Merge pull request #2 from nomad-coe/magnetic_properties

Magnetic properties

runschema/calculation.py

@@ -2029,6 +2029,206 @@ class RadiusOfGyration(AtomicGroup):
     )
 
 
+class MagneticShielding(MSection):
+    """
+    Section containing the information of magnetic shielding tensors. This is the nuclear
+    response of a material to shield the effects of an applied external field. It is:
+
+        B_induced = - magnetic_shielding * B_external
+
+    The isotropic part can be calculated as 1 / 3 * Tr(magnetic_shielding).
+
+    See, e.g, https://pubs.acs.org/doi/10.1021/cr300108a.
+    """
+
+    m_def = Section(validate=False)
+
+    value = Quantity(
+        type=np.float64,
+        shape=["n_atoms", 3, 3],
+        unit="dimensionless",
+        description="""
+        Value of the magnetic shielding tensor per atom. The first index runs for all the
+        atoms in the unit cell, while 3x3 refers to each axis direction. This quantity
+        relates with the induced magnetic field in the presence of an external magnetic as:
+
+            B_induced = - magnetic_shielding * B_external
+        """,
+    )
+
+    isotropic_value = Quantity(
+        type=np.float64,
+        shape=["n_atoms"],
+        unit="dimensionless",
+        description="""
+        Value of the isotropic part of the magnetic shielding tensor per atom. The first
+        index runs for all the atoms in the unit cell. This quantity relates with magnetic
+        shielding tensor as:
+
+            isotropic_value = 1 / 3 * Tr(value)
+
+        This part is relevant for solution state NMR or for powdered solids under magnetic
+        angle spinning conditions.
+        """,
+    )
+
+
+class ElectricFieldGradient(MSection):
+    """
+    Section containing the information of electric field gradient tensors. These tensors
+    are relevant for nuclear magnetic responses and address the interaction between the
+    quadrupole moment of the nucleus and the electric field gradient (EFG) at the nucleus
+    position generated by the surrounding charges.
+
+    The eigenvalues of these tensors can be used to compute the quadrupolar coupling constant
+    and the asymmetry parameter.
+
+    See, e.g, https://pubs.acs.org/doi/10.1021/cr300108a.
+    """
+
+    # TODO generalize this to other cases
+
+    m_def = Section(validate=False)
+
+    contribution = Quantity(
+        type=MEnum("total", "local", "non_local"),
+        description="""
+        Type of contribution to the electric field gradient (EFG). The total EFG is
+        composed of `local` and `non_local` contributions.
+        """,
+    )
+
+    value = Quantity(
+        type=np.float64,
+        shape=["n_atoms", 3, 3],
+        unit="volt / meter ** 2",
+        description="""
+        Value of the electric field gradient (EFG) for each `contribution` per unit area.
+        The first index runs for all the atoms in the unit cell, while 3x3 refers to each
+        axis direction.
+        """,
+    )
+
+    quadrupolar_coupling_constant = Quantity(
+        type=np.float64,
+        shape=["n_atoms"],
+        description="""
+        Quadrupolar coupling constant for each atom in the unit cell. It is computed from
+        the eigenvalues of the EFG tensor as:
+
+            quadrupolar_coupling_constant = efg_zz * e * Z / h
+
+        where efg_zz is the largest eigenvalue of the EFG tensor, Z is the atomic number.
+        """,
+    )
+
+    asymmetry_parameter = Quantity(
+        type=np.float64,
+        shape=["n_atoms"],
+        description="""
+        Asymmetry parameter for each atom in the unit cell. It is computed from the
+        eigenvalues of the EFG tensor as:
+
+            asymmetry_parameter = (efg_xx - efg_yy) / efg_zz
+
+        where efg_xx, efg_yy and efg_zz are the eigenvalues of the EFG tensor ordered
+        such that |efg_zz| > |efg_yy| > |efg_xx|.
+        """,
+    )
+
+
+class SpinSpinCoupling(MSection):
+    """
+    Section containing the information of spin-spin couplings. These are the indirect
+    interactions between 2 nuclear spins that arises from hyperfine interactions between
+    the nuclei and local electrons.
+
+    Synonyms:
+        - IndirectSpinSpinCoupling
+    """
+
+    # TODO extend this to other spin-spin coupling types besides indirect (which is useful in NMR)
+
+    m_def = Section(validate=False)
+
+    contribution = Quantity(
+        type=MEnum(
+            "total",
+            "direct_dipolar",
+            "fermi_contact",
+            "orbital_diamagnetic",
+            "orbital_paramagnetic",
+            "spin_dipolar",
+        ),
+        description="""
+        Type of contribution to the indirect spin-spin coupling. The total indirect spin-spin
+        coupling is composed of:
+
+            `total` = `direct_dipolar` + J_coupling
+
+        Where the J_coupling is:
+            J_coupling = `fermi_contact`
+                        + `spin_dipolar`
+                        + `orbital_diamagnetic`
+                        + `orbital_paramagnetic`
+
+        See https://pubs.acs.org/doi/full/10.1021/cr300108a.
+        """,
+    )
+
+    value = Quantity(
+        type=np.float64,
+        shape=["n_atoms", "n_atoms", 3, 3],
+        unit="joule",
+        description="""
+        Value of the indirect spin-spin couplings for each contribution. The first and second
+        indices run for all the combinations of pairs of atoms in the unit cell, while
+        3x3 refers to each axis direction.
+        """,
+    )
+
+    reduced_value = Quantity(
+        type=np.float64,
+        shape=["n_atoms", "n_atoms", 3, 3],
+        unit="kelvin**2 / joule",
+        description="""
+        Reduced value of the indirect spin-spin couplings for each contribution. The first and second
+        indices run for all the combinations of pairs of atoms in the unit cell, while
+        3x3 refers to each axis direction. It relates with the normal value as:
+
+            reduced_value = value / (gyromagnetic_ratio_i * gyromagnetic_ratio_j * 2 * np.pi * hbar)
+
+        where i, j runs for each atom in the unit cell.
+        """,
+    )
+
+
+class MagneticSusceptibility(MSection):
+    """
+    Section containing the information of magnetic susceptibility tensor. Degree of
+    magnetization of a material in the presence of a magnetic field.
+    """
+
+    # TODO currently only the macroscopic quantity is being supported
+
+    m_def = Section(validate=False)
+
+    scale_dimension = Quantity(
+        type=MEnum("microscopic", "macroscopic"),
+        description="""
+        Identifier of the scale dimension of the magnetic susceptibility tensor.
+        """,
+    )
+
+    value = Quantity(  # TODO extend this to microscopic contributions
+        type=np.float64,
+        shape=[3, 3],
+        description="""
+        Value of the magnetic susceptibility. The 3x3 refers to each axis direction.
+        """,
+    )
+
+
 class BaseCalculation(ArchiveSection):
     """
     Contains computed properties of a configuration as defined by the corresponding
@@ -2190,6 +2390,18 @@ class BaseCalculation(ArchiveSection):
 
     radius_of_gyration = SubSection(sub_section=RadiusOfGyration.m_def, repeats=True)
 
+    magnetic_shielding = SubSection(sub_section=MagneticShielding.m_def, repeats=True)
+
+    electric_field_gradient = SubSection(
+        sub_section=ElectricFieldGradient.m_def, repeats=True
+    )
+
+    spin_spin_coupling = SubSection(sub_section=SpinSpinCoupling.m_def, repeats=True)
+
+    magnetic_susceptibility = SubSection(
+        sub_section=MagneticSusceptibility.m_def, repeats=True
+    )
+
     volume = Quantity(
         type=np.dtype(np.float64),
         shape=[],

runschema/method.py

@@ -2728,6 +2728,31 @@ class Method(ArchiveSection):
 
     m_def = Section(validate=False)
 
+    label = Quantity(
+        type=MEnum("DFT", "TB", "GW", "DMFT", "BSE", "kMC", "NMR"),
+        description="""
+        Label to identify the method applied in the simulation. Allowed values are:
+
+        | Label | Name | Reference |
+
+        | ----- | ---- | ----------- |
+
+        | `'DFT'` | Density Functional Theory | https://en.wikipedia.org/wiki/Density_functional_theory |
+
+        | `'TB'` | Tight-Binding models | https://en.wikipedia.org/wiki/Tight_binding |
+
+        | `'GW'` | GW approximation | https://en.wikipedia.org/wiki/GW_approximation |
+
+        | `'DMFT'` | Dynamical Mean-Field Theory | https://en.wikipedia.org/wiki/GW_approximation |
+
+        | `'BSE'` | Bethe-Salpeter Equation | https://en.wikipedia.org/wiki/Bethe-Salpeter_equation |
+
+        | `'kMC'` | Kinetic Monte Carlo |https://en.wikipedia.org/wiki/Kinetic_Monte_Carlo |
+
+        | `'NMR'` | Nuclear Magnetic Resonance | https://en.wikipedia.org/wiki/Nuclear_magnetic_resonance |
+        """,
+    )
+
     stress_tensor_method = Quantity(
         type=str,
         shape=[],