diff --git a/day_3/RuNNerMD.ipynb b/day_3/RuNNerMD.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..2dac058f04b1204751b182315bb1e79e2b0c316f
--- /dev/null
+++ b/day_3/RuNNerMD.ipynb
@@ -0,0 +1,364 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "extended-alliance",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from pyiron import Project"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "heard-leone",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "pr = Project('md_run')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "boolean-grammar",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "civilian-trigger",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "hungry-invite",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "input.nn scaling.data\tweights.029.data weights.029.out\n"
+ ]
+ }
+ ],
+ "source": [
+ "!ls fit"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "id": "animal-elite",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "custom_potential = pd.DataFrame({\n",
+ " 'Name': ['Cu'],\n",
+ " 'Filename': [[f'{os.getcwd()}/fit/input.nn', f'{os.getcwd()}/fit/weights.029.data', f'{os.getcwd()}/fit/scaling.data']],\n",
+ " 'Model': ['Custom'],\n",
+ " 'Species': [['Cu']],\n",
+ " 'Config': [['pair_style nnp dir \"./\" showew no showewsum 0 resetew no maxew 100 cflength 1.8897261328 cfenergy 0.0367493254 emap \"1:Cu\"\\n',\n",
+ " 'pair_coeff * * 12\\n'\n",
+ " ]]\n",
+ "})"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "id": "chemical-jungle",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "j = pr.create.job.Lammps(\"md\", delete_existing_job=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "id": "interior-advancement",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "j.potential = custom_potential"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "id": "loved-fiber",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "j.structure = pr.create.structure.ase_bulk('Cu', cubic=True).repeat(3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "id": "prerequisite-membrane",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Cu: [0. 0. 0.]\n",
+ "Cu: [0. 1.805 1.805]\n",
+ "Cu: [1.805 0. 1.805]\n",
+ "Cu: [1.805 1.805 0. ]\n",
+ "Cu: [0. 3.61 0. ]\n",
+ "Cu: [0. 5.415 1.805]\n",
+ "Cu: [1.805 3.61 1.805]\n",
+ "Cu: [1.805 5.415 0. ]\n",
+ "Cu: [0. 7.22 0. ]\n",
+ "Cu: [0. 9.025 1.805]\n",
+ "Cu: [1.805 7.22 1.805]\n",
+ "Cu: [1.805 9.025 0. ]\n",
+ "Cu: [3.61 0. 0. ]\n",
+ "Cu: [3.61 1.805 1.805]\n",
+ "Cu: [5.415 0. 1.805]\n",
+ "Cu: [5.415 1.805 0. ]\n",
+ "Cu: [3.61 3.61 0. ]\n",
+ "Cu: [3.61 5.415 1.805]\n",
+ "Cu: [5.415 3.61 1.805]\n",
+ "Cu: [5.415 5.415 0. ]\n",
+ "Cu: [3.61 7.22 0. ]\n",
+ "Cu: [3.61 9.025 1.805]\n",
+ "Cu: [5.415 7.22 1.805]\n",
+ "Cu: [5.415 9.025 0. ]\n",
+ "Cu: [7.22 0. 0. ]\n",
+ "Cu: [7.22 1.805 1.805]\n",
+ "Cu: [9.025 0. 1.805]\n",
+ "Cu: [9.025 1.805 0. ]\n",
+ "Cu: [7.22 3.61 0. ]\n",
+ "Cu: [7.22 5.415 1.805]\n",
+ "Cu: [9.025 3.61 1.805]\n",
+ "Cu: [9.025 5.415 0. ]\n",
+ "Cu: [7.22 7.22 0. ]\n",
+ "Cu: [7.22 9.025 1.805]\n",
+ "Cu: [9.025 7.22 1.805]\n",
+ "Cu: [9.025 9.025 0. ]\n",
+ "Cu: [0. 0. 3.61]\n",
+ "Cu: [0. 1.805 5.415]\n",
+ "Cu: [1.805 0. 5.415]\n",
+ "Cu: [1.805 1.805 3.61 ]\n",
+ "Cu: [0. 3.61 3.61]\n",
+ "Cu: [0. 5.415 5.415]\n",
+ "Cu: [1.805 3.61 5.415]\n",
+ "Cu: [1.805 5.415 3.61 ]\n",
+ "Cu: [0. 7.22 3.61]\n",
+ "Cu: [0. 9.025 5.415]\n",
+ "Cu: [1.805 7.22 5.415]\n",
+ "Cu: [1.805 9.025 3.61 ]\n",
+ "Cu: [3.61 0. 3.61]\n",
+ "Cu: [3.61 1.805 5.415]\n",
+ "Cu: [5.415 0. 5.415]\n",
+ "Cu: [5.415 1.805 3.61 ]\n",
+ "Cu: [3.61 3.61 3.61]\n",
+ "Cu: [3.61 5.415 5.415]\n",
+ "Cu: [5.415 3.61 5.415]\n",
+ "Cu: [5.415 5.415 3.61 ]\n",
+ "Cu: [3.61 7.22 3.61]\n",
+ "Cu: [3.61 9.025 5.415]\n",
+ "Cu: [5.415 7.22 5.415]\n",
+ "Cu: [5.415 9.025 3.61 ]\n",
+ "Cu: [7.22 0. 3.61]\n",
+ "Cu: [7.22 1.805 5.415]\n",
+ "Cu: [9.025 0. 5.415]\n",
+ "Cu: [9.025 1.805 3.61 ]\n",
+ "Cu: [7.22 3.61 3.61]\n",
+ "Cu: [7.22 5.415 5.415]\n",
+ "Cu: [9.025 3.61 5.415]\n",
+ "Cu: [9.025 5.415 3.61 ]\n",
+ "Cu: [7.22 7.22 3.61]\n",
+ "Cu: [7.22 9.025 5.415]\n",
+ "Cu: [9.025 7.22 5.415]\n",
+ "Cu: [9.025 9.025 3.61 ]\n",
+ "Cu: [0. 0. 7.22]\n",
+ "Cu: [0. 1.805 9.025]\n",
+ "Cu: [1.805 0. 9.025]\n",
+ "Cu: [1.805 1.805 7.22 ]\n",
+ "Cu: [0. 3.61 7.22]\n",
+ "Cu: [0. 5.415 9.025]\n",
+ "Cu: [1.805 3.61 9.025]\n",
+ "Cu: [1.805 5.415 7.22 ]\n",
+ "Cu: [0. 7.22 7.22]\n",
+ "Cu: [0. 9.025 9.025]\n",
+ "Cu: [1.805 7.22 9.025]\n",
+ "Cu: [1.805 9.025 7.22 ]\n",
+ "Cu: [3.61 0. 7.22]\n",
+ "Cu: [3.61 1.805 9.025]\n",
+ "Cu: [5.415 0. 9.025]\n",
+ "Cu: [5.415 1.805 7.22 ]\n",
+ "Cu: [3.61 3.61 7.22]\n",
+ "Cu: [3.61 5.415 9.025]\n",
+ "Cu: [5.415 3.61 9.025]\n",
+ "Cu: [5.415 5.415 7.22 ]\n",
+ "Cu: [3.61 7.22 7.22]\n",
+ "Cu: [3.61 9.025 9.025]\n",
+ "Cu: [5.415 7.22 9.025]\n",
+ "Cu: [5.415 9.025 7.22 ]\n",
+ "Cu: [7.22 0. 7.22]\n",
+ "Cu: [7.22 1.805 9.025]\n",
+ "Cu: [9.025 0. 9.025]\n",
+ "Cu: [9.025 1.805 7.22 ]\n",
+ "Cu: [7.22 3.61 7.22]\n",
+ "Cu: [7.22 5.415 9.025]\n",
+ "Cu: [9.025 3.61 9.025]\n",
+ "Cu: [9.025 5.415 7.22 ]\n",
+ "Cu: [7.22 7.22 7.22]\n",
+ "Cu: [7.22 9.025 9.025]\n",
+ "Cu: [9.025 7.22 9.025]\n",
+ "Cu: [9.025 9.025 7.22 ]\n",
+ "pbc: [ True True True]\n",
+ "cell: \n",
+ "Cell([10.83, 10.83, 10.83])"
+ ]
+ },
+ "execution_count": 58,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "j.structure"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "id": "removable-place",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "j.calc_md(n_ionic_steps=1000, temperature=500)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "id": "patent-translation",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "The job md was saved and received the ID: 13491011\n"
+ ]
+ }
+ ],
+ "source": [
+ "j.run()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "id": "conventional-dayton",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8e5a59a520a54c0993233c27cb8156bb",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "NGLWidget(max_frame=100)"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "j.animate_structure()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "intimate-retail",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "s = j.structure"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "id": "hearing-negative",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "e = s.elements[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "id": "compressed-texture",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'Cu'"
+ ]
+ },
+ "execution_count": 67,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "e.Abbreviation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "coral-concentrate",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.9"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/day_3/fit/input.nn b/day_3/fit/input.nn
new file mode 100644
index 0000000000000000000000000000000000000000..4792cbf805e04e70b463a1749dd422ca36b9bbab
--- /dev/null
+++ b/day_3/fit/input.nn
@@ -0,0 +1,95 @@
+### ####################################################################################################################
+### This is the input file for the RuNNer tutorial (POTENTIALS WORKSHOP 2021-03-10)
+### This input file is intended for release version 1.2
+### RuNNer is hosted at www.gitlab.com. The most recent version can only be found in this repository.
+### For access please contact Prof. Jörg Behler, joerg.behler@uni-goettingen.de
+###
+### ####################################################################################################################
+### General remarks:
+### - commands can be switched off by using the # character at the BEGINNING of the line
+### - the input file can be structured by blank lines and comment lines
+### - the order of the keywords is arbitrary
+### - if keywords are missing, default values will be used and written to runner.out
+### - if mandatory keywords or keyword options are missing, RuNNer will stop with an error message
+###
+########################################################################################################################
+########################################################################################################################
+### The following keywords just represent a subset of the keywords offered by RuNNer
+########################################################################################################################
+########################################################################################################################
+
+########################################################################################################################
+### general keywords
+########################################################################################################################
+nn_type_short 1 # 1=Behler-Parrinello
+runner_mode 3 # 1=calculate symmetry functions, 2=fitting mode, 3=predicition mode
+number_of_elements 1 # number of elements
+elements Cu # specification of elements
+random_seed 10 # integer seed for random number generator
+random_number_type 6 # 6 recommended
+
+########################################################################################################################
+### NN structure of the short-range NN
+########################################################################################################################
+use_short_nn # use NN for short range interactions
+global_hidden_layers_short 2 # number of hidden layers
+global_nodes_short 15 15 # number of nodes in hidden layers
+global_activation_short t t l # activation functions (t = hyperbolic tangent, l = linear)
+
+########################################################################################################################
+### symmetry function generation ( mode 1):
+########################################################################################################################
+test_fraction 0.10000 # threshold for splitting between fitting and test set
+
+########################################################################################################################
+### symmetry function definitions (all modes):
+########################################################################################################################
+cutoff_type 1
+symfunction_short Cu 2 Cu 0.000000 0.000000 12.000000
+symfunction_short Cu 2 Cu 0.006000 0.000000 12.000000
+symfunction_short Cu 2 Cu 0.016000 0.000000 12.000000
+symfunction_short Cu 2 Cu 0.040000 0.000000 12.000000
+symfunction_short Cu 2 Cu 0.109000 0.000000 12.000000
+
+symfunction_short Cu 3 Cu Cu 0.00000 1.000000 1.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 1.000000 2.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 1.000000 4.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 1.000000 16.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 1.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 2.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 4.000000 12.000000
+symfunction_short Cu 3 Cu Cu 0.00000 -1.000000 16.000000 12.000000
+
+########################################################################################################################
+### fitting (mode 2):general inputs for short range AND electrostatic part:
+########################################################################################################################
+epochs 20 # number of epochs
+fitting_unit eV # unit for error output in mode 2 (eV or Ha)
+precondition_weights # optional precondition initial weights
+
+########################################################################################################################
+### fitting options ( mode 2): short range part only:
+########################################################################################################################
+short_energy_error_threshold 0.10000 # threshold of adaptive Kalman filter short E
+short_force_error_threshold 1.00000 # threshold of adaptive Kalman filter short F
+kalman_lambda_short 0.98000 # Kalman parameter short E/F, do not change
+kalman_nue_short 0.99870 # Kalman parameter short E/F, do not change
+use_short_forces # use forces for fitting
+repeated_energy_update # optional: repeat energy update for each force update
+mix_all_points # do not change
+scale_symmetry_functions # optional
+center_symmetry_functions # optional
+short_force_fraction 0.01 #
+force_update_scaling -1.0 #
+
+########################################################################################################################
+### output options for mode 2 (fitting):
+########################################################################################################################
+write_trainpoints # write trainpoints.out and testpoints.out files
+write_trainforces # write trainforces.out and testforces.out files
+
+########################################################################################################################
+### output options for mode 3 (prediction):
+########################################################################################################################
+calculate_forces # calculate forces
+calculate_stress # calculate stress tensor
diff --git a/day_3/fit/scaling.data b/day_3/fit/scaling.data
new file mode 100644
index 0000000000000000000000000000000000000000..fc3779e520a3d6719fd3682760a4022ef86dc7d6
--- /dev/null
+++ b/day_3/fit/scaling.data
@@ -0,0 +1,14 @@
+ 1 1 14.256833324 19.604083786 16.584187995
+ 1 2 10.772870436 14.917517522 12.575789477
+ 1 3 7.067719199 9.940850811 8.325756144
+ 1 4 3.063546892 4.514143322 3.699677080
+ 1 5 0.443438674 0.840539370 0.611310762
+ 1 6 11.372207256 23.338043099 16.099109800
+ 1 7 30.908289966 62.610854904 43.470717798
+ 1 8 4.747847116 10.201151151 6.890568480
+ 1 9 24.299123692 49.473962957 34.262176478
+ 1 10 1.690730707 3.912715044 2.559298728
+ 1 11 16.549052901 34.322241783 23.555567314
+ 1 12 0.252821214 0.820637834 0.460356083
+ 1 13 4.065311900 9.687837138 6.245172716
+ -0.1359667057 -0.1284178204
diff --git a/day_3/fit/weights.029.data b/day_3/fit/weights.029.data
new file mode 100644
index 0000000000000000000000000000000000000000..e3505a1a2b72b867f9885f58fb9e494952e26609
--- /dev/null
+++ b/day_3/fit/weights.029.data
@@ -0,0 +1,466 @@
+ 0.0002929493
+ -0.6941954269
+ 0.9059192336
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+ 0.6945597416
+ 0.4158165063
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+ 0.4146182872
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