Fluoroelastomer Formulations JSON-LD

FE Formulations JSON-LD Description

In Fluoroelastomer (FE) Formulations JSON-LD template, the fluoroelastomer sample is defined by material, batch and other properties. Please note that batch signifies different formulation of the fluoroelastomer; two fluoroelastomers may be made up of the same material but could have different formulations.

The template is made up of two sub-categories, namely atomic force microscopy (AFM) experimental parameters and information about fluoroelastomers. Under fluoroelastomers, there are parameters related to film preparation and fluoroelastomer specifications as well as properties. The detailed structure is shown in the schema diagram below.

Creating JSON-LD for FE Formulations in R

library(FAIRmaterials)

# An example data frame for FE formulations
fe_exp <- data.frame(
  'material' = c('FK-800', 'Kel-F'),
  'batch' = c('AA', 'G-mixed'),
  'substrate' = c('Si', 'Glass'),
  'afmChannel' = c('Height', 'Phase'),
  'solventType' = c('Ethanol', 'Ethyl acetate')
)

# This will generate JSON-LD file for the example data
output <- fairify_data(fe_exp, domain = 'fluoroelastometerFormulation')

Creating JSON-LD for FE Formulations in Python

from fairmaterials.fairify_data import *
import pandas as pd

# Create an example data frame for FE formulations
fe_exp = pd.DataFrame(
  'material' = ['FK-800', 'Kel-F'],
  'batch' = ['AA', 'G-mixed'],
  'substrate' = ['Si', 'Glass'],
  'afmChannel' = ['Height', 'Phase'],
  'solventType' = ['Ethanol', 'Ethyl acetate'],
)

# This will generate JSON-LD file for the example data
output <- fairify_data(fe_exp, domain = 'PolymerAM')

FE Formulations schema diagram

Acknowledgment

This material is based upon research in the Materials Data Science for Stockpile Stewardship Center of Excellence (MDS3-COE), and supported by the Department of Energy’s National Nuclear Security Administration under Award Number(s) DE-NA0004104.