[HTML][HTML] Exploring the potential of nano technology: A assessment of nano-scale multi-layered-composite coatings for cutting tool performance

S Ganeshkumar, A Kumar, J Maniraj, YS Babu… - Arabian Journal of …, 2023 - Elsevier
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 …

[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 …

[HTML][HTML] Modelling and optimization of microhardness of electroless Ni–P–TiO2 composite coating based on machine learning approaches and RSM

IA Shozib, A Ahmad, MSA Rahaman… - Journal of Materials …, 2021 - Elsevier
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 …

Estimation of coating thickness in electrostatic spray deposition by machine learning and response surface methodology

UMR Paturi, NS Reddy, S Cheruku, SKR Narala… - Surface and Coatings …, 2021 - Elsevier
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 …

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 …

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 …

[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 …

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 …

[HTML][HTML] Surface quality prediction by machine learning methods and process parameter optimization in ultra-precision machining of AISI D2 using CBN tool

UL Adizue, AD Tura, EO Isaya, BZ Farkas… - The International Journal …, 2023 - Springer
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 …

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 …