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Effect of solute-solute interactions on strengthening of random alloys from dilute to high entropy alloys

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Solute-strengthening in metal alloys with short-range order

William Curtin, Shankha Nag

Recent surging interest in strengthening of High Entropy Alloys (HEAs) with possible chemical ordering motivates the development of new theory. Here, an existing theory for random alloys that accounts for solute-dislocation and solute–solute interactions i ...

2024

Strengthening of edge prism dislocations in Mg-Zn by cross-core diffusion

William Curtin

The activation of prismatic slip in Mg and its alloys can be beneficial for deformation and forming. Experiments show that addition of Zn and Al solutes have a softening effect at/below room temperature, attributed to solutes facilitating basal-prism-basal ...

2024

The influence of lattice misfit on screw and edge dislocation-controlled solid solution strengthening in Mo-Ti alloys

William Curtin, Carolina Baruffi, You Rao

Mo-Ti alloys form solid solutions over a wide range of compositions, with lattice misfit parameters increasing significantly with titanium content. This indicates a strong increase in the critical stress for edge dislocation motion. Here, we probe the tran ...

SPRINGERNATURE2023

Tuning the mechanical properties of metals, including strength, through adjusting the type and/or concentration of added solute elements, has been recognized as an effective way to design and produce materials with desired or optimized mechanical propertie ...

EPFL2022

Screw vs. edge dislocation strengthening in body-centered-cubic high entrophy alloys and implications for guided alloy design

William Curtin, Francesco Maresca, Carolina Baruffi

Body-centered-cubic (BCC) high entropy alloys (HEAs) can show exceptionally high strength up to high temperatures. Mechanistic theories are needed to guide alloy discovery within the immense multicomponent HEA compositional space. Here, two new theories fo ...

SPRINGER HEIDELBERG2022

Machine learning for metallurgy IV: A neural network potential for Al-Cu-Mg and Al-Cu-Mg-Zn

William Curtin, Daniel John Gilles Marchand

Most metallurgical properties, e.g., dislocation propagation, precipitate formation, can only be fully understood atomistically but most phenomena and quantities of interest cannot be measured experimentally. Accurate simulation methods are essential but f ...

AMER PHYSICAL SOC2022

Modeling of precipitate strengthening with near-chemical accuracy: case study of Al-6xxx alloys

William Curtin, Yi Hu

Many metal alloys are strengthened by controlling precipitation to achieve an optimal peak-aged condi-tion where the strength-limiting processes of precipitate shearing and Orowan looping are thought to be comparable. Qualitative models have long captured ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Neural Network Potentials for Age Hardening Aluminum Alloys

Daniel John Gilles Marchand

High-strength metal alloys achieve their performance via careful control of precipitates and solutes.The nucleation, growth, and kinetics of precipitation, and the resulting mechanical properties, are inherently atomic scale phenomena, particularly during ...

EPFL2022

Modeling peak-aged precipitate strengthening in Al–Mg–Si alloys

William Curtin, Yi Hu

Strengthening by needle-shaped precipitates is critical in Al–Mg–Si alloys. Here, the strengthening is studied computationally at the peak-aged condition where precipitate shearing and Orowan looping are usually considered to have equal strengths. Pseudo-r ...

2021

Under common processing conditions, both dilute and complex concentrated alloys are often realized as random alloys, with no correlation in the occupancy of lattice sites by the constituent atom types. The current thesis primary addresses two problems in r ...

EPFL2020