# This file is part of tad-dftd4.
#
# SPDX-Identifier: Apache-2.0
# Copyright (C) 2024 Grimme Group
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Data: Chemical hardnesses
=========================
Element-specific chemical hardnesses.
Used in DFT-D4, for example, for the charge scaling function to extrapolate
the C6 coefficients.
"""
from __future__ import annotations
import torch
__all__ = ["GAM"]
[docs]
def GAM(
dtype: torch.dtype | None = torch.double, device: torch.device | None = None
) -> torch.Tensor:
"""Element-specific chemical hardnesses."""
_GAM = [
0.00000000, # None
0.47259288, # H
0.92203391, # He
0.17452888, # Li (2nd)
0.25700733, # Be
0.33949086, # B
0.42195412, # C
0.50438193, # N
0.58691863, # O
0.66931351, # F
0.75191607, # Ne
0.17964105, # Na (3rd)
0.22157276, # Mg
0.26348578, # Al
0.30539645, # Si
0.34734014, # P
0.38924725, # S
0.43115670, # Cl
0.47308269, # Ar
0.17105469, # K (4th)
0.20276244, # Ca
0.21007322, # Sc
0.21739647, # Ti
0.22471039, # V
0.23201501, # Cr
0.23933969, # Mn
0.24665638, # Fe
0.25398255, # Co
0.26128863, # Ni
0.26859476, # Cu
0.27592565, # Zn
0.30762999, # Ga
0.33931580, # Ge
0.37235985, # As
0.40273549, # Se
0.43445776, # Br
0.46611708, # Kr
0.15585079, # Rb (5th)
0.18649324, # Sr
0.19356210, # Y
0.20063311, # Zr
0.20770522, # Nb
0.21477254, # Mo
0.22184614, # Tc
0.22891872, # Ru
0.23598621, # Rh
0.24305612, # Pd
0.25013018, # Ag
0.25719937, # Cd
0.28784780, # In
0.31848673, # Sn
0.34912431, # Sb
0.37976593, # Te
0.41040808, # I
0.44105777, # Xe
0.05019332, # Cs (6th)
0.06762570, # Ba
0.08504445, # La
0.10247736, # Ce
0.11991105, # Pr
0.13732772, # Nd
0.15476297, # Pm
0.17218265, # Sm
0.18961288, # Eu
0.20704760, # Gd
0.22446752, # Tb
0.24189645, # Dy
0.25932503, # Ho
0.27676094, # Er
0.29418231, # Tm
0.31159587, # Yb
0.32902274, # Lu
0.34592298, # Hf
0.36388048, # Ta
0.38130586, # W
0.39877476, # Re
0.41614298, # Os
0.43364510, # Ir
0.45104014, # Pt
0.46848986, # Au
0.48584550, # Hg
0.12526730, # Tl
0.14268677, # Pb
0.16011615, # Bi
0.17755889, # Po
0.19497557, # At
0.21240778, # Rn
0.07263525, # Fr (7th)
0.09422158, # Ra
0.09920295, # Ac
0.10418621, # Th
0.14235633, # Pa
0.16394294, # U
0.18551941, # Np
0.22370139, # Pu
0.25110000, # Am
0.25030000, # Cm
0.28840000, # Bk
0.31000000, # Cf
0.33160000, # Es
0.35320000, # Fm
0.36820000, # Md
0.39630000, # No
0.40140000, # Lr
0.00000000, # Rf
0.00000000, # Db
0.00000000, # Sg
0.00000000, # Bh
0.00000000, # Hs
0.00000000, # Mt
0.00000000, # Ds
0.00000000, # Rg
0.00000000, # Cn
0.00000000, # Nh
0.00000000, # Fl
0.00000000, # Lv
0.00000000, # Mc
0.00000000, # Ts
0.00000000, # Og
]
return torch.tensor(_GAM, dtype=dtype, device=device, requires_grad=False)
