Surface Stability and Morphology of Calcium Phosphate Tuned by pH Values and Lactic Acid Additives: Theoretical and Experimental Study

Abstract

The ubiquitous mineralization of calcium phosphate (CaP) facilitates biological organisms to produce hierarchically structured minerals. The coordination number and strength of Ca 2+ ions with phosphate species, oxygen-containing additives, and solvent molecules played a crucial role in tuning nucleation processes and surface stability of CaP under the simulated body fluid (SBF) or aqueous solutions upon the addition of oligomeric lactic acid (LACn, n=1, 8) and changing pH values. As revealed by ab initio molecular dynamics (AIMD), density functional theory (DFT), and molecular dynamics (MD) simulations as well as high-throughput experimentation (HTE), the binding of LAC molecules with Ca 2+ ions and phosphate species could stabilize both pre-nucleation clusters and brushite (DCPD, CaHPO4• 2H2O) surface through intermolecular electrostatic and hydrogen bonding interactions. When the concentration of Ca 2+ ions ([Ca 2+ ]) is very low, the amount of the formed precipitation decreased with the addition of LAC based on UV-Vis spectroscopic analysis due to the reduced chance for the LAC capped Ca 2+ ions to coordinate with phosphates and the increased solubility in acid solution. With the increasing [Ca 2+ ] concentration, the kinetically stable DCPD precipitation was obtained with high Ca 2+ coordination number and low surface energy. Morphologies of DCPD precipitation are in plate, needle, or rod, depending on the initial pH values that tuned by adding NH3•H 2O, HCl, or CH3COOH. The prepared samples at pH ≈ 7.4 with different Ca/P ratios exhibited negative zeta potential values, which were correlated with the surface electrostatic potential distributions and potential biological applications.3 INTRODUCTIONBones and teeth of vertebrates are known to come from mineralization of calcium phosphate (CaP) 1 through two possible nucleation processes, i.e., a classical aggregation or a two-step nucleation pathway. 2 The real nucleation process of CaP in biological conditions becomes much more complicated, attracting extensive interest both experimentally and theoretically.The first factor in controlling nucleation process of CaP is the pH value, which could affect the occurrence of different phosphate species, such as H3PO4 (called 3H for short), H2PO4 -(2H), HPO4 2-(1H), and PO4 3-(0H), shown in Figure 1a. Thus, properties of CaP precipitation, 3, 4 adsorption of organic acid 5 , phase composition 6 , morphology 7, 8 , zeta potentials [9][10][11][12] , and crystal size of CaP 13 could be varied with different pH values.Secondly, through the modulation of interfacial interaction and kinetic stability, the introduction of many kinds of additives, such as metal ions, acid or basic solutions, amino acids, dopamine, and citrate, could change the nucleation or phase transformation paths and morphologies 8, 14-19 . Starting from the ion pair CaHPO4 in a neutral or basic CaP solution, a Ca-deficient pre-nucleation cluster, Ca(HPO4)3 4-, is formed at the early stage of nucleation process. [20][21][22][23][24] Subsequently, those sm...

In Situ Fluorescence Probing of the Formation of Calcium Phosphate Prenucleation Clusters

“…In this PAA-simulating system, after adding HPO 4 2− to the pre-PNCs, the system pH displays a dependence on HPO 4 2− , favoring the bonding with Ca 2+ to form PNCs (Figure 6d−h). 33 In addition, MDS profiles obtained at 300, 310, and 353 K (Figure S11) display that the formation of PNCs is endothermic, and the increase of temperature promotes the formation. Accordingly, the MDS study supports the PNC formation character revealed by the in situ Eu 3+ fluorescence probe.…”

“…pH variation studies: At 300 K and a pressure of 1 atm, the respective concentrations of Ca 2+ and HPO 4 2− were 0.18 M and 75 mmol, with PAA containing 25 repeat units (25 e − ), and the type of phosphate species was altered to generate conditions equivalent to pH values of 7.0, 9.0, or 13.0 (Table S2). 33 All MDSs employed the AMBER/general AMBER force field. 34−36 In the cubic simulation unit with an initial size of 10 nm, the step change was set to 1 fs, and all simulations were run for 50 ns in real time using Gromacs (University of Groningen, Groningen, The Netherlands).…”

Molecular dynamic simulation of prenucleation of apatite at a type I collagen template: ion association and mineralization control

“…In order to get complete understanding the roles of HPO 4 2À in the first stage of the apatite nucleation, more work on the collagen fibril model should be conducted. Interestingly, in a recent theoretical and experimental study on the mineralisation of calcium phosphate using the oligomeric lactic acid as the template material, Chen et al 74 observed the kinetic stable brushite (CaHPO 4 ÁH 2 O) can be stabilised by lactic acid. Furthermore, the increasing of concentration of calcium ions can largely promote the cluster growth and crystallisation.…”

Discovery of Electronic Structure and Interfacial Interaction Features in Catalytic Activity

“…53 Moreover, highthroughput calculations and experiments are effective in studying the different aspects of materials science while efficiently providing a large amount data. 54 Combined with rich databases, accessible features, and automatic search programs, researchers can build virtual laboratories to accelerate catalyst discovery with the assistance of machine-learning approaches.…”

“…The stochastic surface walking (SSW) proposed by Liu et al could explore the potential energy surface to investigate the significant structures along reaction pathways in catalytic systems and the metal–support interaction. ,, A combined molecular dynamics and coordinate driving (MD/CD) method could search the reaction pathways automatically . Moreover, high-throughput calculations and experiments are effective in studying the different aspects of materials science while efficiently providing a large amount data . Combined with rich databases, accessible features, and automatic search programs, researchers can build virtual laboratories to accelerate catalyst discovery with the assistance of machine-learning approaches.…”