diff --git a/docs/source/index.rst b/docs/source/index.rst
index 88a70f03..09207a61 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -21,24 +21,14 @@ for deep learning assisted reacting flow simulations. It is also has the scope t
.. toctree::
:maxdepth: 3
:numbered:
- :caption: Installation
- :glob:
-
- installation/index
-
-.. _quikstart:
-
-.. toctree::
- :maxdepth: 3
:caption: Quick Start
:glob:
- quickstart/index
+ qs/install
+ qs/examples
+ qs/input
-
-
-
.. _solvers:
.. toctree::
diff --git a/docs/source/installation/index.rst b/docs/source/installation/index.rst
deleted file mode 100644
index eb139885..00000000
--- a/docs/source/installation/index.rst
+++ /dev/null
@@ -1,108 +0,0 @@
-
-Install OpenFOAM-7 (if not already installed)
-====================================================
-
-.. Note:: If Ubuntu is used as the subsystem, please use `Ubuntu:20.04 `_ instead of the latest version. OpenFOAM-7 accompanied by ParaView 5.6.0 is not available for `Ubuntu-latest `_.
-
-.. code-block:: bash
-
- sudo sh -c "wget -O - https://dl.openfoam.org/gpg.key | apt-key add -"
- sudo add-apt-repository http://dl.openfoam.org/ubuntu
- sudo apt-get update
- sudo apt-get -y install openfoam7
-
-OpenFOAM 7 and ParaView 5.6.0 will be installed in the ``/opt`` directory.
-
-Source your OpenFOAM
-======================
-
-.. code-block:: bash
-
- source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
-
-This depends on your own path for OpenFOAM bashrc.
-
-Clone the DeepFlame repository
-===========================================
-
-.. code-block:: bash
-
- git clone https://github.com/deepmodeling/deepflame-dev.git
- cd deepflame-dev
-
-
-Install dependencies and DeepFlame based on your need
-=================================================================
-DeepFlame supports three compilation choices: no torch, LibTorch, and PyTorch.
-
- .. Note:: You are encouaged to try all three options, but remember to install the next version in a new terminal to clean previous environment variables.
-
-
-
-PyTorch version (**RECOMMEND**)
--------------------------------
-
-PyTorch version aims to support computation on CUDA. If you have compatible platform, run the following command to install DeepFlame.
-
-.. code-block::
-
- conda create -n df-pytorch python=3.8
- conda activate df-pytorch
- conda install -c cantera libcantera-devel
- conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge
- conda install pybind11
- . install.sh --use_pytorch
-
-.. Note:: You may come accross an error regarding shared library ``libmkl_rt.so.2`` when libcantera is installed through cantera channel. If so, go to your conda environment and check the existance of ``libmkl_rt.so.2`` and ``libmkl_rt.so.1``, and then link ``libmkl_rt.so.2`` to ``libmkl_rt.so.1``.
-
-
-.. code-block:: bash
-
- cd ~/miniconda3/envs/df-pytorch/lib
- ln -s libmkl_rt.so.1 libmkl_rt.so.2
-
-
-LibTorch version
--------------------------------
-
-If you choose to use LibTorch (C++ API for Torch), first create the conda env and install `LibCantera `_:
-
-.. code-block:: bash
-
- conda create -n df-libtorch
- conda activate df-libtorch
- conda install -c cantera libcantera-devel
-
-Then you can pass your own libtorch path to DeepFlame.
-.. code-block:: bash
-
- . install.sh --libtorch_dir /path/to/libtorch/
-
-
-.. Note:: Some compiling issues may happen due to system compatability. Instead of using conda installed Cantera C++ lib and the downloaded Torch C++ lib, try to compile your own Cantera and Torch C++ libraries.
-
-No Torch version
--------------------------
-
-If your are using DeepFlame's CVODE solver without DNN model, just install LibCantera via `conda `_.
-
-.. code-block:: bash
-
- conda create -n df-notorch
- conda activate df-notorch
- conda install -c cantera libcantera-devel
-
-.. Note:: Check your ``Miniconda3/envs/libcantera`` directory and make sure the install was successful (lib/ include/ etc. exist).
-
-
-If the conda env ``df-notorch`` is activated, install DeepFlame by running:
-
-.. code-block:: bash
-
- . install.sh
-
-If ``df-notorch`` not activated (or you have a self-complied libcantera), specify the path to your libcantera:
-
-.. code-block:: bash
-
- . install.sh --libcantera_dir /your/path/to/libcantera/
\ No newline at end of file
diff --git a/docs/source/quickstart/0Dcvode.jpg b/docs/source/qs/0Dcvode.jpg
similarity index 100%
rename from docs/source/quickstart/0Dcvode.jpg
rename to docs/source/qs/0Dcvode.jpg
diff --git a/docs/source/qs/compile_success.png b/docs/source/qs/compile_success.png
new file mode 100644
index 00000000..0967e2ae
Binary files /dev/null and b/docs/source/qs/compile_success.png differ
diff --git a/docs/source/qs/examples.rst b/docs/source/qs/examples.rst
new file mode 100644
index 00000000..b6856563
--- /dev/null
+++ b/docs/source/qs/examples.rst
@@ -0,0 +1,88 @@
+Two Examples
+===================
+
+DeepFlame with DNN
+--------------------------
+
+If you choose to use PyTorch as the integratgor and use the compilation flag `--use_pytorch`, you can run examples stored in `$HOME/deepflame-dev/examples/.../pytorchIntegratgor`. To run an example, you first need to source your OpenFOAM:
+
+.. code-block:: bash
+
+ source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
+
+Then, source your DeepFlame:
+
+.. code-block:: bash
+
+ source $HOME/deepflame-dev/bashrc
+
+Next, you can go to the directory of any example case that you want to run. For example:
+
+.. code-block:: bash
+
+ cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/pytorchIntegratgor
+
+This is an example for the zero-dimensional hydrogen combustion with PyTorch as the integrator. All files needed by DNN are stored in `pytorchDNN` folder, and the inference file is `inference.py`. Configurations regarding DNN are included in `constant/CanteraTorchProperties`.
+
+The case is run by simply typing:
+
+.. code-block:: bash
+
+ ./Allrun
+
+.. Note:: Users can go to `constant/CanteraTorchProperties` and check if `torch` is switched on. Switch it `on` to run DNN cases, and switch `off` to run CVODE cases.
+
+If you plot PyTorch's result together with CVODE's result, the graph is expected to look like:
+
+.. figure:: pytorch.png
+
+ Visualisation of 0D results from PyTorch and CVODE integrators
+
+
+
+DeepFlame without DNN
+------------------------------
+CVODE Integrator is the one without the application of Deep Neural Network (DNN). Follow the steps below to run an example of CVODE. Examples are stored in the directory:
+.. code-block:: bash
+
+ $HOME/deepflame-dev/examples
+
+To run these examples, first source your OpenFOAM, depending on your OpenFOAM path:
+
+.. code-block:: bash
+
+ source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
+
+Then, source your DeepFlame:
+
+.. code-block:: bash
+
+ source $HOME/deepflame-dev/bashrc
+
+Next, you can go to the directory of any example case that you want to run. For example:
+
+.. code-block:: bash
+
+ cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/cvodeIntegrator
+
+This is an example for the zero-dimensional hydrogen combustion with CVODE integrator.
+
+The case is run by simply typing:
+
+.. code-block:: bash
+
+ ./Allrun
+
+The probe used for post processing is defined in ``/system/probes``. In this case, the probe is located at the coordinates (0.0025 0.0025 0.0025) to measure temperature variation with time.
+If the case is successfully run, the result can be found in ``/postProcessing/probes/0/T``, and it can be visualized by running:
+
+.. code-block:: bash
+
+ gunplot
+ plot "/your/path/to/postProcessing/probes/0/T"
+
+You will get a graph:
+
+.. figure:: 0Dcvode.jpg
+
+ Visualisation of the zero-dimensional hydrogen combustion result with CVODE integrator
\ No newline at end of file
diff --git a/docs/source/qs/input.rst b/docs/source/qs/input.rst
new file mode 100644
index 00000000..afcc24a9
--- /dev/null
+++ b/docs/source/qs/input.rst
@@ -0,0 +1,59 @@
+Brief Introduction to Inputs
+======================================
+The dictionary ``CanteraTorchProperties`` is the original dictionay of DeepFlame. It read in netowrk realted parameters and configurations. It typically looks like:
+
+.. code-block::
+
+ chemistry on;
+ CanteraMechanismFile "ES80_H2-7-16.yaml";
+ transportModel "Mix";//"UnityLewis";
+ odeCoeffs
+ {
+ //"relTol" 1e-15;
+ //"absTol" 1e-24;
+ }
+ inertSpecie "N2";
+
+ zeroDReactor
+ {
+ constantProperty "pressure";
+ }
+
+ torch on;
+ GPU on;
+ torchModel1 "ESH2-sub1.pt";
+ torchModel2 "ESH2-sub2.pt";
+ torchModel3 "ESH2-sub3.pt";
+
+ torchParameters1
+ {
+ Tact 700 ;
+ Qdotact 3e7;
+ coresPerGPU 4;
+ }
+ torchParameters2
+ {
+ Tact 2000;
+ Qdotact 3e7;
+ }
+ torchParameters3
+ {
+ Tact 2000;
+ Qdotact 7e8;
+ }
+ loadbalancing
+ {
+ active false;
+ //log true;
+ }
+
+
+In the above example, the meanings of the parameters are:
+
+* ``CanteraMechanismFile``: the name of the reaction mechanism file
+* ``odeCoeffs``: the ode torlerance. 1e-15 and 1e-24 are used for network training, so it should keep the same when comparing results with nd without DNN.
+* ``torch``: the switch used to control the on and off of DNN. If users are running CVODE, this needs to be switched off.
+* ``GPU``: the switch used to control whether GPU or CPU is used to carry out inference.
+* ``torchModel``: name of network.
+* ``torchParameters``: thresholds used to decide when to use network.
+* ``coresPerGPU``: number of CPU cores on one node.
diff --git a/docs/source/qs/install.rst b/docs/source/qs/install.rst
new file mode 100644
index 00000000..b3e88358
--- /dev/null
+++ b/docs/source/qs/install.rst
@@ -0,0 +1,141 @@
+Installation
+======================
+
+Prerequisites
+------------------------
+The installation of DeepFlame is simple and requires **OpenFOAM-7**, **LibCantera**, and **PyTorch**.
+
+.. Note:: If Ubuntu is used as the subsystem, please use `Ubuntu:20.04 `_ instead of the latest version. OpenFOAM-7 accompanied by ParaView 5.6.0 is not available for `Ubuntu-latest `_.
+
+First install OpenFOAM-7 if it is not already installed.
+
+.. code-block:: bash
+
+ sudo sh -c "wget -O - https://dl.openfoam.org/gpg.key | apt-key add -"
+ sudo add-apt-repository http://dl.openfoam.org/ubuntu
+ sudo apt-get update
+ sudo apt-get -y install openfoam7
+
+OpenFOAM-7 and ParaView-5.6.0 will be installed in the ``/opt`` directory.
+
+.. Note:: There is a commonly seen issue when installing OpenFOAM via ``apt-get install`` with an error message: ``could not find a distribution template for Ubuntu/focal``. To resolve this issue, you can refer to `issue#54 `_.
+
+**LibCantera** and **PyTorch** can be easily installed via `conda `_. If you have compatible platform, run the following command to install DeepFlame.
+
+.. code-block:: bash
+
+ conda create -n deepflame python=3.8
+ conda activate deepflame
+ conda install -c cantera libcantera-devel
+ conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
+ conda install pybind11 easydict
+
+
+.. Note:: Please go to PyTorch's official website to check your system compatability and choose the installation command line that is suitable for your platform.
+
+.. Note:: Check your ``Miniconda3/envs/deepflame`` directory and make sure the install was successful (lib/ include/ etc. exist).
+
+
+Configure
+-------------------------
+**1. Source your OpenFOAM-7 bashrc to configure the $FOAM environment.**
+
+.. Note:: This depends on your own path for OpenFOAM-7 bashrc.
+
+If you have installed using ``apt-get install``, use:
+
+.. code-block:: bash
+
+ source /opt/openfoam7/etc/bashrc
+
+If you compiled from source following the `official guild `_, use:
+
+.. code-block:: bash
+
+ source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
+
+.. Note:: Check your environment using ``echo $FOAM_ETC`` and you should get the directory path for your OpenFOAM-7 bashrc you just used in the above step.
+
+**2. Clone the DeepFlame repository:**
+
+.. code-block:: bash
+
+ git clone https://github.com/deepmodeling/deepflame-dev.git
+
+**3. Configure the DeepFlame environment:**
+
+.. code-block:: bash
+
+ cd deepflame-dev
+ . configure.sh --use_pytorch
+ source ./bashrc
+
+.. Note:: Check your environment using ``echo $DF_ROOT`` and you should get the path for the deepflame-dev directory.
+
+Build and Install
+-------------------------------
+Finally you can build and install DeepFlame:
+
+.. code-block:: bash
+
+ . install.sh
+
+.. Note:: You may come accross an error regarding shared library ``libmkl_rt.so.2`` when libcantera is installed through cantera channel. If so, go to your conda environment and check the existance of ``libmkl_rt.so.2`` and ``libmkl_rt.so.1``, and then link ``libmkl_rt.so.2`` to ``libmkl_rt.so.1``.
+
+.. code-block:: bash
+
+ cd ~/miniconda3/envs/df-pytorch/lib
+ ln -s libmkl_rt.so.1 libmkl_rt.so.2
+
+**If you have compiled DeepFlame successfully, you should see the print message in your terminal:**
+
+.. figure:: compile_success.png
+
+Other Options
+-------------------------------
+DeepFlame also provides users with LibTorch and CVODE (no DNN version) options.
+
+**1. If you choose to use LibTorch (C++ API for Torch), first create the conda env and install** `LibCantera `_:
+
+.. code-block:: bash
+
+ conda create -n df-libtorch
+ conda activate df-libtorch
+ conda install -c cantera libcantera-devel
+
+Then you can pass your own libtorch path to DeepFlame.
+
+.. code-block:: bash
+
+ cd deepflame-dev
+ . configure.sh --libtorch_dir /path/to/libtorch/
+ source ./bashrc
+ . install.sh
+
+.. Note:: Some compiling issues may happen due to system compatability. Instead of using conda installed Cantera C++ lib and the downloaded Torch C++ lib, try to compile your own Cantera and Torch C++ libraries.
+
+
+**2. If you just need DeepFlame's CVODE solver without DNN model, just install LibCantera via** `conda `_.
+
+.. code-block:: bash
+
+ conda create -n df-notorch
+ conda activate df-notorch
+ conda install -c cantera libcantera-devel
+
+If the conda env ``df-notorch`` is activated, install DeepFlame by running:
+
+.. code-block:: bash
+
+ cd deepflame-dev
+ . configure.sh
+ source ./bashrc
+ . install.sh
+
+If ``df-notorch`` not activated (or you have a self-complied libcantera), specify the path to your libcantera:
+
+.. code-block:: bash
+
+ . configure.sh --libcantera_dir /your/path/to/libcantera/
+ source ./bashrc
+ . install.sh
diff --git a/docs/source/quickstart/pytorch.png b/docs/source/qs/pytorch.png
similarity index 100%
rename from docs/source/quickstart/pytorch.png
rename to docs/source/qs/pytorch.png
diff --git a/docs/source/quickstart/cvode.rst b/docs/source/quickstart/cvode.rst
deleted file mode 100644
index 9a75c85f..00000000
--- a/docs/source/quickstart/cvode.rst
+++ /dev/null
@@ -1,47 +0,0 @@
-CVODE Intergrator
-===================
-CVODE Integrator is the one without the application of Deep Neural Network (DNN), and it can be used to validate PyTorch and LibTorch integrators.
-Follow the steps below to run an example of CVODE. Examples are stored in the directory:
-.. code-block:: bash
-
- $HOME/deepflame-dev/examples
-
-To run these examples, first source your OpenFOAM, depending on your OpenFOAM path:
-
-.. code-block:: bash
-
- source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
-
-Then, source your DeepFlame:
-
-.. code-block:: bash
-
- source $HOME/deepflame-dev/bashrc
-
-Next, you can go to the directory of any example case that you want to run. For example:
-
-.. code-block:: bash
-
- cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/cvodeIntegrator
-
-This is an example for the zero-dimensional hydrogen combustion with CVODE integrator.
-
-The case is run by simply typing:
-
-.. code-block:: bash
-
- ./Allrun
-
-The probe used for post processing is defined in ``/system/probes``. In this case, the probe is located at the coordinates (0.0025 0.0025 0.0025) to measure temperature variation with time.
-If the case is successfully run, the result can be found in ``/postProcessing/probes/0/T``, and it can be visualized by running:
-
-.. code-block:: bash
-
- gunplot
- plot "/your/path/to/postProcessing/probes/0/T"
-
-You will get a graph:
-
-.. figure:: 0Dcvode.jpg
-
- Visualisation of the zero-dimensional hydrogen combustion result with CVODE integrator
\ No newline at end of file
diff --git a/docs/source/quickstart/index.rst b/docs/source/quickstart/index.rst
deleted file mode 100644
index 0e941bc8..00000000
--- a/docs/source/quickstart/index.rst
+++ /dev/null
@@ -1,18 +0,0 @@
-Examples for Each Chemistry Integrator
-=========================================
-
-DeepFlame provides users with three avaiblable integrators: CVODE, LibTorch, and PyTorch. CVODE integraotr does not include any machine learning capability, while the other two use different APIs to make computation with neural neworks on different platforms possible.
-To get a quick start with all three integrators, there are several examples stored in ``/deepflame-dev/examples/`` that can be run. More details regarding each integrator can be found in the following sections.
-
-
-.. _quickstart:
-
-.. toctree::
- :numbered:
- :glob:
-
- pytorch
- libtorch
- cvode
-
-
\ No newline at end of file
diff --git a/docs/source/quickstart/libtorch.png b/docs/source/quickstart/libtorch.png
deleted file mode 100644
index 5a07c1f1..00000000
Binary files a/docs/source/quickstart/libtorch.png and /dev/null differ
diff --git a/docs/source/quickstart/libtorch.rst b/docs/source/quickstart/libtorch.rst
deleted file mode 100644
index f0e9146f..00000000
--- a/docs/source/quickstart/libtorch.rst
+++ /dev/null
@@ -1,35 +0,0 @@
-Libtorch Integrator
-===================
-If you choose to use LibTorch as the integratgor and use the compilation flag `--libtorch_dir`, you can run examples stored in `$HOME/deepflame-dev/examples/.../libtorchIntegratgor`. To run an example, you first need to source your OpenFOAM:
-
-.. code-block:: bash
-
- source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
-
-Then, source your DeepFlame:
-
-.. code-block:: bash
-
- source $HOME/deepflame-dev/bashrc
-
-Next, you can go to the directory of any example case that you want to run. For example:
-
-.. code-block:: bash
-
- cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/libtorchIntegratgor
-
-This is an example for the zero-dimensional hydrogen combustion with LibTorch as the integrator. All files needed by DNN are listed under the case folder. Configurations regarding DNN are included in `constant/CanteraTorchProperties`.
-
-The case is run by simply typing:
-
-.. code-block:: bash
-
- ./Allrun
-
-.. Note:: Users can go to `constant/CanteraTorchProperties` and check if `torch` is switched on. Switch it `on` to run DNN cases, and switch `off` to run CVODE cases.
-
-If you plot LibTorch's result together with CVODE's result, the graph is expected to look like:
-
-.. figure:: libtorch.png
-
- Visualisation of 0D results from LibTorch and CVODE integrators
diff --git a/docs/source/quickstart/pytorch.rst b/docs/source/quickstart/pytorch.rst
deleted file mode 100644
index b6b8749f..00000000
--- a/docs/source/quickstart/pytorch.rst
+++ /dev/null
@@ -1,36 +0,0 @@
-PyTorch Integrator
-===================
-
-If you choose to use PyTorch as the integratgor and use the compilation flag `--use_pytorch`, you can run examples stored in `$HOME/deepflame-dev/examples/.../pytorchIntegratgor`. To run an example, you first need to source your OpenFOAM:
-
-.. code-block:: bash
-
- source $HOME/OpenFOAM/OpenFOAM-7/etc/bashrc
-
-Then, source your DeepFlame:
-
-.. code-block:: bash
-
- source $HOME/deepflame-dev/bashrc
-
-Next, you can go to the directory of any example case that you want to run. For example:
-
-.. code-block:: bash
-
- cd $HOME/deepflame-dev/examples/zeroD_cubicReactor/H2/pytorchIntegratgor
-
-This is an example for the zero-dimensional hydrogen combustion with PyTorch as the integrator. All files needed by DNN are stored in `pytorchDNN` folder, and the inference file is `inference.py`. Configurations regarding DNN are included in `constant/CanteraTorchProperties`.
-
-The case is run by simply typing:
-
-.. code-block:: bash
-
- ./Allrun
-
-.. Note:: Users can go to `constant/CanteraTorchProperties` and check if `torch` is switched on. Switch it `on` to run DNN cases, and switch `off` to run CVODE cases.
-
-If you plot PyTorch's result together with CVODE's result, the graph is expected to look like:
-
-.. figure:: pytorch.png
-
- Visualisation of 0D results from PyTorch and CVODE integrators
\ No newline at end of file