# This file is part of tad-mctc.
#
# 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: Charges
=============
This module contains the following constants:
- number of core electrons for GFN
- effective nuclear charges from the def2-ECPs (DFT-D4 reference polarizibilities)
- charge of the valence shell (dipole moment in GFN)
"""
from __future__ import annotations
import torch
__all__ = ["ECORE", "ZEFF", "ZVALENCE"]
def ECORE(
device: torch.device | None = None, dtype: torch.dtype | None = torch.int8
) -> torch.Tensor:
"""Number of core electrons."""
if dtype is None:
dtype = torch.int8
# fmt: off
_ECORE = [
0, # dummy
0, 0, # 1-2
2, 2, 2, 2, 2, 2, 2, 2, # 3-10
10, 10, 10, 10, 10, 10, 10, 10, # 11-18
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, # 19-29
28, 28, 28, 28, 28, 28, 28, # 30-36
36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, # 37-47
46, 46, 46, 46, 46, 46, 46, # 48-54
54, 54, # 55-56
54, 54, 54, 54, 54, 54, 54, 54, 54, 54, 54, 54, 54, 54, 54, # 57-71
68, 68, 68, 68, 68, 68, 68, 68, # 72-79
78, 78, 78, 78, 78, 78, 78, # 80-86
]
# fmt: on
return torch.tensor(_ECORE, dtype=dtype, device=device, requires_grad=False)
[docs]
def ZEFF(
device: torch.device | None = None, dtype: torch.dtype | None = torch.int8
) -> torch.Tensor:
"""Effective nuclear charges from the def2-ECPs."""
if dtype is None:
dtype = torch.int8
# fmt: off
_ZEFF = [
0, # None
1, 2, # H-He
3, 4, 5, 6, 7, 8, 9,10, # Li-Ne
11,12, 13,14,15,16,17,18, # Na-Ar
19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36, # K-Kr
9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26, # Rb-Xe
9,10,11,30,31,32,33,34,35,36,37,38,39,40,41,42,43, # Cs-Lu
12,13,14,15,16,17,18,19,20,21,22,23,24,25,26, # Hf-Rn
# just copy and paste from above
9,10,11,30,31,32,33,34,35,36,37,38,39,40,41,42,43, # Fr-Lr
12,13,14,15,16,17,18,19,20,21,22,23,24,25,26 # Rf-Og
]
# fmt: on
return torch.tensor(_ZEFF, dtype=dtype, device=device, requires_grad=False)
def ZVALENCE(
device: torch.device | None = None, dtype: torch.dtype | None = torch.int8
) -> torch.Tensor:
"""Charge of the valence shell."""
if dtype is None:
dtype = torch.int8
# fmt: off
_ZVALENCE = [
0, # dummy
1, 2, # 1-2
1, 2, 3, 4, 5, 6, 7, 8, # 3-10
1, 2, 3, 4, 5, 6, 7, 8, # 11-18
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, # 19-29
2, 3, 4, 5, 6, 7, 8, # 30-36
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, # 37-47
2, 3, 4, 5, 6, 7, 8, # 48-54
1, 2, # 55-56
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, # 56-71
4, 5, 6, 7, 8, 9, 10, 11, # 72-79
2, 3, 4, 5, 6, 7, 8, # 80-86
]
# fmt: on
return torch.tensor(
_ZVALENCE, dtype=dtype, device=device, requires_grad=False
)
