Login / Signup

Thermally-healable network solids of sulfur-crosslinked poly(4-allyloxystyrene).

Timmy ThiounnMoira K LauerMonte S BedfordRhett C SmithAndrew G Tennyson
Published in: RSC advances (2018)
Network polymers of sulfur and poly(4-allyloxystyrene), PAOS x ( x = percent by mass sulfur, where x is varied from 10-99), were prepared by reaction between poly(4-allyloxystyrene) with thermal homolytic ring-opened S 8 in a thiol-ene-type reaction. The extent to which sulfur content and crosslinking influence thermal/mechanical properties was assessed. Network materials having sulfur content below 50% were found to be thermosets, whereas those having >90% sulfur content are thermally healable and remeltable. DSC analysis revealed that low sulfur-content materials exhibited neither a T g nor a T m from -50 to 140 °C, whereas higher sulfur content materials featured T g or T m values that scale with the amount of sulfur. DSC data also revealed that sulfur-rich domains of PAOS 90 are comprised of sulfur-crosslinked organic polymers and amorphous sulfur, whereas, sulfur-rich domains in PAOS 99 are comprised largely of α-sulfur (orthorhombic sulfur). These conclusions are further corroborated by CS 2 -extraction and analysis of extractable/non-extractable fractions. Calculations based on TGA, FT-IR, H 2 S trapping experiments, CS 2 -extractable mass, and elemental combustion microanalysis data were used to assess the relative percentages of free and crosslinked sulfur and average number of S atoms per crosslink. Dynamic mechanical analyses indicate high storage moduli for PAOS 90 and PAOS 99 (on the order of 3 and 6 GPa at -37 °C, respectively), with a mechanical T g between -17 °C and 5 °C. A PAOS 99 sample retains its full initial mechanical strength after at least 12 pulverization-thermal healing cycles, making it a candidate for facile repair and recyclability.
Keyphrases
  • machine learning
  • electronic health record
  • single cell
  • risk assessment
  • big data
  • molecular dynamics
  • molecular dynamics simulations
  • reduced graphene oxide