QCConst

Physical constants, conversion factors, and a periodic table with clear source information for every value. Data from NIST CODATA 2022, Pubchem, and Washington University. All data in atomic units (e.g., length in Bohr).

Data Sources

Each piece of data contains a link to its source. Primary data sources include:

Installation

python -m pip install qcconst

Quickstart

Constants

Top-level constants can be accessed at attributes on the constants module for easy discovery and TAB-completion in Jupyter Notebooks or IDEs. This is the most convenient way to access constants. Most values come directly from CODATA (or are conversion factors computed directly from CODATA) that are given more computationally-friendly names for easy access.

>>> from qcconst import constants

>>> constants.BOHR_TO_ANGSTROM
0.529177210544, unit=Å, source=https://physics.nist.gov/cgi-bin/cuu/Value?bohrrada0

# Use constants just like a float
>>> constants.BOHR_TO_ANGSTROM * 10
5.29177210544

# Know the source of every constant
>>> constants.BOHR_TO_ANGSTROM.source
'https://physics.nist.gov/cgi-bin/cuu/Value?bohrrada0'

# See sources for all constants
>>> constants.sources
['https://physics.nist.gov/cgi-bin/cuu/Value?bohrrada0', 'https://physics.nist.gov/cgi-bin/cuu/Value?hrj|search_for=hartree+to+joule', 'https://physics.nist.gov/cuu/Constants/Table/allascii.txt', 'https://www.nist.gov/pml/special-publication-811/nist-guide-si-appendix-b-conversion-factors/nist-guide-si-appendix-b8']

# List all available constants
>>> constants.as_list()
['ANGSTROM_TO_BOHR', 'AVOGADRO_NUMBER', 'BOHR_TO_ANGSTROM', 'BOLTZMANN_CONSTANT', 'HARTREE_TO_JOULE', 'HARTREE_TO_KCAL_PER_MOL', 'KCAL_TO_JOULE', ...]

# Human readable print out of all available constants
>>> constants.show()
name                              value  unit      source
-----------------------  --------------  --------  ---------------------------------------------------------
ANGSTROM_TO_BOHR            1.88973      Bohr      Derived as 1 / BOHR_TO_ANGSTROM
AVOGADRO_NUMBER             6.02214e+23  mol⁻¹     https://physics.nist.gov/cuu/Constants/Table/allascii.txt
BOHR_TO_ANGSTROM            0.529177     Å         https://physics.nist.gov/cgi-bin/cuu/Value?bohrrada0
BOLTZMANN_CONSTANT          1.38065e-23  J/K       https://physics.nist.gov/cuu/Constants/Table/allascii.txt
...

All CODATA Physical Constants

The full CODATA 2022 set of constants are available by their NIST-given name at constants.phys or constants.codata2022. constants.phys will always point to the latest CODATA values. Currently this is the 2022 release.

>>> from qcconst import constants

>>> constants.phys['atomic unit of permittivity']
1.1126500562e-10, unit=kg m s^-1, source=CODATA 2022: https://physics.nist.gov/cuu/Constants/Table/allascii.txt

>>> constants.codata2022['conventional value of von Klitzing constant']
25812.807, unit=ohm, source=CODATA 2022: https://physics.nist.gov/cuu/Constants/Table/allascii.txt

Periodic Table

>>> from qcconst import periodic_table as pt

>>> pt.Ni
Element(symbol='Ni', number=28, name='Nickel', mass=58.6934, group=10, period=4, block='d', electron_config='[Ar] 3d8 4s2')

>>>pt.Ni.number
28

# Lookup by atomic number
>>> pt.number(4)
Element(symbol='Be', number=4, name='Beryllium', mass=9.012183, group=2, period=2, block='Alkaline earth metal', electron_config='[He]2s2')

>>> pt.group(1)
[Element(symbol='H', number=1, name='Hydrogen', mass=1.00784, group=1, period=1, block='s', electron_config='1s1'),
Element(symbol='Li', number=3, name='Lithium', mass=6.94, group=1, period=2, block='s', electron_config='[He] 2s1'),
Element(symbol='Na', number=11, name='Sodium', mass=22.98976928, group=1, period=3, block='s', electron_config='[Ne] 3s1'),
Element(symbol='K', number=19, name='Potassium', mass=39.0983, group=1, period=4, block='s', electron_config='[Ar] 4s1'),
Element(symbol='Rb', number=37, name='Rubidium', mass=85.4678, group=1, period=5, block='s', electron_config='[Kr] 5s1'),
Element(symbol='Cs', number=55, name='Cesium', mass=132.90545196, group=1, period=6, block='s', electron_config='[Xe] 6s1'),
Element(symbol='Fr', number=87, name='Francium', mass=223.0, group=1, period=7, block='s', electron_config='[Rn] 7s1')]

>>> pt.period(3)
[Element(symbol='Na', number=11, name='Sodium', mass=22.9897693, group=1, period=3, block='Alkali metal', electron_config='[Ne]3s1'),
Element(symbol='Mg', number=12, name='Magnesium', mass=24.305, group=2, period=3, block='Alkaline earth metal', electron_config='[Ne]3s2'),
Element(symbol='Al', number=13, name='Aluminum', mass=26.981538, group=13, period=3, block='Post-transition metal', electron_config='[Ne]3s2 3p1'),
Element(symbol='Si', number=14, name='Silicon', mass=28.085, group=14, period=3, block='Metalloid', electron_config='[Ne]3s2 3p2'),
Element(symbol='P', number=15, name='Phosphorus', mass=30.973762, group=15, period=3, block='Nonmetal', electron_config='[Ne]3s2 3p3'),
Element(symbol='S', number=16, name='Sulfur', mass=32.07, group=16, period=3, block='Nonmetal', electron_config='[Ne]3s2 3p4'),
Element(symbol='Cl', number=17, name='Chlorine', mass=35.45, group=17, period=3, block='Halogen', electron_config='[Ne]3s2 3p5'),
Element(symbol='Ar', number=18, name='Argon', mass=39.9, group=18, period=3, block='Noble gas', electron_config='[Ne]3s2 3p6')]

# Know the sources of the data
>>> pt.sources
['Alvarez 2013: https://doi.org/10.1039/C3DT50599E', 'Pyykkö et al. 2009: https://doi.org/10.1002/chem.200901472', 'PubChem: https://pubchem.ncbi.nlm.nih.gov/periodic-table', 'Cordero et al. 2008: https://doi.org/10.1039/b801115j']

# Human readable print out of the Periodic Table data
>>> pt.show()
Sources: ['Pyykkö et al. 2009: https://doi.org/10.1002/chem.200901472', 'Cordero et al. 2008: https://doi.org/10.1039/b801115j', 'Alvarez 2013: https://doi.org/10.1039/C3DT50599E', 'PubChem: https://pubchem.ncbi.nlm.nih.gov/periodic-table']

symbol  number  name           mass    group  period  block                  electron_config                    electronegativity  atomic_radius  cov_radius  cov_radius_double  cov_radius_triple  vdw_radius
------  ------  -------------  ------  -----  ------  ---------------------  ---------------------------------  -----------------  -------------  ----------  -----------------  -----------------  ----------
H            1  Hydrogen        1.008      1       1  Nonmetal               1s1                                              2.2         2.2677     0.58582                                            2.2677
He           2  Helium         4.0026     18       1  Noble gas              1s2                                                          2.6456     0.52912                                            2.7023
Li           3  Lithium             7      1       2  Alkali metal           [He]2s1                                         0.98         3.4393      2.4188             2.3433                         4.0062
Be           4  Beryllium      9.0122      2       2  Alkaline earth metal   [He]2s2                                         1.57         2.8913      1.8141             1.7008             1.6063      3.7417
B            5  Boron           10.81     13       2  Metalloid              [He]2s2 2p1                                     2.04         3.6283      1.5874              1.474             1.3795      3.6094
C            6  Carbon         12.011     14       2  Nonmetal               [He]2s2 2p2                                     2.55         3.2125      1.4362             1.2661             1.1338      3.3448
N            7  Nitrogen       14.007     15       2  Nonmetal               [He] 2s2 2p3                                    3.04         2.9291      1.3417             1.1338             1.0205      3.1369
...

Solvents

Solvents are accessed with a dictionary lookup rather than attribute lookup because many of their names are invalid Python attributes (i.e., they start with a number or contain - characters). For example, solvents.1,2-dimethoxyethane is invalid syntax. As a result, solvents are looked up using solvents['name'] rather than solvents.name.

from qcconst import solvents

>>> solvents["1,4-dioxane"]
Solvent(name='1,4-dioxane', dielectric=2.25, sources=['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf'])

>>> solvents["1,4-dioxane"].dielectric
2.25

# Will return None if solvent not found
>>> solvents.get("Fake Solvent")
>>>

# List all available solvents
>>> solvents.as_list()
['acetic acid', 'acetone', 'acetonitrile', 'anisole', 'benzene', 'bromobenzene', 'carbon disulfide', 'carbon tetrachloride', 'chlorobenzene', 'chloroform', 'cyclohexane', 'dibutyl ether', 'o-dichlorobenzene', '1,2-dichloroethane', 'dichloromethane', 'diethylamine', 'diethyl ether', '1,2-dimethoxyethane', 'n', 'n,n-dimethylformamide', 'dimethyl sulfoxide', '1,4-dioxane', 'ethanol', 'ethyl acetate', 'ethyl benzoate', 'formamide', 'hexamethylphosphoramide', 'isopropyl alcohol', 'methanol', '2-methyl-2-propanol', 'nitrobenzene', 'nitromethane', 'pyridine', 'tetrahydrofuran', 'toluene', 'trichloroethylene', 'triethylamine', 'trifluoroacetic acid', '2,2,2-trifluoroethanol', 'water', 'o-xylene', ...]

# Know the sources of the data
>>> solvents["water"].sources
['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']

# Human readable print out of all available solvents
>>> solvents.show()
name                       dielectric  sources
-----------------------  ------------  ------------------------------------------------------------------------------
acetic acid                      6.15  ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
acetone                         20.7   ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
acetonitrile                    37.5   ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
anisole                          4.33  ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
benzene                          2.27  ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
bromobenzene                     5.17  ['https://depts.washington.edu/eooptic/linkfiles/dielectric_chart%5B1%5D.pdf']
...

Adding New Values

Adding new values is simple! Just add it to one of the .csv files in src/qcconst/data. Include the value, its source, and any other required metadata and then open a PR. That's it! ✨

The QC Suite of Programs

The QC Suite works in harmony to provide fast, structured, and interoperable quantum chemistry tools.

• qcconst - Physical constants, conversion factors, and a periodic table with clear source information for every value.
• qcdata - Elegant and intuitive data structures for quantum chemistry, featuring seamless Jupyter Notebook visualizations. Documentation
• qcinf - Cheminformatics algorithms and structure utilities using standardized qcdata data structures.
• qccodec - A package for translating between standardized qcdata data structures and native QC program inputs and outputs.
• qccompute - A package for operating quantum chemistry programs using standardized qcdata data structures. Compatible with TeraChem, psi4, QChem, NWChem, ORCA, Molpro, geomeTRIC and many more.
• BigChem - A distributed application for running quantum chemistry calculations at scale across clusters of computers or the cloud. Bring multi-node scaling to your favorite quantum chemistry program.
• ChemCloud - A web application and associated Python client for exposing a BigChem cluster securely over the internet.