[HTML][HTML] Exploring the potential of nano technology: A assessment of nano-scale multi-layered-composite coatings for cutting tool performance
Abstract Nano-scale Multi-layered Composite Coatings (Nano scale MLCC) offer potential
benefits for cutting tool performance. Such coatings can be designed to improve tool …
benefits for cutting tool performance. Such coatings can be designed to improve tool …
[HTML][HTML] Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies
M Kambara, S Kawaguchi, HJ Lee… - Japanese Journal of …, 2022 - iopscience.iop.org
Low-temperature plasma-processing technologies are essential for material synthesis and
device fabrication. Not only the utilization but also the development of plasma-related …
device fabrication. Not only the utilization but also the development of plasma-related …
[HTML][HTML] Modelling and optimization of microhardness of electroless Ni–P–TiO2 composite coating based on machine learning approaches and RSM
In this study, experimental investigations on the microhardness of the synthesized
electroless Ni–P–TiO 2 coated aluminium composite was carried out. The coated samples …
electroless Ni–P–TiO 2 coated aluminium composite was carried out. The coated samples …
Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology
To improve the quality and productivity of the process or system before resorting to
expensive and laborious experimental tests, it is essential to model and predict the system …
expensive and laborious experimental tests, it is essential to model and predict the system …
Estimation of microhardness and crystal grain size values of electrodeposited Ni-B/TiC nanocomposite coatings by artificial neural networks (ANN) method
E Ünal, A Yaşar, İH Karahan - Journal of Alloys and Compounds, 2023 - Elsevier
In this study, composite coatings with Ni-B alloy main structure reinforced with TiC
nanoparticles were coated on a stainless steel substrate by electrodeposition method. The …
nanoparticles were coated on a stainless steel substrate by electrodeposition method. The …
Application of artificial neural networks throughout the entire life cycle of coatings: a comprehensive review
Z Ning, X Zhao, L Fan, Z Peng, F Ma, Z Jin… - Progress in Organic …, 2024 - Elsevier
Artificial neural networks (ANNs) have been widely employed in performance testing and life
prediction throughout the entire life cycle of coatings due to their self-learning and arbitrary …
prediction throughout the entire life cycle of coatings due to their self-learning and arbitrary …
[HTML][HTML] Digital advancements in smart materials design and multifunctional coating manufacturing
J Verma, AS Khanna - Physics Open, 2023 - Elsevier
This article reviewed the present state of advanced digital technologies such as Artificial
Intelligence (AI) and Machine Learning (ML) for the development of smart materials design …
Intelligence (AI) and Machine Learning (ML) for the development of smart materials design …
Estimation of abrasive wear of nanostructured WC-10Co-4Cr TIG weld cladding using neural network and fuzzy logic approach
UMR Paturi, DG Vanga, S Cheruku… - Materials Today …, 2023 - Elsevier
Surface engineering is a great way to make wear-resistant mechanical components and
increase their service life in industrial and commercial applications. The behaviour of …
increase their service life in industrial and commercial applications. The behaviour of …
[HTML][HTML] Surface quality prediction by machine learning methods and process parameter optimization in ultra-precision machining of AISI D2 using CBN tool
High-quality machining is a crucial aspect of contemporary manufacturing technology due to
the vast demand for precision machining for parts made from hardened tool steels and super …
the vast demand for precision machining for parts made from hardened tool steels and super …
Conditional generative adversarial network driven approach for direct prediction of thermal stress based on two-phase material SEM images
L Ning, Z Cai, Y Liu, W Wang - Ceramics International, 2021 - Elsevier
A conditional generative adversarial network (cGAN)-driven approach for the direct
prediction of thermal stress is proposed. Synthetic two-phase structure images of ceramic …
prediction of thermal stress is proposed. Synthetic two-phase structure images of ceramic …