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The compatibility of poly(lactic acid) (PLA)/poly(propylene carbonate) (PPC) blends was investigated with Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and tensile testing. The PLA/PPC blends were prepared over the whole composition range. FTIR spectroscopy revealed that there were several specific interactions between the chains of PLA and PPC: the interaction between CÀ ÀH and O¼ ¼CÀ À and C¼ ¼OÁÁÁO¼ ¼C or C¼ ¼OÁÁÁOÀ ÀC dipole-dipole interactions. Moreover, PLA and PPC were compatible. DSC indicated that PLA and PPC were partially miscible but compatible to some extent because of the similar chemical natures of the blend components. TGA showed that the compatibility of PLA and PPC enhanced the thermal stability of PPC in the blends. As calculated by the Horowitz-Metzger equation, the activation energy for decomposition (E t ) of PPC in PLA/PPC (70/30) was 200.6 kJ/mol, whereas E t of pure PPC was only 56.0 kJ/mol. A study of the mechanical properties versus the composition and the strain versus the stress illustrated that there was good compatibility between PLA and PPC, and the phase inversion of the PLA/PPC system occurred between 70 and 60 wt % PLA in the PLA/PPC blends. The Pukanszky model gave credit to very strong interfacial adhesion between PLA and PPC. V V C 2005 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 94-101, 2006

Starch nanoparticles (SN) were prepared by delivering ethanol as the precipitant into starch-paste solution dropwise. Citric acid (CA) modified SN (CASN) were fabricated with the dry preparation technique. According to the characterization of CASN with Fourier transform infrared, X-ray diffraction, rapid visco analyzer, and scanning electron microscopy (SEM), amorphous CASN could not be gelatinized in hot water because of the cross-linking, and most of CASN ranged in size from about 50 to 100 nm. The nanocomposites were also prepared using CASN as the filler in glycerol plasticized-pea starch (GPS) matrix by the casting process. SEM revealed that CASN was dispersed evenly in the GPS matrix. As shown in dynamic mechanical thermal analysis, the introduction of CASN could improve the storage modulus and the glass transition temperature of CASN/GPS composites. The tensile yield strength and Young's modulus increased from 3.94 to 8.12 MPa and from 49.8 to 125.1 MPa, respectively, when the CASN contents varied from 0 to 4 wt %. Moreover, the values of water vapor permeability decreased from 4.76 x 10(-10) to 2.72 x 10(-10) g m(-1) s(-1) Pa(-1). The improvement of these properties could be attributed to the good interaction between CASN filler and GPS matrix. The comprehensive application of green chemistry principles were demonstrated in the preparation of CASN and CASN/GPS composites.

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BERT model has been successfully applied to open-domain QA tasks. However, previous work trains BERT by viewing passages corresponding to the same question as independent training instances, which may cause incomparable scores for answers from different passages. To tackle this issue, we propose a multi-passage BERT model to globally normalize answer scores across all passages of the same question, and this change enables our QA model find better answers by utilizing more passages. In addition, we find that splitting articles into passages with the length of 100 words by sliding window improves performance by 4%. By leveraging a passage ranker to select high-quality passages, multipassage BERT gains additional 2%. Experiments on four standard benchmarks showed that our multi-passage BERT outperforms all state-of-the-art models on all benchmarks. In particular, on the OpenSQuAD dataset, our model gains 21.4% EM and 21.5% F 1 over all non-BERT models, and 5.8% EM and 6.5% F 1 over BERT-based models. 1

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