Machine Learning Prediction of the Corrosion Rate of Zinc-Based Alloys Containing Copper, Lithium, Magnesium, and Silver DOI
Artur R. Davletshin, Elena A. Korznikova, Andrey A. Kistanov

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: unknown, P. 114 - 122

Published: Dec. 20, 2024

Implementation of machine learning (ML) techniques in materials science often requires large data sets. However, a proper choice features and regression methods allows the construction accurate ML models able to work with relatively small set. In this work, an extensive, although still limited, experimental set corrosion-related properties Zn-based alloys used biomedicine was created. On basis set, robust model built predict corrosion behavior alloys. This highlights effectiveness for assessing alloys, which can facilitate their application bioimplants.

Language: Английский

Corrosion Mechanism of Press-Hardened Steel with Aluminum-Silicon Coating in Controlled Atmospheric Conditions DOI Creative Commons
Nikola Macháčková, Darya Rudomilova, Tomáš Prošek

et al.

Metals, Journal Year: 2025, Volume and Issue: 15(1), P. 97 - 97

Published: Jan. 20, 2025

The effect of various atmospheric parameters on the corrosion mechanism press-hardened steel (PHS) coated with Al-Si (AS) was studied. Quantitative models composition soluble and stable products were developed. A high chloride concentration led to a localized due presence cracks in coating. Increased resistance silicon-rich Al8Fe2Si AlFe at expense Al5Fe2 phase low silicon content shown. Under low-chloride-deposition conditions, coating exhibited good provided sufficient protection underlying steel. formation more local anodes cathodes under conditions lower relative humidity reduction depth pits substrate. Constant sulphate deposits surface critical for acceleration cracks.

Language: Английский

Citations

0
Additively manufactured biodegradable Zn-Mn-based implants with an unprecedented balance of strength and ductility DOI

Chengcong Huang,

Wang Yizhu, Fan Yang

et al.

Acta Biomaterialia, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Atomic-scale study of lattice distortion and oxygen-rich environment impact on the surface degradation dynamics of zinc-based alloys DOI
V. A. Bryzgalov, Andrey A. Kistanov, Artem A. Izosimov

et al.

Computational Materials Science, Journal Year: 2025, Volume and Issue: 252, P. 113797 - 113797

Published: March 3, 2025

Language: Английский

Citations

0
Density Functional Theory-Based Indicators to Estimate the Corrosion Potentials of Zinc Alloys in Chlorine-, Oxidizing-, and Sulfur-Harsh Environments DOI Creative Commons

Azamat Mukhametov,

Insaf Samikov,

Elena A. Korznikova

et al.

Molecules, Journal Year: 2024, Volume and Issue: 29(16), P. 3790 - 3790

Published: Aug. 10, 2024

Nowadays, biodegradable metals and alloys, as well their corrosion behavior, are of particular interest. The process alloys under various harsh conditions can be studied via the investigation atom adsorption on metal surfaces. This performed using density functional theory-based simulations. Importantly, comprehensive analytical data obtained in simulations including parameters such energy, amount charge transferred, atomic coordinates, etc., utilized machine learning models to predict ability, catalytic activity, alloys. In this work, indicators Zn surfaces Cl-, S-, O-rich environments collected. A dataset containing height, partial states, work function values, electronic charges individual atoms is presented. addition, based these descriptors, it found that a Cl-rich environment less harmful for different compared an environment, more S-rich environment.

Language: Английский

Citations

3
Introduction to Biodegradable Metals DOI
VP Muhammad Rabeeh,

T. Hanas

SpringerBriefs in materials, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 1, 2025

Language: Английский

Citations

0
Research advances and future perspectives of zinc-based biomaterials for additive manufacturing DOI

Kun-Shan Yuan,

Chengchen Deng,

Xiang-Xiu Wang

et al.

Rare Metals, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Language: Английский

Citations

0
Spray-synthesized organic composite/hydroxyapatite coating on magnesium alloys with enhanced corrosion resistance DOI Creative Commons
Guoqiang Wang, Yi Wei,

Jinquan Hong

et al.

Frontiers in Chemistry, Journal Year: 2025, Volume and Issue: 13

Published: April 2, 2025

The development and production of anti-corrosive coatings are critical for medical implants, particularly those that utilize composite made from both flexible organic materials rigid inorganic materials, which exhibit advantageous mechanical properties resistance to corrosion. In this work, an composite/hydroxyapatite (HA) coating on magnesium alloys is fabricated through a two-step process, involves the application spray technique silica [polyethyleneimine (PEI)/silica sol (Si)], followed by hydrothermal treatment deposit hydroxyapatite. dense tight layer-by-layer assembly PEI/Si/HA Mg substrate exhibited corrosion current density 10-5.6 A/cm2, significantly lower than HA substrate. After immersion 13 days, demonstrated minimal amount H2 generation negligible fluctuations in pH within solution. Meanwhile, weaker synthesized using method. Both electrochemical dynamic data structural characteristics demonstrate enhanced coatings, polymer chains provided more volume as buffer molecules. This huge potential applications orthopedics.

Language: Английский

Citations

0
Machine Learning Prediction of the Corrosion Rate of Zinc-Based Alloys Containing Copper, Lithium, Magnesium, and Silver DOI
Artur R. Davletshin, Elena A. Korznikova, Andrey A. Kistanov

et al.

The Journal of Physical Chemistry Letters, Journal Year: 2024, Volume and Issue: unknown, P. 114 - 122

Published: Dec. 20, 2024

Implementation of machine learning (ML) techniques in materials science often requires large data sets. However, a proper choice features and regression methods allows the construction accurate ML models able to work with relatively small set. In this work, an extensive, although still limited, experimental set corrosion-related properties Zn-based alloys used biomedicine was created. On basis set, robust model built predict corrosion behavior alloys. This highlights effectiveness for assessing alloys, which can facilitate their application bioimplants.

Language: Английский

Citations

2