Effect of Nanoscale Roughness on Adhesion between Glassy Silica

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Effect of Nano-Scale Roughness on Adhesion between Glassy Silica and Polyimides: A Molecular Dynamics Study Sung Hoon Lee, Ross J. Stewart, Hyunhang Park, Sushmit Goyal, Venkatesh Botu, Hyunbin Kim, Kyoungmin Min, Eunseog Cho, Aravind Raghavan Rammohan, and John C. Mauro J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b08361 • Publication Date (Web): 16 Oct 2017 Downloaded from http://pubs.acs.org on October 17, 2017

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The Journal of Physical Chemistry

Effect of Nano-Scale Roughness on Adhesion between Glassy Silica and Polyimides: A Molecular Dynamics Study Sung Hoon Lee1,*, Ross J. Stewart2, Hyunhang Park1, Sushmit Goyal2, Venkatesh Botu2, Hyunbin Kim1, Kyoungmin Min3, Eunseog Cho3, Aravind R. Rammohan2, John C. Mauro2,a

1

Corning Technology Center Korea, Corning Precision Materials Co., Ltd., 212 Tangjeong-ro, Asan, Chungcheongnam-do, 31454, Republic of Korea

2

Science and Technology Division, Corning Incorporated, One Science Center Drive, Corning, New York 14831, United States

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Platform Technology Lab, Samsung Advanced Institute of Technology, 130 Samsung-ro, Suwon, Gyeonggi-do 443-803, Republic of Korea

* Sung Hoon Lee: E-mail [email protected]; Tel +82-41-520-5691

a

Current address: Department of Materials Science and Engineering, The Pennsylvania State

University, University Park, PA 16802, United States © 2017 Corning Incorporated. All Rights Reserved.

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ABSTRACT: The effect of nano-scale roughness on the adhesion between glassy silica and polyimides is examined by molecular dynamics simulation. Different silica surfaces, with varying degrees of roughness, were generated by cleaving bulk structures with a pre-defined surface and a desired average roughness, with different roughness periods and hydroxylation densities in an effort to study the influence of these surface characteristics on adhesion at the silica-polyimide interface. The calculated results reveal that average roughness Ra is the primary controlling factor within the considered conditions. Further, an energy decomposition analysis of the pulling process suggests that hydrogen bonding contributes to the adhesion on all the rough surfaces, while the Coulombic energy contribution becomes significant at higher Ra. From a structural analysis of the vacant volume and surface area, it is shown that the periodicity of roughness provides a rather interesting trend for the adhesion energy. Adhesion can increase with a reduction in period due to the corresponding surface area expansion; however, if vacant volumes exist at the interface, the level of adhesion can decrease. Competition between two opposing tendencies leads to the maximum adhesion, and hence, both Ra and period are key parameters to control the adhesion in nano-scale roughness.

© 2017 Corning Incorporated. All Rights Reserved.

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1. INTRODUCTION The excellent thermal and chemical resistive properties of polyimide (PI) type materials have made it widely applicable in electronic devices and the aerospace industry.1-5 Recently, there has been significant interest in PI as a potential candidate for flexible substrates in organic light emitting devices or printed circuit boards due to its high flexibility and thermal stability.3-5 However, PI is often detached from a supporting glass carrier during the manufacturing process, which is characterized by structural failures. Therefore, understanding adhesion between the glass carrier and PI is critical to improve structural reliability characteristics of such flexible devices. Our past work focused on understanding the fundamentals of adhesion between silica and PI,6-8 as characterized by silica surface, hydroxylation conditions, crystallinity of silica, and oxygen density within PI. The strongest adhesion was predicted when the glassy silica surface was fully hydroxylated and PI had higher oxygen density,6 and it was also revealed that hydrogen bonding is the origin of this increased adhesion. Since hydroxylation density plays a significant role for adhesion, increasing hydroxyl groups on the surface could be an effective way to enhance adhesion between glassy silica and PI, but it is not easily controllable within the ambient condition. A practical alternative is to tune the surface roughness in an effort to introduce additional surface area for the hydroxyl groups, thereby, increasing adhesion energy. © 2017 Corning Incorporated. All Rights Reserved.

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There have been only a few reports which investigated the adhesion behavior of polymer to glass or silica with nano-scale roughness.9-13 Ramakrishna et al., reported the effect of surface roughness on the interaction between polyethylene microspheres attached to atomic force microscope (AFM) cantilevers and silica nanoparticles by varying the nanoparticle density on the substrates, and observed the minimum pull-off force at an optimal silica roughness.9 Some efforts were also made on studying the pull-off forces between polyethylene beads attached to atomic force microscope (AFM) cantilevers and silicon wafer with oxide layer on top.10, 11 Meine et al., studied a correlation between contact area and adhesion force by introducing nanostructures on the substrates and interpreted that the adhesion force is dependent not only on the contact area but also on the circumference of asperities.10 Drelich et al., analyzed the effect of asperity size and shape, spacing between asperities, as well as deformation of materials using experimental data.11 Ndoro et al., and Eslami et al., reported the effect of silica nanoparticle curvature on the local structures and dynamic properties of polymers with molecular dynamics simulations.

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However, in-depth understanding such as adhesion mechanism or quantitative

relation between adhesion and glass roughness is still lacking. In this regard, we aim to understand the effect of the nano-scale roughness of glassy silica on the adhesion with PI. The pulling test was chosen for measuring the adhesion between glassy silica and PI because it mimics the experimental detachment process in the flexible display © 2017 Corning Incorporated. All Rights Reserved.

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manufacturing process.7 Steered molecular dynamics (SMD) simulations14, 15 are implemented to investigate fundamentals of adhesion during the pulling test, and the Interface force field16, 17 was adopted to represent molecular interactions. For systematic analysis of roughness, both the amplitude and the spacing parameters of roughness are considered with various hydroxylation densities. First, the effect of amplitude parameters and hydroxylation densities are investigated. Then, dependence of spacing and amplitude parameters of roughness is studied. The role of each parameter is analyzed, and a key parameter for the adhesion is selected. To find the origin of the adhesion, energetic contributions to the total energy are decomposed and analyzed. Structural analysis such as surface area or vacant volume variation is performed to understand the PI-glassy silica adhesion mechanism with respect to the silica roughness, and finally the trend of the adhesion energy of PI on glassy silica with nano-scale roughness is predicted.

2. METHODS 2.1. Generating rough surfaces Initial bulk structures are prepared with a melting and quenching using the Pedone interatomic potential,18, 19 which accurately reproduces bulk properties and structure of glassy silica. When the periodicity of roughness is 20, 30, and 60 Å, the bulk structure is prepared


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with a size of 60 Å × 60 Å × 60 Å, and the bulk size of 120 Å × 120 Å× 120 Å is prepared for a period of 120 Å. To create roughness on the surface, we cut a bulk glassy silica model with a pre-defined surface. As shown in Fig. 1, we first define a shape of the surface by a specific mathematical function and then cut the initial bulk structure along with the surface by keeping all atoms under that function. Roughness can be adjusted by modulating the defined surface function. The details of the nano-scale are changed by varying amplitudes and spacing,20 applying a sinusoidal function to adjust both parameters as follows,

z = Asin sin +

(1)

where A, Lx, Ly, and z0 represent roughness amplitude, spacing along each axis, and the average chosen height, respectively. Various amplitudes (A= 0, 5, 10, 15, 20 Å) and spacings (Lx = Ly = 20, 30, 60, 120 Å) are considered to analyze the effect of each parameter in this work. Regardless of amplitude or spacing of roughness, the distance from the minimum of the roughness to the bottom of the model is set as a constant 30 Å, and thus, thickness of bulk area is identical for all structures. Experimentally, the amplitude parameter is usually represented as the height variation of the surface compared to a reference plane, and the arithmetic average, Ra, is the most common parameter to present amplitude of roughness.20 Thus, Ra is measured for the prepared structure © 2017 Corning Incorporated. All Rights Reserved.

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and listed as an amplitude parameter instead of A in this work. Ra is calculated using atomic coordinate of surface atoms with the following equation,

= ∑| − ̅|

(2)

where zi is the z coordinate of each element and ̅ is the average value of the z coordinates. Due to the symmetric shape of a sine function, Ra is almost half of the amplitude value (A). As the increase of amplitude values from 0 to 5, 10, 15, and 20 Å, Ra varies from 1.0 Å to 2.4, 4.4, 6.5, and 8.4 Å, respectively. Spacing of roughness corresponds to the period of a sine curve (Lx or Ly in the function) and hence, period is listed as a spacing parameter of roughness. 2.2. Surface hydroxylation In addition to the amplitude and period of roughness, hydroxylation density of a surface is varied since hydroxyl groups on the glassy silica surface have a major role for the adhesion at the glassy silica–PI interface.6 To adjust hydroxylation density, coordination numbers (CN) of oxygen and silicon atoms, which are 2 and 4 in glassy silica, are considered. If lower CN atoms exist, which are oxygen atoms with CN = 1 or silicon atoms with CN < 4, those atoms are naturally hydroxylated with moisture in the air due to their high reactivity. In this work, since the surface is artificially cut by hand, there exist many lower CN atoms on top of the surface, and thus we hydroxylated lower CN atoms adding hydrogen atoms or hydroxyl groups onto oxygen atoms or silicon atoms, respectively. When the cut surface is completely hydroxylated, © 2017 Corning Incorporated. All Rights Reserved.

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hydroxylation density is around 6.5 OH/nm2, which is much higher than the experimentally measured 4.6 ± 0.5 OH/nm2 on a realistic silica surface.21 To match the hydroxylation density of a model with the experimental value, surfaces are de-hydroxylated by extracting H2O molecules from the surface. When the two hydroxyl groups are close to each other, OH atoms from one side and H atom from the other side are combined as a H2O molecule and extracted connecting both lower CN atoms of silicon and oxygen on the glassy silica surface. With the same procedure, we further decrease the density without lowering the CN of atoms on the surface, and both 4.8 and 2.4 OH/nm2 hydroxylation densities are considered in this work to check the dependence on hydroxylation density. All of the atoms on the prepared surfaces are completely saturated with hydroxyl groups. To measure a surface area for the prepared surface, we use atomic volume and surface tools in Materials Studio (ver. 8.0, Accelrys Inc.).22 Solvent surface at a probe radius of 2.0 Å and grid interval of 0.75 Å are used to determine surface area. 2.3 Generating polymer structure For the polymer structure, we chose diamine-3,3´-dihydroxy benzidine (DHBZ) with dianhydride-3,3´,4,4´-biphenyl tetracarboxylic dianhydride (BPDA), i.e., DHBZ-BPDA. The molecular structure of DHBZ-BPDA is depicted in Fig. 2, and an atomic structure is generated with 30 chains of linear polymer, each including 7 repeat-unit monomers. The initial structure is © 2017 Corning Incorporated. All Rights Reserved.

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constructed using the confined layer task using the Amorphous Cell module of Materials Studio (ver. 8.0, Accelrys Inc.).22 Two surfaces of 60 Å × 60 Å or 120 Å × 120 Å are chosen to be identical to the glass surface, and a uniform thickness of 30 Å is used for the structure. Three initial structures of PI are calculated for the statistical analysis.

2.4 Calculating the adhesion energy of glassy silica-PI composite system Each PI is placed on top of the glass surface with a vacuum space of 100 Å in the z-direction, and the glassy silica–PI composite system is then thermally annealed and relaxed to reach an equilibrium. Molecular Dynamics (MD) simulations are conducted with the LAMMPS package23 with the Interface–PCFF force field17 which accurately predicts adsorption properties at the glass–polymer interface.6, 17 The combined structure is relaxed at 700 K for 1 ns followed by annealing to 300 K for 500 ps with the NVT ensemble. Then, the structure is relaxed for 1 ns at 300 K with the NVT ensemble and for another 1 ns at 300K and 1 atm with the NPT ensemble maintaining vacuum area in the z-direction. The Nosé–Hoover thermostat and barostat are applied with 100 fs and 1000 fs for damping parameters, respectively. The time step is 0.5 fs, and Particle–Particle Particle–Mesh (PPPM) solver was used for the summation of long-range Coulomb interactions with the precision of 10-4.


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With the relaxed structures, Steered Molecular Dynamics (SMD) with the NVT ensemble is adopted14,

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to investigate pulling behavior between rough glassy silica and PI. SMD can

calculate the potential of mean force (PMF) employing Jarzynski’s equality which relates the equilibrium quantity (PMF) to the non-equilibrium process.15 In the SMD method, a virtual spring is considered to connect atoms in the structure and dummy atoms, which are displaced with a constant velocity from the atoms. Thus, force is applied on the atoms to detach them from each other, the generated force due to the constant velocity is defined as, !"#$% = −∇'"#$%

(3)

where Uspring is the generated potential with a harmonic spring type model, defined as '"#$% = ([*+ − (-! (+. − -! . ∙ 0-!]

(4)

where k is the spring constant of a virtual spring, v is the constant pulling velocity, t is the time, -! (+. and -! are the current and initial positions of the center of mass of the pulled atoms, and 0-! is the pulling direction. Therefore, work done (W) during the pulling process is calculated as $6

W = 3$6 7 ∇'"#$% ∙ 45!

(5)

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where R0 and Rf are the initial and final positions of the center of mass. Using Jarzynski’s equality, PMF is computed as,

PMF = − < =>?〈A B

Effect of Nanoscale Roughness on Adhesion between Glassy Silica

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