Optimization strategies of high-entropy alloys for electrocatalytic applications

L Xiao, Z Wang, J Guan - Chemical Science, 2023 - pubs.rsc.org
High-entropy alloys (HEAs) are expected to become one of the most promising functional
materials in the field of electrocatalysis due to their site-occupancy disorder and lattice order …

Tailoring the strengthening mechanisms of high-entropy alloys toward excellent strength-ductility synergy by metalloid silicon alloying: A review

MJ Sohrabi, A Kalhor, H Mirzadeh, K Rodak… - Progress in Materials …, 2024 - Elsevier
Metalloids and transition/refractory elements typically differ significantly in the electronic
structure and atomic size, allowing for stronger solid-solution hardening in high-entropy …

Deformation-induced martensitic transformations: A strategy for overcoming the strength-ductility trade-off in high-entropy alloys

MS Mehranpour, N Rasooli, HS Kim… - Current Opinion in Solid …, 2024 - Elsevier
High-entropy alloys (HEAs) have become an important topic in modern materials science
due to their exceptional properties. Despite their attractive properties, achieving a superior …

[HTML][HTML] Unraveling phase prediction in high entropy alloys: A synergy of machine learning, deep learning, and ThermoCalc, validation by experimental analysis

M Veeresham, N Sake, U Lee, N Park - Journal of Materials Research and …, 2024 - Elsevier
The phase formation in high entropy alloys (HEAs) presents a significant challenge due to
the complexity of their composition and the intricate interactions between multiple elements …

[HTML][HTML] Enhancing flow stress predictions in CoCrFeNiV high entropy alloy with conventional and machine learning techniques

SK Dewangan, R Jain, S Bhattacharjee, S Jain… - Journal of Materials …, 2024 - Elsevier
A machine learning technique leveraging artificial intelligence (AI) has emerged as a
promising tool for expediting the exploration and design of novel high entropy alloys (HEAs) …

[HTML][HTML] Optimizing microwave-assisted synthesis of akermanite nanoparticles using citric acid as a chelating agent: A combined machine learning and experimental …

N Balighieh, MR Zamani, SF Kashani-Bozorg… - Journal of Materials …, 2024 - Elsevier
This study aims to synthesize akermanite (Ca 2 MgSi 2 O 7) using an eco-friendly and fast
microwave-assisted method and understand the effect of using citric acid (CA) as a chelating …

Analysis of the possibility of using exploration and learning algorithms in the production of castings

A Bitka, M Witkowski, K Jaśkowiec, M Małysza… - Archives of Civil and …, 2025 - Springer
The research presented in the article indicates the process of building models based on
machine learning algorithms, linear regression, decision trees, ensemble learning, random …

Enhanced strength of (CoFeNiMn)100−xCrx (x = 5, 20, 35 at.%) high entropy alloys via formation of carbide phases produced from industrial-grade raw materials

G Polat - Materials Testing, 2024 - degruyter.com
Abstract (CoFeNiMn) 100− xCrx (x= 5, 20, 35 at.%) HEAs were produced using vacuum arc
melting followed by suction casting using industrial-grade raw materials and subsequent …