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https://github.com/mrauha/compchem_start

How to get started with computational chemistry research. Directed to new people in our lab, may be useful in general.
https://github.com/mrauha/compchem_start

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How to get started with computational chemistry research. Directed to new people in our lab, may be useful in general.

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README 

        
# Computational chemistry - how to get started



This document has resources for people new to computational quantum chemistry. Mainly directed for people starting at [our lab](https://blogs.helsinki.fi/johansson-group/).



This list is currently quite rough looking, I'm constantly making updates :)



List of abbreviations:

  * DFT - Density functional theory

  * QC - Quantum chemistry

  * QM - Quantum mechanics

  * MD - Molecular dynamics



# Books and lecture notes



## Quantum chemistry

* [Atkins: Molecular Quantum Mechanics](https://www.amazon.com/Molecular-Quantum-Mechanics-Peter-Atkins/dp/0199541426)

* [Piela: Ideas of Quantum Chemistry](https://www.amazon.com/Ideas-Quantum-Chemistry-Lucjan-Piela/dp/0444522271)



## Computational chemistry



### General



* [Szabo, Ostlund: Modern Quantum Chemistry](https://www.amazon.com/Modern-Quantum-Chemistry-Introduction-Electronic/dp/0486691861)

  * Quite dense

* [Jensen: Introduction to Computational Chemistry](https://www.amazon.com/Introduction-Computational-Chemistry-Frank-Jensen/dp/1118825993/ref=dp_ob_image_bk)

  * Accessible

* [Bachrach: Computational Organic Chemistry](https://www.amazon.com/Computational-Organic-Chemistry-Steven-Bachrach/dp/1118291921/ref=dp_ob_title_bk)

  * Nice examples, easy to read

* [Cramer: Essential of Computational Chemistry](https://www.amazon.com/Essentials-Computational-Chemistry-Theories-Models/dp/0470091827)

  * Nice explanations, accessible

* [Helgaker, Jorgensen, Olsen: Molecular Electronic-Structure Theory](https://www.amazon.com/Molecular-Electronic-Structure-Theory-Trygve-Helgaker/dp/0470017600/ref=dp_ob_title_bk)

  * Very dense, a reference book



### DFT

* [Koch, Holthausen: A Chemist's Guide to Density Functional Theory ](https://www.amazon.com/Chemists-Guide-Density-Functional-Theory/dp/3527303723)



### Other

* [Reiher: Relativistic Quantum Chemistry](https://www.amazon.com/Relativistic-Quantum-Chemistry-Fundamental-Molecular/dp/3527334157)

* [Berendsen: Simulating the Physical World](https://www.amazon.com/Simulating-Physical-World-Hierarchical-Mechanics/dp/0521835275)

  * Simulating materials, describes different models needed for different scales very well



# Working with remote clusters



* All the heavy computational work is done on remote computers

* All these computers run on linux

  * DigitalOcean (provides virtual private servers for websites etc) has good tutorials: [link](https://www.digitalocean.com/community/tutorials/)

  * Terminal basics

    * Learn to use shell efficiently

      * mkdir, mv, cp, ls, pwd, ...

    * [Basic Linux Navigation and File Management](https://www.digitalocean.com/community/tutorials/basic-linux-navigation-and-file-management)

  * Connect with ssh if you use linux/mac, with [putty](https://putty.org/) etc on Windows

    * [Tutorial ](https://www.digitalocean.com/community/tutorials/ssh-essentials-working-with-ssh-servers-clients-and-keys)

  * Copying files done with SCP

    * [Tutorial](https://www.digitalocean.com/community/questions/how-to-copy-files-from-one-server-to-another-droplet)



## CSC

* The calculations require a lot of resources

* [CSC](https://research.csc.fi/guides) provides computational resources for us

  * Taito supercluster

  * Sisu supercomputer

* A lot of chemistry software preinstalled

  * [Listed here](https://research.csc.fi/software?p_p_id=122&p_r_p_564233524_categoryId=53920)

* Access to [several databases](https://research.csc.fi/chemistry/databases)

  * [Cambridge Structural Database System](https://research.csc.fi/-/csd)

    * X-ray structures of molecules, useful toolkits for searching structures

    * Web interface [WebCSD](https://www.ccdc.cam.ac.uk/structures/)

      * Search with DOI etc

      * The .cif files can be opened with avogadro, chemcraft, ...

## Resource allocation

  * Clusters have a lot of users, workload manager is used to allocate resources

  * Define the resources you need

    * Amount of cores, memory, time, ...

  * [SLURM](https://slurm.schedmd.com/) workload manager is used in our environments

    * Batch job file

      * Used to define the calculation

        * Resources and software needed

    * [CSCs tutorial](https://research.csc.fi/taito-constructing-a-batch-job-file)

    * Here's another[ tutorial](https://github.com/abalter/slurm-tutorial/wiki/slurm-tutorial)



# Used methods



## Quantum chemistry



$H\Psi = E\Psi$



* Basis sets

* BO approximation

* HF

* Electron correlation

* DFT

  * Functionals



## Workflow

1) Build the molecule with some visual tool (see below)

  * [xyz file format](https://en.wikipedia.org/wiki/XYZ_file_format)

2) Create an input file

  * Each QC program has their own

3) Send the job to queue

4) Check results

  * Errors are usually due to

    * faulty input file

    * not enough resources, such as time, memory

    * convergence problems

      * several ways to proceed, see Jensen's book

5) Collect and analyze results

  * Spreadsheets, Python, ...



## Molecular dynamics

* Classical simulations

    * Potential is defined as a sum of bond, angle, dihedral, van der Waals, electrostatic terms

      * Parameters from experiments, QC calculations

  * No quantum mechanical effects

    * Bond breaking, polarization, ...



* Not very useful in our stuff, we mostly look at small molecules



# Software



## Quantum chemistry



* [ORCA](https://orcaforum.cec.mpg.de/)

  * [On CSC](https://research.csc.fi/software-details/-/asset_publisher/bwNv9EAV4eYX/content/orca)

  * Active community, good forum

  * [ORCA input library](https://sites.google.com/site/orcainputlibrary/) is *amazing*. Easy to get started with this!

  * Free for scientists! :)

  * Good for spectroscopy

  * DLPNO-CCSD(T) method!



* [Turbomole](http://www.turbomole.com/)

  * [On CSC](https://research.csc.fi/-/turbomole?redirect=https%3A%2F%2Fresearch.csc.fi%2Fsoftware%3Fp_p_id%3D101_INSTANCE_wfvLxzjnZlJx%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_p_col_id%3Dcolumn-2%26p_p_col_pos%3D1%26p_p_col_count%3D4%26p_r_p_564233524_categoryId%3D61753%26p_r_p_564233524_resetCur%3Dtrue)

  * Fast!

  * No typical input files

    * Jobs are set up using the interactive define-script

      * Not very user friendly, must be scripted away when running large-scale calculations



* [Gaussian](http://gaussian.com/)

  * [On CSC](https://research.csc.fi/software-details/-/asset_publisher/bwNv9EAV4eYX/content/gaussian)



* [NWChem](http://www.nwchem-sw.org/index.php/Main_Page)

  * [On CSC](https://research.csc.fi/software-details/-/asset_publisher/bwNv9EAV4eYX/content/nwchem?redirect=https%3A%2F%2Fresearch.csc.fi%2Fsoftware-details%3Fp_p_id%3D101_INSTANCE_bwNv9EAV4eYX%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_p_col_id%3Dcolumn-2%26p_p_col_count%3D1)

  * Open-source! :)

  * Good for LARGE problems, scales to thousands of processors



## Molecular dynamics



* [GROMACS](http://www.gromacs.org/)

  * The manual is a good intro to MD!



## Visualization and



* [Avogadro](https://avogadro.cc/)

  * Open source, quite powerful

  * Best tool for building molecules, UFF force field for preoptimization

  * Conformation search

  * Visualization of orbitals, vibrations, Bader analysis, ...



* [VMD](http://www.ks.uiuc.edu/Research/vmd/)

  * Excellent and scriptable program, heavily used in MD field



* [Chemcraft](https://www.chemcraftprog.com/)

  * Good for many manipulations, visualization

  * Not free, 150 days free trial period



## Wavefunction analysis

  * [MultiWFN](http://sobereva.com/multiwfn/)

    * Excellent tool for wave function analysis

    * Pretty much everything is implemented

    * Takes as an input eg. a molden-file

  * [NCIPlot](http://www.lct.jussieu.fr/pagesperso/contrera/nciplot.html)

    * Visual analysis of weak interactions



## Scripting and working with data



### Python

* Best choice in my opinion!

  * I use it for everything: scientific computing, workflow automation, web development, deep learning, home automation...

  * One of the most popular languages

    * Excellent resources available!

  * Slow for number crunching

    * Can be used as front-end for C, Fortran through libraries

* So many resources!

  * Programming intros

    * [How to Think Like a Computer Scientist](https://interactivepython.org/runestone/static/thinkcspy/index.html)

    * [Think Python](https://greenteapress.com/wp/think-python-2e/), OK book

  * [Full stack python](https://www.fullstackpython.com/table-of-contents.html)

  * [/r/python](https://old.reddit.com/r/Python/) subreddit, check the side panel!



#### [Notebooks](https://jupyter.org/)



* Jupyter Notebooks: Very nice graphical user interface

* Each notebook consists of cells

  * May contain code, markdown text, latex

  * Can be run separately

* Inline plotting

* Can be shared

* See Johansson's [Scientific python lectures](https://github.com/jrjohansson/scientific-python-lectures), excellent intro to python, notebooks, the scientific stack



#### Excellent data science stack, useful libraries:



* [Numpy](https://docs.scipy.org/doc/numpy-1.14.0/reference/)

  * linear algebra calculations and much more



* [SciPy](https://docs.scipy.org/doc/scipy/reference/)

  * special functions, integrals, a lot of numerical tools



* [Matplotlib](https://matplotlib.org/index.html)

  * plotting, excellent for visualizations

*[Pandas](https://pandas.pydata.org/pandas-docs/version/0.22.0/10min.html)

  * "excel", data structures, good for data manipulation, analysis



* [Scikit-learn](http://scikit-learn.org/)

  * Machine learning, regression, statistics



* [Keras](https://keras.io/), [tensorflow](https://www.tensorflow.org/)

  * Deep learning, cool stuff



### Bash tools

  * sed

  * awk

  * gnuplot



### [Cheminformatics](https://en.wikipedia.org/wiki/Cheminformatics)

* "Information technologies for chemistry"

#### Software

  * [RDKit](http://www.rdkit.org/docs/GettingStartedInPython.html)

    * Very nice open-source library, python interface

  * [CDK](https://cdk.github.io/)

    * Apparently quite good, in Java

#### Data structures for molecules

  * For storing, searching, ...

  * [SMILES](https://en.wikipedia.org/wiki/Simplified_molecular-input_line-entry_system)

  * [SMARTS](https://en.wikipedia.org/wiki/Smiles_arbitrary_target_specification)

  * [InCHL](https://en.wikipedia.org/wiki/International_Chemical_Identifier)



#### Databases

  * Relational databases (MySQL, sqlite, postgreSQL, ...)

  * Non-relational (MongoDB, ...)

  * Pandas is quite good in my opinion