def corr_KC():
atoms = graphene_nanoribbon(1,
1,
type='armchair',
C_C=bond,
saturated=False)
atoms.rotate([1, 0, 0], np.pi / 2, rotate_cell=True)
if edge == 'ac':
atoms.rotate([0, 0, 1], -np.pi / 2, rotate_cell=True)
del atoms[[0, 3]]
trans_idx = 1
elif edge == 'zz':
del atoms[[1, 0]]
trans_idx = 0
atoms.set_cell([20, 20, 10])
atoms.center()
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
add_KC = KC_potential_p(params, True)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters=lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
#plot_posits(atoms, edge, bond)
trans_vec = trans_atomsKC(atoms.positions[trans_idx], edge, bond)
atoms.translate(trans_vec)
#plot_posits(atoms, edge, bond)
init_pos = atoms.positions.copy()
r_around = init_pos[trans_idx]
#thetas = np.linspace(0, np.pi/3, 7) #, endpoint = False)
#thetas_deg = np.array([1,3,5,7,9,11,12,13,15,17,43,45,47,48,49,51,57,55,57,59])
thetas_deg = np.array([
.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5, 11.5, 12.5,
13.5, 14.5, 15.5, 16.5, 17.5, 18.5, 19.5
])
traj = PickleTrajectory(path + '%s_corr_twist_thetas_(%.1f-%.1f).traj' \
%(edge, np.min(thetas_deg),
np.max(thetas_deg)), 'w', atoms)
n = 100
for i, theta_deg in enumerate(thetas_deg):
fname = path + 'corr_%s_theta=%.2f.data' % (edge, theta_deg)
print 'Calculating theta = %.2f' % (theta_deg)
theta = theta_deg / 360 * np.pi * 2
print 'time ' + str(datetime.now().time())
atoms.positions = init_pos
atoms.rotate([0, 0, 1], theta, center=r_around)
rot_init_pos = atoms.positions.copy()
lat_vec_theta1 = lat_vec1.copy()
lat_vec_theta2 = lat_vec2.copy()
trans_vec2 = lat_vec_theta2.copy() / n
data = np.zeros((n, n))
for k in range(n):
atoms.positions = rot_init_pos
atoms.translate(lat_vec_theta1 * float(k) / n)
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
print '%.1f percent done' % (100 * float(k) / n)
for l in range(n):
atoms.translate(trans_vec2)
emin = get_optimal_h(atoms, len(atoms), dyn=False)[0]
data[
k,
l] = emin #atoms.get_potential_energy()/len(atoms) #emin #
saveAndPrint(atoms, traj, False)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin \n\
the lattice vectors are l1 = [%.5f, %.5f, %.5f] and l2 = [%.5f, %.5f, %.5f], they are divided in %i parts. data[i,j,:] \n\
-> atoms pos += l1/n*i + l2/n*j, initial position is such that atom1 is in middle if hexagon.' \
%(edge, len(atoms), lat_vec_theta1[0], lat_vec_theta1[1], lat_vec_theta1[2], \
lat_vec_theta2[0], lat_vec_theta2[1], lat_vec_theta2[2], n)
np.savetxt(fname, data, header=header)
def corr_KC(width, edge):
#width = 5
#edge = 'ac'
params0 = get_simulParams(edge)[-1]
bond = params0['bond']
atoms = create_stucture(1, width, edge, key='top', a=bond)[0]
atoms.set_cell([40, 40, 20])
atoms.center()
atoms.positions[:, 2] = 3.4
h_t = []
for i in range(len(atoms)):
if atoms[i].number == 1:
h_t.append(i)
del atoms[h_t]
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
add_KC = KC_potential_p(params)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters=lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
trans_vec = trans_atomsKC(atoms.positions[0], edge, bond)
atoms.translate(trans_vec)
init_pos = atoms.positions.copy()
middle = [
np.average(init_pos[:, 0]),
np.average(init_pos[:, 1]),
np.average(init_pos[:, 2])
]
thetas = np.linspace(np.pi / 2, np.pi, 91)
L = 4 * bond
ds = .05
n = int(L / ds)
for i, theta in enumerate(thetas):
fname = path + 'corr_w=%02d_%s_theta=%.2f.data' % (width, edge, theta /
(2 * np.pi) * 360)
if not os.path.isfile(fname):
print 'Calculating w=%i, theta = %.2f' % (width, theta /
(2 * np.pi) * 360)
atoms.positions = init_pos
atoms.rotate([0, 0, 1], theta, center=middle)
trans_vec = np.array([-np.sin(theta), np.cos(theta), 0])
data = np.zeros((n, 3))
for j in range(n):
atoms.translate(ds * trans_vec)
emin, hmin = get_optimal_h(atoms, len(atoms), dyn=False)
data[j, :] = [j * ds, emin, hmin]
#plot_posits(atoms, edge, bond)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin' % (
edge, len(atoms))
np.savetxt(fname, data, header=header)
def corr_KC(width, edge):
params0 = get_simulParams(edge)[-1]
bond = params0['bond']
'''
atoms = graphene_nanoribbon(1, 1, type= 'armchair', C_C=bond, saturated = False)
atoms.rotate([1,0,0], np.pi/2, rotate_cell = True)
atoms.rotate([0,0,1], -np.pi/2, rotate_cell = True)
atoms.set_cell([20, 20, 10])
atoms.center()
del atoms[[2,3]]
'''
atoms = create_stucture(2, width, edge, key='top', a=bond)[0]
atoms.set_cell([70, 70, 20])
atoms.center()
atoms.positions[:, 2] = 3.4
h_t = []
for i in range(len(atoms)):
if atoms[i].number == 1:
h_t.append(i)
del atoms[h_t]
#view(atoms)
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
params['no_edge_neigh'] = True
add_KC = KC_potential_p(params)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters=lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
#plot_posits(atoms, edge, bond)
trans_vec = trans_atomsKC(atoms.positions[0], edge, bond)
atoms.translate(trans_vec)
#plot_posits(atoms, edge, bond)
#exit()
init_pos = atoms.positions.copy()
r_around = init_pos[1]
thetas = np.linspace(0, np.pi / 3, 61)
n = 15
lat_vec1 = np.array([3. / 2 * bond, np.sqrt(3) / 2 * bond, 0.])
lat_vec2 = np.array([3. / 2 * bond, -np.sqrt(3) / 2 * bond, 0.])
for i, theta in enumerate(thetas):
fname = path + 'corr_%s_theta=%.2f.data' % (edge, theta /
(2 * np.pi) * 360)
#if not os.path.isfile(fname):
print 'Calculating theta = %.2f' % (theta / (2 * np.pi) * 360)
atoms.positions = init_pos
atoms.rotate([0, 0, 1], theta, center=r_around)
R = np.array([[np.cos(theta), -np.sin(theta), 0.],
[np.sin(theta), np.cos(theta), 0.], [0., 0., 1.]])
lat_vec_theta1 = np.dot(R, lat_vec1.copy())
lat_vec_theta2 = np.dot(R, lat_vec2.copy())
#trans_vec1 = lat_vec_theta1.copy()/n
trans_vec2 = lat_vec_theta2.copy() / n
data = np.zeros((n, n))
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
for k in range(n):
atoms.positions = init_pos
atoms.translate(lat_vec_theta1 * float(k) / n)
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
#print trans_vec1*float(k)/n, k, n, float(k)/n
for l in range(n):
atoms.translate(trans_vec2)
emin, hmin = get_optimal_h(atoms, len(atoms), dyn=False)
#data[k,l,:] = [emin, hmin]
data[k, l] = emin #atoms.get_potential_energy()/len(atoms)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin \n\
the lattice vectors are l1 = [%.5f, %.5f, %.5f] and l2 = [%.5f, %.5f, %.5f], they are divided in %i parts. data[i,j,:] \n\
-> atoms pos += l1/n*i + l2/n*j, initial position is such that atom1 is in middle if hexagon.' \
%(edge, len(atoms), lat_vec_theta1[0], lat_vec_theta1[1], lat_vec_theta1[2], \
lat_vec_theta2[0], lat_vec_theta2[1], lat_vec_theta2[2], n)
np.savetxt(fname, data, header=header)
def corr_KC():
atoms = graphene_nanoribbon(1, 1, type= 'armchair', C_C=bond, saturated = False)
atoms.rotate([1,0,0], np.pi/2, rotate_cell = True)
if edge == 'ac':
atoms.rotate([0,0,1], -np.pi/2, rotate_cell = True)
del atoms[[0,3]]
trans_idx = 1
elif edge == 'zz':
del atoms[[1,0]]
trans_idx = 0
atoms.set_cell([20, 20, 10])
atoms.center()
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
add_KC = KC_potential_p(params, True)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters = lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
#plot_posits(atoms, edge, bond)
trans_vec = trans_atomsKC(atoms.positions[trans_idx], edge, bond)
atoms.translate(trans_vec)
#plot_posits(atoms, edge, bond)
init_pos = atoms.positions.copy()
r_around = init_pos[trans_idx]
#thetas = np.linspace(0, np.pi/3, 7) #, endpoint = False)
#thetas_deg = np.array([1,3,5,7,9,11,12,13,15,17,43,45,47,48,49,51,57,55,57,59])
thetas_deg = np.array([.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5,12.5,13.5,14.5,15.5,16.5,17.5,18.5,19.5])
traj = PickleTrajectory(path + '%s_corr_twist_thetas_(%.1f-%.1f).traj' \
%(edge, np.min(thetas_deg),
np.max(thetas_deg)), 'w', atoms)
n = 100
for i, theta_deg in enumerate(thetas_deg):
fname = path + 'corr_%s_theta=%.2f.data' %(edge, theta_deg)
print 'Calculating theta = %.2f' %(theta_deg)
theta = theta_deg/360*np.pi*2
print 'time ' + str(datetime.now().time())
atoms.positions = init_pos
atoms.rotate([0,0,1], theta, center = r_around)
rot_init_pos = atoms.positions.copy()
lat_vec_theta1 = lat_vec1.copy()
lat_vec_theta2 = lat_vec2.copy()
trans_vec2 = lat_vec_theta2.copy()/n
data = np.zeros((n,n))
for k in range(n):
atoms.positions = rot_init_pos
atoms.translate(lat_vec_theta1*float(k)/n)
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
print '%.1f percent done' %(100*float(k)/n)
for l in range(n):
atoms.translate(trans_vec2)
emin = get_optimal_h(atoms, len(atoms), dyn = False)[0]
data[k,l] = emin #atoms.get_potential_energy()/len(atoms) #emin #
saveAndPrint(atoms, traj, False)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin \n\
the lattice vectors are l1 = [%.5f, %.5f, %.5f] and l2 = [%.5f, %.5f, %.5f], they are divided in %i parts. data[i,j,:] \n\
-> atoms pos += l1/n*i + l2/n*j, initial position is such that atom1 is in middle if hexagon.' \
%(edge, len(atoms), lat_vec_theta1[0], lat_vec_theta1[1], lat_vec_theta1[2], \
lat_vec_theta2[0], lat_vec_theta2[1], lat_vec_theta2[2], n)
np.savetxt(fname, data, header = header)
def corr_KC(width, edge):
#width = 5
#edge = 'ac'
params0 = get_simulParams(edge)[-1]
bond = params0['bond']
atoms = create_stucture(1, width, edge, key = 'top', a = bond)[0]
atoms.set_cell([40, 40, 20])
atoms.center()
atoms.positions[:,2] = 3.4
h_t = []
for i in range(len(atoms)):
if atoms[i].number == 1:
h_t.append(i)
del atoms[h_t]
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
add_KC = KC_potential_p(params)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters = lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
trans_vec = trans_atomsKC(atoms.positions[0], edge, bond)
atoms.translate(trans_vec)
init_pos = atoms.positions.copy()
middle = [np.average(init_pos[:,0]),
np.average(init_pos[:,1]),
np.average(init_pos[:,2])]
thetas = np.linspace(np.pi/2, np.pi, 91)
L = 4*bond
ds = .05
n = int(L/ds)
for i, theta in enumerate(thetas):
fname = path + 'corr_w=%02d_%s_theta=%.2f.data' %(width, edge, theta/(2*np.pi)*360)
if not os.path.isfile(fname):
print 'Calculating w=%i, theta = %.2f' %(width, theta/(2*np.pi)*360)
atoms.positions = init_pos
atoms.rotate([0,0,1], theta, center = middle)
trans_vec = np.array([-np.sin(theta), np.cos(theta), 0])
data = np.zeros((n, 3))
for j in range(n):
atoms.translate(ds*trans_vec)
emin, hmin = get_optimal_h(atoms, len(atoms), dyn = False)
data[j, :] = [j*ds, emin, hmin]
#plot_posits(atoms, edge, bond)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin' %(edge, len(atoms))
np.savetxt(fname, data, header = header)
def corr_KC(width, edge):
params0 = get_simulParams(edge)[-1]
bond = params0['bond']
'''
atoms = graphene_nanoribbon(1, 1, type= 'armchair', C_C=bond, saturated = False)
atoms.rotate([1,0,0], np.pi/2, rotate_cell = True)
atoms.rotate([0,0,1], -np.pi/2, rotate_cell = True)
atoms.set_cell([20, 20, 10])
atoms.center()
del atoms[[2,3]]
'''
atoms = create_stucture(2, width, edge, key = 'top', a = bond)[0]
atoms.set_cell([70, 70, 20])
atoms.center()
atoms.positions[:,2] = 3.4
h_t = []
for i in range(len(atoms)):
if atoms[i].number == 1:
h_t.append(i)
del atoms[h_t]
#view(atoms)
params = {}
params['positions'] = atoms.positions
params['chemical_symbols'] = atoms.get_chemical_symbols()
params['ia_dist'] = 10
params['edge'] = edge
params['bond'] = bond
params['ncores'] = 2
params['no_edge_neigh'] = True
add_KC = KC_potential_p(params)
constraints = []
for i in range(len(atoms)):
fix_l = FixedLine(i, [0., 0., 1.])
constraints.append(fix_l)
constraints.append(add_KC)
lamp_parameters = get_lammps_params(H=False)
calc = LAMMPS(parameters = lamp_parameters) #, files=['lammps.data'])
atoms.set_calculator(calc)
atoms.set_constraint(constraints)
#dyn = BFGS(atoms, trajectory = 'test.traj')
#dyn.run(fmax=0.05)
#plot_posits(atoms, edge, bond)
trans_vec = trans_atomsKC(atoms.positions[0], edge, bond)
atoms.translate(trans_vec)
#plot_posits(atoms, edge, bond)
#exit()
init_pos = atoms.positions.copy()
r_around = init_pos[1]
thetas = np.linspace(0, np.pi/3, 61)
n = 15
lat_vec1 = np.array([3./2*bond, np.sqrt(3)/2*bond, 0.])
lat_vec2 = np.array([3./2*bond, -np.sqrt(3)/2*bond, 0.])
for i, theta in enumerate(thetas):
fname = path + 'corr_%s_theta=%.2f.data' %(edge, theta/(2*np.pi)*360)
#if not os.path.isfile(fname):
print 'Calculating theta = %.2f' %(theta/(2*np.pi)*360)
atoms.positions = init_pos
atoms.rotate([0,0,1], theta, center = r_around)
R = np.array([[np.cos(theta), -np.sin(theta), 0.],
[np.sin(theta), np.cos(theta), 0.],
[0., 0., 1.]])
lat_vec_theta1 = np.dot(R, lat_vec1.copy())
lat_vec_theta2 = np.dot(R, lat_vec2.copy())
#trans_vec1 = lat_vec_theta1.copy()/n
trans_vec2 = lat_vec_theta2.copy()/n
data = np.zeros((n,n))
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
for k in range(n):
atoms.positions = init_pos
atoms.translate(lat_vec_theta1*float(k)/n)
#plot_posits(atoms, edge, bond, vecs = [lat_vec_theta1, lat_vec_theta2])
#print trans_vec1*float(k)/n, k, n, float(k)/n
for l in range(n):
atoms.translate(trans_vec2)
emin, hmin = get_optimal_h(atoms, len(atoms), dyn = False)
#data[k,l,:] = [emin, hmin]
data[k,l] = emin #atoms.get_potential_energy()/len(atoms)
header = '%s runs along x-dir, angle measured from x-axis, natoms = %i. x (Angs), e (eV/atom), hmin \n\
the lattice vectors are l1 = [%.5f, %.5f, %.5f] and l2 = [%.5f, %.5f, %.5f], they are divided in %i parts. data[i,j,:] \n\
-> atoms pos += l1/n*i + l2/n*j, initial position is such that atom1 is in middle if hexagon.' \
%(edge, len(atoms), lat_vec_theta1[0], lat_vec_theta1[1], lat_vec_theta1[2], \
lat_vec_theta2[0], lat_vec_theta2[1], lat_vec_theta2[2], n)
np.savetxt(fname, data, header = header)
