Titlebook: Computational Materials System Design; Dongwon Shin,James Saal Book 2018 Springer International Publishing AG 2018 CALPHAD.Computational T

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書目名稱Computational Materials System Design影響因子(影響力)




書目名稱Computational Materials System Design影響因子(影響力)學(xué)科排名




書目名稱Computational Materials System Design網(wǎng)絡(luò)公開度




書目名稱Computational Materials System Design網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Materials System Design被引頻次




書目名稱Computational Materials System Design被引頻次學(xué)科排名




書目名稱Computational Materials System Design年度引用




書目名稱Computational Materials System Design年度引用學(xué)科排名




書目名稱Computational Materials System Design讀者反饋




書目名稱Computational Materials System Design讀者反饋學(xué)科排名

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Design of Materials Processing Using Computational Thermodynamics,mputational thermodynamics for the design of new materials and materials processing in reducing the trial-and-error research activities. The evolution of the CALPHAD (CALculation of PHAse Diagrams) approach is discussed from the development of thermodynamic databases and new software to the extensio

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1D Solidification Model for the Prediction of Microstructural Evolution in Light Alloys,kinetics. The present 1D solidification model coupling the CALPHAD-type thermodynamic database and classical solidification theories can reasonably predict the microstructural evolution including solidification path, primary and secondary dendrite arm spacing, microsegregation, and secondary phase f

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Multiscale Crystalline Plasticity for Materials Design,ctive atomic scale approaches through responses of polycrystals. Intermediate forms of models vary from discrete (and often dynamic) methods to statistical and continuum methods. These range from coarse-grained atomistic and microscopic phase field models, discrete dislocation dynamics, dislocation

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Ab Initio Molecular Dynamics Studies of Fast Ion Conductors,c conductors that are of immense interest to energy storage and other application. In this chapter, we will first provide an introduction of the theoretical underpinnings of AIMD, including both the Car-Parrinello and Born-Oppenheimer variants and the analysis of such simulations for diffusion prope

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Materials Data Infrastructure and Materials Informatics,e art in materials data infrastructure, focusing in detail on four infrastructure projects spanning academia, government, and industry. We also discuss data standards as an enabling step on the path to community-scale materials data infrastructure. We then introduce materials informatics as a potent

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