Login / Signup

Disposable Nitrile Glove Resistance to Limonene: Dextrous Robot Hand Versus ASTM F739 Comparison.

Sean BanaeeAirek MathewsShane S Que Hee
Published in: Journal of chemical health & safety (2024)
The current technique to assess glove resistance to chemicals for worker protection relies on challenging a flat, 2.54 cm diameter glove piece at or near room temperature. This does not simulate a donned whole glove near the skin temperature subjected to work activity forces. Four different types of disposable nonpowdered unlined/unsupported nitrile gloves in triplicate were measured for thickness, porosity, and for the acrylonitrile content ( A ) of the challenge and collection sides. Limonene permeation at 35 °C through a whole glove on a clenching and nonclenching dextrous robot hand and with the standard ASTM F739 technique were facilitated by taking samples from the collection sides for GC-MS analysis. The standardized breakthrough time (SBT) when permeation reached 100 ng/cm 2 /min and the steady state permeation rate (SSPR) depended on A , thickness, and porosity. Only the thinnest glove (Lavender) showed statistically significant ( p ≤ 0.05) increased average SSPR for the clenching hand relative to the nonclenching hand and for the ASTM technique. The ASTM test data for the three thickest gloves were not statistically different from those of the robot hand, but differed from the manufacturer's. More research with different chemicals and higher clenching forces is needed. Clenching forces can enhance the permeation. Workers wearing ultrathin disposable nitrile gloves have a higher potential for chemical penetration/permeation. Company glove permeation data obtained near room temperature may have a longer SBT and lower SSPR than in practice. Double gloving may be advisible in emergencies and for unknown chemicals when no appropriate thicker Chemical Protective glove is available.
Keyphrases
  • room temperature
  • ionic liquid
  • healthcare
  • electronic health record
  • primary care
  • big data
  • climate change
  • deep learning
  • artificial intelligence
  • metal organic framework
  • essential oil