Fixed small errors in readme.

Classical-MD-Modules/modules/nn_structure_detection/n2sd_dataset_generator/readme.rst

+:ignore:
+
 ..  In ReStructured Text (ReST) indentation and spacing are very important (it is how ReST knows what to do with your
     document). For ReST to understand what you intend and to render it correctly please to keep the structure of this
     template. Make sure that any time you use ReST syntax (such as for ".. sidebar::" below), it needs to be preceded
@@ -10,7 +12,7 @@
 ..  sidebar:: Software Technical Information
 
   Name
-    Input dataset generator for neural network structure detection (NNSD)
+    Input dataset generator for neural network structure detection (N2SD)
 
   Language
     C++ / Python
@@ -19,7 +21,7 @@
     `GPL <https://opensource.org/licenses/gpl-license>`_
 
   Documentation Tool
-    ReST_ ???
+    In-source documentation / Doxygen
 
   Application Documentation
     missing
@@ -50,7 +52,7 @@ Input dataset generator for neural network structure detection
     into YYYY process, which in turn should allow ZZZZ to be simulated. If successful, this could make it possible to
     produce compound AAAA while avoiding expensive process BBBB and CCCC."
 
-Over the last decade Behler-Parrinello symmerty functions [Behler2007]_ have been successfully applied to a wide variety of problems. Beside their key role in Neural Network Potential fitting they have also used for neural network based bond-order paramters [Geiger2013]_.
+Over the last decade Behler-Parrinello symmerty functions [Behler2007]_ have been successfully applied to a wide variety of problems. Beside their key role in Neural Network Potential fitting they have also used for neural network based bond-order parameters [Geiger2013]_.
 
 .. [Behler2007] J. Behler and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007)
 .. [Geiger2013] P. Geiger and Ch. Dellago, J. Chem. Phys. 139, 164105 (2013)