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 …
Enhancing robustness in machine-learning-accelerated molecular dynamics: A multi-model nonparametric probabilistic approach
In this work, we present a system-agnostic probabilistic framework to quantify model-form
uncertainties in molecular dynamics (MD) simulations based on machine-learned (ML) …
uncertainties in molecular dynamics (MD) simulations based on machine-learned (ML) …
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 …