SYNTHESIS AND STUDY OF THE STRUCTURE OF BIOACTIVE MAGNESIUM SILICATE NANOPARTICLES
This paper presents the results of a study of bioactive magnesium silicate nanoparticles. The nanoparticles themselves were obtained by chemical precipitation in an aqueous medium. The size and shape of the samples were examined on a TEM microscope. It is established that objects of detection by aggregates are detected. In turn, the aggregates consist of spherical magnesium silicate nanoparticles with sizes from 10 to 20 nm. At the next stage, with the help of neural network processing of experimental data, the synthesis of nanoparticles was optimized. Analysis of the obtained ternary surface showed that to obtain samples with the smallest aggregate size (700 nm), the synthesis parameters are: temperature – 50 °C, stirring speed – 600 rpm, precursor concentration – 0.5 mol/l. Having determined the optimal parameters for the synthesis of magnesium silicate, computer quantum chemical modeling was carried out. As a result of calculations, it was found that the energy of the configuration was E = –709.302 kcal/mol, the value of chemical hardness η = 0.191 eV, and softness – S = 2.62 eV–1. Based on the data obtained, it can be concluded that MgSiO3 has a high stability and is characterized as a relatively soft molecule. At the final stage of the work, the samples were examined on an IR spectrometer. An analysis of the IR spectrum showed the presence of characteristic absorption bands, which correspond to bond vibrations in the MgSiO3 molecule.
Recently, the field of biocompatible materials necessary to accelerate bone tissue regeneration has been actively developed in medicine [1–4]. One of the promising areas of this industry is the development of various bone cements. Bone cements are materials that are used to fill bone defects in order to restore bone integrity and functionality. They offer a number of advantages, such as high bactericidal resistance, possibility of precise application and bone formation, and possibility of shorter healing times. There are many types of bone cements, including ceramic, polymeric and hydrogel cements. Ceramic bone cements such as hydroxyapatite and tricalcium phosphate with inclusions of magnesium and zinc silicate nanoparticles are highly bioactive and have an optimal resorption rate, which makes them particularly attractive for medical use [5–7]. For example, polymeric bone cements, polyacrylonitrile and polymethyl methacrylate, have improved strength and durability, but have higher toxicity and risk of causing allergic reactions [8]. Despite some disadvantages and risks, bone cements will be an important tool in the treatment of bone defects for a long time [9].
There are also many promising studies on new materials development based on nanoscale forms of mineral components for bone osteogenesis [10–15]. These materials are more effective and safer due to their unique physicochemical and biomedical properties. Numerous researchers have established influence of methods for preparation of bone cements with nanoparticles using ultrasound or introduction of additives in the mixing of components and formation of the suspensions themselves [16, 17].
In general, bone cements based on phosphate-silicate nanocomposite matrices of calcium, zinc and magnesium represent an important class of biomaterials for treatment of bone defects, which have many advantages and have been used in clinical practice for many years. Based on the presented data on the topical application of such material as MgSiO3 in regenerative medicine, the aim of the work was the synthesis and study of the bioactive magnesium silicate nanoparticles structure.
RESEARCH METHODS
Magnesium silicate nanoparticles were produced by chemical precipitation in aqueous medium at room temperature. The synthesis scheme is shown in Fig.1.
Magnesium acetate was used as magnesium precursor and sodium metasilicate as precipitant. In the first step sodium metasilicate and magnesium-containing precursor solutions were prepared with a concentration of 0.8 M. Then, a solution of the magnesium-containing precursor was added to the sodium metasilicate solution. The resulting sols were washed by centrifugation. Then, the washed sediments were dried in the desiccator at 80 °C.
Optimization of the synthesis technique for magnesium silicate nanoparticles was carried out using planning matrix and neural network selection of mathematical models. The multifactorial experiment allows us to consider influence of various factors (variables) on the average hydrodynamic radius of the obtained samples. As input parameters we chose: temperature, stirring speed and precursor concentration. The levels of variation are shown in Table 1. The precipitant was taken in stoichiometric quantities.
In order to study mutual influence of all factors with a minimum number of experiments, a planning matrix of 9 experiments was generated (Table 2).
With the help of mathematical processing of the experimental data obtained in the Neural Statistica Network application package formed a neural network with a given mathematical model. Based on the generated mathematical model, a ternary surface describing mutual influence of the synthesis technological parameters on the average hydrodynamic radius of nanoparticles was obtained.
Average hydrodynamic radius of obtained magnesium silicate samples was studied by dynamic light scattering on Photocor-Complex spectrometer (Antek-97, Moscow, Russian Federation). Computer processing of the obtained experimental results was carried out using DynaLS computer software.
The shape and size of the particles were studied by transmission electron microscopy on a Tecnai G2 30F STWIN STEM instrument (FEI Company, Hillsborough, USA).
The functional groups in dried samples of magnesium silicate nanoparticles were studied by Fourier transform infrared spectroscopy on FSM-1201 infrared spectrometer (INFRASPEK, St. Petersburg, Russia).
Computer quantum chemical modeling of magnesium silicate nanoparticles was performed in QChem application package using IQmol molecular editor. Quantum-chemical parameters were calculated using the equipment of the data processing centre (Schneider Electric) of the North Caucasian Federal University.
Mathematical processing of the experimental data was performed using the application programs OriginPro 2021 and STATISTICA 12.
RESULTS
In the first stage, the magnesium silicate nanoparticle samples were examined by PEM microscopy. The results are shown in Fig.2.
Thus, during the examination of magnesium silicate nanoparticles PEM-micrographs were obtained in dark-field mode, characterizing the shape and size of the particles.
The synthesis of magnesium silicate nanoparticles was further optimised. By means of neural network processing and machine learning we obtained mathematical model describing mutual influence of synthesis process parameters on average radius of copper silicate nanoparticles. Based on the generated mathematical model, a ternary surface was formed, which is shown in Fig.3.
The analysis of the data obtained showed that two areas can be distinguished in the ternary surface: with the largest and smallest average particle radius.
In the next step, quantum-chemical computer simulation of magnesium silicate nanoparticles was carried out. The results are shown in Fig.4.
Thus, computer quantum-chemical simulations yielded a model of the molecular complex, electron density distribution, as well as models of the higher populated molecular orbital and the lower free molecular orbital.
In the following step, the samples were examined by infrared spectroscopy. The IR spectrum of magnesium silicate nanoparticles is shown in Fig.5.
The analysis of the results showed that the IR spectrum of magnesium silicate nanoparticles shows bands characteristic of bond vibrations in the MgSiO3 molecule.
DISCUSSION
The analysis of the PEM microscopy results showed that particle structure is represented by large aggregates with sizes ranging from 150 nm to 2 μm. In turn, these aggregates consist of magnesium silicate nanospheres with diameters ranging from 10 to 20 nm.
After studying dispersion characteristics of magnesium silicate nanoparticles we analyzed obtained ternary surface, which is shown in Fig.3. It was found that the smallest radius (700 nm) have samples that were obtained at the following parameters: synthesis temperature – 50 °C, stirring speed – 600 rpm, the precursor concentration – 0.5 mol/l. In turn, the results of sample study by dynamic light scattering showed the average size of aggregates consisting of nanoparticles of spherical shape. This fact was confirmed by the transmission electron microscopy results.
Having determined the optimal synthesis parameters, computer quantum-chemical simulations of magnesium silicate particles themselves were performed. The calculations showed that configuration energy was E = –709.302 kcal/mol, EHOMO = –0.396 eV, ELUMO = –0.015 eV. From these data we calculated chemical stiffness of the molecule which was equal to η = 0.191 eV. This fact indicates the stability of the molecular complex as η > 0.1 eV and the relative softness of the molecule as S = 2.62 eV–1.
After studying the quantum-chemical values, the obtained samples were examined by infrared spectroscopy. IR spectrum analysis of magnesium silicate nanoparticles showed presence of intense bands of strain vibrations of the following bonds: at 500 to 1800 cm–1; the region at 532 to 677 cm–1 corresponds to metal-oxygen vibrations of the magnesium Mg–O bond, at 829 and 896 cm–1 to symmetrical vibrations of the O–Si–O bond, the region at 974 to 1118 cm–1 corresponds to vibrations of the Si–O bond, at 1327 and 1382 cm–1 to vibrations of the Si–O–Si bond, the band at 1510 and the region 1633–1672 cm–1 correspond to vibrations of the Si–O bond. Thus, it can be concluded that in infrared spectrum one observes characteristic absorption bands which correspond to bond vibrations in the MgSiO3 molecule.
CONCLUSIONS
Thus, magnesium silicate nanoparticles were obtained in this work. The size and shape of the obtained particles were investigated by PEM microscopy. The analysis of obtained results showed that the samples surface is represented by large aggregates. In turn, the aggregates consist of spherical magnesium silicate nanoparticles with sizes ranging from 10 to 20 nm.
The next step was to optimise nanoparticle synthesis. Using neural network processing of experimental data and machine learning, a ternary surface describing mutual influence of the synthesis process parameters on the average particle radius was obtained. The size was determined by dynamic light scattering. It was found that the optimal synthesis parameters of magnesium silicate nanoparticles are: synthesis temperature – 50 °C, stirring speed – 600 rpm, and precursor concentration – 0.5 mol/l.
Further quantum-chemical computer simulations of magnesium silicate particles were performed. As a result of calculations, a model of molecular complex with electron density distribution, EHOMO and ELUMO was obtained. It was found that configuration energy was E = –709.302 kcal/mol, the chemical stiffness value η = 0.191 eV and softness value S = 2.62 eV–1. Thus, it can be concluded that MgSiO3 has high stability and is characterized as a relatively soft molecule.
In the final stage of the work, the nanoparticle samples were examined by infrared spectroscopy. The results showed that in the infrared spectrum of the particles characteristic absorption bands were observed, which correspond to bond vibrations in the MgSiO3 molecule.
ACKNOWLEDGMENTS
This work was carried out with the financial support of the Grants Council of the President of the Russian Federation (project SP-476.2022.4).
PEER REVIEW INFO
Editorial board thanks the anonymous reviewer(s) for their contribution to the peer review of this work. It is also grateful for their consent to publish papers on the journal’s website and SEL eLibrary eLIBRARY.RU.
Declaration of Competing Interest. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.