Modified Monte Carlo approach for simulation of grain growth and Ostwald ripening in two-phase Zn–22Al alloy

Mohammadi, Hossein; Eivani, A.R.; Seyedein, S.H.; Ghosh, Manojit

doi:10.1016/j.jmrt.2020.06.017

Cited by 14 publications

(5 citation statements)

References 56 publications

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“…Moreover, with the increase of annealing temperature, the number of precipitates gradually decreases while the size increases according to the Ostwald ripening mechanism. [ 31,32 ] Further increasing the annealing temperature, the free of precipitates are observed in samples annealed at 1000 °C (Figure 4k) and 1100 °C (Figure 4l).…”

Section: Resultsmentioning

confidence: 99%

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

et al. 2023

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Eutectic high‐entropy alloys (EHEAs), with good castability, compositional homogeneity, and outstanding properties, are becoming hotpots in materials field. It is worth noting that most reported EHEAs are based on expensive and high density of metal elements, such as Hf, Zr, Ta, Nb, W, and Pd, which increase the overall cost and quality. Herein, by selecting the cost‐effective and low‐density of Ti and Si as eutectic forming elements, a novel CoCrFeNi2(TiSi)0.7 EHEA with face‐centered‐cubic (FCC) + M16Ti6Si7‐type silicide is designed and prepared. The evolution of microstructure and mechanical properties is investigated under different annealing conditions. The CoCrFeNi2(TiSi)0.7 EHEA shows excellent high‐temperature mechanical properties. At 800 °C, the as‐cast and annealed samples do not fracture under a compressive strain exceeding 50%. In particular, a long period of high‐temperature annealing dramatically increases the high‐temperature yield strength from 510 to 703 MPa, which exceeds that of most reported EHEAs and some refractory high‐entropy alloys.

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Section: Resultsmentioning

confidence: 99%

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

et al. 2023

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“…According to the effective heat of formation (EHF) model proposed by Pretorius et al [ 25 ], the effective Gibbs free energy of formation can be obtained by analogy. The formation of primary phases of the Al-Fe binary system on the reaction and the order of formation of each phase can be predicted.…”

Section: Resultsmentioning

confidence: 99%

“…Calculate the net energy change (Δ H = H 2 − H 1 ) before and after reorientation or orientation exchanges. The new orientation assignment or exchange is accepted with a transition probability, P x , of [ 25 , 26 ]:

where T is the simulation temperature, k B is the Boltzmann’s constant. Generate a random probability R between 0 and 1.…”

Section: Methodsmentioning

confidence: 99%

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Formation and Evolution Mechanism of Intermetallic Compounds of Friction Stir Lap Welded Steel/Aluminum Joints

Liu,

Pang,

Zhang

et al. 2023

Materials

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Interfacial layers with brittle intermetallic compounds (IMC) greatly influence the performance of steel–aluminum friction stir lap welding (FSLW) joints. Thus, the formation and evolution of IMC between 7075-T6 aluminum alloy and galvanized DP590 steel in steel–aluminum FSLW joints were investigated. An FSLW numerical model was developed using the computational fluid dynamics method to analyze the interface temperature between the aluminum alloy and steel. Scanning electron microscopy (SEM) was conducted to observe the microstructure characterization and measure the IMC thickness. Phases among different joint zones were analyzed by X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS). IMC layer formation was predicted by the effective Gibbs free energy model presented in this paper according to thermodynamic principles. The Monte Carlo method was utilized to predict the thickness of IMC layers. It was found that the IMC layer at the interface of the welded joint is composed of Fe2Al5, FeAl3, and Al-Zn eutectic. The IMC thickness decreased from 4.3 μm to 0.8 μm with the increasing welding speed, which was consistent with the Monte Carlo simulation results.

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“…Strictly MC-based methods have been used to investigate material properties such as phase coexistence − and phase transitions, the phase space for single- and multicomponent systems, and cluster nucleation and growth. − For biological systems, MC methods have been used to perform constant-pH simulations, calculations of absolute binding free energies, enhanced sampling of protein conformations, , and protein folding. , Furthermore, coupled MCMD has been used to study protonation dynamics, − protein bond cleavage, and configurational properties of systems containing metals, , among other applications …”

Section: Introductionmentioning

confidence: 99%

Drug Discovery by Automated Adaptation of Chemical Structure and Identity

Patel

Chau

Debesai

et al. 2022

J. Chem. Theory Comput.

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Computer-aided drug design offers the potential to dramatically reduce the cost and effort required for drug discovery. While screening-based methods are valuable in the early stages of hit identification, they are frequently succeeded by iterative, hypothesis-driven computations that require recurrent investment of human time and intuition. To increase automation, we introduce a computational method for lead refinement that combines concerted dynamics of the ligand/protein complex via molecular dynamics simulations with integrated Monte Carlo-based changes in the chemical formula of the ligand. This approach, which we refer to as ligand-exchange Monte Carlo molecular dynamics, accounts for solvent- and entropy-based contributions to competitive binding free energies by coupling the energetics of bound and unbound states during the ligand-exchange attempt. Quantitative comparison of relative binding free energies to reference values from free energy perturbation, conducted in vacuum, indicates that ligand-exchange Monte Carlo molecular dynamics simulations sample relevant conformational ensembles and are capable of identifying strongly binding compounds. Additional simulations demonstrate the use of an implicit solvent model. We speculate that the use of chemical graphs in which exchanges are only permitted between ligands with sufficient similarity may enable an automated search to capture some of the benefits provided by human intuition during hypothesis-guided lead refinement.

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Modified Monte Carlo approach for simulation of grain growth and Ostwald ripening in two-phase Zn–22Al alloy

Cited by 14 publications

References 56 publications

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

Formation and Evolution Mechanism of Intermetallic Compounds of Friction Stir Lap Welded Steel/Aluminum Joints

Drug Discovery by Automated Adaptation of Chemical Structure and Identity

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Modified Monte Carlo approach for simulation of grain growth and Ostwald ripening in two-phase Zn–22Al alloy

Cited by 14 publications

References 56 publications

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi2(TiSi)0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi2(TiSi)0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

Formation and Evolution Mechanism of Intermetallic Compounds of Friction Stir Lap Welded Steel/Aluminum Joints

Drug Discovery by Automated Adaptation of Chemical Structure and Identity

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Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions

Evolution of Microstructure and Mechanical Properties of a Novel CoCrFeNi₂(TiSi)_0.7 Eutectic High‐Entropy Alloys under Different Annealing Conditions