the primary ion in ToF-SIMS [9]. According to this model, our super-piranha cleaning method has the potential to be superior to the piranha method for a reproducible and well-ordered SAM formation.

Fig. 1. (a) Scores plot from PCA of the negative ion spectra of 1-dodecanethiol SAM produced on gold substrate after each surface cleaning. Note the excellent grouping and separation of the super-piranha spectra from the other groups; (b) corresponding loadings plot on PC 1 (94.03%).

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Fig. 2. (a) Standard deviation percentage for each molecular ion of 1-dodecanethiol SAM on gold surface produced in one day; (b) percentage difference among intensities of spectra obtained from day-to-day samples.

Fig. 3. Contact angles on a gold surface treated by various cleaning methods. The time represents cleaning time of gold substrate in each solution.

To quantitatively measure reproducibility of the SAM formation after each cleaning method, the standard deviation percentage and percentage difference were calculated and are shown in Fig. 2a and b, respectively. In Fig. 2a, the standard deviation of the intensities for each molecular peak of ToF-SIMS spectra in the super-piranha group is always below 3%. The piranha group shows a low value of 6%. However, for samples produced with piranha cleaning on other days, the intensities showed a greater percentage difference, 20%, while it was 10% in the case of the super-piranha group, as shown in Fig. 2b. Statistically, since data have excellent reproducibility and precision when the standard deviation percentage and percentage difference are below 10%, the super-piranha cleaning method on gold substrates prior to a SAM formation would well used for quantitative analysis in medical applications using biochips. We applied the super-piranha cleaning method to other alkanethiol SAMs such as 11-mercapto-1-undecanol and 11mercaptoundecanoic acid and obtained standard deviation percentages and percentage differences similar to the DDT SAM. Clearly, the super-piranha cleaning method is more effective to reproducibly remove contamination on substrates than the piranha cleaning method, but since the chemical reaction in a super-piranha solution is basically equivalent to that in a piranha solution, it is interesting to see why this is the case. A small amount of nitric acid added to the piranha solution as a catalyst to rapidly and sufficiently dehydrate the hydrogen peroxide in the solution is what sets apart these two methods. In a piranha solution the

reaction between sulfuric acid and hydrogen peroxide was relatively slow. This in part contributed to the efficiency of the reaction, which was also sensitive to the ratio of hydrogen peroxide and sulfuric acid, the temperature, and the immersion time of the substrates. These experimental parameters were also difficult to reproducibly control. In a super-piranha, however, dehydration of the hydrogen peroxide quickly reached a critical point by catalysis reaction, and thus the organic materials on the substrates could be removed completely and reproducibly. Contact angle analysis as shown in Fig. 3 supports our explanation. Initially, a contact angle of bare gold was about 778, but it decreased to around 608 as the surface became hydrophilic [11] after the aqueous cleaning process. To further test this, five gold wafer pieces were placed in each cleaning solution and taken out at the same time. For gold substrates with piranha cleaning, two groups were differentiated by cleaning times. For substrates treated by the piranha solution, the deviation of contact angles is generally much larger than one in the super-piranha group, even if the contact angles decrease as cleaning time increases from 5 min to 10 min. This result confirms the poor reproducibility of substrate cleaning by a piranha solution compared to one by a super-piranha solution. Variations of the surface wettability directly affected the reproducible SAM formation. 4. Conclusions We produced alkanethiol SAMs on gold substrates cleaned by various surface cleaning methods and analyzed them quantitatively using ToF-SIMS spectra. PCA and numerical calculations showed that the cleaning method on a gold substrate critically affects the quality and reproducibility of SAMs formed on the cleaned substrate. The super-piranha cleaning method was superior to the piranha cleaning method and may be an essential process for biochips based on SAMs for quantitative and reproducible analysis in medical applications. Acknowledgements This work was supported by the Bio-Signal Analysis Technology Innovation Program (M106450100002-06N4501-00210) of MEST/ KOSEF and the Next-Generation New-Technology Development Program for MKE. References [1] A. Ulman, Chem. Rev. 96 (1996) 1533.

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[2] J.C. Love, L.A. Estroff, J.K. Kriebel, R.G. Nuzzo, G.M. Whitesides, Chem. Rev. 105 (2005) 1103. [3] G.E. Poirier, E.D. Pylant, Science (Washington, DC) 272 (1996) 1145. [4] R.G. Nuzzo, J. Am. Chem. Soc. 105 (1983) 4481. [5] W.C. Bigelow, D.L. Pickett, W.A. Zisman, J. Colloid Interface Sci. 1 (1946) 513. [6] G. Gillen, J. Bennett, M.J. Tarlov, R.F. Donald, J. Burgess, Anal. Chem. 66 (1994) 2170.

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A. Chilkoti, B.D. Ratner, D. Briggs, Anal. Chem. 65 (1993) 1736. D.J. Graham, S.W. Matthew, D.G. Castner, Appl. Surf. Sci. 252 (2006) 6860. D.J. Graham, B.D. Ratner, Langmuir 18 (2002) 5861. W. Kern, Handbook of Semiconductor Wafer Cleaning Technology: Science, Technology, and Applications Material Science and Process Technology Series, Noyes Publications, Park Ridge, NJ, 1993, pp. 3–56. [11] M.-Y. Tsai, J.-C. Lin, J. Colloid Interface. Sci. 238 (2001) 259.