Mixed Network Former Effect on Structure, Physical Properties and

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Mixed Network Former Effect on Structure, Physical Properties and Bioactivity of 45S5 Bioactive Glasses: An Integrated Experimental and Molecular Dynamics Simulation Study Xiaonan Lu, Lu Deng, Caitlin Huntley, Mengguo Ren, Po Hsuen Kuo, Ty Thomas, Jonathan Chen, and Jincheng Du J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.7b12127 • Publication Date (Web): 01 Feb 2018 Downloaded from http://pubs.acs.org on February 4, 2018

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The Journal of Physical Chemistry

Mixed Network Former Effect on Structure, Physical Properties and Bioactivity of 45S5 Bioactive Glasses: an Integrated Experimental and Molecular Dynamics Simulation Study Xiaonan Lu1, Lu Deng1, Caitlin Huntley1, Mengguo Ren1, Po-Hsuen Kuo1, Ty Thomas1, Jonathan Chen1, Jincheng Du1* 1

Department of Materials Science and Engineering, University of North Texas, Denton, TX 76203 (*Corresponding Author. Email: [email protected])

Abstract: Boron-containing bioactive glasses display a strong potential in various biomedical applications lately due to their controllable dissolution rates. In this paper, we prepared a series of B2O3/SiO2-substituded 45S5 bioactive glasses and performed in vitro biomineralization tests with both simulated body fluid (SBF) and K2HPO4 solutions to evaluate the bioactivities of these glasses as a function of boron oxide to silica substitution. The samples were examined with scanning electron microscopy (SEM), Xray diffraction (XRD), and Fourier transform infrared spectrometry (FTIR) after immersing them in the two solutions (simulated body fluid and K2HPO4) up to three weeks. It was found that introduction of boron oxide delayed the formation of hydroxyapatite (HAp), but all the glasses were shown to be bioactive. Molecular dynamics (MD) simulations were used to complement the experimental efforts to understand the structural changes due to boron oxide to silica substitution by using newly developed partial charge composition-dependent potentials. Local structures around the glass network formers, medium-range structural information, network connectivity and self-diffusion coefficients of ions were elucidated from MD simulation. Relationships between boron content and glass properties such as structure, density, glass transition temperature and in vitro bioactivity were discussed in light of both experimental and simulation results.

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1. Introduction 45S5 Bioglass® (46.1SiO2-24.4Na2O-26.9CaO-2.6P2O5 in mol%) was one of the first bioactive glasses discovered by Prof. Larry Hench about five decades ago and is still one of the most studied bioactive glass compositions.1,2 Many new glass compositions have been proposed and found several biomedical applications from dental filling, drug delivery, coating to load bearing metal implants, to tissue engineering.3 The glass matrix can accommodate various dopants while maintaining the glass character and basic physical and chemical properties.4 This composition flexibility enables large design space and the capability to introduce additional functionality such as enhancement of osteogrowth by Sr2+,5–7 angiogenesis by Cu2+,8–10 and antibacterial by Ag+ in bioactive glasses.11 Boron oxide was not in the initial bioactive glass compositions. However, recent works have shown specific biomedical applications for boron-containing bioactive glasses such as controllable dissolution rate,12,13 supporting tissue infiltration,13 soft tissue repair,14 improving adhesion between glass and Ti/Ti alloy substrates,15,16 widen the processing window for coating metallic implants17 and improving mechanical properties by crystallization.18 Whereas, mixed results were found in terms of bioactivity in silicate bioactive glasses with boron oxide additions. Several studies showed that replacing SiO2 with B2O3 produced a more rapid conversion of the glass to HAp, and pure borate glasses could be fully converted to HAp in vitro.12,13,19 On the other hand, studies have also shown that the addition of boron impeded the HAp formation in vitro.20–23 Manupriya et al.22 observed that 45S5 is much more bioactive than its borate counterpart according to their in vitro bioactivity tests. Similar observation were found in a recent study by Yu and Edén as well.24 A high B2O3 content was also shown to prevent cell proliferation, or it can even be toxic;13,25,26 however, the negative effect could be minimized in the dynamic in vivo body fluid environment.14,27 Immersing materials in simulated body fluids (SBFs) for in vitro bioactivity evaluation is commonly adopted due to its economic advantage and accessibility as compared to in vivo testing; nevertheless, it should be pointed out that bioactivity evaluated by SBF immersion has some notable exceptions although it is generally agreeable with in vivo bioactivity.28,29 Several details of the experimental conditions can


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significantly alter the dissolution rate and HAp formation. These experimental details include, but are not limited to, glass mass to solution volume ratio,30 glass surface area to solution volume ratio,22 particle size,19 SBF preparation28 and solution replenishment frequency,31 which directly affect the final results and interpretation of the glass bioactivity. In a recent study by Stone-Weiss et al.,32 a detailed introduction on experimental challenges for study dissolution and bioactivity of boron-containing glasses is presented. Our study adopted a unified evaluation protocol proposed by Macon et al.33 for bioactivity evaluation of glasses. Mechanisms of HAp formation in vivo and in vitro of silicate bioactive glasses and ceramics mainly consist of five stages:34 (I) ion exchange between glass and solution; (II) breakage of Si-O-Si bonds and formation of Si-OH at the glass solution interface; (III) condensation and repolymerization on a SiO2-rich layer; (IV) migration of Ca2+ and PO43groups and formation of an amorphous CaO-P2O5-rich film on the top of the SiO2 film; (V) crystallization of the amorphous CaO-P2O5 film by incorporation of OH-, CO32- or Fanions. For borate-based bioactive glasses, the mechanism of HAp formation is similar with silicate glasses, except for the absence of a SiO2-rich layer.13,25,35 The faster dissolution rate of borate-based glasses is the main reason for its higher level of bioactivity as compared to silicate bioactive glasses in many studies.9,12,13,19,36 However, the Si-OH groups in SiO2-rich layer were believed to provide nucleation sites for the apatite formation,37,38 which might be one of the reasons that introducing B2O3 reduced the bioactivities in some studies.20–23 Finding the appropriate amount of B2O3/SiO2 substitution in silicate bioactive glasses to tailor their bioactivity and dissolution rate are thus essential for various biomedical applications. Traditional materials design adopts a “trial-and-error” approach. This includes many series of bioactive glasses that were studied with gradually compositional changes, and then investigated their properties and bioactivities.13,39–44 This approach, however, becomes problematic in new biomaterial design, especially when various biomedical applications require a much faster rate of discovery for new materials with different requirements.32 The material genome approach, on the other hand, can potentially expedites the new material exploration by integration of computation, simulation, data exploration in combination with experimental studies. Integrated simulation and


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experimental study can be an effective approach to next generation biomaterial designs. This includes correlation of dissolution and bioactivity to atomic-level glass structures or correlation of glass properties to certain structural descriptors through the quantitative structure property relationship (QSPR) approach.32,45,46 We explore in this paper the integration of molecular dynamic (MD) simulations, one of the most effect methods to understand the atomic-level structure of glasses, with experimental glass synthesis and in vitro bioactivity evaluation to understand structure-bioactivity relation of boron oxide containing silicate bioactive glasses. In terms of glass structural study, MD simulations provide quantitative and statistical information that can be utilized to study the relationship between glass structure and bioactivity of glasses. For instance, effects of SrO substitution of CaO on structure and diffusion behavior of 45S5, 55S4.3 and 60S3.8 bioactive glasses have systematically revealed with MD simulation,47–49 as well as in combination of MD with X-ray and neutron diffractions,50 and solid-state nuclear magnetic resonance (NMR).51 Water/glass interfaces and initial dissolution of bioactive glasses were also successfully studied with ab initio molecular dynamics simulation.52 Recently, Yu et al.60 probed bioactive borophosphosilicate glasses with both MD simulation and NMR in order to reveal detailed structural involution altered by B2O3. However, very few simulation studies were conducted on boron-containing bioactive glasses, which is mainly due to the lack of reliable empirical potentials that can properly reproduce the boron coordination change with glass composition that has been determined by 11B solid state NMR experimentally.53 Recently, Deng and Du54 proposed a composition-dependent pairwise potential set to study the structure and properties of the sodium boroaluminosilicate glasses. One important feature of this composition-dependent potential set is that it reproduces the theoretically predicted percentage of 4-coordinated boron from Yun-DellBray model,55,56 which plays an important role in both glass structure (e.g., boroxol rings and sodium distribution) and properties (e.g., vibrational density of states and mechanical properties). Composition-dependent potential sets with boron parameters can effectively produce reasonable glass structures and properties,54,57–59 therefore, reasonable glass structure is expected to be obtained through a normal melt-quench process. B2O3 substitution of SiO2 in a SrO-containing bioactive glass was studied previously using


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similar composition-dependent potential set, where short- and medium-range structural information were investigated and used to discuss bioactivity observed from experiments.23 In this paper, we aim to understand the structure and bioactivity of B2O3/SiO2substituded 45S5 bioactive glasses by combining experimental studies and MD based computer simulations. These glasses were prepared using a conventional melt-quench process and performed in vitro evaluations in both simulated body fluids (SBFs) and K2HPO4 solutions with a fixed range of particle size and a fixed glass mass to solution volume ratio. The objectives of the experimental efforts include studying the relationship between physical properties (e.g., density and glass transition temperature) as a function of boron oxide/silica substitution, and investigating the influence of boron oxide concentration on in vitro bioactivity of 45S5. Furthermore, these compositions were also simulated using classical MD simulation to obtain detailed structural information and properties such as ionic diffusion. Local structures around the glass network formers (e.g., bond length, bond angle distribution and coordination numbers), medium-range structural information (e.g., Qn distributions and network connectivity) and self-diffusion coefficients of ions were obtained. Relationship between boron content and glass properties such as structure, density, glass transition temperature and bioactivity were discussed in light of both experimental and simulation results.

2. Methodology 2.1 Glass synthesis procedures Compositions of the glasses studied in this paper are shown in Table 3. 0B denotes to the composition of 45S5. Silica was replaced (34%, 67%, and 100%) with boron oxide to understand the changes on physical property and bioactivity due to this substitution. The glasses were prepared by thoroughly mixing analytical grade H3BO3, NH4H2PO4, SiO2, NaCO3 and CaCO3 chemicals before melting in an Al2O3 crucible at 1200 °C for 2 h in an electrical furnace (Deltech Furnaces). Molten glasses were poured onto a stainless plate and cooled to room temperature. Bulk glasses were manually crushed, ground with an alumina mortar and pestle, and then sieved to 32 µm to 45 µm with stainless steel sieves. Glass powders were cleaned in deionized (DI) water and ethanol two times each


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in an ultrasonic cleanser, respectively. Cleaned glass powders were oven-dried (60 °C) overnight.

2.2 Glass characterizations Density measurements were carried out on the glass powders using specific gravity of solids method with density bottles at room temperature. Bubbles in the glass powders and DI water were removed ultrasonically until there was no visible bubble movement. Density of DI water at 25 °C used for calculation was 0.997 g/cm3.61 Differential scanning calorimetry (DSC) was carried on a NETZSCH STA 499 F3 in an argon environment with a gas flow of 60 mL/min, a heating rate of 20 ˚C/min, and a powdered glass sample (particle size between 32 µm to 45 µm) weighing between 23 mg and 25 mg in an Al2O3 pan without a lid. The glass transition temperatures (Tg) was determined by intersecting tangents from the DSC curves. Estimated errors Tg are ± 3 °C, similar to a study by Guerette et al.,62 where tangent intersecting was also used for determining Tg. Glass powders were characterized with high resolution X-ray diffraction (XRD) on a Rigaku Ultima III with a scanning speed of 3 °/min and a step of 0.03 °/point. A commercial HAp powder (calcium phosphate tribasic) obtained from Fisher Scientific was taken as a reference material. XRD pattern analysis was performed with JADE 9 software package. Fourier transform infrared spectrometer (FTIR) equipped with an attenuated total reflection (ATR) sampling technique was conducted with a Nicolet 6700 spectrometer (Thermo Electron) at room temperature. A diamond substrate was used for the ATR sampling. A total of 32 scans for background and per sample were used with a resolution of 2 cm-1. Environmental scanning electron microscopy (ESEM) was conducted on an FEI Quanta ESEM with electron energy of 15 kV and an FEI Nova NanoSEM 230 with electron energy of 10 kV or 15 kV to observe surface tomography of SBF or K2HPO4 solution treated samples after Au-Pd coating.

2.3 Bioactivity evaluations


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Simulated body fluid (SBF) was prepared following procedures of Kokubo and Takadama28 by mixing reagent grade chemicals in the following order (see Table 1): NaCl (8.035 g), NaHCO3 (0.355 g), KCl (0.225 g), K2HPO4·3H2O (0.231 g), MgCl2·6H2O (0.311 g), 1 mol/L HCl (39 mL), CaCl2 (0.292 g) and Na2SO4 (0.072 g) in DI water (700 mL) with a plastic beaker at 37 °C. After the chemicals completely dissolved, DI water was added up to 900 mL in total, and the pH of the solution was 1.5 ± 0.1 at the time. The fluid was buffered to a pH value of 7.40 at 36 ± 0.5 °C by slowly adding tris(trihydroxymethyl)-aminomethane (total 6.118 g) and drops of 1 mol/L HCl. After dissolving all tris(trihydroxymethyl)-aminomethane, the solution was filled with DI water up to 1 L at room temperature. The 0.02 mol/L K2HPO4 solution was prepared by dissolving reagent grade K2HPO4·3H2O in DI water, where the starting pH was 9.10 at room temperature. pH measurements were performed on a bench-top pH/mV meter (Sper Scientific) with an accuracy of ± 0.02 pH. Table 1. Procedures for 1 L of SBF preparation. Order

Chemicals/solution

Amount

1

DI water

700 mL

2

NaCl

8.035 g

3

NaHCO3

0.355 g

4

KCl

0.225 g

5

K2HPO43H2O

0.231 g

6

MgCl26H2O

0.311 g

7

1M HCl

39 mL

8

CaCl2

0.292 g

9

Na2SO4

0.072 g

10

DI water

Add up to 900 mL (pH = 2.0 ± 1.0)

11

TRIS

12

DI water

6.118 g (maintain a pH between 7.40 and 7.45 by adjusting using HCl) Add up to 1 L at room temperature


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Each 75 ± 0.5 mg glass powder was put in a polypropylene self-standing tube (Corning) with a 50 mL SBF or K2HPO4 solution at 37 ± 0.2 °C up to three weeks. The tubes were agitated at an interval time throughout the in vitro tests to prevent glass powders from sticking together. Glass powders were washed in ethanol and oven-dried (60 °C) overnight after being obtained in a time period of 4 h, 24 h (1 day), 72 h (3 days), 168 h (1 week), 336 h (2 weeks) and 504 h (3 weeks).

2.4 Computer simulation details MD simulations have been conducted by the DL_POLY simulation package developed at Daresbury Laboratory in the UK.63,64 A set of pairwise partial charge potential that has been successfully used to simulate multicomponent silicate and phosphosilicate glasses including several bioactive glass compositions47–49 were adopted in this work by addition of composition-dependent boron parameters. Potential parameters of O-O, Na-O, Si-O, P-O and Ca-O pairs were reported earlier49 and, together with the newly developed the boron related pair parameters, are listed in Table 2. Compatible boron related parameters were recently developed and have been successfully applied to study a series of boron containing bioactive glasses.23 The interatomic interactions are described by the Born model of solids using partial charge pairwise potentials. The partial covalence of Si-O bond is modeled by employing the partial charge for ions. The partial atomic charges are shown in Table 2. The short-range interaction has the Buckingham form denoted by following equation:

= exp − ⁄ − ⁄

(1)

where, i and j are the elements of the i - j pair, , and are the empirical parameters for pair i - j and is the interatomic distance of the i - j pair. To solve the high temperature issue (when two atoms are close to each other at a high temperature, the potential value may quickly drop down to the negative infinity which is not reasonable), a repulsion term ( =

+ ) was added to correct it. The , and values

were obtained by keeping the potential, force and first derivative of the force curve continuous at the point where the second derivative of the force was approaching 0.


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, and parameters in the Buckingham form used in the simulations are listed in Table 2. For the B-O interaction the value changes with the composition, while the and are constants. The value for 34B is also listed in Table 2, and the values for 67B and 100B are 12723.3163 eV and 12791.0362 eV, respectively.

Table 2. Atomic charges and Buckingham potential parameters (*Aij for 34B composition). Pair

A (eV)

ρ (Å)

C (eV Å6)

Si2.4-O-1.2

13702.9050

0.193817

54.681

B1.8-O-1.2

12701.0167* 0.171281

28.500

Na0.6-O-1.2

4383.7555

0.243838

30.700

Ca1.2-O-1.2

7747.1834

0.252623

93.109

P3.0-O-1.2

26655.4720

0.181968

86.856

O-1.2-O-1.2

2029.2204

0.343645

192.580

Compositions, densities, total number of atoms and cell sizes of the simulated structures are listed in Table 3, where 0B, 34B, 67B and 100B represent different molar percentages of boron substitution on silicon in the glass compositions.

Table 3. Compositions (mol%), experimental measured densities (g/cm3), total number of atoms and cell sizes (Å) of the simulated glasses. Composition (mol%)

Experimental

Sample B2O3 SiO2 Na2O CaO P2O5

density (g/cm3)

Total

Cell

number of

size

atoms

(Å)*

0B

0

46.1

24.4

26.9

2.6

2.69 ± 0.03

6002

43.11

34B

15.4

30.7

24.4

26.9

2.6

2.65 ± 0.03

6002

42.25

67B

30.7

15.4

24.4

26.9

2.6

2.54 ± 0.004

6000

41.86


9


100B

46.1

0

24.4

26.9

2.6

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2.51 ± 0.006

5999

41.17

*All simulation cells were in cubic shape.

The initial configurations were generated by randomly distributing atoms in a cubic simulation box with the experimental density. Three parallel tests for each composition were performed through a melt-quench process to form the final glass structures. The initial structures were first energy minimized at 0K to remove high energy configurations of the initial random structure, and then relaxed at 300 K under the canonical ensemble (with constant atom number, volume and temperature values (NVT)) for 60 picosecond (ps) each. The systems were melted at 6000 K for 60 ps, equilibrated at 5000 K for 100 ps, and then cooled down to 300 K with a cooling rate of 5 K/ps. The NVT ensemble was applied every 100 K during the cooling section. After the melt-quench process, the structures were relaxed at 300 K under the isothermal-isobaric ensemble (with constant atom number, pressure and temperature values (NPT)) for 100 ps followed with the NVT ensemble for 60 ps. The final structures were relaxed in the microcanonical ensemble (constant number, volume and energy (NVE)) for 60 ps in order to remove unreasonable structural features and inner stresses. The cutoff distance used for both short-range and long-range interactions were 10 Å, which were calculated using the Ewald summation with a relative precision of 1×10-6. Integration of the motion equations used is the Verlet Leapfrog algorithm with a timestep of 1 femtosecond (fs). Cutoff distances used in the coordination number (CN) calculations and bond angle distribution (BAD) analysis are presented in Table 4. The cutoff values were determined as the first minimum in the plots of partial correlation functions for certain pairs.

Table 4. Cutoff distances (Å) chosen for the coordination number calculation and the bond angle distribution analysis. Pair

Si-O

P-O

Na-O

Ca-O

B-O

Cutoff

2.25

2.25

3.34

3.14

1.85


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Pair

Si-Na

Si-Ca

B-Na/Ca

P-Na/Ca

Cutoff

4.42

4.37

4.40

4.44

Diffusion calculations were further investigated for the glass structures generated from the melt-quench process. The glasses were gradually heated from 300 K to 3700 K with intervals of 800, 940, 1040, 1140, 1240, 1340, 1450, 1750, 2000, 2500, 2700, 3000 and 3300 K. At each temperature, the glasses were first equilibrated for 60 ps under NVT ensemble and then run under NVE for 200 ps, within which the trajectory was recorded every 10 fs in the last 180 ps for diffusion analysis. The mean square displacements (MSDs) were calculated from these trajectories, where the self-diffusion coefficients were obtained using Einstein’s equation,

= !"→$

% & ' "

(2)

where < > is MSD and t is time. The diffusion activation energy barriers were then calculated from diffusion coefficient at different temperatures by taking the logarithm on Arrhenius equation,

= * +,-(

∆01 23

)

(3)

where Ea is the diffusion energy barrier, T is the temperature and R is the gas constant. Details of calculations can be found in a study by Ren and Du.65

3. Results 3.1 Density and glass transition temperature Measured densities of 0B, 34B, 67B and 100B glass (listed in Table 3), together with calculated molar volume and atomic packing factor (APF), are plotted in Figure 1, as a function of B2O3 concentration. APF was calculated according to a study by Rouxel,66 which provide more information on free volume in the glass for diffusion as compared to overall molar volume. Density of 45S5 (0B) is 2.69 ± 0.03 g/cm3, which is in good agreement with 2.7 g/cm3 measured using the Archimedes method.67 As seen in the figure, density showed a decrease trend with increasing boron oxide content. Glass


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density decreased ~6.7% from 0B to 100B, while molar volume increased ~13.8%. The increase of molar volume suggests a more opened overall glass structure with increasing B2O3 concentration. The decreased density partially caused by the diminished network modifiers per network former when SiO2 was replaced with equal mole of B2O3, which resulted in more network formers and fewer modifiers to fill the void in glass structure. This trend is also consistent with a study by Smedskjaer et al.68 and our previous study on B2O3 substitution on a SrO-containing bioactive glasses.23 APF increased ~8.9% from 0B to 100B, suggesting that free volume in the glass structure was reduced after B2O3 substitution. The molar volume and free volume analysis revealed that more voids were created but with a smaller size of these voids in the glass structures as a results of equal molar substitution of B2O3/SiO2. No mixed network former effect was observed in comparison with a study on B2O3/SiO2 substitution of a soda-lime borosilicate glass by Smedskjaer et al.,68 probably due to the high modifier contents and only four glass compositions investigated in this study.

Figure 1. Plot of density (a), molar volume (b) and atomic packing factor (APF) (c) as a function of B2O3 concentration in the glass system. Figure 2 shows the DSC analysis curves and measured glass transition temperature (Tg) for the bioactive glasses. The glass transition temperatures (Tg) (insert of Figure 2) show a decrease trend with boron oxide concentration. Tg decreased from 510 °C for 0B to 464 °C for 100B. For sodium silicate glasses with a higher silica content (24Na2O-


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76SiO2 in mol%), initial B2O3/SiO2 substitution first led to a significant increase of Tg at around 18 mol% of B2O3 and then Tg decreased almost linearly with further substitutions.32 In literature, Tg of 45S5 measured using differential thermal analysis (DTA) was 552 ± 3 °C with a heating rate of 15 °C/min,69 while Tg measured with a heating rate of 10 °C/min was 560 °C70 or 540 °C.71 Liang et al.36 analyzed Tg of a sodium calcium borate glass, which has the same composition with 100B, is 480 °C obtained by DTA at a heating rate of 10 °C/min. It was also found in literature that addition of B2O3 reduced the Tg of 45S5 (up to 4 mol% B2O3)18 and a Si-Ca-P glass system.72 The decreasing trend of Tg from 0B to 100B is consistent with the overall expansion of glass network; however, Tg is more complicatedly related to the structural changes. According to the temperature dependent constraint theory, glass transition temperature is related to numbers of bridging oxygen (BO), non-bridging oxygen (NBO), Qn distribution of each network former and numbers and strength of the modifying cation to NBO constraint.73

Figure 2. DSC curves of 0B, 34B, 67B and 100B samples. The inserted figure is a plot of glass transition temperature (Tg) as a function of B2O3 concentration.


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3.2 In vitro biomineralization test pH variations (measured at room temperature) of both SBF and K2HPO4 solution with 0B, 34B, 67B and 100B glass samples through the in vitro tests are shown in Figure 3. Generally, the evolution of pH values with treatment time can be an indication of the degree of degradation in a particular solution. The pH value of SBF with the 0B sample increased from 7.55 to 8.14 after 72 h and plateaued at this point. The final pH value of SBF decreased in a trend of 0B-34B-67B-100B, where 67B and 100B have a similar final pH value. Final pH values of all samples were higher than blank SBF reference, which indicates that the buffer capacity of SBF was not high enough to buffer the solution during the glass dissolution. On the contrary, pH of SBF did not change significantly for boron-containing glasses in the previous study of 55S4.3,23 which is probably due to the acidity of boron species formed in combined with buffer capacity of SBF, where the glass dissolution of boron-containing glasses was buffered by SBF. A similar trend of decreasing final pH value with increasing B2O3 content observed for in vitro test with K2HPO4 solution, except that the starting pH (9.10) was much higher than the SBF (7.55). This observation is consistent with a study by Huang et al.,19 where higher B2O3/SiO2 substitution ratio in 45S5 leads to a lower final pH value in a 0.02 M K2HPO4 solution. On the contrary, some studies showed that higher B2O3/SiO2 ratio in a silicate bioactive glass 13-93 led to a higher final pH value in both SBF13 and K2HPO4 solution.12 However, Li et al.74 found that only when the pH of the solution is carefully controlled, SBF could be used as a tool to study HAp formation and bioactivity in vitro. In their study, it was found that Ca/P molar ratio in precipitated calcium phosphates only becomes close to stoichiometric value of HAp (1.67), when the SBF was well buffered or the pH of SBF was adjusted everyday.74


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Figure 3. pH variations (measured at room temperature) of SBF (a) and K2HPO4 solution (b) with 0B, 34B, 67B and 100B glass samples, and a blank reference through the in vitro tests. XRD patterns of 0B, 34B, 67B and 100B glass powders before biomineralization tests are shown in Figure 4. There is an indication of crystallization of 34B and 67B glasses as compared to powder diffraction file of Na3Ca6(PO4)5 or hexagonal Na2Ca4(PO4)2SiO4, even though clear identification was not possible due to the large amount of amorphous material in the samples. XRD patterns of the commercial HAp powder, 0B, 34B, 67B and 100B powders after 3 weeks of SBF and K2HPO4 solution treatments are shown in Figure 5. HAp formed on the 0B sample after the SBF immersion, which was deduced by comparing with the commercial HAp powder. As for K2HPO4 solution treatment, HAp formed on both 0B and 34B samples after three weeks of immersion. No HAp formation was identified with XRD for 34B, 67B and 100B after SBF treatment, and 67B and 100B for K2HPO4 solution treatment.


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Figure 4. XRD patterns of 0B, 34B, 67B and 100B powders before in vitro treatments (a), XRD pattern of 67B compared with powder diffraction file (#00-011-0236) of Na3Ca6(PO4)5 (b), and compared with powder diffraction file (#00-033-1229) of hexagonal Na2Ca4(PO4)2SiO4 (c).

Figure 5. XRD patterns of the commercial HAp powder, 0B, 34B, 67B and 100B powders after 3 weeks of SBF (a) and K2HPO4 solution (b) treatments.

FTIR spectra of the commercial HAp powder, 0B and 34B glass powders with varied SBF and K2HPO4 solution treatment time are shown in Figure 6 and Figure 7,


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respectively. HAp formation was clearly identified after 72 h of SBF immersion and 24 h of K2HPO4 solution immersion for 0B glass. HAp was formed on 34B after 24 h of K2HPO4 solution treatment, while no HAp formation was observed after SBF treatment. No HAp formation was identified for 67B and 100B glass powders after both SBF and K2HPO4 solution treatments.

Figure 6. FTIR spectra of the commercial HAp powder and 0B glass powders treated with varied SBF (a) and K2HPO4 solution (b) immersion time.

Figure 7. FTIR spectra of the commercial HAp powder and 34B glass powders treated with varied SBF (a) and K2HPO4 solution (b) immersion time.


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Surface morphology of 0B, 34B, 67B and 100B glass powders after three weeks of SBF or K2HPO4 solution treatment are presented in Figure 8. Precipitates seemed to form on the glass surface in all compositions, whereas the morphology of the precipitates varied between SBF and K2HPO4 solution treatment. Precipitates of the glasses treated with SBF have a spherical feature in comparison with K2HPO4 solution treated samples. As confirmed with XRD and FTIR, HAp formed on the entire surface of 0B glass powder after three weeks of both SBF and K2HPO4 solution treatments. For 34B sample, HAp formation was identified with both XRD and FTIR after only K2HPO4 solution treatment, even though precipitates were observed with SEM for both SBF and K2HPO4 treatments. This might be a result of only small amount of precipitates or non-crystalline precipitates formed on the glass surface.


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Figure 8. SEM images of glass surface of 0B (a and e), 34B (b and f), 67B (c and g) and 100B (d and h) after three weeks of SBF (a, b, c and d) or K2HPO4 solution (e, f, g and h) treatments. 3.3 MD simulation results of the bioactive glasses In order to study local structure of cations, partial pair distribution function (PDF) and coordination number (CN) distribution were analyzed, and plots of PDF and CN for simulated 34B glass are presented in Figure 9 and Figure 10, respectively. Bond distances of Si-O, P-O, Na-O and Ca-O are around 1.60, 1.49, 2.40 and 2.39 Å, respectively. The PDF of B-O has a peak and a tail, which are contributed by 3-coordinated boron-oxygen ([3]B-O) pair at ~1.39 Å and 4-coordinated boron-oxygen ([4]B-O) pair at ~1.49 Å. No noticeable changes were observed on bond distance of cation-oxygen pairs with composition. Both Si and P are 4-coordinated with oxygen, while CN of B is slightly lower (3.2) due to the mixed of [3]B and [4]B. CNs of Na-O and Ca-O at the cutoff distances increase from 6.7 to 7.8 and 6.3 to 7.1 with increasing B2O3 concentration, respectively.

Figure 9. Partial pair distribution functions (PDFs) of B-O, Si-O, P-O, Na-O and Ca-O in simulated 34B glass. Numbers in parenthesis are the interatomic distances at the highest


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intensity with a standard deviation from three parallel tests. The inserted figure is a plot of PDFs of B-O, [3]B-O and [4]B-O.

Figure 10. Coordination numbers (CNs) of B-O, Si-O, P-O, Na-O and Ca-O in simulated 34B. Numbers in parenthesis are the CNs at cutoff distances. The inserted figure is a plot of the CNs of Na and Ca as a function of B2O3 concentration. Coordination number of network formers such as Si4+, B3+ and P5+ all show a plateau region on the accumulated coordination distribution (Figure 10) indicating well-defined first coordination shell. Both silicon and phosphorus have perfect 4-fold coordination of oxygen and remain unchanged with composition. The coordination number of boron is a mixture of [3]B and [4]B, with majority of boron ions are 3-fold coordinated. Average boron coordination numbers are found to be 3.21, 3.20 and 3.24 for 34B, 67B and 100B, respectively. These are close but slightly lower (less than 2%) than the average coordination predicted by the widely adopted Yun, Dell and Bray (YDB) model55,56: 3.14, 3.24 and 3.30 for the three compositions, respectively. These results indicate the empirical potential used in this work is capable to describe the mixed glass former situation in the bioactive glasses.


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The percentage of 4-coordinated boron (N4) is also considered as important structural information. N4 for 34B, 67B and 100B are 20.9 ± 0.6, 20.0 ± 1.1 and 23.8% ± 0.9% from the MD simulation, respectively. These numbers are less than 6% of difference as compared to YDB model,55,56 where N4 for 34B, 67B and 100B are 14, 24 and 30%, respectively. In a recent study by Yu et al.,60 N4 derived from NMR for 45S5 with 30%, 60% and 100% of SiO2 substituted by B2O3 are 29.5, 33.5 and 33.4%, respectively. The coordination of glass modifier cations (Na+ and Ca2+) around glass former cations reveals structure information of the distribution and segregation of the modifier cations. CNs of modifiers around former cations as a function of B2O3 concentration are plotted in Figure 11. CNs of Si-Na, Si-Ca, P-Na and P-Ca for 0B are 5.2, 3.0, 6.1 and 3.8, respectively, which is consistent with a previous MD study on 45S5 by Xiang and Du.47 CNs of B-Na, B-Ca, P-Na and P-Ca for 100B are 4.1, 2.3, 5.3 and 3.0, respectively. As shown in the figure, both CN of Na and Ca around each network former decrease with higher B2O3/SiO2 ratio, which might be caused by the increased number of network former to modifier ratio. Numbers of Ca ions around each former are lower as compared to Na due to the higher content of Na in each glass composition. In order to eliminate these compositional effects, preferential distributions of modifier cations around glass former cations were calculated according to a study by Tilocca et al.,75 :;?@AB@CD1 96>?@AB@CE1

6

× 6 E1

D1

(4)

where N is the number of modifier cations present. Preferential distributions for Na and Ca around B, Si and P are plotted in Figure 12. A ratio of R > 1 indicates the preference for Na, and vice versa. Si prefers Ca over Na as charge compensator in 0B, while Si prefer Na over Ca after boron was induced. On the other hand, P prefers Ca in all compositions with a highest tendency for 34B glasses. It is correlated with the crystallization tendency at initial boron substitution, which is promising of utilizing MD simulation to predict glass crystallization tendency.


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Figure 11. Coordination numbers (CNs) of glass former-modifier pairs at the cutoff distances as a function of B2O3 concentration.

Figure 12. Preferential distributions for Na and Ca around B, Si and P as a function of B2O3 concentration.


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Bond angle distributions (BADs) of O-B-O, O-Si-O and O-P-O were investigated, and plots of BADs for the simulated 34B glass are shown in Figure 13. Bond angle at the highest intensity of both O-Si-O and O-P-O are at ~109°, which is consistent with a MD study on 45S5 by Xiang and Du.47 There are two peaks for the BAD of O-B-O, which the highest intensity at ~120° is corresponded to O-[3]B-O and the other at ~110° is O-[4]B-O. No significant difference was observed in terms of bond angle between compositions.

Figure 13. Bond angle distributions (BADs) of O-B-O, O-Si-O and O-P-O in simulated 34B glass. Numbers in parenthesis are the bond angles at the highest intensity with a standard deviation from three parallel tests. Network connectivity is an indication of oxide glass bioactivity. Glasses with average network connectivity between 2 to 3 are shown to have bioactivity in silicate and phosphosilicate glasses. This rule, however, has not applied to borate containing glasses. Average network connectivity (NC) of each glass former atom and overall NC of each glass composition calculated from Qn distributions are listed in Table 5. In Qn distribution, n represents the number of bridging oxygen ions per silicon, boron or phosphorus polyhedron. Details of the calculations can be found in a study by Lu et al.23 As shown in the table, numbers of bridging oxygen around the three network former atoms increase with higher boron substitution, indicating an increased connection of network. The NCSi of 0B (45S5) is 2.16 ± 0.02 from MD simulation, which is close to the NC (2.11)


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calculated from composition.76 Snapshots of the simulated glass structures with polyhedron representation of the glass formers and zoomed in network linkages are shown in Figure 14.

Table 5. Average network connectivity (NC) of each glass former atom and overall NC of 0B, 34B, 67B and 100B from MD simulation. Network connectivity Sample NCSi

NCB

0B

2.16±0.02

-

34B

2.44±0.03 2.16±0.02 1.24±0.05 2.22±0.01

67B

2.64±0.02 2.33±0.04 1.28±0.03 2.32±0.02

100B

-

NCP

NCoverall

1.19±0.03 2.06±0.02

2.51±0.02 1.35±0.06 2.45±0.02


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Figure 14. Snapshots of simulated 0B (a), 34B (b), 67B (c) and 100B (d) glasses. Si, yellow polyhedra; B, blue polyhedra; O, grey balls; Na, purple crosses; Ca, green crosses; P, red balls. Ionic diffusion plays an important role in bioactivity and consists the first step of the mechanisms that led to the formation of hydroxyl apatite layers on the glass surface. Diffusion activation energy barriers of Ca and Na in simulated glasses in both low temperature (1040-1750K) and high temperature (2000-3700K) range were calculated based on diffusion coefficient at different temperatures using Arrhenius relationship. The results are listed in Table 6. Ea of Na for 0B in low temperature range is ~0.55 eV and ~0.62 eV in high temperature range, which is consistent with a previous MD simulation study by Du and Xiang.49 In low temperature range, Ea of Ca and Na in simulated glasses increase ~25% and ~31% with increasing B2O3/SiO2 substitution, while Ea of Ca and Na


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in higher temperature range decrease ~18% and ~8%, respectively. These results show that diffusion energy barriers of sodium (and calcium) increases with boron oxide concentration in the low temperature range, which is relevant to bioactivity at ambient temperature. High temperature diffusion energy barrier of Na and Ca, on the other hand, decrease with boron oxide concentration.

Table 6. Diffusion activation energy (Ea, eV) of Ca and Na in simulated 0B, 34B, 67B and 100B glasses calculated from MD simulation with a standard deviation obtained from three parallel tests. Low temperature

High temperature

Ea (eV) Ca

Na

Ca

Na

0B

0.79±0.07 0.55±0.02 0.87±0.02 0.62±0.02

34B

0.93±0.04 0.64±0.03 0.82±0.03 0.64±0.01

67B

0.91±0.02 0.67±0.03 0.78±0.01 0.59±0.01

100B

0.99±0.02 0.72±0.02 0.71±0.02 0.57±0.02

4. Discussions Glass network connectivity (NC) has been used as useful measure to predict dissolution and bioactivity of glasses.21,47,76,77 NC can be derived from theoretical calculation of glass composition,21,76 split network theory77 and from structure data from computer simulation.47 Due to the complication of mixed network formers in our glass compositions, it is challenging to calculate NC from composition for boron-containing glasses. In our MD simulation results, the NCSi of 0B (45S5) is 2.16 ± 0.02, which is close to the NC (2.11) calculated from composition.76 Both theoretical composition and split network theory calculation concluded that bioactive glasses have network connectivity between 2 to 3, and glasses with high NC normally display low bioactivity.76,77 The NC increases from 2.11 for 0B to 2.45 for 100B and the bioactivity decreased in vitro with higher B2O3/SiO2 substitution in our study, which is consistent


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with the relationship between NC and bioactivity concluded from literature. However, as compared to the previous study of 55S4.3,23 glass without boron substitution (55S4.3_0B) exhibited higher bioactivity in vitro than 45S5_100B in this study under the same experimental condition, even though NC of 55S4.3_0B (2.59) is higher than 45S5_100B (2.54). The use of NC to predict bioactivity of glass is complicated by systems with multiple network formers, owing to their different hydrolysis or reaction rates. For instance, from the percentage of N4 obtained from MD, N4 slightly increases from 20.9 ± 0.6 to 23.8% ± 0.9% from 34B to 100B. This trend is consistent with both YDB model55,56 and NMR data.24 In our previous study, N4 values of 55S4.3 series with boron oxide substitution are about 40% for all compositions.23 The higher cross-linked [4]B and its slower hydrolysis rate as compared to [3]B,24,78 the increased N4 might partially contributed for a more durable glass. One of the other reasons for the delayed HAp formation with increasing boron oxide concentration in vitro is the role of amorphous silica gel layer on bioactivity. After in contact with body fluid environment, silicate bioactive glass surfaces become rich in SiOH groups after dissolution alkali (and borate in the compositions in this study) species through ion exchange, and these silanol group polymerize to form porous silica gel layer which is believed to provide nucleation sites for hydroxyl apatite formation.37,38 Another reason for the inhibited HAp formation for boron-containing glasses might be due to the protection/passivating effects from the alteration layer. Generally, boron is among the first components to be leached into solution, which makes it a good species for analyzing dissolution properties of glasses.83 In this case, boron content results in a higher initial dissolution and leaving with a depleted and hydrated silica rich alteration layer to passivate the glass surface to prevent further dissolution of glasses.84,85 As for borate glasses, missing of Si-OH groups might delay the nucleation and formation of apatite. However, there are a number of studies that have shown glasses without Si can also form HAp in vitro;12,22,79–82 therefore, further understanding of nucleation mechanism of HAp for borate glasses is thus needed. The different morphology of precipitates observed from SEM can be related to the pH variations of solutions (when immersed in the same type of solution). For instance, the spherical precipitates formed on the surface of 34B sample is similar in size and shape


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with the previous 55S4.3 study, where the final pH value of SBF was 7.87 for 34B in our study and 7.82 for 55S4.3_0B in previous.23 No spherical precipitates were observed for K2HPO4 treated samples, which might be a result of the high starting pH value (9.1). Hence, sufficient buffer capacity of SBF to accommodate dissolved ions or a welladjusted pH is essential for study the bioactivity and HAp formation in vitro. Additionally, various factors such as glass composition, solution preparation, solution replenishment, glass mass/glass surface area to solution volume, etc., can alter the bioactivity tested in vitro, interpretation of glass dissolution and HAp formation mechanism, which were already discussed/summarized in previous studies.23,32 Therefore, following an ISO standard or a unified evaluation procedural such as the proposal from Macon et al.33 would greatly benefit the comparison between studies. In our diffusion analysis from MD simulation, self-diffusion activation energy barriers exhibit two opposite trends, where Ea of each ion increases with higher B2O3/SiO2 substitution in low temperature range and decreases in high temperature range. This two-range or non-Arrhenius behavior of ion diffusion has been observed with both experimental study86 and simulation study49 on 45S5. The separation of the two ranges is the glass transition temperature. Above glass transition temperature, glasses behave similarly with liquid and inducing boron oxide lowered melting temperature, which is in agreement with the decreased Ea trend in high temperature range. In contrast, glasses behave as a solid below glass transition temperature, where cations diffuse mostly by hopping through interstitial sites. In our case, the increased Ea trend in low temperature range is mainly caused by the increased NC of glasses and decreased free volume, even though the overall molar volume increases with higher B2O3/SiO2 substitution. This phenomenon was also observed by Smedskjaer et al.,68 glass becomes more tightly packed with decreasing SiO2/(SiO2+B2O3), which leads to lowered diffusivities measured experimentally, while the molar volume is increasing. It suggests that diffusivity is more affected by the free volume in the network structure than the overall molar volume of the glass.68 Lastly, it should be pointed out that in the glass compositions studied, SiO2 was substituted with equal mole of B2O3 in this study, which was often chosen for study substitution effect of SiO2/B2O3 in literature.12,13,24,32,60,68,87 In this case, one extra boron


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and one oxygen are induced after SiO2/B2O3 substitution, resulting in fewer modifier atoms per network former. Thus, Ca and Na atoms act as charge compensators for Si and B, instead of creating non-bridging oxygen, which lead to the increased NC of glass. The fewer modifier atoms per network former corresponds to the decreased density and the expanded overall molar volume, while increased NC of glasses correlates to the decreased free volume and increased Ea of self-diffusion of Na and Ca at low temperature. In vitro bioactivity of glasses is more complicatedly related to structural features, due to the influences from solution chemistry of SBF, complexities from glass dissolution and uncertainty of HAp formation mechanism for borate glasses. The delayed HAp formation in vitro with high B2O3-containing glasses might be caused by the increased NC, decreased Ca diffusion, passivating effect from alteration layer or reduced Si-OH groups for nucleation of HAp. Future study of SiO2/BO3/2 substitution is suggested for study the mixed network former effect on structure, physical properties and bioactivity of glasses with both experiments and MD simulations.

5. Conclusions A series of B2O3/SiO2-substituded 45S5 bioactive glasses have been studied by combining experimental and MD based computer simulation investigations. It was found that glass density decreases while molar volume increases with increasing B2O3/SiO2 ratio; atomic packing factor, at the same time, increases, indicating a decrease of free volume. Glass transition temperature decreases almost linearly with increasing B2O3/SiO2 substitution, suggesting no mixed network former effect for the compositions studied. Formation of hydroxyapatite was observed on the glass surfaces of all compositions after 3 weeks of in vitro biomineralization tests in two kinds of solutions, but the glasses with higher boron oxide were slower and took longer to form HAp. Different morphologies of HAp were also observed between SBF and K2HPO4 solution treatments, which was probably due to the different final/stable pH values of the two solutions reached during the in vitro evaluation. Overall network connectivity obtained from MD simulations increased with increasing boron oxide content: from 2.06 for 45S5 to 2.45 for its pure borate glass. The increase of network connectivity with boron oxide concentration is at least partially responsible for the delayed HAp formation in vitro after inducing boron.


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Furthermore, low temperature alkali diffusion energy barriers also increase with boron oxide concentration, which can also contributed to less bioactivity of the borate containing glasses. Both Na and Ca were found to be effective for charge compensation of [4]B. Phosphorous, on the other hand, prefers Ca in all compositions. Overall, combining experimental studies and MD simulations is very effective and promising to systematically investigate the relationship between glass structure and bioactivity, as well as to understand the structural origin of properties such as density, glass transition temperature in complex glass compositions. This integrated approach can be highly valuable in designing next generation bioactive glasses.

Acknowledgments We gratefully acknowledge financial support by National Science Foundation (NSF) (project # 1508001). SEM, XRD and FTIR experiments were conducted at the Materials Research Facility (MRF), a shared research facility for multidimensional fabrication and characterization at University of North Texas (UNT). Computer simulations were performed on UNT Talon 2 high-performance computer (HPC) cluster. We also would like to acknowledge Dr. Bharat Gwalani for the help with the FEI Nova NanoSEM 230.

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Mixed Network Former Effect on Structure, Physical Properties and

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