Multiscale computational modeling techniques in study and design of 2D materials: recent advances, challenges, and opportunities
This article provides an overview of recent advances, challenges, and opportunities in
multiscale computational modeling techniques for study and design of two-dimensional (2D) …
multiscale computational modeling techniques for study and design of two-dimensional (2D) …
Exploring sustainable solutions for soil stabilization through explainable Gaussian process-assisted multi-objective optimization
The adoption of sustainable solutions in soil stabilization has piqued the interest of the
scientific community due to the potential reduction in carbon footprint. In this regard, the …
scientific community due to the potential reduction in carbon footprint. In this regard, the …
A Comparative Analysis of Machine Learning Techniques for Predicting the Wear Rate of Ceramic Coated Steel
N Radhika, M Sabarinathan, S Sivaraman - IEEE Access, 2024 - ieeexplore.ieee.org
Ceramic coatings are necessary for steel as they offer resistance to corrosion, high-
temperature degradation, and abrasion, thereby enhancing the wear characteristics of steel …
temperature degradation, and abrasion, thereby enhancing the wear characteristics of steel …
Exploring nano-scale scratching induced tribological behavior of graphene engineered AlCoCrFeNi high-entropy alloy
S Barman, K Kumar Gupta… - Journal of Applied …, 2024 - asmedigitalcollection.asme.org
Motivated by the recent discoveries concerning the exceptional surface engineering
capabilities offered by high-entropy alloys (HEAs), this article investigates the tribological …
capabilities offered by high-entropy alloys (HEAs), this article investigates the tribological …
Comparative study on constitutive models of a near β titanium alloy TC18 during thermoplastic deformation based on machine learning
S Ding, S Gao, X Jiang, S Shi, Y Liang - Materials Today Communications, 2025 - Elsevier
The hot deformation behavior of TC18 alloy has been systematically studied at the
temperature of 993–1113 K and strain rate of 0.001–1 s− 1. Based on the stress-strain data …
temperature of 993–1113 K and strain rate of 0.001–1 s− 1. Based on the stress-strain data …
Machine learning-based study of hardness in polypropylene/carbon nanotube and low-density polyethylene/carbon nanotube composites
H Sharma, G Arora, R Kumar, S Debnath… - Discover Materials, 2025 - Springer
In the present work, the hardness prediction of polypropylene/carbon nanotubes (PP/CNT)
and low-density polyethylene/carbon nanotubes (LDPE/CNT) composite materials …
and low-density polyethylene/carbon nanotubes (LDPE/CNT) composite materials …