|
|
Line 1: |
Line 1: |
| | {{DISPLAYTITLE:ML_LHEAT}} |
| {{TAGDEF|ML_LHEAT|[logical]|.FALSE.}} | | {{TAGDEF|ML_LHEAT|[logical]|.FALSE.}} |
|
| |
|
Line 44: |
Line 45: |
| The heat flux is written to the file {{TAG|ML_HEAT}}. | | The heat flux is written to the file {{TAG|ML_HEAT}}. |
|
| |
|
| == Related Tags and Sections == | | == Related tags and articles == |
| {{TAG|ML_LMLFF}}, {{TAG|ML_LEATOM}} | | {{TAG|ML_LMLFF}}, {{TAG|ML_LEATOM}} |
|
| |
|
Line 50: |
Line 51: |
| ---- | | ---- |
|
| |
|
| [[Category:INCAR]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]][[Category: Alpha]] | | [[Category:INCAR tag]][[Category:Machine Learning]][[Category:Machine Learned Force Fields]] |
Revision as of 07:31, 7 April 2022
ML_LHEAT = [logical]
Default: ML_LHEAT = .FALSE.
Description: This tag specifies whether the heat flux is calculated or not in the machine learning force field method.
The heat flux within machine learning force fields can is decomposed into atomic contributions written as
where , and denote the position vector, velocity and energy of atom , respectively. The number of atoms in the system is denoted by . The heat flux can be further rewritten as
Using the equation of motions
the heat flux can be simplified to
Finally (in a post-processing step), the thermal conductivity at temperature in the Green-Kubo formalism can be calculated from the correlation of the heat flux as
where and denotes the volume of the system and the Boltzmann constant, respectively.
The heat flux is written to the file ML_HEAT.
Related tags and articles
ML_LMLFF, ML_LEATOM
Examples that use this tag