# Polymer Additive Manufacturing JSON-LD

#### Hein Htet Aung, Roger H. French, Laura S. Bruckman

#### 2023-08-09

## Polymer AM JSON-LD Description

In Polymer Additive Manufacturing (AM) JSON-LD template, the sample information (sample id) is related to printing parameters to produce the part, the build geometry of the part, material properties of the part and the characterization techniques (in-situ and ex-situ) performed on the part.

More detailed structure is shown in the schema diagram below.

## Creating JSON-LD for Polymer AM in R

    library(FAIRmaterials)

    # An example data frame for polymer AM
    polymerAM_data <- data.frame(
      'sampleID' = c('sa12345', 'sa24682'),
      'printMethod' = c('FDM', 'FDM'),
      'manufacturer' = c('A', 'B'),
      'material' = c('ABS', 'PLA'),
      'surfaceRoughness' = c(10, 5),
      'flowRate' = c(8, 12)
    )

    # This will generate json-ld files for the example data.
    polymer_output <- fairify_data(polymerAM_data, domain = 'PolymerAM', saveLocal = TRUE)

## Creating JSON-LD for Polymer AM in Python

    from fairmaterials.fairify_data import *
    import pandas as pd

    # Create an example data frame for Polymer AM
    data = pd.DataFrame(
      'sampleID' = ['sa12345', 'sa24682'],
      'printMethod' = ['FDM', 'FDM'],
      'manufacturer' = ['A', 'B'],
      'material' = ['ABS', 'PLA'],
      'surfaceRoughness' = [10, 5],
      'flowRate' = c[8, 12]
    )

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

## Polymer AM schema diagram

Polymer AM schema diagram

## Acknowledgment

This material is based upon work supported by the Department of Energy (National Nuclear Security Administration) under Award Number(s) DE-NA0004104.