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Thermochimica Acta
Elsevier
Thermochimica Acta

Elsevier

0040-6031

Thermochimica Acta/Journal Thermochimica ActaSCIAHCIISTPEI
正式出版
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    Theoretical and experimental studies on the size- and morphology-dependent thermodynamics of nanoparticle electrodes

    Wang, ChenyuCui, ZixiangWang, YuantaoWang, Mengying...
    15页
    查看更多>>摘要:The morphology and size of nanoparticles have a significant effect on the thermodynamics of nanoparticle electrodes due to the nanometer effect. However, the influencing mechanism and regularity of morphology and particle size on electrochemical thermodynamics of nanometer electrodes are still unclear. Herein, the universal thermodynamics equations of nanometer electrodes which consisting of nanoparticles with different morphologies and particle sizes are deduced theoretically and we discuss the influencing mechanism and regularity of morphology and size on electrochemical thermodynamics. Experimentally, we adopt a hydrothermal method to prepare nanometer In2O3 particles with different particle sizes and morphologies and make them into nanometer electrodes. The electrode potentials at different temperatures are measured by a potentiometer, the standard electrode potentials, temperature coefficients of electrode potential, reaction equilibrium constants, reaction thermodynamic properties, and reversible reaction heats are obtained for the nanometer electrode with diverse particle morphologies and sizes. The effects of particle size and morphology on these thermodynamic properties are discussed and we find that the experimental results conform to the corresponding theoretical relations. The electrochemical thermodynamics theory of nanoparticle electrodes can quantitatively describe the electrochemical thermodynamic behavior of nanometer electrodes with different morphologies and particle sizes, explain relevant experimental phenomena, and provide theoretical guidance and support reference to design, research, and apply various nanometer electrode.

    Thermophysical properties of liquid Co-Cr-Mo alloys measured by electromagnetic levitation in a static magnetic field

    Adachi, MasayoshiOhtsuka, MakotoChiba, AkihikoKoizumi, Yuichiro...
    9页
    查看更多>>摘要:This study aimed to provide thermophysical property data of Co-Cr-Mo (CCM) alloys that are used as biomedical materials to understand and improve additive manufacturing processes. The density, surface tension, normal spectral emissivity, specific heat capacity and thermal conductivity of two CCM alloys that contained a low (0.053 mass%) and a high (0.251 mass%) carbon content were measured in a liquid state using an electromagnetic levitation technique. The liquidus temperatures of the CCM alloys were measured by differential scanning calorimetry. A static magnetic field was applied to the levitated CCM droplets to suppress the surface oscillation and translational motion of the droplets, and convection flow inside the droplet for each property measurement as needed. Uncertainty analysis was conducted for all thermophysical property data. No major difference was found in the thermophysical properties for the low- and high-carbon CCM melts within experimental uncertainty. An ideal solution model reproduced the CCM melt density within experimental uncertainty, however, we obtained large positive excess heat capacities of the CCM melts.

    Thermal analysis applied to the development of nanostructured lipid carriers loading propranolol using quality-by-design strategies

    Rocha, Jessika L.Pires, Felipe Q.Gratieri, TaisGelfuso, Guilherme M....
    9页
    查看更多>>摘要:This work aimed to employ thermal analysis to develop nanostructured lipid carriers (NLC) using propranolol (PPL) as a model drug. The rationale for this is such delivery system could enable PPL repositioning for the treatment of skin diseases. For this, preformulation studies were first performed following a simplex centroid mixture design using thermal and spectroscopic analytical tools. Next, PPL-loaded NLC were developed, varying the production parameters according to a Box-Behnken design. A high degree of thermal interaction was observed among the formulation components, mainly between the Rosa rubiginosa essential oil and soy lecithin lipids, which resulted in an NLC entrapment efficiency above 98%. Infrared data, in turn, showed the components of the formulation are chemically compatible, even under heating production conditions. The optimized model for PPL-loaded NLC production allowed to accurately control the parameters of particle size and PdI ondemand over a wide range of particle sizes (400-1,500 nm). Particularly, Turrax rotation and Turrax agitation time were the most decisive process parameters for these responses. The optimized model was tested in the production of 500-nm and 900-nm NLC, leading to particle sizes of 569.4 +/- 87.3 nm and 823.9 +/- 58.0 nm, respectively, within the 95% confidence interval. Moreover, the PdI results were also very close to the prediction. In conclusion, the precise control of PPL-loaded NLC characteristics through the optimized model offers exciting perspectives for modulating the PPL skin permeation profile to meet different therapeutic propositions.

    Waste-tyre pyrolysis and gasification via the reverse boudouard reaction: derivation of empirical kinetics from TGA data

    Jansen, Arnold Alexandervan der Walt, Izak JacobusCrouse, Philippus Lodewyk
    15页
    查看更多>>摘要:The pyrolysis of scrap tyre rubber crumbs under nitrogen and treatment with pure carbon dioxide was investigated both isothermally and dynamically up to 1100 degrees C, at heating rates up to 20 degrees C min(-1). The rubber sample was a mixture of industrially representative tread and sidewall material. Workable, but not definitive, models could be derived from the isothermal analysis: Jander D3 diffusion for the first pyrolysis event under nitrogen up to 550 degrees C; the Mampel mechanism for high-temperature pyrolysis above 550 degrees C; and shrinking-particle chemical-reaction control as the rate limiting step for the reverse Boudouard reaction. The isothermally derived pre-exponential factors and activation energies were further refined by non-linear fitting to the dynamic data of all heating rates, and by making both parameters functions of the degree of conversion. In addition, the Sestak-Berggren equation was directly fitted to the full data set, i.e., for all heating rates, also using pre-exponential factors and activation energies that are dependent on degree of conversion. Both the approaches yielded workable engineering kinetics, with the Sestak-Berggren performing worse. With single-value pre-exponential factors and activation energies, the models fitted the data less satisfactorily across the range of heating rates. The required numerical analysis is fully implementable on a commercial spreadsheet.

    Failure kinetics of ionomer membranes

    Bhattacharya, SandeepSingh, YadvinderLauritzen, Michael, VKjeang, Erik...
    6页
    查看更多>>摘要:The equivalence of the role of thermal fluctuations in the failure of fuel cell ionomer membranes is investigated in light of the kinetic theory of the strength of solids. Specifically, the activation energy of the membrane material is determined using two physically distinct methods, each exemplifying the role of thermal fluctuations. The failure kinetics of ionomer membranes is a function of the applied load as well as the temperature under which the membranes operate in a fuel cell. Time-to-failure data is thus generated for varied environmental conditions, and kinetic parameters are calculated by treatment using established methods. Separately, thermal decomposition data of the membrane material is generated for various heating rates, and the kinetic parameters so obtained are compared with those from the mechanically induced failure approach. The results from the two methods are found to confirm each other and may be used in the investigation of fracture modeling and lifetime prediction of fuel cell membranes.

    Thermal behavior of magnetite nanoparticles with various coatings in the range 30-1000 degrees C

    Alexandrovskaya, Yu M.Pavley, Yu R.Grigoriev, Yu, VGrebenev, V. V....
    7页
    查看更多>>摘要:Thermal properties of iron oxide nanoparticles (IONPs) stabilized with starch, 5-sulfosalicylic acid (SA) and oleic acid (OA) were studied in the range 30-1000 degrees C by thermogravimetry and differential thermal analysis in oxidizing atmosphere. Synchronized mass spectrometry data was collected. The sizes and morphology of IONPs were determined with transmission and scanning electron microscopy analyses. Three stages of thermal transformation were revealed: (I) water desorption, (II) organic content pyrolysis and (III) iron oxide phase transition. The thermal stability of the organic part was analyzed. Thermal conversions of modified IONPs were compared with the data for uncoated magnetite.

    Characterization of the heat behavior of amiodarone hydrochloride

    Mhoumadi, AtouryaPrillieux, SylvainDumas, Jean-BernardCollas, Franck...
    5页
    查看更多>>摘要:Amiodarone hydrochloride, an antiarrhythmic and vasodilatory drug, was characterized from a thermodynamic point of view. Its XRPD profile was found to be in agreement with the single crystal structure previously reported. When the DSC heating rates are not high enough, the compound starts to degrade before melting. This phenomenon is emphasized during melting and also in the liquid state. The degradation products were identified by coupling TGA/FTIR experiments. When increasing the DSC scan rates, the onset of melting as well as the endothermic value of the signal increase to reach plateau values. This clearly indicates that the degradation processes have been pushed back to higher temperatures than the melting temperature. This allowed determining accurately the melting characteristics of the compound. The so-obtained melting temperature was then confirmed by Fast Scanning Calorimetry.

    The machine learning method for overlapping peak decompositions in differential scanning calorimetry

    Li, TaoZhang, Shuo-XunHuang, Hai-HanChen, Wen-Ming...
    13页
    查看更多>>摘要:An overlapping peak resolving (OPR) method based on the machine learning theory is developed to identify the independent peaks constituting the overlapping peaks in differential scanning calorimetry. The content prediction model (CPM) is presented to analyze the contents of the chemical constituents by decomposing the overlapping peaks and establishing the relationship between the contents and peak areas of the substances. The model is applied respectively to some theoretically constructed and experimentally measured overlapping peaks to validate the reliability and feasibility of the proposed method. The results show that the contents of the chemical constituents can be accurately calculated by the CPM. The validations indicate that the analysis errors of the CPM show a relatively stable trend with the changes of the separation degrees and peak-height ratios. Furthermore, the computational burden of the proposed method is also less than that of the existing OPR techniques.

    Polymer informatics based on the quantitative structure-property relationship using a machine-learning framework for the physical properties of polymers in the ATHAS data bank

    Ishikiriyama, Kazuhiko
    12页
    查看更多>>摘要:In polymer informatics based on the quantitative structure-property relationship (QSPR) through machine learning (ML), one of the key issues is how to utilize a high-quality database of polymer properties. The ATHAS data bank is one of the valuable databases of polymer-specific physical properties, including glass transition temperature (T-g) and heat capacity difference at T-g for fully amorphous polymers, equilibrium melting point and heat of fusion at 100% crystallinity, etc. Using the ATHAS data bank, QSPRs between fingerprints of repeating polymeric structural units and each physical property were obtained by ML. Two types of hidden-layer structures of artificial neural network (ANN) were examined as regression models, and their optimal hidden-layer structures were determined by the contour plots of root mean square error in each physical property. In both ANN structures, a good correlation was found between the registered values and the predicted ones, suggesting that the physical properties may be predicted from only the repeating polymeric structural units. Furthermore, the physical properties of poly(p-dioxanone), which are not yet registered in the ATHAS data bank, were predicted, indicating that the predicted properties agreed with the measured properties from literature within +/- 25% in the practical temperature range. A new method for predicting heat capacity for polymers is proposed by combining ML and ATHAS analysis.