ML RCUT2

ML_RCUT2 = [real]
Default: ML_RCUT2 = 5.0 

Description: This flag sets the cutoff radius $R_{\text{cut}}$ for the angular descriptor $\rho _{i}^{(3)}(r)$ in the machine learning force field method. The unit of the cut-off radius is $\mathrm {\AA}$.

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The angular descriptor is constructed from

$\rho _{i}^{(3)}\left(r,s,\theta \right)=\iint d{\hat {\mathbf {r} }}d{\hat {\mathbf {s} }}\delta \left({\hat {\mathbf {r} }}\cdot {\hat {\mathbf {s} }}-\mathrm {cos} \theta \right)\sum \limits _{j=1}^{N_{a}}\sum \limits _{k\neq j}^{N_{a}}\rho _{ik}\left(r{\hat {\mathbf {r} }}\right)\rho _{ij}\left(s{\hat {\mathbf {s} }}\right),\quad {\text{where}}\quad \rho _{ij}\left(\mathbf {r} \right)=f_{\mathrm {cut} }\left(r_{ij}\right)g\left(\mathbf {r} -\mathbf {r} _{ij}\right)$

and $g\left(\mathbf {r} \right)$ is an approximation of the delta function. A basis set expansion of $\rho _{i}^{(3)}(r)$ yields the expansion coefficients $p_{n\nu l}^{i}$ which are used in practice to describe the atomic environment (see this section for details). The tag ML_RCUT2 sets the cutoff radius $R_{\text{cut}}$ at which the cutoff function $f_{\mathrm {cut} }\left(r_{ij}\right)$ decays to zero.

Mind: The cutoff radius determines how many neighbor atoms $N_{\mathrm {a} }$ are taken into account to describe each central atom's environment. Hence, important features may be missed if the cutoff radius is set to a too small value. On the other hand, a large cutoff radius increases the computational cost as the cutoff sphere contains more neighbor atoms. A larger cutoff can also significantly degrade the learning efficiency. A good compromise is system-dependent, therefore different values should be tested to achieve satisfying accuracy and speed.

For materials (i.e. organic molecules, polymers) containing only H, B, C, O, N, and F, the learning efficiency might increase when ML_RCUT2 is set to values around 4 $\mathrm {\AA}$ (that is, less training data are required to achieve a specific accuracy), wheres for materials with very long bonds, a larger value around 6 $\mathrm {\AA}$ might improve the accuracy,

Related tags and articles

ML_LMLFF, ML_RCUT1, ML_W1, ML_SION1, ML_SION2, ML_MRB1, ML_MRB2

Examples that use this tag

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