Crystallographic Data and Melting Points for Various Polymers

Miller, Robert L.

doi:10.1002/0471532053.bra038

Cited by 12 publications

(9 citation statements)

References 1,672 publications

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“…The maximum amorphous density was 1.2651 g/cm 3 for PLA72.5, which is much lower than the crystal density (1.378 g/cm 3 ) of PLLA, but close to the crystal density (1.274 g/cm 3 ) of the stereo complex of enantiomeric PLLA and PDLA. [17] Extrapolation of the linear line to 0 and 100%ee suggests that the amorphous density of the racemic and the optically pure PLA is 1.271 and 1.258 g/ cm 3 , respectively. These data suggest that the free volume of the glassy PLA specimens increases with increasing OP.…”

Section: Stereosequences Of the Pla Samplesmentioning

confidence: 97%

Microstructure and Thermomechanical Properties of Glassy Polylactides with Different Optical Purity of the Lactate Units

Urayama

Kanamori

Kimura

2001

Macromol. Mater. Eng.

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Microstructure and thermomechanical properties of polylactides (PLA) with different optical purity (OP) of the lactate units were studied in detail. Thermal analysis by DSC revealed that the melting (Tm) and glass transition (Tg) temperatures of PLA can be simulated by the theoretical equations of Flory and Fox, respectively, both decreasing with decreasing OP. The sequential analysis of the PLA samples by 13C NMR spectroscopy suggested that the meso‐sequence is more favorably formed than the racemic sequence in the L‐rich samples. Their glassy specimens made by injection‐moltding showed characteristic behaviors in dynamic mechanical analysis (DMA); the storage modulus (G ′) of the L‐rich PLA specimens (L ratio = 99.0, 96.1, and 95.8) dropped and subsequently jumped up above Tg correspondingly to the glass‐to‐rubber and rubber‐to‐crystal transitions, respectively. In the G ′ curve of PLA with low L contents (90 and 72.5), only a drop was shown due to the simple glass‐to‐rubber transition. Wide‐angle X‐ray diffraction (WAXD) of the former L‐rich PLA supported the responsibility of the crystallization for the jump‐up of G ′ above Tg. The tensile strength of these glassy PLA specimens decreased with their decreased OP, while the tensile modulus was almost identical irrespectively of OP. On the other hand, the density of the PLA specimens was inversely proportional to OP, being in contrast to the above Tg change. The opposite relationship between Tg and density changes can reasonably be explained by a packing model in which the partial helices are formed along the L‐sequenced segments of the PLA chain and randomly packed in solid state to afford a large free volume in between the helices.

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Section: Stereosequences Of the Pla Samplesmentioning

confidence: 97%

Microstructure and Thermomechanical Properties of Glassy Polylactides with Different Optical Purity of the Lactate Units

Urayama

Kanamori

Kimura

2001

Macromol. Mater. Eng.

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“…where T m 0 is the melting point of the corresponding PHA homopolyester with a sufficient molecular weight (458 K for PLA [24] and 342 K for PCL [18] ), M side is the numberaverage molecular weight of polyester chains introduced onto CA, per an originally residual hydroxyl position and a, b, C 0 , and k 0 are arbitrary constants. Here, M side is hypothetically determined from M side ¼ M a /(3-acetyl DS) with an available number-average molecular weight M a of graft chains per anhydroglucopyranose unit, by assuming that the residual hydroxyls of CA are completely replaced by PHA.…”

Section: Composition Dependence Of the Melting Transition Of Crystallmentioning

confidence: 99%

Cellulose Acetate‐graft‐Poly(hydroxyalkanoate)s: Synthesis and Dependence of the Thermal Properties on Copolymer Composition

Teramoto

Ama

Higeshiro

et al. 2004

Macro Chemistry & Physics

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Summary: Several different series of cellulose acetate‐graft‐poly(hydroxyalkanoate)s (CA‐g‐PHAs) were synthesized over a wide range of compositions by the graft copolymerization of lactic acid, L‐lactide, (R,S)‐β‐butyrolactone, δ‐valerolactone and ε‐caprolactone onto the residual hydroxyl positions of CA, by virtue of a suitable catalyst, solvent and procedure for each individual case. To achieve a diversity of molecular architectures of the respective graft copolymer series, the degree of acetyl substitution (acetyl DS) of the CA starting material was also varied, resulting in different levels of the intramolecular density of grafts. The CA‐g‐PHAs thus obtained were subjected to differential scanning calorimetric measurements and the relationship between their molecular structure and thermal transition behavior was estimated, in comparison with some semi‐empirical equations available for polymer blends or comb‐like polymers. In particular, the composition dependence of the Tgs of the graft copolymers was represented well in terms of a formula proposed by Reimschuessel for comb‐like polymers, when CAs of acetyl DS ≈2 were employed as a trunk polymer. The deviation of the glass transition data from the model function was discussed in connection with the manner of graft modification.

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“…The candidates are chosen based on a particular chemical subspace which includes seven linearly repeated chemical building blocks (CH 2 , NH, CO, C 6 H 4 , C 4 H 2 S, CS, and O). These building blocks are commonly found for many polymer materials and can effectively represent electronic and dielectric properties of polymeric materials [76]. In order to obtain the dataset at a reasonable computational cost, four blocks forming a repeating unit was set for generating the candidate space.…”

Section: Design Of Polymer Dielectricsmentioning

confidence: 99%

Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges

et al. 2020

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Organic molecules and polymers have a broad range of applications in biomedical, chemical, and materials science fields. Traditional design approaches for organic molecules and polymers are mainly experimentally-driven, guided by experience, intuition, and conceptual insights. Though they have been successfully applied to discover many important materials, these methods are facing significant challenges due to the tremendous demand of new materials and vast design space of organic molecules and polymers. Accelerated and inverse materials design is an ideal solution to these challenges. With advancements in high-throughput computation, artificial intelligence (especially machining learning, ML), and the growth of materials databases, ML-assisted materials design is emerging as a promising tool to flourish breakthroughs in many areas of materials science and engineering. To date, using ML-assisted approaches, the quantitative structure property/activity relation for material property prediction can be established more accurately and efficiently. In addition, materials design can be revolutionized and accelerated much faster than ever, through ML-enabled molecular generation and inverse molecular design. In this perspective, we review the recent progresses in ML-guided design of organic molecules and polymers, highlight several successful examples, and examine future opportunities in biomedical, chemical, and materials science fields. We further discuss the relevant challenges to solve in order to fully realize the potential of ML-assisted materials design for organic molecules and polymers. In particular, this study summarizes publicly available materials databases, feature representations for organic molecules, open-source tools for feature generation, methods for molecular generation, and ML models for prediction of material properties, which serve as a tutorial for researchers who have little experience with ML before and want to apply ML for various applications. Last but not least, it draws insights into the current limitations of ML-guided design of organic molecules and polymers. We anticipate that ML-assisted materials design for organic molecules and polymers will be the driving force in the near future, to meet the tremendous demand of new materials with tailored properties in different fields.

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Crystallographic Data and Melting Points for Various Polymers

Cited by 12 publications

References 1,672 publications

Microstructure and Thermomechanical Properties of Glassy Polylactides with Different Optical Purity of the Lactate Units

Microstructure and Thermomechanical Properties of Glassy Polylactides with Different Optical Purity of the Lactate Units

Cellulose Acetate‐graft‐Poly(hydroxyalkanoate)s: Synthesis and Dependence of the Thermal Properties on Copolymer Composition

Machine-Learning-Assisted De Novo Design of Organic Molecules and Polymers: Opportunities and Challenges

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