H-transport-materials

Installation

pip install h-transport-materials

Usage

Access the internal database
Add custom properties
Filters
Compute mean values
Export to BibTeX

Access the internal database

import h_transport_materials as htm
import matplotlib.pyplot as plt

# filter only tungsten and H
diffusivities = htm.diffusivities.filter(material="tungsten").filter(isotope="h")

htm.plotting.plot(diffusivities)


plt.yscale("log")
plt.ylabel("Diffusivity (m$^2$/s)")
plt.legend()
plt.show()

Figure_1

Add custom properties

import h_transport_materials as htm

import numpy as np

# Create a custom property
my_custom_property = htm.ArrheniusProperty(pre_exp=1e-5, act_energy=0.2)

# From (T, y) data
my_fitted_property = htm.ArrheniusProperty(
    data_T=[300, 400, 500, 600],
    data_y=[1e-8, 1e-7, 1e-6, 1e-5],
)

print("Pre-exponential factor: {:.2e}".format(my_fitted_property.pre_exp))
print("Activation energy: {:.2f} eV".format(my_fitted_property.act_energy))

# Pre-exponential factor: 4.40e-03
# Activation energy: 0.35 eV

Filters

import h_transport_materials as htm

# tungsten solubilities
htm.solubilities.filter(material="tungsten")

# copper and cucrzr solubilities
htm.solubilities.filter(material=["copper", "cucrzr"])

# all_authors_except_ryabchikov
htm.diffusivities.filter(material="tungsten").filter(author="ryabchikov", exclude=True)

# only Tritium
htm.diffusivities.filter(isotope="t")

Compute mean values

import h_transport_materials as htm
import matplotlib.pyplot as plt

tungsten_diffusivities = htm.diffusivities.filter(material="tungsten").filter(
    author=["moore", "zakharov"], exclude=True
)

# compute mean diffusivity
mean_diffusivity = tungsten_diffusivities.mean()

# plot
htm.plotting.plot(tungsten_diffusivities, alpha=0.5)

htm.plotting.plot(mean_diffusivity, color="black", linewidth=3)

x_annotation = 0.0034
plt.annotate("mean value", (x_annotation, mean_diffusivity.value(T=1 / x_annotation)))

plt.ylabel("Diffusivity (m$^2$ s$^{-1}$)")
plt.yscale("log")
plt.show()

Figure_1

Export to BibTeX

The refernces of properties and properties groups can be exported to a bibfile.

import h_transport_materials as htm

tungsten_diffusivities = htm.diffusivities.filter(material="tungsten")

tungsten_diffusivities.export_bib("my_bibfile.bib")

Contributions

The current database is far from complete. Contributions are most welcome to extend it by adding new properties and also new materials!

Release files for h-transport-materials 0.12.7a0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for h-transport-materials 0.12.7a0
File	Size	Uploaded
h_transport_materials-0.12.7a0.tar.gz	4.6 MB	May 2, 2023	Details

Built distribution (wheel)

Table of built distributions (wheels) for h-transport-materials 0.12.7a0
File	Interpreter	ABI	Platform	Reset
h_transport_materials-0.12.7a0-py3-none-any.whl 150.8 kB May 2, 2023	Python 3	none	any	Details

Total release size: 4.7 MB

Release files / h_transport_materials-0.12.7a0.tar.gz

Download URL	h_transport_materials-0.12.7a0.tar.gz
Size	4.6 MB
Tags	Source
SHA-256 checksum How to use checksums	`22d0051cf07ad4e842099f7e8c78d1e0ff22646bb3397ce3053f913997049005`
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Upload date	May 2, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.9.16`

Release files / h_transport_materials-0.12.7a0-py3-none-any.whl

Download URL	h_transport_materials-0.12.7a0-py3-none-any.whl
Size	150.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`23c1eaf008f8b0ad7afbdd129082368242df645d0578940c2f00326f10eb18ca`
BLAKE2b-256 checksum How to use checksums	`3e74d552f2fd682c54794ea4176594cdf9f6c926bc44459e3270c12b78d93936`
Upload date	May 2, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.9.16`