Proper mechanical properties are essential for the clinical application of magnesium-based implants. In the present work, a novel multilayer model composed of three layers with desirable features was developed. The modulus of the multilayer model can be adjusted by changing the thickness of each layer. To combine three layers and improve the corrosion resistance of the whole multilayer model, the polycaprolactone coating was employed. In the immersion test, pH values, the concentration of released magnesium ions, and weight loss indicate that the corrosion rate of multilayer models is considerable lower than that of the one-layer bare substrate. The three-point bending test, which is used to examine models' mechanical properties, shows that the flexural modulus of multilayer models is reduced effectively. In addition, the mechanical degradation of multilayer models is more stable, compared to the one-layer substrate.
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http://dx.doi.org/10.1007/s10856-015-5504-5 | DOI Listing |
Heliyon
January 2025
Department of Mathematics, University of Dhaka, Dhaka 1000, Bangladesh.
This study analyzes the influences of surface reactions on the natural convective flow, temperature, and oxygen concentration distributions in vertically placed multilayered cavities. A mathematical model for this problem is formulated with proper boundary conditions. At first, the governing equations are made dimensionless using the variable transformations.
View Article and Find Full Text PDFSmall
January 2025
Department of Precision Instrument, Tsinghua University, Beijing, 100084, China.
The rapid development of flexible electronics necessitates simplified processes that integrate heterogeneous materials and structures. In this study, laser engraving is combined with electrochemical deposition (ECD) to directly fabricate various micro/nano-structured components and flexible electronic circuits. A theoretical framework and simulation model are developed to design the on-demand ECD on laser induced graphene (LIG), enabling the generation of multi-scale copper (Cu) materials with controllable oxidation states.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital of Capital Medical University, Beijing, 101100, China.
Background: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experimental techniques for identifying SM-miRNA associations highlight the necessity for efficient computational methodologies in this field.
Results: In this study, we proposed a deep learning method called Multi-source Data Fusion and Graph Neural Networks for Small Molecule-MiRNA Association (MDFGNN-SMMA) to predict potential SM-miRNA associations.
Sci Rep
January 2025
School of Chemical, Petroleum and Gas Engineering, Iran University of Science and Technology, P.O. Box: 16765-163, Tehran, Iran.
In this study, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were developed to estimate the equilibrium solubility and partial pressure of CO in blended aqueous solutions of diisopropanolamine (DIPA) and 2-amino-2-methylpropanol (AMP). In this study, several key parameters were analyzed to understand the behavior of the aqueous DIPA/AMP system for CO capture. Including DIPA (9-21 wt%), AMP (9-21 wt%), temperature (323.
View Article and Find Full Text PDFEnvironmental degradation due to the rapid increase in CO₂ emissions is a pressing global challenge, necessitating innovative solutions for accurate prediction and policy development. Machine learning (ML) techniques offer a robust approach to modeling complex relationships between various factors influencing emissions. Furthermore, ML models can learn and interpret the significance of each factor's contribution to the rise of CO.
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