diff --git a/msspecbook/Activity10/Activity10.ipynb b/msspecbook/Activity10/Activity10.ipynb
index 1c3fa45..82b4118 100644
--- a/msspecbook/Activity10/Activity10.ipynb
+++ b/msspecbook/Activity10/Activity10.ipynb
@@ -9,12 +9,97 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "526d98f6-5a18-4ed9-9870-29b08b54e073",
+   "cell_type": "markdown",
+   "id": "1dccb5e3-1cd3-4732-a7ba-81a8a94c89dc",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "As you can see from the previous examples, a complete simulation may require several multiple scattering calculations, for instance to calculate the total intensity of a substrate or to optimize the geometry of a system. As the calculations are often time consuming, it can be useful to distribute these tasks over several processors to make the most of hardware resources.\n",
+    "Although MsSpec is not fully parallelized, the code does offer a number of features, which we will explore here.\n",
+    "\n",
+    "## Matrix inversion parallelization\n",
+    "\n",
+    "When available during installation, MsSpec will link with the system lapack library. It will be used to invert the matrix in the `inversion` option of the MsSpec `calculator`. To allow MsSpec to use this shared memory parallelism, you need to set the number of cores to be used in the `OMP_NUM_THREADS` environment variable.\n",
+    "\n",
+    "You can set this variable just for the execution of your script. For example:\n",
+    "\n",
+    "```sh\n",
+    "$ OMP_NUM_THREADS=12 python my_script.py\n",
+    "```\n",
+    "\n",
+    "will use 12 cores for inverting the matrix in your script.\n",
+    "\n",
+    "It is also possible to set environment variable inside your python script.\n",
+    "\n",
+    "```python\n",
+    "import os\n",
+    "\n",
+    "os.environ['OMP_NUM_THREADS'] = 12\n",
+    "```\n",
+    "\n",
+    "It may be useful for technical reasons or to use different number of cores in some parts of your script.\n",
+    "\n",
+    "## Process-based parallelism\n",
+    "\n",
+    "Another kind of parallelization used in MsSpec is multiprocessing. Quite often, you need to run different *independent* calculations. MsSpec provides a simple *looper* that can be useful for multiprocessing. Let's demonstrate it with the previous example CO/Fe(001).\n",
+    "\n",
+    "[This script](COFe_mp.py) is the multiprocessed version of the previous one. You can see that the previous nested for loops are now replaced by some declarative content (lines 63-67) and the definition of a `process` function (whose name \n",
+    "can be changed).\n",
+    "\n",
+    "With the `msspec.looper` package, the user define `Sweep` objects that are parameters of the calculation or of the cluster. The `process` function must accept as many arguments as parameters to sweep (+ the `**kwargs`).\n",
+    "\n",
+    "A `Looper` object is created (line 76) and the `process` function is set to its `pipeline` attribute (line 77). When MsSpec will run the `looper`, it will combine all parameters values to unique individual sets and MsSpec will distribute the calculations over the number of processors specified in the `ncpu` option.\n",
+    "\n",
+    ":::{literalinclude} COFe_mp.py\n",
+    ":lineno-start: 63\n",
+    ":linenos: true\n",
+    ":lines: 63-84\n",
+    ":::\n",
+    "\n",
+    "\n",
+    "::::{tab-set}\n",
+    "\n",
+    ":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
+    "In the paper discussed in {ref}`RFactor`, experimental values of the anisotropy suggest an adsorption height between 0.2 and 0.6 Å. Modify the script to add another sweep for variying the adsorption height of the CO molecule.\n",
+    ":::\n",
+    "\n",
+    "::::"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9da716db-069f-422b-a5fd-2c2b509eb621",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Å\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('\\U0000212B')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0a1fabce-c42d-4cb4-9720-bcd21ff0cd09",
+   "metadata": {},
+   "source": [
+    "```{toggle}\n",
+    "\n",
+    ":::{literalinclude} COFe_mp_completed.py\n",
+    ":lineno-start: 63\n",
+    ":linenos: true\n",
+    ":lines: 63-86\n",
+    ":emphasize-lines: 6,7, 9,10, 18\n",
+    ":::\n",
+    "\n",
+    "\n",
+    "```"
+   ]
   }
  ],
  "metadata": {
@@ -33,7 +118,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.13"
+   "version": "3.11.3"
   }
  },
  "nbformat": 4,
diff --git a/msspecbook/Activity10/COFe_mp.py b/msspecbook/Activity10/COFe_mp.py
new file mode 100644
index 0000000..d233450
--- /dev/null
+++ b/msspecbook/Activity10/COFe_mp.py
@@ -0,0 +1,96 @@
+from ase import Atoms
+from ase.build import add_adsorbate, bulk
+
+from msspec.calculator import MSSPEC, RFACTOR
+from msspec.utils import hemispherical_cluster
+from msspec.looper import Sweep, Looper
+
+import numpy as np
+
+
+def create_cluster(height=1., theta=45, phi=0, bond_length=1.15):
+    # Fill the body of this function. The 'cluster' object in built according to
+    # values provided by the keyword arguments:
+    # height (in angströms): the 'z' distance between the Fe surface and the C atom
+    # theta and phi (in degrees): the polar and azimuthal orientation of the CP molecule
+    #                             (theta=0° aligns the molecule withe the surface normal
+    #                              phi=0° corresponds to the [100] direction of iron)
+    # bond_length (in angströms): the C-O distance
+
+    iron = bulk('Fe', cubic=True)
+    cluster = hemispherical_cluster(iron, diameter=5, planes=2, emitter_plane=1)
+
+    t = np.radians(theta)
+    p = np.radians(phi)
+
+    z = bond_length * np.cos(t)
+    x = bond_length * np.sin(t) * np.cos(p)
+    y = bond_length * np.sin(t) * np.sin(p)
+    CO=Atoms('CO',positions=[(0,0,0),(x,y,z)])
+
+    add_adsorbate(cluster,CO, height=height)
+
+    # Keep those 2 lines at the end of your function
+    # Store some information in the cluster object
+    cluster.info.update(adsorbate={'theta': theta, 'phi': phi, 'height': height, 
+                                   'bond_length': bond_length})
+    return cluster
+
+
+def compute_polar_scan(cluster, folder='calc'):
+    calc = MSSPEC(spectroscopy='PED', algorithm='expansion', folder=folder)
+    calc.set_atoms(cluster)
+
+    # SSC calculations
+    calc.calculation_parameters.scattering_order = 1
+
+    # Add temperature effects
+    [atom.set('mean_square_vibration', 0.005) for atom in cluster]
+    calc.calculation_parameters.vibrational_damping = 'averaged_tl'
+
+    polar_angles = np.arange(-5, 85, 0.5)
+    # set the Carbon as absorber and compute the polar scan
+    cluster.absorber = cluster.get_chemical_symbols().index('C')
+    data = calc.get_theta_scan(level='1s', theta=polar_angles, kinetic_energy=1202)
+    calc.shutdown()
+
+    return data
+
+
+###############################################################################
+# Main part
+###############################################################################
+# 1) Multiprocess calculations 
+theta = Sweep(key='theta', comments="The molecule tilt angle",
+              start=50, stop=60, step=1, unit='degree')
+phi = Sweep(key='phi', comments="The molecule azimuthal angle",
+            values=[0,45], unit='degree')
+
+def process(theta, phi, **kwargs):
+    cluster = create_cluster(theta=theta, phi=phi, height=0.6, bond_length=1.157)
+    i = kwargs.get('sweep_index')
+    data = compute_polar_scan(cluster, folder=f'calc_{i:d}')
+    dset = data[-1]
+    return dset.theta, dset.cross_section
+
+looper = Looper()
+looper.pipeline = process
+df = looper.run(theta, phi, ncpu=4)
+
+# Black magic to convert the pandas dataframe object 'df' to the 
+# parameters dict and the resulst list (will be easier in a future
+# version ;-) ).
+parameters = df.to_dict('list')
+results = np.reshape(parameters.pop('output'), (df.shape[0]*2,-1))
+
+# 2) R-Factor analysis
+# Load the experimental data
+exp_data = np.loadtxt('experimental_data.txt')
+
+# Create an R-Factor calculator
+rfc = RFACTOR()
+rfc.set_references(exp_data[:,0], exp_data[:,1])
+
+# Perform the R-Factor analysis
+data = rfc.run(*results, **parameters)
+data.view()
diff --git a/msspecbook/Activity10/COFe_mp_completed.py b/msspecbook/Activity10/COFe_mp_completed.py
new file mode 100644
index 0000000..94adc50
--- /dev/null
+++ b/msspecbook/Activity10/COFe_mp_completed.py
@@ -0,0 +1,98 @@
+from ase import Atoms
+from ase.build import add_adsorbate, bulk
+
+from msspec.calculator import MSSPEC, RFACTOR
+from msspec.utils import hemispherical_cluster
+from msspec.looper import Sweep, Looper
+
+import numpy as np
+
+
+def create_cluster(height=1., theta=45, phi=0, bond_length=1.15):
+    # Fill the body of this function. The 'cluster' object in built according to
+    # values provided by the keyword arguments:
+    # height (in angströms): the 'z' distance between the Fe surface and the C atom
+    # theta and phi (in degrees): the polar and azimuthal orientation of the CP molecule
+    #                             (theta=0° aligns the molecule withe the surface normal
+    #                              phi=0° corresponds to the [100] direction of iron)
+    # bond_length (in angströms): the C-O distance
+
+    iron = bulk('Fe', cubic=True)
+    cluster = hemispherical_cluster(iron, diameter=5, planes=2, emitter_plane=1)
+
+    t = np.radians(theta)
+    p = np.radians(phi)
+
+    z = bond_length * np.cos(t)
+    x = bond_length * np.sin(t) * np.cos(p)
+    y = bond_length * np.sin(t) * np.sin(p)
+    CO=Atoms('CO',positions=[(0,0,0),(x,y,z)])
+
+    add_adsorbate(cluster,CO, height=height)
+
+    # Keep those 2 lines at the end of your function
+    # Store some information in the cluster object
+    cluster.info.update(adsorbate={'theta': theta, 'phi': phi, 'height': height, 
+                                   'bond_length': bond_length})
+    return cluster
+
+
+def compute_polar_scan(cluster, folder='calc'):
+    calc = MSSPEC(spectroscopy='PED', algorithm='expansion', folder=folder)
+    calc.set_atoms(cluster)
+
+    # SSC calculations
+    calc.calculation_parameters.scattering_order = 1
+
+    # Add temperature effects
+    [atom.set('mean_square_vibration', 0.005) for atom in cluster]
+    calc.calculation_parameters.vibrational_damping = 'averaged_tl'
+
+    polar_angles = np.arange(-5, 85, 0.5)
+    # set the Carbon as absorber and compute the polar scan
+    cluster.absorber = cluster.get_chemical_symbols().index('C')
+    data = calc.get_theta_scan(level='1s', theta=polar_angles, kinetic_energy=1202)
+    calc.shutdown()
+
+    return data
+
+
+###############################################################################
+# Main part
+###############################################################################
+# 1) Multiprocess calculations 
+theta = Sweep(key='theta', comments="The molecule tilt angle",
+              start=50, stop=60, step=1, unit='degree')
+phi = Sweep(key='phi', comments="The molecule azimuthal angle",
+            values=[0,45], unit='degree')
+height = Sweep(key='height', comments="The molecule adsorption height",
+               start=0.2, stop=0.6, num=3, unit='angström')
+
+def process(theta, phi, height, **kwargs):
+    cluster = create_cluster(theta=theta, phi=phi, height=height, bond_length=1.157)
+    i = kwargs.get('sweep_index')
+    data = compute_polar_scan(cluster, folder=f'calc_{i:d}')
+    dset = data[-1]
+    return dset.theta, dset.cross_section
+
+looper = Looper()
+looper.pipeline = process
+df = looper.run(theta, phi, height, ncpu=4)
+
+# Black magic to convert the pandas dataframe object 'df' to the 
+# parameters dict and the resulst list (will be easier in a future
+# version ;-) ).
+parameters = df.to_dict('list')
+results = np.reshape(parameters.pop('output'), (df.shape[0]*2,-1))
+
+# 2) R-Factor analysis
+# Load the experimental data
+exp_data = np.loadtxt('experimental_data.txt')
+
+# Create an R-Factor calculator
+rfc = RFACTOR()
+rfc.set_references(exp_data[:,0], exp_data[:,1])
+
+# Perform the R-Factor analysis
+data = rfc.run(*results, **parameters)
+data.view()
diff --git a/msspecbook/Activity10/experimental_data.txt b/msspecbook/Activity10/experimental_data.txt
new file mode 100644
index 0000000..5745a71
--- /dev/null
+++ b/msspecbook/Activity10/experimental_data.txt
@@ -0,0 +1,250 @@
+# Polar angle (°)         C1s/O1s Signal (a.u.)
+-5.163000000000000256e+00 3.649999999999999911e-01
+-4.858999999999990216e+00 3.639999999999999902e-01
+-4.556000000000000050e+00 3.629999999999999893e-01
+-4.251999999999999780e+00 3.619999999999999885e-01
+-3.947999999999990184e+00 3.609999999999999876e-01
+-3.677999999999999936e+00 3.599999999999999867e-01
+-3.375000000000000000e+00 3.579999999999999849e-01
+-3.104999999999999982e+00 3.569999999999999840e-01
+-2.766999999999999904e+00 3.559999999999999831e-01
+-2.462999999999989864e+00 3.549999999999999822e-01
+-2.193000000000000060e+00 3.539999999999999813e-01
+-1.991000000000000103e+00 3.529999999999999805e-01
+-1.754999999999999893e+00 3.519999999999999796e-01
+-1.519000000000009898e+00 3.509999999999999787e-01
+-1.215000000000000080e+00 3.499999999999999778e-01
+-1.012000000000000011e+00 3.499999999999999778e-01
+-6.749999999999970468e-01 3.499999999999999778e-01
+-4.389999999999930069e-01 3.509999999999999787e-01
+-1.009999999999989934e-01 3.519999999999999796e-01
+2.019999999999979867e-01 3.529999999999999805e-01
+5.739999999999979563e-01 3.529999999999999805e-01
+9.789999999999989821e-01 3.539999999999999813e-01
+1.417000000000000037e+00 3.539999999999999813e-01
+1.956999999999990081e+00 3.539999999999999813e-01
+2.327999999999999847e+00 3.549999999999999822e-01
+2.564999999999999947e+00 3.559999999999999831e-01
+2.766999999999999904e+00 3.579999999999999849e-01
+2.970000000000000195e+00 3.589999999999999858e-01
+3.071000000000000174e+00 3.609999999999999876e-01
+3.239999999999989999e+00 3.619999999999999885e-01
+3.407999999999999918e+00 3.629999999999999893e-01
+3.576999999999999957e+00 3.649999999999999911e-01
+3.712000000000000188e+00 3.659999999999999920e-01
+3.813000000000000167e+00 3.679999999999999938e-01
+3.880999999999999783e+00 3.679999999999999938e-01
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+4.352999999999989988e+00 3.699999999999999956e-01
+4.758000000000000007e+00 3.709999999999999964e-01
+5.197000000000000064e+00 3.709999999999999964e-01
+5.602000000000000313e+00 3.719999999999999973e-01
+5.972999999999999865e+00 3.719999999999999973e-01
+6.243000000000000327e+00 3.729999999999999982e-01
+6.479000000000000092e+00 3.739999999999999991e-01
+6.682000000000000384e+00 3.750000000000000000e-01
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+7.187999999999999723e+00 3.780000000000000027e-01
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+7.389999999999999680e+00 3.810000000000000053e-01
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+7.727999999999989988e+00 3.830000000000000071e-01
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+8.403000000000009351e+00 3.840000000000000080e-01
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+9.212999999999990308e+00 3.850000000000000089e-01
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+1.063000000000000078e+01 3.820000000000000062e-01
+1.103500000000000014e+01 3.810000000000000053e-01
+1.143999999999999950e+01 3.800000000000000044e-01
+1.174399999999999977e+01 3.800000000000000044e-01
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+1.910000000000000142e+01 3.930000000000000160e-01
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+3.988799999999999812e+01 4.239999999999999880e-01
+4.009000000000000341e+01 4.249999999999999889e-01
+4.039399999999999835e+01 4.259999999999999898e-01
+4.073100000000000165e+01 4.269999999999999907e-01
+4.103499999999999659e+01 4.279999999999999916e-01
+4.130499999999999972e+01 4.299999999999999933e-01
+4.160900000000000176e+01 4.309999999999999942e-01
+4.187899999999999778e+01 4.319999999999999951e-01
+4.221600000000000108e+01 4.329999999999999960e-01
+4.248599999999999710e+01 4.329999999999999960e-01
+4.275600000000000023e+01 4.339999999999999969e-01
+4.295799999999999841e+01 4.349999999999999978e-01
+4.322800000000000153e+01 4.359999999999999987e-01
+4.346500000000000341e+01 4.380000000000000004e-01
+4.376800000000000068e+01 4.390000000000000013e-01
+4.403799999999999670e+01 4.400000000000000022e-01
+4.424099999999999966e+01 4.420000000000000040e-01
+4.444299999999999784e+01 4.430000000000000049e-01
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