A Combined Experimental and Molecular Simulation Study of Factors

Article pubs.acs.org/JPCB

A Combined Experimental and Molecular Simulation Study of Factors Influencing the Selection of Antioxidants in Butadiene Rubber Wei Zheng,† Youping Wu,† Wei Yang,‡ Zhuo Zhang,‡ Liqun Zhang,† and Sizhu Wu*,† †

State Key Laboratory of Organic−Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, P.R. China Global Energy Interconnection Research Institute, State Key Laboratory of Advanced Transmission Technology, Beijing 102211, P. R. China

‡

ABSTRACT: For the selection of antioxidants, internal factors were proposed by analyzing the thermal-oxidative aging process, which consisted of the following two inseparable steps: (1) the physical process of oxygen (O2) entering the rubber network and (2) the complex chemical process of O2 reacting with the rubber network. Antioxidants 2246, 6PPD, and MB, examples of amines, phenols, and heterocycles, respectively, were chosen to study these factors influencing the selection of antioxidants for the thermal-oxidative aging of butadiene rubber (BR). Through thermogravimetric analysis coupled with Fourier transform infrared spectroscopy and kinetic analysis by the Flynn−Wall−Ozawa method, the dissociation reaction of BR was identified to be the ratedetermining step for the thermal-oxidative aging of BR. Meanwhile, the decisive positions of the dissociation reactions for the three antioxidants in improving the thermal-oxidative stability of BR were also identified. Therefore, the internal factors were subdivided into five items (i.e., the free energy of reaction for the dissociation of antioxidant, the mole ratio of active radicals or hydroperoxides that could react with the same mass of antioxidant, the solubility and mobility of the antioxidant in BR, and the permeability of O2). Combined with molecular dynamics simulations and quantum mechanics simulations, the five internal factors were clarified and quantified over the entire usable temperature range of BR. To clarify the relative importance of each factor in the selection of antioxidants, we identified the time-dependent tensile strength and elongation at break as the only responses for the first and second gray relational analyses. The relative importance of the five internal factors was evaluated and ranked in terms of gray relational grade. The two analyses were consistent and showed that, in the selection of antioxidants, we should give priority to the free energy of the dissociation reaction and the permeability of O2.

1. INTRODUCTION Because of its good physical properties (e.g., high elasticity, good abrasion resistance, and low heat buildup), butadiene rubber (BR) has become one of the most popular synthetic rubbers and is widely used in industrial, technological, and military fields.1 However, aging, especially in thermal-oxidative environments, may greatly restrict the service life of BR. Recent studies have found that the addition of antioxidants is one of the most convenient methods for retarding or preventing the thermal-oxidative aging process.2,3 The thermal-oxidative aging process consists of the following two inseparable steps: (1) the physical process of oxygen (O2) entering the rubber network and (2) the complex chemical process of O2 reacting with the rubber network.4 Thus, in the selection of antioxidants, the ability of an antioxidant to lower both the permeation rate for O2 entering the rubber matrix and the rate of the chemical reaction between O2 and the rubber polymer chain is of vital importance. According to their chemical structures, antioxidants are classified as amines, phenols, heterocycles, reactive antioxidants, waxes, and others.5 According to their mecha© 2017 American Chemical Society

nisms, antioxidants are classified as carbon radical scavengers, peroxy radical scavengers, and peroxide-decomposing antioxidants.6 Among these types, amines are acknowledged to be the most widely used peroxy radical scavengers.7 Many factors can influence the effect of an antioxidant because they can influence one or both of the rates mentioned above. Tang attributed the good antioxidant effect of graphene in styrene−butadiene rubber to its abilities to lower the permeability of O2 and to scavenge free radicals.8 Ferradino found that antioxidants typically showed a plateau in effect vs dosage, indicating that limited solubility and blooming could limit the effect of an antioxidant.6 Clough also confirmed that the thermal-oxidative aging rate was slower in elastomers stabilized with low-volatility antioxidants.9 Hawkins declared that the mobility of an antioxidant influenced the rate at which the antioxidant scavenged the active radicals or decomposed peroxides to Received: December 7, 2016 Revised: January 17, 2017 Published: January 23, 2017 1413

DOI: 10.1021/acs.jpcb.6b12339 J. Phys. Chem. B 2017, 121, 1413−1425

Article

The Journal of Physical Chemistry B

energy for the dissociation reaction of the antioxidant, the mole ratio of active radicals or hydroperoxides that the same mass of antioxidant could react with, the solubility and mobility of the antioxidant in BR, and the permeability of O2). After identifying the time-dependent tensile strength and elongation at break as the only responses for the first and second GRA, the GRG of the five internal factors were evaluated twice. The two results are consistent. This research attempts to determine the mechanisms for three types of antioxidants and determine the priorities for antioxidant selection.

lower the rate of the complex chemical reaction between O2 and rubber.10 The Handbook of Rubber Industry summarized the above-mentioned internal factors (i.e., permeability of O2, mechanism, solubility, and mobility of antioxidant) and regarded them to be guiding principles in the selection of antioxidants.5 In previous studies, because of the diverseness of factors, the complexity of the thermal-oxidative aging mechanism, and the weakness of theoretical studies, researchers usually relied on their practical experience or theoretical studies of limited factors to select antioxidants. For example, Cibulková reported that the order of the effectiveness for six N,N′-substituted pphenylenediamine antioxidants was inversely proportional to the dissociation energy of their C−H bonds.11 Clough reported that heterogeneous thermal-oxidative aging was only caused by oxygen diffusion effects and did not depend on the antioxidant used in the formulation.9 Few researchers comprehensively consider the effects of all the factors of antioxidants on the changes in the macroscopic properties during thermal-oxidative aging. The relative importance of each factor is also not clarified in the selection of antioxidants. Thanks to the development of powerful computer hardware and software, molecular simulation, as a valuable theoretical tool, has been used to predict the dynamics and quantum mechanical properties of diverse materials on multiple scales. On the molecular scale, molecular dynamics (MD) simulations have been widely applied in exploring the structure−property relationships of amorphous materials. MD simulations help us obtain detailed insights about microstructures and provide direct quantitative information about the solubility parameters,12 mean square displacement,13 and other structural features of amorphous materials. On the micro scale, quantum mechanics (QM) simulations based on density functional theory14,15 have been successfully applied to reveal the underlying reaction mechanisms that are difficult to obtain in experiments and to design reliable synthetic methodologies for diverse materials.16 After using the correct experiments to identify the rate-determining reaction in thermal-oxidative aging, QM simulations can accurately calculate the free energy of the reaction. With molecular simulations, researchers can easily clarify the solubility and mobility of an antioxidant and the permeation process for O2 during thermal-oxidative aging. By comparing the free energy of reaction for antioxidants in molecular simulations, the mechanisms of different antioxidants can also be clarified. Furthermore, the simulated attempts indicate that, with proper simulation methods, the dynamics and quantum mechanical properties of a simulated system can effectively reflect the experimental properties of a real system.17−19 Meanwhile, an effective statistical method, gray relational analysis (GRA), has been developed to solve problems with a complicated interrelationship between multiple factors and a single response.20,21 After evaluating the relative importance of the factors in order of gray relational grade (GRG), the complicated interrelationship between the multiple factors and response can be clarified without knowing the mathematical relationships. In this study, the antioxidants 2,2′-methylenebis(4-methyl-6tert-butylphenol) (2246), N-(1,3-dimethylbutyl)-N′-phenyl-pphenylenediamine (6PPD), and 2-mercaptobenzimidazole (MB) were selected from the amines, phenols, and heterocycles, respectively, to prepare BR composites. By combining experiments and simulations, we subdivided the internal factors in the selection of antioxidants into five items (i.e., the free

2. METHODS 2.1. Experimental Methodology. 2.1.1. Materials. Antioxidants 2246, 6PPD, and MB, in powder form, were purchased from Tianjin Changli Rubber Trading Co., Ltd. (China), as was BR 9000. Other rubber additives such as sulfur, zinc oxide, and stearic acid were of commercial grade. All materials were used without further purification. 2.1.2. Preparation of Samples. The base formulation of the four BR samples is as follows (phr): BR 9000, 100; zinc oxide, 5; stearic acid, 2; accelerator N-cyclohexyl-2-benzothiazolesulfenamide (CZ), 0.7; sulfur, 1.5; carbon black N330, 25. In addition, 2 phr of antioxidant 2246, antioxidant 6PPD, antioxidant MB, and 0 phr of antioxidant were added to the base formulation to prepare samples A, B, C, and P, respectively. To prepare the BR samples, the ingredients above were first kneaded in a φ 152.4 mm open two-roll mill (Guangdong Zhanjiang Rubber and Plastic Machinery Factory, China) for mixing. Then, an oscillating disc rheometer (Beijing Huanfeng Mechanical Factory, China) was used to determine the optimum vulcanization time (t90) of the compounds. Finally, the compounds were hot-pressed and vulcanized in a 25 T Automatic Operation Vulcanizing Press (Shanghai Rubber Machinery Factory, China) at 150 °C for t90 to gain BR samples. 2.1.3. Thermo-Oxidative Accelerated Aging Experiments. BR samples were formed into dumbbell-shaped tensile splines as required for mechanical property tests. These splines were subjected to controlled deterioration in an air-circulating cabinet oven GT-7017-E (Gotech Testing Machines Co., Ltd., China) at 80 °C and atmospheric pressure to produce the effects of natural aging in a short time.22 2.1.4. Mechanical Property Tests. According to ISO 372011,23 the mechanical properties of at least five aged tensile splines were measured with an SLBL electronic universal material testing machine (Shimadzu Corporation, Japan) every day for a period of 5 d and were compared with those of at least five unaged samples. 2.1.5. Thermogravimetric Analysis Coupled with Fourier Transform Infrared Spectroscopy (TGA/FT-IR). The TGA/FTIR analyses were performed using a TGA/DSC 1 thermogravimetric analyzer (Mettler-Toledo Co., Switzerland) coupled with a Nicolet 6700 infrared spectrometer (Thermo Fisher Scientific Inc., USA). The pure BR sample P weighing approximately 7−10 mg was heated from 30 to 800 °C at a scanning rate of 10 °C/min under a constant air flow of 24 mL/ min. The Fourier transform infrared spectra were recorded in the wavenumber range from 4000 to 600 cm−1. 2.1.6. Thermogravimetric (TG) Measurements. The nonisothermal thermogravimetric (TG) measurements at different heating rates (5, 10, 20, and 30 K/min) were performed on a thermogravimetric analyzer (TGA)/differential scanning calo1414


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(the number of atoms, the pressure, and the temperature of the system were kept constant during the run) cycles of heating and cooling (from 300 to 500 K and back to 300 K by steps of 40 K), to gain a final structure with a realistic density.26 The resulting periodic cell was the initial structure for all subsequent MD simulations. To predict the corresponding properties, MD simulations were performed on the resulting cell using the NPT ensemble at atmospheric pressure and different temperatures. These equilibration runs lasted from 1 to 2 ns until the system reached equilibrium. The stable resulting system was the desired system, and the data were subsequently collected every 1 ps during the last 0.5 ns to predict the corresponding property. In all of the simulations, the temperature and pressure were controlled by Andersen’s method27 and Berendsen’s method,28 respectively. The electrostatic interactions were controlled by the Ewald method29 with an accuracy of 0.001 kcal/mol, and Newton’s equation of motion was integrated by the Verlet velocity time integration method30 with a time step of 1 fs. For the quantum mechanics (QM) simulations, all of the theoretical calculations were performed using the DMol3 module in the MS suite software. The QM simulations are based on density functional theory (DFT), which states that all ground-state properties of a multiparticle system are functions of its charge density.14 In DFT, the Kohn−Sham (KS) equation15 is the basic equation being solved. In our QM simulations, the generalized gradient approximation (GGA) in the form of the Perdew−Burke−Ernzerhof (PBE) function31 was chosen to approximately treat the exchange-correlation potential in the KS equation. The all electron core treatment, which provides no special treatment of cores and is appropriate for atoms up to about atomic number 36 (Kr), was chosen to approximately treat the external potential in the KS equation. Meanwhile, triple numerical atomic orbitals augmented by additional polarization functions (TNPs)32 were used as the basis set. For free radicals, the multiplicity was set to be a doublet. To make sure all of the structures were fully optimized, the self-consistent field (SCF) procedure with a convergence tolerance of 10−6 au was employed in conjunction with fine criteria for the other convergence qualities. To compute the thermodynamic properties (e.g., entropy, free energy, and heat capacity) at constant pressure as a function of temperature, a frequency analysis was performed on the optimized structure. Because frequency analysis yields the total electron energy at 0 K, a thermodynamic cycle is used in

rimetry (DSC) calorimeter (Mettler-Toledo Co., Switzerland). Sample P weighing approximately 7−10 mg was heated from 30 to 600 °C under an air flow of 50 mL/min. 2.2. Model and Simulation Details. For the molecular dynamics (MD) simulations, the Amorphous Cell and Forcite modules of the Materials Studio (MS) suite software were used.12 All calculations were performed by applying the condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field, which has been validated to accurately predict structural, conformational, and thermophysical properties for a broad range of materials (including polymers) under a wide range of temperatures and pressures.24,25 Cubic periodic boundary conditions (PBC) were applied as well. Figure 1 shows the entire construction process

Figure 1. Entire processes of constructing three types of amorphous cells (6PPD is the antioxidant in this example, and the blue, magenta, gray, and red spheres represent H, N, C, and O atoms, respectively).

for three types of amorphous cells (i.e., a pure BR or antioxidant cell, a BR and antioxidant cell, and a BR, antioxidant, and O2 cell) used in predicting the corresponding properties. Cells were constructed according to the composition listed in Table 1 for the simulation systems. To obtain a low potential energy, cells were first relaxed by geometry optimization using the smart method. Afterward, cells were annealed by a temperature cycle protocol, which consisted of four NPT Table 1. Composition of the Simulation Systems

statistics

a b

simulation systems

Nrepeat unit

BR 2246 6PPD MB BR&2246 BR&6PPD BR&MB BR&2246&O2 BR&6PPD&O2 BR&MB&O2

35 × 4

78 62 35 78 62 35

× × × × × ×

4 4 4 4 4 4

a

Nantioxidant

b

NO2

30 30 30 1 1 1 1 1 1

11 9 5

c

mBR:mantioxidant

49.59:1 50.01:1 50.47:1 49.59:1 50.01:1 50.47:1

d

4NO2:Nrepeat unit

0.141:1 0.145:1 0.143:1

The total number of butadiene repeating units, X × Y. X is the number of butadiene repeating units in one chain, and Y is the number of chains. The total number of antioxidant molecules. cThe total number of O2 molecules. dThe mass ratio of BR and antioxidant in the simulation system. 1415


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where D is the diffusion coefficient, C is the concentration of permeate molecules, and x is the effective thickness of the material. Fick’s second law36 gives the following equation

Figure 2 to determine the free energy of the dissociation reaction at a certain K temperature (ΔGcertain K).

dC d2C =D 2 dt dx

(6)

where t is time. When constant conditions (p1 and p2) are applied after a certain time, a steady state is reached. We obtain Figure 2. Example of the thermodynamic cycle for BR in the DMol3 module.

According to Figure 2, ΔG

certain K

is determined by

=P

12,33,34

(H•)certainK + Gcorr (A − H)certainK = EA • + E H • − EAH − Gcorr (A•)certainK (H•)certainK + Gcorr + Gcorr (A•)certainK (H•)certainK = (EA • + Gcorr ) + (E H • + Gcorr )

(1)

where ΔG is the free energy of the dissociation reaction at 0 K K K K; G(A−H)certain , G(A•)certain , and G(H•)certain are the thermal corr corr corr corrections to the free energy at the certain K temperature (including the translational, rotational, and vibrational components and zero-point vibrational energy (ZPVE)) for compound AH and the two free radicals A•, H•; and EA•, EH•, and EAH are the total electron energies at 0 K computed for the two free radicals A• and H• and the compound AH. On the basis of eq 1, the energy of a compound or a free radical at a certain K temperature, Gcertain K, is determined by the following equation:12,34 0K

GcertainK = E + Gcorr certainK

By substituting eq 2 into eq 1, we obtain certain K

⎡ x1 ⎤ ⎡ x11 x12 ⎢x ⎥ ⎢x 2 21 x 22 x=⎢ ⎥=⎢ ⎢⋮⎥ ⎢ ⋮ ⋮ ⎢x ⎥ ⎢ ⎣ m ⎦ ⎣ xm1 xm2

(2)

y = [ y1 y2 ... yn ] (3)

Step 2: Nondimensionalization. To eliminate the effects of dimensions or orders of magnitude and to maintain the effectiveness of the original data in the comparison and the reference matrices, a mean value treatment is adopted as follows:

certain K

where GA• and GH• are the energies of the two free radicals A• and H• at a certain temperature and GAHcertain K is the energy of the compound AH at a certain temperature. 2.3. Theoretical Basis. 2.3.1. Permeation Process. The entire permeation process consists of the following three steps: (1) sorption of permeate molecules at the upstream side of the material, (2) diffusive transport across the material, and (3) desorption of permeate molecules at the downstream side.35 The concentrations of permeate molecules at the upstream side (C1) and downstream side (C2) are described as C1 = S ·p1

and

C2 = S ·p2

xij′ =

dC dx

xij 1 n

n ∑ j = 1 xij

,

yj′ =

yj 1 n

n

∑ j = 1 yj

(8)

Step 3: Calculate the gray relational coefficient (GRC) min(min|yj ′ − xij′|) + ρ max(max|yj ′ − xij′|)

(4)

GRCij =

where S is the solution coefficient and p1 and p2 are the pressures at the upstream and downstream sides. Diffusive transport across the material can be described by the flux (J). According to Fick’s first law,36 J is determined by

J = −D

⋯ x1n ⎤ ⋯ x 2n ⎥ ⎥ ⋮ ⋮ ⎥ ⎥ ⋯ xmn ⎦

The reference matrix, which should also be studied under n conditions, is written as follows:

12,17

ΔGcertainK = GA •certainK + G H •certainK − GAH certainK

(7)

x

We define the permeation coefficient (P) to be D·S. p1, p2, and x are subjected to external condition and mold shape, whereas D, S, and the resulting P are intrinsic material properties. Therefore, P is an important index of the permeability and is the subject of our molecular simulations. 2.3.2. Gray Relational Analysis (GRA). GRA is an effective statistical method for evaluating the relative importance of multiple factors in a sequence ordered by a gray relational grade (GRG).20,21 In this study, this method was employed to study the relative importance of five internal factors, on the changes in the mechanical properties of BR after thermal-oxidative aging. GRA should be performed as follows: Step 1: Determine the comparison matrix and the reference matrix. If m types of factors are studied under n conditions, the comparison matrix should be written as follows:

(A − H)certainK (A•)certainK ΔGcertainK = ΔG 0K − Gcorr + Gcorr

(A − H)certainK − (EAH + Gcorr )

p − p2 C − C1 ΔC dC = −D = −D 2 = D·S 1 Δx dx x x p1 − p2

J = −D

i

j

i

j

|yj ′ − xij′| + ρ max(max|yj ′ − xij′|) i

j

(9)

where ρ is the resolution coefficient used to reduce the bias caused by excessive maximum value. Generally, ρ ∈ [0, 1]. In this study, ρ was chosen to be 0.5. Step 4: Calculate the gray relational grade (GRG).

(5) 1416


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1 n

n

Figure 3 shows that the absorption peak intensities increase with α until α reaches approximately 70%, corresponding to the thermal-oxidative degradation of BR. The subsequent decrease of the absorption peak intensities corresponds to the further degradation of the thermal-oxidative aging products of BR.38 We focus our attention on the first part and summarize the characteristics of the absorption peaks in Table 2 for reference.39,40 The basically stable absorption bands for CH stretching vibrations indicate that BR sample P basically retains the structural characteristics of butadiene. However, the increasing absorption bands for OH, CC, and CO stretching vibrations, etc., indicate the generation of various oxidation products (e.g., carboxylic acids, peroxides, and ketones) and the scission of the BR main chains. Kinetic analyses by model-free methods can provide significant clues and can reflect reliable kinetic information on the thermo-oxidative aging mechanism of a material.37,41 The nonisothermal, isoconversional Flynn−Wall−Ozawa (FWO) method has been reported to be a model-free method by using several different heating rates (β) regardless of the degradation model.42,43 The FWO method is based on the Doyle approximation for heterogeneous chemical reactions44

∑ GRCij (10)

j=1

The larger the GRG value, the greater the relative importance of the factor.

3. RESULTS AND DISCUSSION 3.1. Five Internal Factors. 3.1.1. Thermal-Oxidative Aging Mechanism of BR. First, we focused our attention on the factors that could influence the chemical process of the thermal-oxidative aging process. We know that different antioxidants can influence the complex chemical process of O2 reacting with the rubber network through different mechanisms. To study the mechanisms of different antioxidants, we first need to know the thermal-oxidative mechanism for BR. Therefore, we extracted the TGA/FT-IR spectra of sample P at specified fractional mass losses (α) and listed them

⎛ AEa ⎞ Ea log β = log⎜ ⎟ − 2.315 − 0.4567 RT ⎝ RG(α) ⎠

(12)

where A is a pre-exponential factor, Ea is the activation energy, α is the fractional mass loss, and G(α) is an integral conversional function. For a certain α, G(α) is fixed. Therefore, Ea can be estimated from the slope of the straight line obtained by plotting log β vs T−1. Figure 4 shows the TG curves for BR sample P at different heating rates. The mass decreasing rate changes when approximately 30% of the mass remains. The two decreasing stages correspond to the two thermal-oxidative degradation stages observed in the TGA/FT-IR spectra. The plots of log β versus 1000/T determined by the FWO method at specific α for BR sample P are presented in Figure 5. All of the linear correlation coefficients of the fits to the data are greater than 0.94. The calculated values of Ea are shown in Figure 6. On the basis of Figure 6, we can see that the plot shows two local maxima. The first maximum corresponds to the initiation of the BR main chain,45 and the second corresponds to the decomposition of the thermal-oxidative aging products.46 The first local maximal point is also the global maximal point,

Figure 3. Cross-sectional TGA/FT-IR spectra at specified fractional mass losses (α) during the degradation process of BR under an air atmosphere.

in Figure 3 to observe the variation in internal groups. The value of α can be calculated from eq 1137 w − wt α= 0 w0 − w∞ (11) where w0 is the initial mass of the sample, wt is the mass at time t during the TGA/FT-IR measurement, and w∞ is the remaining mass after the TGA/FT-IR measurement.

Table 2. Absorption Peak Ranges, Assignments, and Origin of Corresponding Chemical Structures for the TGA/FT-IR Spectra absorption peak ranges (cm−1) corresponding to specified α increase

stable

3600−3200 2935 2870 1789 1745−1715 1715−1650 1540 1172 940−900

assignments

origin of the chemical structures

OH stretching vibration CH antisymmetry stretching vibration CH stretching vibration CO stretching vibrations CO stretching vibrations CO stretching vibrations CC stretching vibration COC antisymmetry stretching OH out-of-plane deformation

carboxylic acids, alcohols, hydroperoxides, etc. R1CH2R2 R1CHR2 anhydrides, lactones, peracids, peroxides, etc. aldehydes, ketones, etc. ketones, aldehydes, α, β unsaturated acids (CCCOOH), etc. vinyl groups long-chain esters (RCOOR), ethers carboxyl

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In the chain initiation process (Scheme 1), BR first dissociates to form alkyl free radicals. This step requires the Scheme 1. Chain Initiation Process for BRa

a

R represents alkyl.

maximal Ea to occur and is the rate-determining step for the thermal-oxidative aging of BR.45 After being oxidized by O2, these alkyl free radicals generate peroxy radicals, which not only react through hydrogen abstraction from RH to form hydroperoxides but also participate in the chain propagation process as a reactant. The chain propagation process accounts for scission of the BR main chain and generation of the oxidation products. When the concentration of hydroperoxides is adequate, they can dissociate to form alkoxyl radicals. After chain scission, alkoxyl radicals can form aldehydes, which can be further oxidized to form peracids. Esters, anhydrides, carboxylic acids, etc., are formed through various reactions, which are shown in Scheme 2. The chain termination process, involving the recombination of two free radicals, can also form stable oxidation products and is the main reason for the increasing cross-linking of the BR main chain. 3.1.2. The Mechanisms of Different Antioxidants. Antioxidants 2246 and 6PPD are a hindered phenol and an aromatic amine, respectively. They are the dominant types of primary antioxidants, i.e., peroxy radical scavengers. Relative to BR, primary antioxidants contain very active hydrogen radicals that generally dissociate from O−H or N−H bonds and can be preferentially donated to the propagating free radicals, e.g., to the peroxy and alkoxy radicals.6 By competing effectively with the R• dissociated from C−H bonds in BR, antioxidants 2246 and 6PPD decrease the concentrations of the propagating free radicals; thus, these antioxidants can lower the thermaloxidative aging rate of BR. Antioxidant MB is a secondary antioxidant, i.e., a peroxidedecomposing antioxidant. By decomposing hydroperoxides to nonradical products, secondary antioxidants improve the thermal-oxidative stability of BR. The disulfide generated by two free radicals dissociated from S−H bonds in the antioxidant MB, not the active hydrogen atoms dissociated from N−H bonds in the antioxidant MB, plays a decisive role in lowering the thermal-oxidative aging rate of BR.6,48 According to the thermal-oxidative aging mechanism of BR discussed in section 3.1.1, we know that the dissociation reaction of BR is the rate-determining step for thermaloxidative degradation. Additionally, the dissociation reactions of the three antioxidants all play decisive roles in lowering the thermal-oxidative aging rate of BR. Therefore, we calculate the energies of different structures at 298 K and the free energies of different dissociation reactions at 298 K (ΔG298K). The results are listed in Tables 3 and 4. The bond breaking positions from (a) to (f) are shown in Figure 7. According to the results in Table 4, only the ΔG298K for dissociation at position (e) is larger than that for dissociation at

Figure 4. TG curves for BR sample P at different heating rates.

Figure 5. Plots of log β versus 1000/T determined by the FWO method at specific α for BR sample P.

Figure 6. Plot of Ea versus specified α determined by the FWO method.

indicating that initiation of the BR main chain is the ratedetermining step for the thermal-oxidative aging of BR. On the basis of the results from the TGA/FT-IR spectra, kinetic analysis, and other studies,39,45,47 an autocatalytic, free radical chain reaction thermal-oxidative aging mechanism, which divides the thermal-oxidative aging process of BR into chain initiation, chain propagation, and chain termination steps, is shown below. 1418


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The Journal of Physical Chemistry B Scheme 2. Chain Propagation Process for BRa

a

R represents alkyl.

Table 3. E, Gcorr298K, and G298K of Molecules and Free Radicals (BR Free Radicals Break Bonds at Position (a), 6PPD Free Radicals Break Bonds at Position (c) or (d), etc.) structures

E (Hartree)

Gcorr298K (kcal/mol)

Gcorr298K (Hartree)

G298K (Hartree)

H• BR BR•(a) 2246 2246•(b) 6PPD 6PPD•(c) 6PPD•(d) MB MB•(e) MB•(f)

−0.4963430 −157.0518347 −156.4098905 −1045.2088507 −1044.5716424 −809.0994287 −808.4704287 −808.4622947 −777.5868430 −776.9384460 −776.9666488

0 49.439 41.448 273.169 264.584 206.682 197.261 197.909 50.580 42.294 45.409

0 0.0787860 0.0660515 0.4353221 0.4216411 0.3293685 0.3143551 0.3153878 0.0806043 0.0673997 0.0723638

−0.4963430 −156.9730487 −156.3438390 −1044.7735286 −1044.1500013 −808.7700602 −808.1560736 −808.1469069 −777.5062387 −776.8710463 −776.8942850

Table 4. ΔG298K of C−H Bonds in BR at Position (a), N−H Bonds in Antioxidant 6PPD at Position (c) or (d), etc. dissociation position

(a)

(b)

(c)

(d)

(e)

(f)

ΔG298K (kJ/mol)

348.84

333.92

308.87

332.94

364.55

303.54

entire temperature usage range for BR, the values of ΔGcertain K for the same dissociation reaction do not vary greatly and the order of ΔGcertain K for different dissociation reactions still remains unchanged as at 298 K. Thus, the mechanisms for the three antioxidants also remain unchanged as at 298 K. 3.1.3. Suitability of Nrepeat unit Setting. To make sure that the data for the factors calculated from MD simulations are correct, we need to verify the suitability of the Nrepeat unit setting in the simulation system. Generally, the Nrepeat unit of the constructed cell is shorter than that of the real BR. This difference makes the computed density lower than the experimental one,50 which influences the validation of the simulation system. To confirm the validation of the simulation system, a method in which X increased ([CH2CHCHCH2]X, with X = 4, 5, 8, 10, 20, and 35) and Y remained constant (Y = 4) was employed to verify the suitability of the Nrepeat unit setting.25

position (a). This result explains why the antioxidant MB cannot function as a hydrogen donor in protecting BR against thermal-oxidative aging. For antioxidant 6PPD, the ΔG298K dissociation at position (c) is smaller than that for dissociation at position (d), indicating that the antioxidant 6PPD undergoes preferential dissociation of the N−H bond at position (d). On the basis of these conclusions, the mechanisms for the three antioxidants are summarized in Schemes 3−5.10,48,49 We can also see that 1 mol of antioxidants 2246 and 6PPD can react with 4 and 2 mol of propagating peroxy radicals, and 2 mol of antioxidant MB can decompose 2 mol of hydroperoxides. The results in Table 4 are simulated at 298 K; however, BR is used between 213 and 373 K. To study the free energies of different dissociation reactions over the entire temperature usage range for BR, we broadened the simulated temperatures of ΔGcertain K, and the results are shown in Figure 8. Over the 1419


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Figure 7. Bond breaking positions from (a) to (f). (The blue, magenta, gray, red, and yellow spheres represent H, N, C, O, and S atoms, respectively.)

Scheme 3. Mechanism for Antioxidant 2246a

Scheme 5. Mechanism for Antioxidant MBa

a

a

P represents

, and R represents an alkyl group.

3.1.4. Mobility of Antioxidants. In addition to the mechanism, the mobility of an antioxidant can also influence the complex chemical process of O2 reacting with the rubber network because it can influence the rate at which an antioxidant scavenges the active radicals or decomposes peroxides. The mean square displacement (MSD) can be used to study the mobility of molecules.13 MSD is defined by

R represents an alkyl group.

Figure 9 shows that the extrapolated density (X = +∞, 0.898 g/cm3), which represents the density for infinite chain lengths, is in perfect agreement with the experimental value of 0.90 g/ cm3. Figure 9 also shows that, when X is greater than or equal to 35, i.e., 1/X is equal or less than 0.029, the computed density is greater than or equal to 0.892 g/cm3. The small relative error between the simulated density for finite chain lengths and the density for infinite chain length indicates that X ≥ 35 is suitable for the simulation systems. In addition, to ensure that the mass ratio of BR to antioxidant is the same as the formulation of real BR samples, we set the value of Nrepeat unit to the value listed in Table 1.

MSD = ⟨|ri(0) − ri(t )|2 ⟩

(13)

where ri(0) is the initial position of atom i in the selected antioxidant molecule, ri(t) is the position of atom i after a time t, |ri(t) − ri(0)| represents the displacement of this atom during time t, and the brackets ⟨ ⟩ represents the average square of the displacement for all of the atoms in the selected antioxidant. Figure 10 shows that the antioxidant molecules are much more mobile at higher temperatures. Additionally, the relative mobilities of the three antioxidants are MB > 6PPD > 2246 at

Scheme 4. Mechanism for Antioxidant 6PPDa

a

A represents CH(CH3)CH2CH(CH3)2, and R represents an alkyl group. 1420


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The Journal of Physical Chemistry B D = lim

t →∞

1 MSD s ⟨|ri(0) − ri(t )|2 ⟩ = = 6t 6t 6

(14)

where s is the slope of the MSD as a function of time. After increasing the simulated temperatures for the MSD of the three antioxidants, their diffusion coefficients are calculated and shown in Figure 11. The results lead to conclusions similar

Figure 8. ΔGcertain K for C−H bonds in BR at position (a), N−H bonds in antioxidant 6PPD at position (c) or (d), etc.

Figure 11. Diffusion coefficients for antioxidants 2246, 6PPD, and MB in BR.

to those obtained from Figure 10; i.e., over the entire temperature usage range for BR, the mobility of antioxidant MB is the highest, followed by 6PPD, and 2246 has the lowest mobility. 3.1.5. Permeation Coefficient (P). Second, we concentrate on the factors that could influence the physical process of the thermal-oxidative aging process. Because the permeation coefficient (P) directly influences the permeation rate for O2 entering the rubber matrix, we need to know the value of P. To calculate P for O2, we use the same method described in 3.3 to calculate the value of D for O2 and introduce the dual-mode sorption model to calculate S for O2.18 This model is described as

Figure 9. Density variation as a function of X (open triangle: extrapolated density for infinite chain length).

C = KDp +

C Hbp 1 + bp

(15)

where C is the concentration of the permeate molecules in the polymer, KD is Henry’s constant, p is the pressure, CH is the Langmuir adsorption capacity, and b is the Langmuir affinity parameter. S is defined as the ratio of the penetrant concentration to pressure.18 S=

C Hb C = KD + p 1 + bp

(16)

In molecular simulations, S is calculated from the adsorption isotherm using the sorption module. Using the adsorption isotherm task, the affinity of a permeate molecule toward a polymer framework over a range of pressures at a given temperature is characterized. The average cell loading is returned at the end of each fixed pressure simulation. Then, the adsorption isotherm task proceeds by increasing the pressure and starting a new fixed pressure simulation. Finally, a plot of the average cell loading as a function of pressure over a range of pressures is returned. S is the slope of the plot when the pressure approaches a limit of 0 kPa.

Figure 10. MSD for antioxidants 2246, 6PPD, and MB in BR at 298 and 375 K.

both 298 and 375 K, indicating that antioxidant molecules with smaller molecular weights have higher mobilities. To quantitatively describe the mobilities of the three antioxidants over the entire temperature usage range for BR, the Einstein equation is introduced to calculate the diffusion coefficient (D) of the antioxidant molecule51 1421


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Figure 12. D, S, and P of O2 in three antioxidant and BR systems: (a) D; (b) S; (c) P.

S = lim

p→0

C = KD + C Hb p

where Ecoh is the change in internal energy of vaporization, V is the molar volume, ΔHvap is the enthalpy of vaporization, R is the gas constant, and T is the absolute temperature. Empirically, if the absolute difference in the solubility parameters for two materials A and B (Δδ = |δA − δB|) is less than 2.05 (J/cm3)0.5, A and B are compatible. If Δδ is larger than 2.05 (J/cm3)0.5 and less than 6.95 (J/cm3)0.5, A and B are partially compatible. If Δδ is larger than 10.02 (J/cm3)0.5, A and B are incompatible. Table 5 shows the solubility parameters for BR and the antioxidants. The values of Δδ between BR and the three

(17)

During the course of the simulation, the permeate molecules are randomly created and deleted from the polymer framework and are randomly rotated and translated in the framework. The configuration resulting from one of these steps is accepted or rejected according to the selection rules of the Metropolis Monte Carlo method.52 The equilibration step for each fixed pressure simulation is set as 106. The start and end pressures are set to be 10 and 200 kPa, respectively. Figure 12 shows that, over the entire temperature usage range of BR, D increases and S decreases as temperature increases, resulting in the fluctuation of P. P reaches a maximum at approximately 300 K and then tends to be stable, indicating that O2 easily permeates BR when the temperature is higher than 300 K. In addition, P is highest for the BR system with the antioxidant MB, followed by the system with 2246, and is lowest for the system with 6PPD. 3.1.6. Solubility of Antioxidants. Finally, we calculate the fifth factor, the solubility of an antioxidant, which could influence both the permeation rate for O2 entering the rubber matrix and the rate of the chemical reaction between O2 and the rubber polymer chain. To predict the solubility of an antioxidant in BR, we introduce the solubility parameter (δ).12 δ characterizes the strength of the cohesion between molecules and is important in evaluating the compatibility of different materials. δ is defined as the square root of the cohesive energy density (CED) δ=

CED =

Ecoh = V

Table 5. Solubility Parameters for BR and the Antioxidants initial density (g/cm3)

δ (J/cm3)0.5

δlit. (J/cm3)0.5

BR 2246 6PPD MB

0.90 1.06 0.99 1.42

16.981 18.542 20.125 27.619

17.2053 19.7354 26.5254

Δδ = |δantioxidant − δBR| (J/cm3)0.5 1.561 3.144 10.638

antioxidants are in the three different ranges, indicating that the relative solubilities of the three antioxidants in BR is 2246 > 6PPD > MB. The results in Table 5 are simulated at 298 K. To study the solubility of antioxidants over the entire temperature usage range for BR, we increased the range of simulated temperatures for δ. The results show that δ decreases very slightly as temperature increases; this trend has been found in other work.55 Therefore, we simulate the phase diagrams for the three antioxidant and BR systems, instead of the Δδ between antioxidants and BR, to study the solubilities of the antioxidants over the entire temperature usage range for BR.

ΔH vap − RT V

materials

(18) 1422


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The Journal of Physical Chemistry B The phase diagram was simulated with the Blends module. A Blends calculation consists of choosing the task, setting the calculation quality level, and defining the role of the input molecules. In this work, the task was set to Mixing, the calculation quality was set to fine, the role of BR was set to be base, and the roles of the three antioxidants were all set to screen. After running the Blends calculation, the phase diagram was easily obtained from the results. Figure 13 shows that the three systems of antioxidant and BR are all upper critical solution systems. The higher the

Figure 14. Trends for the retained ratios of tensile strength and elongation at break for the three BR samples.

⎡ 9.68 7.84 7.37 6.58 6.06 ⎤ ⎥ ⎢ y = ⎢10.49 8.82 8.59 7.61 6.99 ⎥ ⎢⎣10.47 7.61 7.38 6.09 4.34 ⎥⎦ ⎡ 445.54 361.14 332.18 294.49 242.14 ⎤ ⎥ ⎢ y′ = ⎢ 490.80 418.16 400.37 345.10 332.39 ⎥ ⎢⎣ 515.18 402.54 373.86 316.69 271.63 ⎥⎦ Figure 13. Phase diagrams for the three different antioxidant and BR systems.

The comparison matrices for the first and second GRA are the same and are composed of the 6 factors studied at all 15 conditions. The factors are divided into one external factor (i.e., the time of thermal-oxidative exposure) and five internal factors (i.e., ΔG353K, the mole ratio of active radicals or hydroperoxides that can react with the same mass of antioxidant, the solubility described by the corresponding mass fractions of the spinodal curves at 353 K, D for the antioxidants at 353 K, and P for O2 at 353 K). Because the internal factors do not change with time, the internal factors studied under the 15 conditions actually have 3 sets of data, corresponding to the data for the three BR samples. According to the steps listed in section 2.3.2, the GRG of each internal factor in the two GRA performed is summarized in Table 6.

temperature, the better the solubility of the antioxidant. Figure 13 also shows that, at the same temperature, the order of the corresponding mass fractions for the spinodal curves is BR system with 2246 > with 6PPD > with MB. The spinodal curves determine the incipient unstable points, under conditions beyond which a system will split into two phases. Therefore, the relative solubilities of the antioxidants over the entire temperature usage range of BR is 2246 > 6PPD > MB. This result is consistent with the analysis based on the solubility parameter. 3.2. Response. To perform GRA, we measured the tensile strength and elongation at break of BR samples A, B, and C over 5 d of thermal-oxidative exposure at 80 °C. Meanwhile, we plotted the trends for the retained ratios of tensile strength and elongation at break for the three BR samples in Figure 14. Over 5 d of thermal-oxidative exposure at 80 °C, the retained ratios of tensile strength and elongation at break for the three BR samples both decline, leading to deterioration in the mechanical properties and thermal resistance. Additionally, the relative stabilities of the mechanical properties after thermal-oxidative exposure are sample B > sample A > sample C, indicating that antioxidant 6PPD is most effective in improving the thermaloxidative stability of BR, 2246 less effective, and MB least effective. 3.3. Gray Relational Analysis (GRA). The tensile strength and elongation at break are established as the reference matrix for the first and second GRA, respectively. Because we measured the mechanical properties of the three BR samples at 0, 1, 2, 3, and 5 days, the first (y) and second reference matrix (y′) are both studied under 15 conditions and can be written as follows:

Table 6. GRG of Each Internal Factor in the Two GRA Performed internal influencing factors first GRA second GRA relative importance

GRG

solubility

Dantioxidants

PO2

ΔG353K

mole ratio

0.603 0.578 5

0.760 0.769 4

0.833 0.833 2

0.860 0.844 1

0.772 0.769 3

Table 6 shows the relative importance of the five internal factors on the mechanical properties of BR after thermaloxidative aging. The relative importance rankings calculated for the two GRA are consistent, showing that, among the five internal factors, the free energies of the dissociation reaction, which affects the chemical process of the thermal-oxidative aging process, and the permeability of O2, which affects the physical process of the thermal-oxidative aging process, are most important. This result not only shows that we should give priority to the free energies of dissociation reactions and the permeability of O2 in the selection of antioxidants for BR but 1423


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(2) Komethi, M.; Othman, N.; Ismail, H.; Sasidharan, S. Comparative Study on Natural Antioxidant as an Aging Retardant for Natural Rubber Vulcanizates. J. Appl. Polym. Sci. 2012, 124, 1490−1500. (3) Wu, W.; Zeng, X.; Li, H.; Lai, X.; Li, F.; Guo, J. Synthesis and Characterization of a Novel Macromolecular Hindered Phenol Antioxidant and its Thermo-Oxidative Aging Resistance for Natural Rubber. J. Macromol. Sci., Part B: Phys. 2014, 53, 1244−1257. (4) Murakami, K.; Ono, K. Chemorheology of Polymers; Elsevier Science & Technology: Amsterdam, The Netherlands, 1979. (5) Liang, X.; Zhou, J. In Handbook of Rubber Industry; Liang, X., Zhou, M., Eds.; Chemical Industry Press: Beijing, 1996; Vol. 3, pp 181−184. (6) Ferradino, A. G. Antioxidant Selection for Peroxide Cure Elastomer Applications. Rubber Chem. Technol. 2003, 76, 694−718. (7) Li, G. Y.; Koenig, J. L. FTIR Imaging of Oxidation of Polyisoprene 2. The Role of N-phenyl-N′-dimethyl-butyl-p-phenylenediamine Antioxidant. Polym. Degrad. Stab. 2003, 81, 377−385. (8) Tang, M.; Xing, W.; Wu, J.; Huang, G.; Xiang, K.; Guo, L.; Li, G. Graphene as a Prominent Antioxidant for Diolefin Elastomers. J. Mater. Chem. A 2015, 3, 5942−5948. (9) Clough, R. L.; Gillen, K. T. Oxygen Diffusion Effects in Thermally Aged Elastomers. Polym. Degrad. Stab. 1992, 38, 47−56. (10) Hawkins, W. L. Polymers/Properties and Applications 8, Polymer Degradation and Stabilization; Springer-Verlag: Berlin, Germany, 1984. (11) Cibulková, Z.; Šimon, P.; Lehocký, P.; Balko, J. Antioxidant Activity of P-phenylenediamines Studied by DSC. Polym. Degrad. Stab. 2005, 87, 479−486. (12) BIOVIA Materials Studio. http://accelrys.com/products/ materials-studio/index.html/ (accessed Mar 27, 2015). (13) Bačová, P.; Hawke, L. G.; Read, D. J.; Moreno, A. J. Dynamics of Branched Polymers: A Combined Study by Molecular Dynamics Simulations and Tube Theory. Macromolecules 2013, 46, 4633−4650. (14) Hohenberg, P.; Kohn, W. Inhomogeneous Electron Gas. Phys. Rev. 1964, 136, B864−B871. (15) Kohn, W.; Sham, L. J. Self-Consistent Equations Including Exchange and Correlation Effects. Phys. Rev. 1965, 140, A1133− A1138. (16) Frutos, L. M.; Carriedo, G. A.; Tarazona, M. P.; Saiz, E. Theoretical Study on the Mechanism and Regioselectivity of the Macromolecular Substitution Reactions of [NPCl2]n with Bifunctional Nucleophiles by a Combination of Quantum Mechanical and Molecular Dynamics Calculations. Macromolecules 2009, 42, 8769− 8773. (17) McGrath, M. J.; Kuo, I. W.; Ngouana, W. B.; Ghogomu, J. N.; Mundy, C. J.; Marenich, A. V.; Cramer, C. J.; Truhlar, D. G.; Siepmann, J. I. Calculation of the Gibbs Free Energy of Solvation and Dissociation of HCl in Water via Monte Carlo Simulations and Continuum Solvation Models. Phys. Chem. Chem. Phys. 2013, 15, 13578−13585. (18) Sun, D.; Zhou, J. Molecular Simulation of Oxygen Sorption and Diffusion in the Poly(lactic acid). Chin. J. Chem. Eng. 2013, 21, 301− 309. (19) Eslami, H.; Behrouz, M. Molecular Dynamics Simulation of a Polyamide-66/Carbon Nanotube Nanocomposite. J. Phys. Chem. C 2014, 118, 9841−9851. (20) Ahmad, N.; Kamal, S.; Raza, Z. A.; Hussain, T.; Anwar, F. MultiResponse Optimization in the Development of Oleo-Hydrophobic Cotton Fabric Using Taguchi Based Grey Relational Analysis. Appl. Surf. Sci. 2016, 367, 370−381. (21) Zuo, W.; Jiaqiang, E.; Liu, X.; Peng, Q.; Deng, Y.; Zhu, H. Orthogonal Experimental Design and Fuzzy Grey Relational Analysis for Emitter Efficiency of the Micro-cylindrical Combustor with a Step. Appl. Therm. Eng. 2016, 103, 945−951. (22) ISO 188:2011(E). Rubber, Vulcanized or Thermoplastic Accelerated Ageing and Heat Resistance Tests; ISO Copyright Office: Switzerland, 2011. (23) ISO 37:2011(E). Rubber, Vulcanized or Thermoplastic Determination of Tensile Stress-Strain Properties; ISO Copyright Office: Switzerland, 2011.

also shows that, in the study of thermal-oxidative aging, the physical process of oxygen (O2) entering the rubber network and the complex chemical process of O2 reacting with the rubber network are both absolutely indispensable.

4. CONCLUSIONS (1) The thermal-oxidative aging of BR followed an autocatalytic, free radical chain reaction mechanism. The dissociation reaction of BR was the rate-determining step. The active hydrogen radicals that generally dissociated from the O−H and N−H bonds in antioxidant 2246 and 6PPD could effectively compete in reactions with propagating free radicals to lower the thermal-oxidative aging rate of BR. The disulfide generated by the two free radicals dissociated from S− H bonds in the antioxidant MB could decompose hydroperoxides to lower the rate of BR oxidation. Thus, the free energies of the dissociation reactions were the focus of our attention in the selection of antioxidants by mechanism. (2) Over 5 d of thermal-oxidative exposure at 80 °C, the order of the retained ratios of tensile strength and elongation at break of the three BR samples indicated that antioxidant 6PPD was most effective in improving the thermal-oxidative stability of BR, 2246 was less effective, and MB was least effective. (3) The relative importance of the five internal factors was clarified by the first and second gray relational analyses, which used the tensile strength and elongation at break as the only responses, respectively. The results were consistent and showed that the relative importance ranking was the free energies of the dissociation reactions > the permeability of O2 > the mole ratio of active radicals or hydroperoxides that could react with the same mass of antioxidant > the mobility of antioxidants > the solubility of antioxidants in BR.

■

AUTHOR INFORMATION

Corresponding Author

*Phone/fax: 86-010-64444923. E-mail: [email protected]. Postal address: Box 90, Beijing University of Chemical Technology, No. 15, Beisanhuan Road East, Chaoyang District, Beijing, China. ORCID

Youping Wu: 0000-0001-6723-7043 Sizhu Wu: 0000-0001-7863-2954 Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS Financial support from the National Natural Science Foundation of China under Grant No. 51473012 and the Major Research plan of the Ministry of Science and Technology of China under Grant No. 2014BAE14B01 is gratefully acknowledged.

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REFERENCES

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