Source code for ase.calculators.emt

"""Effective medium theory potential."""

from math import sqrt, exp, log

import numpy as np

from ase.data import chemical_symbols, atomic_numbers
from ase.units import Bohr
from ase.neighborlist import NeighborList
from ase.calculators.calculator import (Calculator, all_changes,
                                        PropertyNotImplementedError)


parameters = {
    #      E0     s0    V0     eta2    kappa   lambda  n0
    #      eV     bohr  eV     bohr^-1 bohr^-1 bohr^-1 bohr^-3
    'Al': (-3.28, 3.00, 1.493, 1.240, 2.000, 1.169, 0.00700),
    'Cu': (-3.51, 2.67, 2.476, 1.652, 2.740, 1.906, 0.00910),
    'Ag': (-2.96, 3.01, 2.132, 1.652, 2.790, 1.892, 0.00547),
    'Au': (-3.80, 3.00, 2.321, 1.674, 2.873, 2.182, 0.00703),
    'Ni': (-4.44, 2.60, 3.673, 1.669, 2.757, 1.948, 0.01030),
    'Pd': (-3.90, 2.87, 2.773, 1.818, 3.107, 2.155, 0.00688),
    'Pt': (-5.85, 2.90, 4.067, 1.812, 3.145, 2.192, 0.00802),
    # extra parameters - just for fun ...
    'H': (-3.21, 1.31, 0.132, 2.652, 2.790, 3.892, 0.00547),
    'C': (-3.50, 1.81, 0.332, 1.652, 2.790, 1.892, 0.01322),
    'N': (-5.10, 1.88, 0.132, 1.652, 2.790, 1.892, 0.01222),
    'O': (-4.60, 1.95, 0.332, 1.652, 2.790, 1.892, 0.00850)}

beta = 1.809  # (16 * pi / 3)**(1.0 / 3) / 2**0.5, preserve historical rounding


[docs]class EMT(Calculator): """Python implementation of the Effective Medium Potential. Supports the following standard EMT metals: Al, Cu, Ag, Au, Ni, Pd and Pt. In addition, the following elements are supported. They are NOT well described by EMT, and the parameters are not for any serious use: H, C, N, O The potential takes a single argument, ``asap_cutoff`` (default: False). If set to True, the cutoff mimics how Asap does it; most importantly the global cutoff is chosen from the largest atom present in the simulation, if False it is chosen from the largest atom in the parameter table. True gives the behaviour of the Asap code and older EMT implementations, although the results are not bitwise identical. """ implemented_properties = ['energy', 'energies', 'forces', 'stress', 'magmom', 'magmoms'] nolabel = True default_parameters = {'asap_cutoff': False} def __init__(self, **kwargs): Calculator.__init__(self, **kwargs) def initialize(self, atoms): self.par = {} self.rc = 0.0 self.numbers = atoms.get_atomic_numbers() if self.parameters.asap_cutoff: relevant_pars = {} for symb, p in parameters.items(): if atomic_numbers[symb] in self.numbers: relevant_pars[symb] = p else: relevant_pars = parameters maxseq = max(par[1] for par in relevant_pars.values()) * Bohr rc = self.rc = beta * maxseq * 0.5 * (sqrt(3) + sqrt(4)) rr = rc * 2 * sqrt(4) / (sqrt(3) + sqrt(4)) self.acut = np.log(9999.0) / (rr - rc) if self.parameters.asap_cutoff: self.rc_list = self.rc * 1.045 else: self.rc_list = self.rc + 0.5 for Z in self.numbers: if Z not in self.par: sym = chemical_symbols[Z] if sym not in parameters: raise NotImplementedError('No EMT-potential for {0}' .format(sym)) p = parameters[sym] s0 = p[1] * Bohr eta2 = p[3] / Bohr kappa = p[4] / Bohr x = eta2 * beta * s0 gamma1 = 0.0 gamma2 = 0.0 for i, n in enumerate([12, 6, 24]): r = s0 * beta * sqrt(i + 1) x = n / (12 * (1.0 + exp(self.acut * (r - rc)))) gamma1 += x * exp(-eta2 * (r - beta * s0)) gamma2 += x * exp(-kappa / beta * (r - beta * s0)) self.par[Z] = {'E0': p[0], 's0': s0, 'V0': p[2], 'eta2': eta2, 'kappa': kappa, 'lambda': p[5] / Bohr, 'n0': p[6] / Bohr**3, 'rc': rc, 'gamma1': gamma1, 'gamma2': gamma2} self.ksi = {} for s1, p1 in self.par.items(): self.ksi[s1] = {} for s2, p2 in self.par.items(): self.ksi[s1][s2] = p2['n0'] / p1['n0'] self.energies = np.empty(len(atoms)) self.forces = np.empty((len(atoms), 3)) self.stress = np.empty((3, 3)) self.sigma1 = np.empty(len(atoms)) self.deds = np.empty(len(atoms)) self.nl = NeighborList([0.5 * self.rc_list] * len(atoms), self_interaction=False) def calculate(self, atoms=None, properties=['energy'], system_changes=all_changes): Calculator.calculate(self, atoms, properties, system_changes) if 'numbers' in system_changes: self.initialize(self.atoms) positions = self.atoms.positions numbers = self.atoms.numbers cell = self.atoms.cell self.nl.update(self.atoms) self.energy = 0.0 self.energies[:] = 0 self.sigma1[:] = 0.0 self.forces[:] = 0.0 self.stress[:] = 0.0 natoms = len(self.atoms) for a1 in range(natoms): Z1 = numbers[a1] p1 = self.par[Z1] ksi = self.ksi[Z1] neighbors, offsets = self.nl.get_neighbors(a1) offsets = np.dot(offsets, cell) for a2, offset in zip(neighbors, offsets): d = positions[a2] + offset - positions[a1] r = sqrt(np.dot(d, d)) if r < self.rc_list: Z2 = numbers[a2] p2 = self.par[Z2] self.interact1(a1, a2, d, r, p1, p2, ksi[Z2]) for a in range(natoms): Z = numbers[a] p = self.par[Z] try: ds = -log(self.sigma1[a] / 12) / (beta * p['eta2']) except (OverflowError, ValueError): self.deds[a] = 0.0 self.energy -= p['E0'] self.energies[a] -= p['E0'] continue x = p['lambda'] * ds y = exp(-x) z = 6 * p['V0'] * exp(-p['kappa'] * ds) self.deds[a] = ((x * y * p['E0'] * p['lambda'] + p['kappa'] * z) / (self.sigma1[a] * beta * p['eta2'])) E = p['E0'] * ((1 + x) * y - 1) + z self.energy += E self.energies[a] += E for a1 in range(natoms): Z1 = numbers[a1] p1 = self.par[Z1] ksi = self.ksi[Z1] neighbors, offsets = self.nl.get_neighbors(a1) offsets = np.dot(offsets, cell) for a2, offset in zip(neighbors, offsets): d = positions[a2] + offset - positions[a1] r = sqrt(np.dot(d, d)) if r < self.rc_list: Z2 = numbers[a2] p2 = self.par[Z2] self.interact2(a1, a2, d, r, p1, p2, ksi[Z2]) self.results['energy'] = self.energy self.results['energies'] = self.energies self.results['free_energy'] = self.energy self.results['forces'] = self.forces if 'stress' in properties: if self.atoms.number_of_lattice_vectors == 3: self.stress += self.stress.T.copy() self.stress *= -0.5 / self.atoms.get_volume() self.results['stress'] = self.stress.flat[[0, 4, 8, 5, 2, 1]] else: raise PropertyNotImplementedError def interact1(self, a1, a2, d, r, p1, p2, ksi): x = exp(self.acut * (r - self.rc)) theta = 1.0 / (1.0 + x) y1 = (0.5 * p1['V0'] * exp(-p2['kappa'] * (r / beta - p2['s0'])) * ksi / p1['gamma2'] * theta) y2 = (0.5 * p2['V0'] * exp(-p1['kappa'] * (r / beta - p1['s0'])) / ksi / p2['gamma2'] * theta) self.energy -= y1 + y2 self.energies[a1] -= (y1 + y2) / 2 self.energies[a2] -= (y1 + y2) / 2 f = ((y1 * p2['kappa'] + y2 * p1['kappa']) / beta + (y1 + y2) * self.acut * theta * x) * d / r self.forces[a1] += f self.forces[a2] -= f self.stress -= np.outer(f, d) self.sigma1[a1] += (exp(-p2['eta2'] * (r - beta * p2['s0'])) * ksi * theta / p1['gamma1']) self.sigma1[a2] += (exp(-p1['eta2'] * (r - beta * p1['s0'])) / ksi * theta / p2['gamma1']) def interact2(self, a1, a2, d, r, p1, p2, ksi): x = exp(self.acut * (r - self.rc)) theta = 1.0 / (1.0 + x) y1 = (exp(-p2['eta2'] * (r - beta * p2['s0'])) * ksi / p1['gamma1'] * theta * self.deds[a1]) y2 = (exp(-p1['eta2'] * (r - beta * p1['s0'])) / ksi / p2['gamma1'] * theta * self.deds[a2]) f = ((y1 * p2['eta2'] + y2 * p1['eta2']) + (y1 + y2) * self.acut * theta * x) * d / r self.forces[a1] -= f self.forces[a2] += f self.stress += np.outer(f, d)