Molecular Dynamics Simulations of Perfluoropolyether Lubricant

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Molecular Dynamics Simulations of Perfluoropolyether Lubricant Degradation in the Presence of Oxygen, Water, and Oxide Nanoparticles using a ReaxFF Reactive Force Field Roghayyeh Lotfi,† Adri C. T. van Duin,*,† and Mousumi Mani Biswas‡ †

Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States ‡ Western Digital Technologies Inc., San Jose, California 95138, United States ABSTRACT: The degradation of a perfluoropolyether lubricant, i.e., D4OH, was studied in the presence of a number of different components in a computer hard disk drive using ReaxFF reactive force field-based molecular dynamics simulations. The chemical reaction between nine D4OH strands with oxygen, water, oxide nanoparticles including SiO2, goethite (FeO(OH)), and Fe2O3 was simulated by using reactive molecular dynamics simulation at T = 1500 K. All oxide nanoparticles were used in three different configurations: (1) untreated − cut from the crystalline structure without further treatment; (2) pretreated with dry air; and (3) pretreated with wet air to simulate a realistic environment. It was observed that water molecules strongly affect the degradation rate of the D4OH lubricant while oxygen molecules do not play a significant role. Moreover, the results indicated that the presence of these nanoparticles in any form accelerates the lubricant degradation. Untreated silica and Goethite nanoparticles have stronger effects on the degradation rates of lubricant strands in comparison to dry-air-treated and wet-airtreated nanoparticles, while in the case of Fe2O3 nanoparticles wet-air-treated nanoparticles have the strongest effect on the degradation rates of lubricant strands. ability, low surface tension, and shear stability.9−12 Fomblin and Demnum are two main categories of PFPE lubricants which are used in HDDs. Fomblin lubricants such as Z and Zdol consist of a linear backbone chain of X-(OCF2-CF2)p(OCF2)q-O-X in which X is the end group and p and q are the numbers of repeating units. On the other hand, Demnum lubricants are formulated as R1-OCH2CF2CF2O(CF2CF2CF2O)mCF2CF2CH2O-R2, wherein R1 and R2 are alkyl chains and m is the number of repeating units. In the present work, we have used a common Demnum class of PFPE lubricants, i.e., D4OH, with both R1 and R2 as CH2-CHOH-CH2OH.13 Although PFPE lubricants are excellent for use in hard disks, they are found to deplete and degrade under certain conditions, which can lead to the failure of the head−disk interface. This is especially important for HAMR systems because of their higher temperatures.14 In general, the main causes of lubricant degradation can be categorized as thermal decomposition, catalytic decomposition, mechanical degradation by a shearing process, and electron-mediated degradation.15−24 Experimental studies on the degradation of PFPE lubricants in the presence of different components have been described in several papers. For

1. INTRODUCTION With increasing demands of data storage requirements, the computer hard disk drive (HDD) industry has experienced major improvements in data storage performance over the past few decades. Currently, the storage capacity of HDDs has increased from less than 1 Mbit/in2 to approximately 1 Tbit/in2.1−3 Heatassisted magnetic recording (HAMR) has the potential to achieve a storage capacity of 50 Tbit/in2, but it faces many challenges.4 In HAMR recording, a pulsed laser is used to write on the magnetic medium at elevated temperature. Consequently, the degradation of the recording medium surface lubricant at high temperatures is one of the major problems in HAMR systems. This lubricant degradation problem may be accelerated by the presence of surface contaminants and humidity and also by the reduced spacing between the recording head and the medium. Thus, it is very important to understand the lubricant degradation at high temperatures in the presence of humidity and various contaminants in the hard disk drive system. Perfluoropolyether (PFPE) lubricants are widely used in computer hard drive media surfaces. These lubricants also have other applications, such as in vacuum pumps, aircraft instrument bearings, reactive chemical environments, and electric motors.5−8 PFPEs are particularly promising lubricants for HDDs due to their numerous advantageous properties, including chemical inertness, thermal stability, low volatility, nonflamm© XXXX American Chemical Society

Received: September 28, 2017 Revised: January 11, 2018

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DOI: 10.1021/acs.jpcc.7b09660 J. Phys. Chem. C XXXX, XXX, XXX−XXX

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different environments and nanoparticles by using ReaxFF. To our knowledge, no previous study has been performed on the interaction of the D4OH lubricant with the environment and oxide nanoparticles by using a reactive force field. The main goal of the current paper is to investigate the degradation of the D4OH lubricant with oxygen, water molecules, and oxide nanoparticles including SiO2, goethite, and Fe2O3 by using ReaxFF-based molecular dynamics simulations. The organization of this paper is as follows. First, an introduction to the computational model will be presented. After that, the simulation setup and Fe/F ReaxFF parameter development are discussed. Next, the degradation of D4OH lubricant with oxygen and water molecules will be presented. Finally, the degradation of the lubricant in the presence of different oxide nanoparticles will be discussed.

instance, the degradation and tribological properties of PFPE lubricants in the presence of diamond-like carbon (DLC) structures have been studied experimentally.25−29 Zhao and Bhushan25,26 used a mass spectrometer to investigate the degradation of PFPE lubricants on the magnetic media. They found that the C−O bond is a weak bond in the lubricant and because of its polar characteristics it can be easily attacked and broken. Moreover, it was shown that the humidity has a noticeable influence on the performance and durability of the PFPE lubricants.30−34 Zhao et al. demonstrated that the durability of the PFPE lubricant can be weakened at high humidity.30 In another work, Kim et al.31 found that lubricant transfer between a slider and disk increases with an increase in the absolute humidity. This can be related to the phenomenon that water molecules may permeate the lubricant film, leading to increased lubricant mobility. Furthermore, it is well known that, in the presence of metals and metal oxides, rapid degradation of PFPEs takes place at temperatures below their decomposition temperatures.2 Among different metal oxides that are present in the hard disks, the effects of some oxides such as ZrO2, Al2O3, and Fe2O3 on lubricant degradation have been investigated experimentally.35−37 Different mechanisms have been suggested for the catalytic lubricant degradation. For example, Yates et al. proposed that the reaction may occur via the attack of ether or acetal carbons by surface oxygens,38−40 whereas Zehe et al. hypothesized that degradation results from acidic attack at the fluorines on the acetal carbon atom.36 The most well-known mechanism for the catalytic degradation of PFPE lubricants has been suggested by Kasai, in which he suggested that degradation happens through electron donation from the oxygen lone pairs of the lubricant to the surface metal atoms leading to chain scission by CO cleavage.19,41 In addition to the experimental works, very few theoretical studies have been carried out on the degradation of PFPEs.42−45 The decomposition of perfluorodimethyl ether, CF3OCF3, the smallest molecule of PFPE lubricants with one ether linkage, was studied by Pacansky et al. through quantum mechanical calculations.42,43 They found a significant reduction in the activation energy of the reaction via the Lewis acid interaction, which leads to the catalytically induced degradation of these materials. In another work, Jiang et al. investigated the effect of AlF3 on the decomposition of CF3OCF3 and CF3CF2OCF2CF3 using ab initio theory.44 They proposed a new reaction mechanism for AlF3 by accepting a fluorine atom from one carbon and simultaneously donating a fluorine atom to another carbon. Later, they developed a method to study the thermal degradation of CF3OCF3 at high temperature using a nonreactive force field within a reactive molecular dynamics (RMD) algorithm.45 Molecular dynamics simulations with reactive force fields would be very useful for better understanding the interaction of the lubricant with different components of hard disks. Reactive molecular dynamics simulations with reactive force fields provide atomistic-level details of materials. ReaxFF is a reactive force field which can simulate chemical reactions as well as transition states with a high level of accuracy.46−53 In our previous work, we studied the degradation of the D4OH lubricant in the presence of diamondlike carbon (DLC) structures by using ReaxFF.48 In other work, the oxidation of aluminum nanoparticles was successfully investigated by ReaxFF.49 All of these studies indicate that it would be feasible to study the degradation of lubricant strands in the presence of

2. METHODS 2.1. Computational Method. ReaxFF is a bond-orderbased reactive force field technique, which allows bond formation and bond dissociation during the molecular dynamics simulation. The bond order is directly calculated between all pairs of atoms from the interatomic distances, and it is updated at every step. As a result, a smooth transition between the nonbonded states and the single, double, or triple bonded states becomes possible. This leads to the simulation of chemical reactions with accuracy comparable to that of the quantum calculations but with a much lower computational cost. Despite traditional force fields, in ReaxFF each element is described by only a single atom type and the reaction site or connectivity information is not needed beforehand. The total interaction energy in ReaxFF is described by the following energy contributions: Esystem = E bond + Eover + Eunder + Etor + Eval + E lp + Evdw + Ecoulombic

(1)

The total energy of the system (Esystem) consists of bonded or covalent interactions (which are bond-order-dependent) and nonbonded interactions. Bond-order-dependent terms include the bond energy (Ebond), overcoordination (Eover), and undercoordination (Eunder). Energy penalty terms include torsionangle energy (Etor), valence-angle energy (Eval), and lone pair energy (Elp). Nonbonded interactions include van der Waals (Evdw) and Coulomb energy (Ecoulomb). All connectivity energy terms, such as the valence angle and torsion angle, are bondorder-dependent. In addition, nonbonded interactions such as van der Waals and Coulomb terms are taken into account for the entire system between each pair of atoms. Atomic charges are derived from an electronegativity equalization method (EEM).54 Force field parameters are optimized by quantum mechanical (QM) calculations and/or experimental values. ReaxFF parameters are fit against the QM-based training sets by using the single-parameter search optimization method while minimizing the total error ⎡ (xi ,QM − xi ,ReaxFF) ⎤2 ⎥ error = ∑ ⎢ σ ⎦ i=1 ⎣ n

(2)

where xi,QM and xi,ReaxFF are the values of the QM and the ReaxFF calculations, respectively, and σ is the weight number defined in the training set. Here, to describe the Fe−F interactions between the lubricant and iron oxide nanoparticles, a training set was developed by carrying out gas-phase cluster calculations with Jaguar 8.3.55 The B

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500 000 MD time steps (50 ps). It should be noted here that because of time-scale limitation of these simulations we chose higher temperatures than in the experiment to accelerate the dynamics of the system on a short time scale. We will also show in section 3.2 that among different temperatures of 1000, 1500, and 2000 K a temperature of 1500 K would be a better choice for MD simulations. The time step in the present work was selected as 0.1 fs. The temperature was controlled by a Berendsen thermostat57 with a damping constant of 250 fs. To investigate the thermal degradation of D4OH in the presence of silica nanoparticles, a silica nanoparticle with a diameter of 16 Å was used. To mimic realistic conditions, an initial silica nanoparticle, i.e., untreated, was placed in the middle of a box (50 × 50 × 50 Å3) containing 100 oxygen molecules to simulate the dry air environment and a box with a mixture of 100 oxygen molecules and 100 water molecules to simulate the wet air environment. The systems were held at 1500 K for 1 000 000 MD time steps (100 ps). In the next step, the obtained nanoparticles were equilibrated with 9 D4OH strands at 1500 K for 500 000 MD time steps (50 ps), and the degradation rate of the lubricant in the presence of these nanoparticles was evaluated. Similar procedures were performed for goethite and Fe2O3 nanoparticles. We used a goethite nanoparticle (αFeOOH), which is a common mineral on earth with an orthorhombic crystal structure that can be found in hard disk drives. Both the goethite and Fe2O3 nanoparticles had the same diameter of 16 Å.

density functional theory (DFT) calculations were performed with the B3LYP functional and 6-31G** basis set. QM-based structures in the training set were obtained by full geometry optimizations for all clusters. Then, bond dissociation energies and angle distortion energies were calculated by fixing the related bond or angle at a certain value and optimizing all of the other coordinates. In the parametrization process, a similar procedure was used; i.e., the structures in the training set were relaxed with the ReaxFF force field while the geometry parameters of interest were constrained. 2.2. Simulation Setup. To evaluate the influence of oxygen and water molecules on the thermal degradation of D4OH, we performed a series of molecular dynamics (MD) simulations at a constant number of particles, volume, and temperature (NVT) on 9 D4OH strands in vacuum in the presence of 100 oxygen molecules and in the presence of 100 water molecules, respectively. All MD simulations were performed with the ADF package.56 The total formula of the D4OH lubricant is C42H18O17F68 (repeating factor of 10) with a molecular weight of 2086.0182 g/mol (Figure 1). Simulations were run at 1500 K for

3. RESULTS AND DISCUSSION 3.1. Fe-F ReaxFF Development. DFT calculations for the bond dissociation and angle distortion energies of Fe/F/H/O clusters were performed using the B3LYP method, and the ReaxFF parameters were fitted against the results of these calculations. The dissociation energy of the Fe−F single bond

Figure 1. Schematic structure of one D4OH strand.

Figure 2. Comparison of QM and ReaxFF results: (a) Bond dissociation energy for teh Fe−F bond in FeF4. (b) angle distortion energy for F−Fe−F in FeF4. (c) angle distortion energy for Fe−F−Fe in Fe2F8. (d) angle distortion energy for O−Fe−F in FeF3OH (Fe, blue; F, yellow; O, red; H, white). C

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Figure 3. Degradation of D4OH lubricant. Initial structure including nine D4OH strands after compression (a) in vacuum and in the presence of (b) oxygen molecules and (c) water molecules. Final structures and degraded strands after NVT simulation (d) in vacuum and in the presence of (e) oxygen molecules and (f) water molecules (C, green; F, yellow; O, red; and H, white).

the system was compressed at 300 K to a volume of 40 × 40 × 45 Å3 to increase the density from 0.24 to 0.43 kg/L. MD-NVT simulations were performed at 1500 K on 9 D4OH strands in vacuum and after adding 100 oxygen and 100 water molecules. Each simulation was run for 500 000 MD time steps (50 ps). Figure 3a−f shows the initial and final structures in vacuum in the presence of oxygen molecules and water molecules, and Figure 4 shows the number of intact strands plotted over time for all three

was calculated by constraining the Fe−F bond distance of the FeF4 molecule. Since the concept of multiplicity is not contained in the ReaxFF description, in order to obtain the correct bond dissociation energy we also calculated the triplet-state energy at the longest bond distance. As shown in Figure 2a, the bond dissociation relative energy calculated by ReaxFF is in good agreement with the QM data with an average deviation of 1.8 kcal/mol around equilibrium (considering five data points). The energy profile for the valence angle distortion of the F−Fe−F angle in the FeF4 molecule (Figure 2b) was also well reproduced in ReaxFF with an average deviation of 0.18 kcal/mol around equilibrium. Figure 2c shows the valence angle distortion of the Fe−F−Fe angle in the Fe2F8 molecule. As can be seen, the trend from the ReaxFF energies agrees with the QM energies, although some deviations do exist in this case. However, since the energy difference for such deviations is less than 1 kcal/mol, this is not a major concern for the current application. The energy profile for the valence angle distortion of the O−Fe−F angle in the FeF3OH molecule (Figure 2d) was also well reproduced in ReaxFF with an average deviation of 0.21 kcal/mol. 3.2. Degradation of Lubricant with Water and Oxygen. To assess the degradation of D4OH strands in vacuum and in the presence of water and oxygen, a series of MD-NVT simulations were performed. In the first step, nine strands of D4OH were placed in a periodic box with dimension of 40 × 40 × 80 Å3. Then

Figure 4. Number of intact strands over time for an NVT simulation of D4OH strands in vacuum and in the presence of oxygen molecules and water molecules. D

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Figure 5. ReaxFF barriers for water release from the functional end group of the D4OH lubricant in the absence and in the presence of a catalytic water molecule (C, green; F, yellow; O, red; and H, white).

Figure 6. Effect of temperature in the number of intact strands for the NVT simulation of D4OH strands in (a) vacuum and in the presence of (b) oxygen molecules and (c) water molecules.

3e). In contrast, the presence of water molecules strongly affects the degradation of D4OH strands, as the number of intact strands reaches from nine to five at the end of the simulation. This effect is consistent with previous experimental results.31 The degraded D4OH strands are converted to C39H10O15F68, C3H6O, C42H19O17F67, C42H17O17F69, C27H9O11F46, C15H9O6F22, and H2O. These results indicate that in the case of lubricant degradation with water molecules, scission occurs both in the

cases over 50 ps. These results reveal that no degradation of lubricant strands is observed in the vacuum case. Similarly, the effect of oxygen molecules on the degradation of D4OH strands is not significant, and only one lubricant strand degrades at the end of the simulation. The degraded D4OH strand is decomposed to C37H9O14F66 and C5H9O3F2, which indicates that lubricant degradation happens only through the functional end cleavage and not in the main chain of the lubricant (Figure E

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Figure 7. (a) Treating silica nanoparticle with 100 O2 molecules and the mechanism for the dissociation of oxygen molecules on the nanoparticle surface. (b) Treating silica nanoparticle with 100 O2 and 100 water molecules and the mechanism for the dissociation of water molecules on the nanoparticle surface (Si, gray; O, red; H, white; O atoms bonded to the silica nanoparticle due to oxidation, pink).

functional ends and main chain of the lubricant (Figure 3f shows two types of degradation). It should be noted that the degradation of the lubricant strand in the main chain (leading to the production of C27H9O11F46 and C15H9O6F22) occurs through the C−O bond cleavage, which is similar to the Kasai mechanism.19 If we compare the different bonds of PFPE lubricants, we observe that the C−O bond is the weakest bond (with a dissociation energy of 360 kJ/mol) in comparison to the C−F, O−H, and C−H bonds (with dissociation energies of 473, 464, and 414 kJ/mol respectively).22 In addition, the C−O bond is a polar bond in which the carbon atom is partially positively charged and the oxygen atom is partially negatively charged. As a result, the C−O bond can be broken easily and is subject to cleavage during lubricant degradation. Such bond cleavage can also be attributed to the effect of polarity and hydrogen bonds formed between water molecules and lubricant strands.

In order to compare the influence of water molecules on the degradation of D4OH lubricants, the ReaxFF energy barriers for water release from the functional end group of the lubricant in the presence and absence of a catalytic water molecule were calculated (Figure 5). The water-formation reaction is initiated by the H-shift in the D4OH functional group. This is later followed by O−C bond cleavage, creating a C3H6O fragment. The results reveal that in both cases the water release reaction is endothermic. The case without an additional water molecule has an energy barrier of 40 kcal/mol, while the presence of a water molecule significantly decreases this reaction barrier ( dry-air-treated nanoparticles > wet-air-treated nanoparticles. 3.4. Degradation of Lubricant with Goethite Nanoparticles. Goethite nanoparticles were also treated with dry and wet air. For the case of treating with dry air, the number of oxygen atoms in the nanoparticle increases by 15, while for wet-airtreated nanoparticles, the total number of oxygen atoms in the nanoparticle increases by 13, and the number of OH groups in the nanoparticle increases by 15 (Figure 11a,b). In the next step, nine D4OH strands and four Goethite nanoparticles were randomly placed in the system, and MDNVT simulations were performed at 1500 K for 50 ps, respectively. The results indicate that, similar to the silica nanoparticles, D4OH strands have the highest rate of

1000 and 2000 K. Figure 6a−c shows the effect of temperature on the number of intact strands for three cases of D4OH strands in vacuum, in the presence of water molecules, and in the presence of oxygen molecules. As can be seen, at a temperature of 1000 K, in all cases, almost all lubricant strands are intact, and when the temperature increases, the rate of lubricant degradation increases. At 2000 K, in all cases, none of the D4OH strands remain intact. This indicates that a temperature of 1500 K is a good choice for performing the degradation simulations since it provides maximum temperature acceleration for the D4OH degradation reactions while avoiding simple pyrolysis events. As a result, we studied the effect of nanoparticles on the lubricant degradation at a temperature of 1500 K. 3.3. Degradation of Lubricant with Silica Nanoparticles. In order to study the degradation of D4OH lubricant in the presence of oxide nanoparticles, in addition to the untreated nanoparticles, we treated them with dry air and wet air. Figure 7 represents the effect of treating silica nanoparticles in dry air (100 O2 molecules) and in wet air (100 O2 molecules and 100 water molecules). As shown in Figure 7a, during the oxidation of silica nanoparticle with oxygen molecules, at first one oxygen molecule is adsorbed on the silica surface. After that, the oxygen molecule is dissociated to two oxygen atoms, making two new bonds with two Si atoms. For the case of oxidation with water molecules (Figure 7b), after the adsorption of a water molecule on the surface of silica the molecule is dissociated to OH (bonding to the Si atom) and H (bonding to the O atom of the silica structure). For case of a silica nanoparticle treated with dry air, the number of oxygen atoms in the nanoparticle increases by 11. Figure 8a shows the rate of oxygen content increase in the silica nanoparticle and the consumption rate of oxygen molecules in the system. On the other hand, for a wet-air-treated nanoparticle, the total number of oxygen atoms in the nanoparticle increases by 14 and the number of OH groups in the nanoparticle reaches 15. Figure 8b shows the rate of oxygen and hydroxyl group increase in the silica nanoparticle and the consumption rate of oxygen and water molecules in the system. Figure 9a shows the structure of nine D4OH strands and four silica nanoparticles, which are randomly placed in the periodic box. Figure 9b−d shows the system with untreated, dry-airtreated, and wet-air-treated nanoparticles after MD-NVT simulation at 1500 K for a simulation time of 50 ps. Figure 9e−g represents three different mechanisms for degradation of the lubricants, which are observed during the simulations. Figure 9e reveals that in the presence of silica nanoparticles an O atom in the functional group of the lubricant attaches to the Si atom, and as a result, a H-shift occurs to the next OH group in the lubricant, leading to the release of a water molecule. Figure 9f shows the G

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Figure 9. (a) Initial system including nine D4OH strands and four silica nanoparticles. Final structures after NVT simulation of D4OH strands with (b) untreated nanoparticles, (c) dry-air-treated nanoparticles, (d) wet-air-treated nanoparticles, (e) mechanism for lubricant degradation by the H-shift on a silica nanoparticle (target Si atom, black; target O atom, pink), (f) mechanism for lubricant degradation from the main chain, and (g) mechanism for lubricant degradation from the functional group (C, green; F, yellow; O, red; H, white; Si, gray).

degradation in the presence of untreated nanoparticles. Figure 12 shows the number of intact D4OH strands by time for different cases in the presence of untreated and dry- and wet-air-treated Goethite nanoparticles. For both cases of untreated and dry-airtreated Goethite nanoparticles, five strands remain intact; however, the lubricant degradation rate in the presence of untreated nanoparticles is higher. On the other hand, in the case of wet-air-treated Goethite nanoparticles, seven D4OH strands remain intact. ReaxFF component analysis during NVT simulation indicates that in case of untreated Goethite nanoparticles three water molecules are formed during this procedure. In the case of dry-air-treated Goethite nanoparticles, 2 water molecules are formed, while in wet-air-treated Goethite

nanoparticles, 16 water molecules are formed. All of these results reveal that the presence of Goethite nanoparticles, in any form, accelerates the degradation of D4OH strands. The order of influence of Goethite nanoparticles upon D4OH degradation is as follows: untreated nanoparticles > dry-air-treated nanoparticles > wet-air-treated nanoparticles. Note that the trends for Goethite nanoparticles are not as conclusive as the trends observed for the silica nanoparticle in the previous section. 3.5. Degradation of Lubricant with Fe2O3 Nanoparticles. The results indicated that for the case of treating Fe2O3 nanoparticles with dry air, the number of oxygen atoms in the nanoparticle increases by 58, while for wet-air-treated nanoparticles, the total number of oxygen atoms in the H

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Figure 10. Number of intact strands over time for the NVT simulation of D4OH strands in the presence of untreated SiO2 nanoparticles, dryair-treated SiO2 nanoparticles, and wet-air-treated SiO2 nanoparticles.

Figure 12. Number of intact strands over time for the NVT simulation of D4OH strands in the presence of untreated Goethite nanoparticles, dry-air-treated Goethite nanoparticles, and wet-air-treated Goethite nanoparticles.

nanoparticle increases by 58 and the number of OH groups in the nanoparticle increases by 53 (Figure 13a,b). Note that the increase in the number of O and OH groups in the Fe2O3 nanoparticles is much higher than that in the silica and Goethite nanoparticles. In the next step, nine D4OH strands and four Fe 2O3 nanoparticles were randomly placed in the system, and MDNVT simulations were performed at 1500 K for 50 ps. Interestingly, the results indicate that D4OH strands have the highest rate of degradation in the presence of wet-air-treated Fe2O3 nanoparticles, while for the case of untreated and dry-airtreated Fe2O3 nanoparticles, the degradation rate of D4OH strands is lower. Figure 14 shows the number of intact D4OH strands during the simulation time for different cases in the presence of untreated and dry- and wet-air-treated nanoparticles. For untreated, dry-air-treated, and wet-air-treated Fe2O3 nanoparticles, six, five, and four D4OH strands remain intact, respectively. Although at the end of the simulation, the number of intact strands with untreated nanoparticles is higher than for the case of dry-air-treated Fe2O3 nanoparticles, the lubricant degradation rate during the simulation in the presence of untreated nanoparticles is higher. ReaxFF component analysis during the NVT simulation indicates that in the case of untreated Fe2O3 nanoparticles no water molecule is formed during the procedure, while in the case of dry-air-treated Fe2O3 nanoparticles 2 water molecules are formed, and in the case of wet-airtreated Fe2O3 nanoparticles 43 water molecules are formed. Similar to silica and goethite nanoparticles, the results reveal that the presence of Fe2O3 nanoparticles, in any form, makes D4OH strands more degradable. However, the order of influence of Fe2O3 nanoparticles on the degradation of D4OH lubricant is as

follows: wet-air-treated nanoparticles > untreated nanoparticles > dry-air-treated nanoparticles. Such a difference in the behavior of wet-air-treated Fe2O3 nanoparticles can be attributed to the fact that during the NVT simulation with these nanoparticles the number of produced water molecules is much larger than the number of water molecules with silica and goethite nanoparticles. Figure 15 shows the comparison for the number of produced water molecules for all wet-air-treated nanoparticles. As can be seen, no water molecule is formed during the NVT simulation of lubricant with silica nanoparticles, while for goethite and Fe2O3 nanoparticles, water molecules are produced (at a much higher rate for the Fe2O3 nanoparticles). The final numbers of water molecules for silica, goethite, and Fe2O3 nanoparticles are 0, 16, and 43, and the numbers of intact lubricant strands are 7, 7, and 4, respectively. However, note that the degradation rate in silica nanoparticles is lower than in goethite nanoparticles. As mentioned previously, the presence of water molecules accelerates the rate of lubricant degradation significantly, and thus it can be hypothesized that there is a reverse relationship between the number of produced water molecules and the number of intact lubricant strands. Furthermore, a comparison of degradation rates for untreated silica, goethite, and Fe2O3 nanoparticles indicates that silica nanoparticles have a stronger effect on the degradation rate of the lubricant strands. This might be described by the higher electron affinity of the Si atom (134.07 kJ/mol) in comparison to that of the Fe atom (14.78 kJ/mol),58,59 which can lead to a higher probability of electron donation from the oxygen lone pairs of the lubricant to the surface Si atoms and consequently easier C−O bond cleavage of the lubricant. For the case of dry-air-treated

Figure 11. Rate of composition change for Goethite nanoparticle treatment in (a) dry air and (b) wet air. I

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Figure 13. Rate of composition change for Fe2O3 nanoparticle treatment in (a) dry air and (b) wet air.

lubricant strands with wet-air-treated Fe2O3 nanoparticles accelerates the degradation rate.

4. CONCLUSIONS PFPE lubricants, which are used in computer hard disks, are subject to degradation under certain thermal and oxidative conditions, leading to the failure of the head−disk interface. We performed reactive MD simulations to study the degradation of D4OH lubricant in the presence of oxygen, water molecules, and oxide nanoparticles including SiO2, goethite, and Fe2O3. The results indicated that water molecules enhance the degradation of lubricant strands, while the effect of oxygen molecules on the lubricant degradation is not significant. In the case of lubricant degradation with water molecules, cleavage occurred in the functional ends as well as the main chain of the lubricant, while in the case of oxygen molecules, lubricant degradation happened only at functional ends of the D4OH strand. In addition, it was shown that the presence of all nanoparticles accelerates the lubricant degradation. The effect of untreated silica and goethite nanoparticles on the degradation of lubricant strands is higher in comparison to that for the dry-air-treated and wet-air-treated nanoparticles, which is due to the presence of more active cites on the untreated nanoparticles. For Fe2O3 nanoparticles, the rate of degradation is higher for wet-air-treated nanoparticles, which is due to the large number of water molecules produced during the simulation. On the other hand, for untreated and dry-airtreated cases, silica nanoparticles have a stronger effect on the degradation of the lubricant strands in comparison to the goethite and Fe2O3 nanoparticles. Thus, it can be concluded that among different components that were studied in this study, preventing the presence of water molecules and silica nanoparticles would be very helpful in reducing the lubricant degradation in hard disk drives.

Figure 14. Number of intact strands over time for the NVT simulation of D4OH strands in the presence of untreated Fe2O3 nanoparticles, dryair-treated Fe2O3 nanoparticles, and wet-air-treated Fe2O3 nanoparticles.

Figure 15. Number of produced water molecules over time for the NVT simulation of D4OH strands in the presence of wet-air-treated silica, goethite, and Fe2O3 nanoparticles.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected].

nanoparticles, a comparison of different nanoparticles shows that lubricants in the presence of Fe2O3 nanoparticles have the lowest degradation rate. This can be attributed to the fact that during treating Fe2O3 nanoparticles with dry air the number of O atoms increased by 58, while it is 15 and 11 for Goethite and silica nanoparticles, respectively. A greater number of O atoms on the surface of a nanoparticle reduces the active cites for the degradation of lubricant. Thus, in comparison to goethite and silica nanoparticles, dry-air-treated Fe2O3 nanoparticles have lower active cites and a lower degradation rate of the lubricant. For the wet-air-treated case, in comparison to other nanoparticles, Fe2O3 nanoparticles have a higher degradation rate of lubricant strands. As mentioned previously, the production of a large number of water molecules during the NVT simulation of

ORCID

Roghayyeh Lotfi: 0000-0002-2051-8910 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS Funding from WD External Collaboration Project for conducting this research study is greatly appreciated. REFERENCES

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