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Melting temperature prediction via first principles and deep learning
Qi Jun Hong
Engineering, Ira A. Fulton Schools of (IAFSE)
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Scopus citations
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Dive into the research topics of 'Melting temperature prediction via first principles and deep learning'. Together they form a unique fingerprint.
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Mathematics
Melting
88%
First-principles
87%
Learning
60%
Prediction
53%
Density Functional Theory
48%
Molecular Dynamics Simulation
25%
Coexistence
18%
Neural Networks
15%
Material Design
14%
Costs
12%
Heating
10%
Configuration Space
9%
Eliminate
8%
Statistical Analysis
8%
Graph in graph theory
7%
Invariance
7%
Permutation
6%
Framework
4%
Model
2%
Physics & Astronomy
learning
72%
melting
51%
density functional theory
51%
predictions
35%
costs
25%
molecular dynamics
24%
permutations
20%
temperature
19%
statistical analysis
17%
melting points
15%
invariance
15%
sampling
13%
simulation
12%
computer programs
12%
heating
10%
configurations
8%
Engineering & Materials Science
Density functional theory
100%
Melting point
70%
Deep learning
59%
Molecular dynamics
37%
Neural networks
20%
Computer simulation
18%
Invariance
17%
Melting
15%
Statistical methods
14%
Costs
12%
Heating
11%
Sampling
11%
Chemical analysis
10%
Temperature
6%
Chemical Compounds
Melting Point
55%
Density Functional Theory
41%
Molecular Dynamics
32%
Simulation
28%
Chemical Formula
27%
Melting
19%
Sampling
18%