Results 21 to 30 of about 5,769 (231)

High-Temperature Thermodynamics of Uranium from Ab Initio Modeling

Applied Sciences, 2023
We present high-temperature thermodynamic properties for uranium in its γ phase (γ-U) from first-principles, relativistic, and anharmonic theory. The results are compared to CALPHAD modeling.
Per Söderlind, Alexander Landa, Emily E. Moore, Aurélien Perron, John Roehling, Joseph T. McKeown   +5 more
doaj   +1 more source

Modelling Microstructure in Casting of Steel via CALPHAD-Based ICME Approach

Alloys, 2023
Integrated computational materials engineering (ICME) is emerging as an increasingly powerful approach to integrate computational materials science tools into a holistic system and address the multiscale modeling challenges in the processing of advanced ...
Chunhui Luo, Karin Hansson, Zhili Song, Debbie Ågren, Ewa Sjöqvist Persson, Fredrik Cederholm, Changji Xuan   +6 more
doaj   +1 more source

Algorithm to optimize thermodynamic parameters: A review [PDF]

Journal of Mining and Metallurgy. Section B: Metallurgy
Computational thermodynamics provides essential information for materials design. The CALPHAD (CALculation of PHAse Diagrams) method based on thermodynamic databases can be used for thermodynamic optimization and for calculating phase diagrams and ...
Zhang Liang, Zhang Xinyi, Liu Yuling, Wang Jiangxing, Fu Taibai, Wen Shiyi, Wang Bo, Xie Ziqing, Du Yong   +8 more
doaj   +1 more source

Experimental study and thermodynamic modeling of the Al–Co–Cr–Ni system

Science and Technology of Advanced Materials, 2015
A thermodynamic database for the Al–Co–Cr–Ni system is built via the Calphad method by extrapolating re-assessed ternary subsystems. A minimum number of quaternary parameters are included, which are optimized using experimental phase equilibrium data ...
Thomas Gheno, Xuan L Liu, Greta Lindwall, Zi-Kui Liu, Brian Gleeson   +4 more
doaj   +1 more source

Formation and Thermal Stability of ω-Ti(Fe) in α-Phase-Based Ti(Fe) Alloys

Metals, 2020
In this work, the formation and thermal stability of the ω-Ti(Fe) phase that were produced by the high-pressure torsion (HPT) were studied in two-phase α-Ti + TiFe alloys containing 2 wt.%, 4 wt.% and 10 wt.% iron.
Mario J. Kriegel, Martin Rudolph, Askar Kilmametov, Boris B. Straumal, Julia Ivanisenko, Olga Fabrichnaya, Horst Hahn, David Rafaja   +7 more
doaj   +1 more source

ON PHASE DIAGRAM OF Au-Si NANOALLOY: MOLECULAR DYNAMICS AND THERMODYNAMIC SIMULATION

Физико-химические аспекты изучения кластеров, наноструктур и наноматериалов, 2019
Phase diagrams for Au-Si nanoparticles were constructed by using molecular dynamics and thermodynamic simulation, based on the CALPHAD methodology extended to nanoscale objects.
I.V. Talyzin, A.Yu. Kartoshkin, S.A. Vasilyev, M.V. Samsonov, V.M. Samsonov   +4 more
doaj   +1 more source

A third generation Calphad description of W-C including a revision of liquid C

, 2022
More physically-based models are used when developing the third generation Calphad descriptions, which en -able to calculate and predict the thermodynamic properties with higher reliability in an extended temperature range.
He, Zhangting,, Selleby, Malin,
core   +1 more source

An approach to determine enthalpies of formation for ternary compounds [PDF]

Journal of Mining and Metallurgy. Section B: Metallurgy, 2010
An integrated approach of experiment and theoretical computation to acquire enthalpies of formation for ternary compounds is described. The enthalpies of formation (DHf ) for Al71Fe19Si10 and Al31Mn6Ni2 are measured via a calorimeter.
Du Y., Wang J., Ouyang Y.F., Zhang L.J., Yuan Z.H., Liu S.H., Nash P.   +6 more
doaj   +1 more source

Unexpected spinodal decomposition in as-cast eutectic high entropy alloy Al30Co10Cr30Fe15Ni15

Materials & Design, 2023
By integrating calculation of phase diagram (CALPHAD) simulations, ab initio molecular dynamics (AIMD) and experimental validation, we shed light on the unexpected spinodal decomposition in as-cast Al30Co10Cr30Fe15Ni15 alloy, as opposed to the eutectic ...
Kewu Bai, Chee Koon Ng, Ming Lin, Baisong Cheng, Yingzhi Zeng, Delvin Wuu, Jing Jun Lee, Siew Lang Teo, Si Rong Ng, Dennis Cheng Cheh Tan, Pei Wang, Zachary Aitken, Yong-Wei Zhang   +12 more
doaj   +1 more source

Stacking fault energy prediction for austenitic steels: thermodynamic modeling vs. machine learning

Science and Technology of Advanced Materials, 2020
Stacking fault energy (SFE) is of the most critical microstructure attribute for controlling the deformation mechanism and optimizing mechanical properties of austenitic steels, while there are no accurate and straightforward computational tools for ...
Xin Wang, Wei Xiong
doaj   +1 more source