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Database optimization for empirical interatomic potential models
Pinchao Zhang,
Dallas R. Trinkle
Materials Science and Engineering
Nuclear, Plasma, and Radiological Engineering
Materials Research Lab
National Center for Supercomputing Applications (NCSA)
Beckman Institute for Advanced Science and Technology
Research output
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peer-review
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Dive into the research topics of 'Database optimization for empirical interatomic potential models'. Together they form a unique fingerprint.
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Mathematics
Optimization
41%
Model
17%
Objective function
17%
Prediction
16%
Prediction Error
15%
Testing
14%
Lennard-Jones Potential
11%
Crystal Structure
9%
Least Square Fitting
9%
Energy
9%
Empirical Measures
8%
Optimal Parameter
8%
Weighted Least Squares
7%
Modeling
4%
Estimate
3%
Chemical Compounds
Interatomic Potential
80%
Error
40%
Lennard-Jones Potential
26%
Pair Potential
26%
Crystal Structure
9%
Physics & Astronomy
optimization
35%
predictions
18%
Lennard-Jones potential
8%
sampling
5%
crystal structure
5%
energy
4%
estimates
3%
Engineering & Materials Science
Set theory
13%
Testing
10%
Crystal structure
8%
Sampling
4%