Kaoru Aou

Highlights
•Low level of elastically effective chains lead to slow viscoelastic (VE) recovery.
•High levels of sol fraction leads to plasticization and faster VE recovery speed.
•Tan-delta from DMTA has no general correlation to viscoelastic (VE) recovery speed.
•VE polyurethane foams have high sol fractions, and <100% NCO conversion.

The relationship between polymer network parameters and speed of viscoelastic (VE) recovery was studied for viscoelastic polyurethane foams.… Show more

Highlights
•Low level of elastically effective chains lead to slow viscoelastic (VE) recovery.
•High levels of sol fraction leads to plasticization and faster VE recovery speed.
•Tan-delta from DMTA has no general correlation to viscoelastic (VE) recovery speed.
•VE polyurethane foams have high sol fractions, and <100% NCO conversion.

The relationship between polymer network parameters and speed of viscoelastic (VE) recovery was studied for viscoelastic polyurethane foams. Reactive network simulation method was developed which use relative reactivity parameters derived from literature and from experiment. Relative reactivity of butylene-oxide (BO) based secondary hydroxyl groups were estimated by comparing simulation results with experimentally derived sol fraction. From the analysis, it is found that BO and propylene oxide (PO) hydroxyl end groups have relative reactivity to isocyanates that are not very different. We also find that the isocyanate conversion is lower only about 91–96%, even though the isocyanates are the limiting factor (i.e. molar ratio NCO:OH = 0.9). It is also found that a foam with faster VE recovery is predicted to have smaller elastically effective chain (EEC) mass fraction (i.e. more imperfect polymer network) and higher sol fraction. Surprisingly, the same foam after solvent extraction was found to have slower VE recovery. It is concluded for foam systems with Tg near ambient temperature, that while lower EEC fraction can lead to slower VE recovery, a large amount of sol fraction in the foam system can cause faster VE recovery via plasticization of the polyurethane matrix. Show less

Several factors were investigated that affect porous strut morphology in the Highly Porous Supersoft Viscoelastic Foam. Porous strut morphology and high air permeability of the Swiss-Cheese TDI VE technology were found to be enabled by the combination of immiscible polyether polyols mixed with a third, highly hydrophobic polyol of high equivalent weight that is immiscible with either of the first two polyether polyols. Completely “punctured through” pores in struts were observed more frequently… Show more

Several factors were investigated that affect porous strut morphology in the Highly Porous Supersoft Viscoelastic Foam. Porous strut morphology and high air permeability of the Swiss-Cheese TDI VE technology were found to be enabled by the combination of immiscible polyether polyols mixed with a third, highly hydrophobic polyol of high equivalent weight that is immiscible with either of the first two polyether polyols. Completely “punctured through” pores in struts were observed more frequently in foam samples where an isocyanate index of 90 versus 100 was employed. When isocyanate index is fixed to 90, it was found that a poly(1,2-butylene oxide) (“PBO”) monol level of ≥3.0 parts per hundred polyol (pphp) was needed to see the first signs of a “punctured” pore strut morphology. Studies show that a “high-Eq.Wt.-hydrophobic-polyol-leaving-voids” model is consistent with observed results. Hydrophobic polyols that allowed the formation of porous strut morphology included BO-4000 monol (Eq.Wt. ∼ 4000) and PBD-10000 diol (Eq.Wt. ∼ 5000). The use of these hydrophobic polyols also yielded air flows that were significantly higher than those obtained with the “standard” viscoelastic foam formulations that were prepared at the same isocyanate index.
(also co-authors: Rogelio R. Gamboa, Renee Cook) Show less

• Two-phase morphology found for viscoelastic PU, not phase-mixed as thought before.
• AFM and time-domain NMR can detect systems with poor phase separation.
• Slower viscoelastic compression recovery in part due to slower segmental mobility.

The morphology of viscoelastic polyurethane (PU) foams is examined and compared with flexible, elastic PU foam. Hard and soft domains for both foam types are found with atomic force microscopy, with good signal to noise. TD-NMR spectroscopy is… Show more

• Two-phase morphology found for viscoelastic PU, not phase-mixed as thought before.
• AFM and time-domain NMR can detect systems with poor phase separation.
• Slower viscoelastic compression recovery in part due to slower segmental mobility.

The morphology of viscoelastic polyurethane (PU) foams is examined and compared with flexible, elastic PU foam. Hard and soft domains for both foam types are found with atomic force microscopy, with good signal to noise. TD-NMR spectroscopy is sensitive to the presence of multiple phases through the contrast in the segmental mobility of the domains. Results on the viscoelastic foams, as with the flexible foams, indicate two-phase morphology, contrary to the conventional wisdom in the industry that viscoelastic polyurethane foams are phase-mixed. Segmental mobility is correlated to tan delta at the experimental temperature. The segmental mobility of the soft domain is correlated to the viscoelastic recovery time of the memory foams. The example of viscoelastic foams demonstrate the detection sensitivity of TD-NMR, where domains with similar composition/density but different mechanical strength are distinguished through segmental mobility contrast. Show less

MALDI spectra of hard segment chains from polyurethane (“PU”) viscoelastic (“Visco”) and conventional flexible (“Flex”) foam series were obtained and analyzed. Results indicate that within each foam series, there was no significant difference at different water levels. However, comparing Visco and Flex shows that the distribution is shifted to lower urea count for the case of Visco. The experimentally determined peak in the distribution was 1 to 2 urea repeats, in contrast with what is reported… Show more

MALDI spectra of hard segment chains from polyurethane (“PU”) viscoelastic (“Visco”) and conventional flexible (“Flex”) foam series were obtained and analyzed. Results indicate that within each foam series, there was no significant difference at different water levels. However, comparing Visco and Flex shows that the distribution is shifted to lower urea count for the case of Visco. The experimentally determined peak in the distribution was 1 to 2 urea repeats, in contrast with what is reported in literature. To understand the fine impacts of formulation, Monte Carlo simulations were performed on the Visco and Flex foam formulations, with urethane-urea catalysis ratio and water levels being varied within each foam series. Experimentally obtained distributions agree very well with the simulation results. Values for number-average degree of polymerization from simulations agree with those predicted from the Schulz-Flory distribution. Furthermore, one finds that the while the calculated shape of the hard segment length distributions is predicted to be sensitive to the catalytic enhancement factor, the average hard segment length values are predicted to be essentially independent of catalysis. The fraction of diurethane linkages were calculated and is found to be sensitive to catalysis (more urethane catalysis = more diurethane linkages). Furthermore, the fraction of diurethane linkages as simulated from foam formulation is correlated well with the Tg of the Flex foam series as obtained from DMA. The same relationship for the Visco foam series is also discussed. Show less

Jeffrey P. Kalish, Kaoru Aou, Xiaozhen Yang and Shaw Ling Hsu

Xiaozhen Yang, Shuhui Kang, Yuning Yang, Kaoru Aou and Shaw Ling Hsu

This study demonstrated that poly(lactic acid) molecules with different chiral purity has different chain rigidity. The regioregularlity was characterized by comparing the experimental Raman spectra of the polymers against simulated Raman spectra derived from Monte Carlo simulation of several combinations of chain conformation (e.g. torsional configuration) and chain configuration (i.e. where the D- and L-units of lactic acid monomers were positions).