Package: radioactivedecay
radioactivedecayis a Python package for radioactive decay calculations.
It supports decay chains of radionuclides, metastable states and branching
decays. By default it uses the decay data from ICRP Publication 107, which
contains 1252 radionuclides of 97 elements, and atomic mass data from the
Atomic Mass Data Center.The code solves the radioactive decay differential equations analytically using
NumPy and SciPy linear algebra routines. There is also a high numerical
precision calculation mode employing SymPy routines. This gives more accurate
results for decay chains containing radionuclides with orders of magnitude
differences between the half-lives.This is free-to-use open source software. It was created for engineers,
technicians and researchers who work with radioactivity, and for
educational use.Full Documentation:https://radioactivedecay.github.io/Installationradioactivedecayrequires Python 3.6+. Installradioactivedecayfrom
thePython Package Indexusingpip:$pipinstallradioactivedecayor fromconda-forge:$condainstall-cconda-forgeradioactivedecayEither command will attempt to install the dependencies (Matplotlib, NetworkX,
NumPy, SciPy, Setuptools & SymPy) if they are not already present in the
environment.UsageDecay calculationsCreate anInventoryof radionuclides and decay it as follows:>>>importradioactivedecayasrd>>>Mo99_t0=rd.Inventory({'Mo-99':2.0},'Bq')>>>Mo99_t1=Mo99_t0.decay(20.0,'h')>>>Mo99_t1.activities('Bq'){'Mo-99': 1.6207863893776937, 'Ru-99': 0.0,'Tc-99': 9.05304236308454e-09, 'Tc-99m': 1.3719829376710406}AnInventoryof 2.0 Bq of Mo-99 was decayed for 20 hours, producing the
radioactive progeny Tc-99m and Tc-99, and the stable nuclide Ru-99.We supplied'h'as an argument todecay()to specify the decay time
period had units of hours. Supported time units include'μs','ms','s','m','h','d','y'etc. Note seconds ('s') is the
default if no unit is supplied todecay().Usecumulative_decays()to calculate the total number of atoms of each
radionuclide that decay over the decay time period:>>>Mo99_t0.cumulative_decays(20.0,'h'){'Mo-99': 129870.3165339939, 'Tc-99m': 71074.31925850797,'Tc-99': 0.0002724635511147602}Radionuclides can be specified in four equivalent ways inradioactivedecay:
three variations of nuclide strings or bycanonical ids. For example, the
following are equivalent ways of specifying222Rn and192nIr:'Rn-222','Rn222','222Rn',862220000,'Ir-192n','Ir192n','192nIr',771920002.Inventories can be created by supplying activity ('Bq','Ci','dpm'...), mass ('g','kg'...), mole ('mol','kmol'...)
units, or numbers of nuclei ('num') to theInventory()constructor. Use
the methodsactivities(),masses(),moles(),numbers(),activity_fractions(),mass_fractions()andmole_fractions()to
obtain the contents of the inventory in different formats:>>>H3_t0=rd.Inventory({'H-3':3.0},'g')>>>H3_t1=H3_t0.decay(12.32,'y')>>>H3_t1.masses('g'){'H-3': 1.5, 'He-3': 1.4999900734297729}>>>H3_t1.mass_fractions(){'H-3': 0.5000016544338455, 'He-3': 0.4999983455661545}>>>C14_t0=rd.Inventory({'C-14':3.2E24},'num')>>>C14_t1=C14_t0.decay(3000,'y')>>>C14_t1.moles('mol'){'C-14': 3.6894551567795797, 'N-14': 1.6242698581767292}>>>C14_t1.mole_fractions(){'C-14': 0.6943255713073281, 'N-14': 0.3056744286926719}Plotting decay graphsUse theplot()method to graph of the decay of an inventory over time:>>>Mo99_t0.plot(20,'d',yunits='Bq')The graph shows the decay of Mo-99 over 20 days, leading to the ingrowth of
Tc-99m and a trace quantity of Tc-99. The activity of Ru-99 is strictly zero as
it is the stable nuclide at the end of the decay chain. Graphs are drawn using
Matplotlib.Fetching decay dataTheNuclideclass can be used to fetch decay information for
individual radionuclides, e.g. for Rn-222:>>>nuc=rd.Nuclide('Rn-222')>>>nuc.half_life('s')330350.4>>>nuc.half_life('readable')'3.8235 d'>>>nuc.progeny()['Po-218']>>>nuc.branching_fractions()[1.0]>>>nuc.decay_modes()['α']>>>nuc.Z# proton number86>>>nuc.A# nucleon number222>>>nuc.atomic_mass# atomic mass in g/mol222.01757601699998There are similar inventory methods for fetching decay data:>>>Mo99_t1.half_lives('readable'){'Mo-99': '65.94 h', 'Ru-99': 'stable', 'Tc-99': '0.2111 My', 'Tc-99m': '6.015 h'}>>>Mo99_t1.progeny(){'Mo-99': ['Tc-99m', 'Tc-99'], 'Ru-99': [], 'Tc-99': ['Ru-99'], 'Tc-99m': ['Tc-99', 'Ru-99']}>>>Mo99_t1.branching_fractions(){'Mo-99': [0.8773, 0.1227], 'Ru-99': [], 'Tc-99': [1.0], 'Tc-99m': [0.99996, 3.7e-05]}>>>Mo99_t1.decay_modes(){'Mo-99': ['β-', 'β-'], 'Ru-99': [], 'Tc-99': ['β-'], 'Tc-99m': ['IT', 'β-']}Decay chain diagramsTheNuclideclass includes aplot()method for drawing decay chain
diagrams:>>>nuc=rd.Nuclide('Mo-99')>>>nuc.plot()These diagrams are drawn using NetworkX and Matplotlib.High numerical precision decay calculationsradioactivedecayincludes anInventoryHPclass for high numerical
precision calculations. This class can give more reliable decay calculation
results for chains containing long- and short-lived radionuclides:>>>U238_t0=rd.InventoryHP({'U-238':1.0})>>>U238_t1=U238_t0.decay(10.0,'d')>>>U238_t1.activities(){'At-218': 1.4511675857141352e-25,'Bi-210': 1.8093327888942224e-26,'Bi-214': 7.09819414496093e-22,'Hg-206': 1.9873081129046843e-33,'Pa-234': 0.00038581180879502017,'Pa-234m': 0.24992285949158477,'Pb-206': 0.0,'Pb-210': 1.0508864357335218e-25,'Pb-214': 7.163682655782086e-22,'Po-210': 1.171277829871092e-28,'Po-214': 7.096704966148592e-22,'Po-218': 7.255923469955255e-22,'Ra-226': 2.6127168262000313e-21,'Rn-218': 1.4511671865210924e-28,'Rn-222': 7.266530698712501e-22,'Th-230': 8.690585458641225e-16,'Th-234': 0.2499481473619856,'Tl-206': 2.579902288672889e-32,'Tl-210': 1.4897029111914831e-25,'U-234': 1.0119788393651999e-08,'U-238': 0.9999999999957525}How radioactivedecay worksradioactivedecaycalculates an analytical solution to the radioactive decay
differential equations using linear algebra operations. It implements the
method described in this paper:M Amaku, PR Pascholati & VR Vanin, Comp. Phys. Comm. 181, 21-23
(2010). See thetheory docpagefor more
details.It uses NumPy and SciPy routines for standard decay calculations
(double-precision floating-point operations), and SymPy for arbitrary numerical
precision calculations.By defaultradioactivedecayuses decay data fromICRP Publication 107
(2008)and atomic mass
data from theAtomic Mass Data Center(AMDC - AME2020 and Nubase2020 evaluations).Thedatasets repocontains
Jupyter Notebooks for creating decay datasets that can be used byradioactivedecay, e.g.ICRP
107.Thecomparisons repocontains some checks ofradioactivedecayagainstPyNEandRadiological
Toolbox.TestsFrom the base directory run:$python-munittestdiscoverLicenseradioactivedecayis open source software released under the MIT License.
SeeLICENSEfile for details.The default decay data used byradioactivedecay(ICRP-107) is copyright
2008 A. Endo and K.F. Eckerman and distributed under a separatelicense.
The default atomic mass data is from AMDC
(license).CitationIf you find this package useful for your research, please consider citing the
paper onradioactivedecaypublished in theJournal of Open Source Software:Alex Malins & Thom Lemoine,radioactivedecay: A Python package for radioactive decay
calculations. Journal of Open Source Software,7(71), 3318 (2022). DOI:10.21105/joss.03318.ContributingContributors are welcome to fix bugs, add new features or make feature
requests. Please open an Issue, Pull Request or new Discussions thread atGitHub repository.Please read thecontribution guidelines.