diff --git a/bin/hyper-elasticity.py b/bin/hyper-elasticity.py
index 4760dee..00630c1 100755
--- a/bin/hyper-elasticity.py
+++ b/bin/hyper-elasticity.py
@@ -1,81 +1,81 @@
 #!/usr/bin/env python3
 """
 file   hyper-elasticity.py
 
 @author Till Junge <till.junge@epfl.ch>
 
 @date   16 Jan 2018
 
 @brief  Recreation of GooseFFT's hyper-elasticity.py calculation
 
 @section LICENSE
 
 Copyright © 2018 Till Junge
 
 µSpectre is free software; you can redistribute it and/or
 modify it under the terms of the GNU General Public License as
 published by the Free Software Foundation, either version 3, or (at
 your option) any later version.
 
 µSpectre is distributed in the hope that it will be useful, but
 WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 General Public License for more details.
 
 You should have received a copy of the GNU General Public License
 along with GNU Emacs; see the file COPYING. If not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA 02111-1307, USA.
 """
 
 import sys
 import os
 import numpy as np
 import argparse
 
 sys.path.append(os.path.join(os.getcwd(), "language_bindings/python"))
 import muSpectre as µ
 
 def compute():
     N = [11, 11, 11]
     lens = [1., 1., 1.]
     incl_size = 3
 
     formulation = µ.Formulation.finite_strain
     cell = µ.Cell(N, lens, formulation)
-    hard = µ.material.MaterialHooke3d.make(cell, "hard",
+    hard = µ.material.MaterialLinearElastic1_3d.make(cell, "hard",
                                            210.e9, .33)
-    soft = µ.material.MaterialHooke3d.make(cell, "soft",
+    soft = µ.material.MaterialLinearElastic1_3d.make(cell, "soft",
                                             70.e9, .33)
     for  pixel in cell:
         # if ((pixel[0] >= N[0]-incl_size) and
         #     (pixel[1] < incl_size) and
         #     (pixel[2] >= N[2]-incl_size)):
         if (pixel[0] < 1):
             hard.add_pixel(pixel)
         else:
             soft.add_pixel(pixel)
 
     print("{} pixels in the inclusion".format(hard.size()))
     cell.initialise();
     cg_tol, newton_tol = 1e-8, 1e-5
     maxiter = 40
     verbose = 3
     dF_bar = np.array([[0, .02, 0], [0, 0, 0], [0, 0, 0]])
 
     if formulation == µ.Formulation.small_strain:
         dF_bar = .5*(dF_bar + dF_bar.T)
 
-    test_grad = np.zeros((9, cell.size()))
+    test_grad = np.zeros((9, cell.size))
     test_grad[:,:] = dF_bar.reshape(-1,1)
     print(cell.directional_stiffness(test_grad)[:,:3])
     solver = µ.solvers.SolverCG(cell, cg_tol, maxiter, verbose=False);
     optimize_res = µ.solvers.de_geus(
         cell, dF_bar, solver, newton_tol, verbose)
     print("nb_cg: {}\n{}".format(optimize_res.nb_fev, optimize_res.grad.T[:2,:]))
 
 def main():
     compute()
 
 if __name__ == "__main__":
     main()
diff --git a/bin/small_case.py b/bin/small_case.py
index 406a369..c7be9be 100755
--- a/bin/small_case.py
+++ b/bin/small_case.py
@@ -1,110 +1,110 @@
 #!/usr/bin/env python3
 """
 file   small_case.py
 
 @author Till Junge <till.junge@epfl.ch>
 
 @date   12 Jan 2018
 
 @brief  small case for debugging
 
 @section LICENSE
 
 Copyright © 2018 Till Junge
 
 µSpectre is free software; you can redistribute it and/or
 modify it under the terms of the GNU General Public License as
 published by the Free Software Foundation, either version 3, or (at
 your option) any later version.
 
 µSpectre is distributed in the hope that it will be useful, but
 WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 General Public License for more details.
 
 You should have received a copy of the GNU General Public License
 along with GNU Emacs; see the file COPYING. If not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA 02111-1307, USA.
 """
 
 import sys
 import os
 import numpy as np
 
 sys.path.append(os.path.join(os.getcwd(), "language_bindings/python"))
 import muSpectre as µ
 
 
 resolution = [51, 51]
 center = np.array([r//2 for r in resolution])
 incl = resolution[0]//5
 
 lengths = [7., 5.]
 formulation = µ.Formulation.small_strain
 
 rve = µ.Cell(resolution, lengths, formulation)
-hard = µ.material.MaterialHooke2d.make(
+hard = µ.material.MaterialLinearElastic1_2d.make(
     rve, "hard", 10e9, .33)
-soft = µ.material.MaterialHooke2d.make(
+soft = µ.material.MaterialLinearElastic1_2d.make(
     rve, "soft",  70e9, .33)
 
 
 for i, pixel in enumerate(rve):
     if np.linalg.norm(center - np.array(pixel),2)<incl:
     #if (abs(center - np.array(pixel)).max()<incl or
     #    np.linalg.norm(center/2 - np.array(pixel))<incl):
         hard.add_pixel(pixel)
     else:
         soft.add_pixel(pixel)
 
 tol = 1e-5
 cg_tol = 1e-8
 
 Del0 = np.array([[.0, .0],
                  [0,  .03]])
 if formulation == µ.Formulation.small_strain:
     Del0 = .5*(Del0 + Del0.T)
 maxiter = 401
 verbose = 2
 
 for solvclass in (µ.solvers.SolverCG,
                   µ.solvers.SolverCGEigen,
                   µ.solvers.SolverBiCGSTABEigen,
                   µ.solvers.SolverGMRESEigen,
                   µ.solvers.SolverDGMRESEigen,
                   µ.solvers.SolverMINRESEigen):
     print()
     try:
         solver = solvclass(rve, cg_tol, maxiter, verbose=False)
         r = µ.solvers.newton_cg(rve, Del0, solver, tol, verbose)
         print("nb of {} iterations: {}".format(solver.name(), r.nb_fev))
     except RuntimeError as err:
         print(err)
     try:
         solver = solvclass(rve, cg_tol, maxiter, verbose=False)
         r = µ.solvers.de_geus(rve, Del0, solver, tol, verbose)
         print("nb of {} iterations: {}".format(solver.name(), r.nb_fev))
     except RuntimeError as err:
         print(err)
 
 
 # print(r.grad.T[:3])
 # print(r.stress.T[:3])
 # 
 # print(r.grad.T.shape)
 # import matplotlib.pyplot as plt
 # stress = r.stress.T.reshape(*resolution, 2, 2)
 # def comp_von_mises(arr):
 #     out_arr = np.zeros(resolution)
 #     s11 = arr[:,:,0,0]
 #     s22 = arr[:,:,1,1]
 #     s21_2 = arr[:,:,0,1]*arr[:,:,1,0]
 # 
 #     out_arr[:] = np.sqrt(.5*((s11-s22)**2) + s11**2 + s22**2 + 6*s21_2)
 #     return out_arr
 # 
 # von_mises = comp_von_mises(stress)
 # plt.pcolormesh(von_mises)
 # plt.colorbar()
 # plt.show()