Thermodynamic properties of the Nd-Bi system via emf measurements, DFT calculations, machine learning, and CALPHAD modeling

Engineering & Materials Science

• Density functional theory 100%
• Phase diagrams 85%
• Electromotive force 85%
• Force measurement 80%
• Thermodynamic properties 62%
• Machine learning 49%
• Activity coefficients 33%
• Lithium Chloride 32%
• Titration 31%
• Potassium chloride 30%
• Crystal structure 28%
• Differential scanning calorimetry 24%
• Solubility 24%
• X ray diffraction 21%
• Molten materials 21%
• Thermodynamics 19%
• Data mining 18%
• Scanning electron microscopy 17%
• Liquids 14%
• Temperature 8%

Chemical Compounds

• Electromotive Force 85%
• Phase Diagrams 60%
• Thermodynamic Property 59%
• Coulometric Titration 46%
• Density Functional Theory 41%
• Liquidus 41%
• Mining 38%
• Differential Scanning Calorimetry 24%
• Alloy 23%
• Solubility 21%
• Thermodynamics 20%
• Scanning Electron Microscopy 19%
• Liquid 18%
• X-Ray Diffraction 16%
• Mixture 14%