ELPH TRANSPORT DRIVER: Difference between revisions

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The Onsager coefficients can be computed using either of the options bellow, each with its own advantages and disadvantages.
The Onsager coefficients can be computed using either of the options below, each with its own advantages and disadvantages.
They are defined as
They are defined as
:<math>
:<math>
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</math>
</math>
where <math>\mathcal{T}(\epsilon)</math> is the [[Electronic_transport_coefficients#Transport_distribution_function | transport distribution function]],   
where <math>\mathcal{T}(\epsilon)</math> is the [[Electronic_transport_coefficients#Transport_distribution_function | transport distribution function]],   
<math>\mu</math> the chemical potential, and <math>f^0</math> the Fermi–Dirac distribution.
<math>\mu</math> the [[Chemical potential in electron-phonon interactions | chemical potential]], and <math>f^0</math> the Fermi–Dirac distribution.


; {{TAGO|ELPH_TRANSPORT_DRIVER|1|op==}}
; {{TAGO|ELPH_TRANSPORT_DRIVER|1|op==}}

Revision as of 14:18, 23 October 2025

ELPH_TRANSPORT_DRIVER = [integer]
Default: ELPH_TRANSPORT_DRIVER = 2 

Description: choose method to compute the Onsager coefficients, which are then used to compute the transport coefficients.

Mind: Available as of VASP 6.5.0

The Onsager coefficients can be computed using either of the options below, each with its own advantages and disadvantages. They are defined as

[math]\displaystyle{ L_{ij} = \int d\epsilon \, \mathcal{T}(\epsilon) \, (\epsilon-\mu)^{i+j-2} \left( -\frac{\partial f^0}{\partial \epsilon} \right), }[/math]

where [math]\displaystyle{ \mathcal{T}(\epsilon) }[/math] is the transport distribution function, [math]\displaystyle{ \mu }[/math] the chemical potential, and [math]\displaystyle{ f^0 }[/math] the Fermi–Dirac distribution.

ELPH_TRANSPORT_DRIVER = 1
The discretized Onsager coefficient is evaluated as
[math]\displaystyle{ L_{ij} \;\approx\; \sum_{k=1}^{N} w_k \; \mathcal{T}(\epsilon_k)\; (\epsilon_k - \mu)^{\,i+j-2}\; \left( -\frac{\partial f^0}{\partial \epsilon} \right). }[/math]
with [math]\displaystyle{ \epsilon_k = \epsilon_\text{min}+(k-1)\Delta \epsilon,\;\; k=1,\dots,N }[/math] and [math]\displaystyle{ \Delta \epsilon = \tfrac{\epsilon_\text{max}-\epsilon_\text{min}}{N-1} }[/math] and [math]\displaystyle{ \epsilon_\text{min} }[/math]=ELPH_TRANSPORT_EMIN and [math]\displaystyle{ \epsilon_\text{max} }[/math]=ELPH_TRANSPORT_EMAX or alternatively both [math]\displaystyle{ \epsilon_\text{min} }[/math] and [math]\displaystyle{ \epsilon_\text{max} }[/math] are set by ELPH_TRANSPORT_DFERMI_TOL, [math]\displaystyle{ w_k }[/math] the weights due to the Simpson integration rule and N=TRANSPORT_NEDOS.
ELPH_TRANSPORT_DRIVER = 2
Use Gauss-Legendre integration to evaluate the Onsager coefficients. The convergence of the integral can be checked by performing a convergence study with respect to N=TRANSPORT_NEDOS alone. In this case the Onsager coefficients are evaluated using the following discretization
[math]\displaystyle{ L_{ij} \;\approx\; \tfrac{1}{2} \sum_{k=1}^N w_k \, \left( \frac{k_B T}{-e} \ln \frac{1+x_k}{1-x_k} \right)^{i+j-2} \mathcal{T}\!\left(\mu + k_B T \ln\frac{1+x_k}{1-x_k}\right), }[/math]
with [math]\displaystyle{ w_k }[/math] and [math]\displaystyle{ x_k }[/math] the weights and abcissae of the Gauss-Legendre quadrature rule.

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