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Rapid Mix Preparation of Bioinspired Nanoscale Hydroxyapatite for Biomedical Applications

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Understanding zinc-doped hydroxyapatite structures using first-principles calculations and convolutional neural

Jing Wang¹, Ruihan Wang¹, Mingli Yang²

¹MOE Key Laboratory of Green Chemistry and Technology, College of Chemistry, Sichuan University, Chengdu, Sichuan, 610064, P. R. China. dgxu@scu.edu.cn.

Journal of Materials Chemistry. B

|February 8, 2022

Summary

This summary is machine-generated.

Element doping enhances material properties, but dopant structures are challenging to determine. This study used computational methods to reveal how zinc (Zn²⁺) doping improves hydroxyapatite (HAP) mechanical strength.

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Area of Science:

Materials Science
Computational Chemistry
Crystallography

Background:

Element doping is crucial for tailoring material properties.
Determining dopant crystallographic structures is essential for effective material design.
Existing methods struggle with precise dopant site identification in complex lattices.

Purpose of the Study:

To elucidate the doping mechanism of Zn²⁺ in hydroxyapatite (HAP).
To develop a computational approach for identifying optimal dopant structures.
To evaluate the impact of Zn²⁺ doping on HAP's mechanical properties.

Main Methods:

Combined first-principles calculations with machine learning (ML) algorithms.
Utilized ML to locate low-energy dopant configurations.
Performed uniaxial stretching simulations on ML-optimized structures.

Main Results:

Identified preferential occupation of Ca(II) sites by Zn²⁺.
Revealed symmetrical incorporation of subsequent Zn atoms to minimize strain.
Computational results align with experimental findings on enhanced fracture toughness.

Conclusions:

The developed computational approach effectively predicts optimal dopant structures.
Zn²⁺ doping enhances the mechanical properties of HAP.
This work offers a pathway for advanced materials design through doping.