Mannul Collection

  • 安装：conda install -c matsci pymatgen

  • 创建分子结构与晶体结构:

    • 自己创建
    from pymatgen import Lattice, Structure, Molecule

coords = [[0, 0, 0], [0.75,0.5,0.75]]
lattice = Lattice.from_parameters(a=3.84, b=3.84, c=3.84, alpha=120,
                                  beta=90, gamma=60)
struct = Structure(lattice, ["Si", "Si"], coords)

coords = [[0.000000, 0.000000, 0.000000],
          [0.000000, 0.000000, 1.089000],
          [1.026719, 0.000000, -0.363000],
          [-0.513360, -0.889165, -0.363000],
          [-0.513360, 0.889165, -0.363000]]
 methane = Molecule(["C", "H", "H", "H", "H"], coords)

    • 读入和写出：

      # Read a POSCAR and write to a CIF.
structure = Structure.from_file("POSCAR")
structure.to(filename="CsCl.cif")

# Read an xyz file and write to a Gaussian Input file.
methane = Molecule.from_file("methane.xyz")
 methane.to(filename="methane.gjf")

      其他方法：

      from pymatgen.io.cif import CifParser
parser = CifParser("mycif.cif")
 structure = parser.get_structures()[0]

      from pymatgen.io.vasp import Poscar
poscar = Poscar.from_file("POSCAR")
 structure = poscar.structure

      from pymatgen.io.vasp import Poscar
from pymatgen.io.cif import CifWriter

p = Poscar.from_file('POSCAR')
w = CifWriter(p.struct)
 w.write_file('mystructure.cif')

      from pymatgen.io.xyz import XYZ
from pymatgen.io.gaussian import GaussianInput

xyz = XYZ.from_file('methane.xyz')
gau = GaussianInput(xyz.molecule,
                    route_parameters={'SP': "", "SCF": "Tight"})
 gau.write_file('methane.inp')

      只要安装了OpenBabel，就可以支持100多种格式的读取与相互转化

    There is also support for more than 100 file types via the OpenBabel interface. But that requires you to install openbabel with Python bindings. Please see the installation guide.

  • 改变结构或分子：

    • 对分子的操作：

      # Change the specie at site position 1 to a fluorine atom.
structure[1] = "F"
molecule[1] = "F"

# Change species and coordinates (fractional assumed for Structures,
# cartesian for Molecules)
structure[1] = "Cl", [0.51, 0.51, 0.51]
molecule[1] = "F", [1.34, 2, 3]

# Structure/Molecule also supports typical list-like operators,
# such as reverse, extend, pop, index, count.
structure.reverse()
molecule.reverse()

structure.append("F", [0.9, 0.9, 0.9])
molecule.append("F", [2.1, 3.2 4.3])

  • 对结构的操作：(超胞，单胞，NEB搜索)

    # Make a supercell
structure.make_supercell([2, 2, 2])

# Get a primitive version of the Structure
structure.get_primitive_structure()

# Interpolate between two structures to get 10 structures (typically for
# NEB calculations.
structure.interpolate(another_structure, nimages=10)

  • 高通量转化：

    pymatgen.alchemy.materials.TransformedStructure可通过cif或POSCAR生成转化结构

    pymatgen.alchemy.transmuters.StandardTransmuter通过cif或POSCAR生成变形结构

    应用例：将所有铁元素换为锰并移除所有Li元素

    from pymatgen.alchemy.transmuters import CifTransmuter
from pymatgen.transformations.standard_transformations import SubstitutionTransformation, RemoveSpeciesTransformation

trans = []
trans.append(SubstitutionTransformation({"Fe":"Mn"}))
trans.append(RemoveSpecieTransformation(["Li"]))
transmuter = CifTransmuter.from_filenames(["MultiStructure.cif"], trans)
structures = transmuter.transformed_structures

  • 兼容性：Mixing GGA and GGA+U runs

    • Ceder组提出的混合GGA和GGA+U的计算，例如为了生成$\ce{Fe-P-O}$相图，金属相如$\ce{Fe,Fe_xP}$适合使用标准GGA，而氧化物如$\ce{FeO_y,Fe_xP_yO_z}$则适合GGA+U

    • 在 pymatgen.io.vasp.sets模块支持生成vasp输入文件

    • 例如如果需要计算$\ce{Fe-P-O}$相图需要生成的一系列vasp输入文件可通过以下脚本实现

      from pymatgen.entries.compatibility import MaterialsProjectCompatibility
from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter

# Get unprocessed_entries using pymatgen.borg or other means.

# Process the entries for compatibility
compat = MaterialsProjectCompatibility()
processed_entries = compat.process_entries(unprocessed_entries)

# These few lines generates the phase diagram using the ComputedEntries.
pd = PhaseDiagram(processed_entries)
plotter = PDPlotter(pd)
plotter.show()

    • 在计算完$\ce{Li-O}$以后可分析结果相图：

      from pymatgen.borg.hive import VaspToComputedEntryDrone
from pymatgen.borg.queen import BorgQueen
from pymatgen.analysis.phase_diagram import PhaseDiagram, PDPlotter

# These three lines assimilate the data into ComputedEntries.
drone = VaspToComputedEntryDrone()
queen = BorgQueen(drone, "Li-O_runs", 2)
entries = queen.get_data()

# It's a good idea to perform a save_data, especially if you just assimilated
# a large quantity of data which took some time. This allows you to reload
# the data using a BorgQueen initialized with only the drone argument and
# calling queen.load_data("Li-O_entries.json")
queen.save_data("Li-O_entries.json")

# These few lines generates the phase diagram using the ComputedEntries.
pd = PhaseDiagram(entries)
plotter = PDPlotter(pd)
plotter.show()

  • 计算反应能量：

    from pymatgen.apps.borg.hive import VaspToComputedEntryDrone
from pymatgen.apps.borg.queen import BorgQueen
from pymatgen.analysis.reaction_calculator import ComputedReaction

# These three lines assimilate the data into ComputedEntries.
drone = VaspToComputedEntryDrone()
queen = BorgQueen(drone)
queen.load_data("Li-O_entries.json")
entries = queen.get_data()

#Extract the correct entries and compute the reaction.
rcts = filter(lambda e: e.composition.reduced_formula in ["Li", "O2"], entries)
prods = filter(lambda e: e.composition.reduced_formula == "Li2O", entries)
rxn = ComputedReaction(rcts, prods)
print(rxn)
print(rxn.calculated_reaction_energy)

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