•This article reviews the state-of-the-art of existing DSC literature in detail from both academic and industrial points of view.•It identifies key limitations and prospects in DSC, summarizes prior ...research and identifies knowledge gaps.•It provides a development framework as a roadmap for future research and practice.
Suppliers, partners, companies and dealers in supply chains do use, generate and share information with others. These associations lead to a multitude of challenges and opportunities within the supply chains. A Digital Supply Chain (DSC) is a smart, value-driven, efficient process to generate new forms of revenue and business value for organizations and to leverage new approaches with novel technological and analytical methods DSC is not about whether goods and services are digital or physical, it is about the way how supply chain processes are managed with a wide variety of innovative technologies, e.g. unmanned aerial vehicles, cloud computing, and internet of things, among others. Recent literature highlights the importance of DSC and many industrial researchers discuss its applications. This article reviews the state-of-the-art of existing DSC literature in detail from both academic and industrial points of view. It identifies key limitations and prospects in DSC, summarizes prior research and identifies knowledge gaps by providing advantages, weaknesses and limitations of individual methods The article also aims at providing a development framework as a roadmap for future research and practice.
This paper reviews the best-known differential scanning calorimetries (DSCs), such as conventional DSC, microelectromechanical systems-DSC, infrared-heated DSC, modulated-temperature DSC, gas ...flow-modulated DSC, parallel-nano DSC, pressure perturbation calorimetry, self-reference DSC, and high-performance DSC. Also, we describe here the most extensive applications of DSC in biology and nanoscience.
•Fast DSC with liquids in the temperature range −100°C to +225°C, at scan rates up to 1000°C/s.•Reproducibility of calculated enthalpy values ca ±7%, of peak temperature values ca ±1°C.•Resolution ...for measuring lysozyme denaturation between 0.1% and 1% lysozyme solution in water by weight.•Measurements for bovine serum show good agreement with DSC results, but typically 1000× faster.•Results for olive oil give good agreement for the freezing peak, a temperature shift for the melting peak compared to DSC.
Based on a modified version of standard chips for fast differential scanning calorimetry, DSC of liquid samples has been performed at temperature scan rates of up to 1000°C/s. This paper describes experimental results with the protein lysozyme, bovine serum, and olive oil. The heating and cooling rate of the sensor is measured for temperature scan rates of up to 1300°C/s with water and 2-butanol, in the temperature range of −90°C/s to +130°C/s. The lysozyme is measured at temperature scan rates varying from 10°C/s to 400°C/s and in concentrations between 0.1% and 10% protein by weight. The bovine serum measurements show two main peaks, in good agreement with standard DSC measurements. Olive oil has been measured, with good agreement for the cooling curve and qualitative agreement for the heater curve, compared to DSC measurements.
The Rock-Eval pyrolysis-stage derived parameters such as free hydrocarbons (S1), heavier pyrolysis-hydrocarbons (S2), pyrolyzable carbon (PC) and pyrolysis Tmax (from S2 curve) have received ...considerable interest for source-rock screening and thermal maturity assessment. On the other hand, the Rock-Eval oxidation-stage S4CO2 curve, which gives the amount of residual carbon (RC), only recently has received some interest. While the pyrolysis-stage S2 temperature-peak (Tmax) is conventionally used as a maturity proxy, in this work we show that the temperature-peak of S4CO2 curve (S4Tmax) can also be used as a thermal maturity proxy for shales. For overmature and low-TOC shale samples, showing asymmetric S2 shape and concomitantly producing doubtful Tmax, the S4 curves showed symmetric nature and consequently the S4Tmax was observed to be a reliable thermal maturity estimate. While the S4Tmax clearly resolved immature and overmature shales, for the early mature and peak mature shales the S4Tmax showed overlapping values. S4Tmax of pre-pyrolyzed and pyrolyzed masses showed good positive correlation with differential scanning calorimetry temperature-peak (DSCTpeak), and consequently indicated its applicability as a thermal maturity proxy. When early mature pre-pyrolyzed samples were directly analyzed using the Rock-Eval oxidation stage, the S4 curves showed formation of two sub-peaks, and consequently the Tmax was observed to decrease. It is recommended that analysts and interpreters should thoroughly cross-check S2 curves before reporting data, and in case of asymmetric or unreliable S2 curves, the S4Tmax can be used as a maturity proxy.
•Importance of Rock-Eval oxidation stage.•S4Tpeak as a thermal maturity proxy for shales.•Critical monitoring of Rock-Eval S2 curves.
•XRD, FT-IR, UV–Vis and Raman spectroscopy.•Photoluminescence.•DFT calculations.
A new intercalation crystalline polymer compound of bis m-nitroanilinium tetrachlorocadmate (II) {(m-C6H7N2O2)2CdCl4}n ...was synthesized and analyzed using single crystal SXRD, differential scanning calorimetry (DSC), DFT analysis, thermal gravimetric analysis (TGA) and FT-IR, Raman, UV–Vis, fluorescence spectroscopy techniques. X-ray diffraction analyses (SXRD, PXRD) show a layered structure consisting of alternating organic bilayers and two-dimensional inorganic sheets in which each CdCl6 octahedron shares four corners with adjacent octahedra. The crystal packing is consolidated by means of classic and non-classic hydrogen bonds and π-π interactions. At room temperature photoluminescence spectra of {(m-C6H7N2O2)2CdCl4}n yield broad peaks in the 469–770 nm range with full width at half maximum (FWHM) values up to 153 nm. Besides, this compound exhibits a semiconducting behavior with bright red-light under 360 nm ultraviolet photoexcitation and possesses a large Stokes shift and direct band gap of 2.69 eV which overlaps well with solar spectrum. The CIE chromaticity coordinates of {(m-C6H7N2O2)2CdCl4}n are (x = 0.4704 and y = 0.4523). The color rendering index CRI and the low correlated color temperature CCT are 84 and 2861 K, respectively. Electronic structure (BS, DOS and PDOS), and optical properties (dielectric constant ε(ω), refractive index n(ω), reflectivity R(ω), absorption coefficient α(ω), optical conductivity σ(ω) and energy loss function L(ω) with the incident photon energy) were determined using (DFT) calculations by CASTEP code.
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Reliable interpretation of the changes occurring in the samples during their heating is ensured by using more than one measurement technique. This is related to the necessity of eliminating the ...uncertainty resulting from the interpretation of data obtained by two or more single techniques based on the study of several samples analyzed at different times. Accordingly, the purpose of this paper is to briefly characterize thermal analysis techniques coupled to non-thermal techniques, most often spectroscopic or chromatographic. The design of coupled thermogravimetry (TG) with Fourier transform infrared spectroscopy (FTIR), TG with mass spectrometry (MS) and TG with gas chromatography/mass spectrometry (GC/MS) systems and the principles of measurement are discussed. Using medicinal substances as examples, the key importance of coupled techniques in pharmaceutical technology is pointed out. They make it possible not only to know precisely the behavior of medicinal substances during heating and to identify volatile degradation products, but also to determine the mechanism of thermal decomposition. The data obtained make it possible to predict the behavior of medicinal substances during the manufacture of pharmaceutical preparations and determine their shelf life and storage conditions. Additionally, characterized are design solutions that support the interpretation of differential scanning calorimetry (DSC) curves based on observation of the samples during heating or based on simultaneous registration of FTIR spectra and X-ray diffractograms (XRD). This is important because DSC is an inherently non-specific technique. For this reason, individual phase transitions cannot be distinguished from each other based on DSC curves, and supporting techniques are required to interpret them correctly.
The present study focuses on the use of Luffa Cylindrica fibers as a reinforcing agent in a fluoroplastic (PTFE) polymer matrix and TiO2 nanoparticles as a photocatalytic agent with different mass ...fractions (%), for the purpose of the preparation and structural characterization of a new biocomposite material. The granulometry and zeta potential were measured using dynamic light scattering and laser Doppler velocimetry respectively. Structural and vibrational properties of the PTFE/TiO2/LC fibers composites were characterized by micro-Raman spectroscopy in oblique backscattering configuration and FTIR spectroscopy. Lastly, thermal properties were investigated using TGA and DSC. Further, the photocatalytic activity of samples was tested for the degradation of Methylene Blue dye (MB) in aqueous medium.
•Please finds below the highlights of the submitted work:•New biocomposite based on PTFE (75%–65%), TiO2 (5%) and fibers of Luffa Cylindrica (25%–35%).•Biocomposite with 25% of Luffa Cylindrica outperforms others in term of electrostatic stabilization.•Raman-spectra analysis highlights the presence of the anatase and rutile phases of TiO2 in all samples.•TGA and DSC analysis points out that over 30% of LC fibers in the sample is unfavorable regarding thermal degradation.
Excelet for Simulation of Indium DSC Graph Catangiu, Adrian; Ungureanu, Dan Nicolae; Nicolescu, Cristina ...
The Scientific Bulletin of "Valahia" University, Materials and Mechanics,
10/2023, Letnik:
19, Številka:
21
Journal Article
Recenzirano
Odprti dostop
Spreadsheets have amazing facilities for graphical representation of data. The computing power and the possibility to get the results without programming, interactivity by using controls make ...spreadsheets a powerful learning tool. Having as starting point an DSC curve for Indium performed between 120°C and 180°C, the shape of curve was modeled, by using Excel, under assumption that, before and after peak corresponding to melting transition, there is no dependence between specific heat of metal and temperature. Even the peak shape it not perfect symmetrical, it was modeled considering a gaussian distribution. Linear regression has been used for computing the medium values of specific heat in solid and liquid state and was used a spinner as interactive tool for peak shape control. Despite the model deficiencies, starting from specific heats, latent heat of melting and peak apex temperature it has been possible the simulation of DSC curve which was in a good correlation with the real one.
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•The thermal lag causes the heating-rate-dependent onset of melting temperature.•At larger samples, the onset temperature increases linearly with the heating rate.•At smaller sample ...mass, the onset temperature behaves nonlinearly.•This behavior is explained by using a heat flow model and an equation is derived.•The heating rate dependence for small samples and fast heating is corrected.
The thermal lag of DSC is a heating rate independent constant and influences the measured onset temperature of melting peaks and must be taken into account during the temperature calibration. In the literature, however, non-linear behavior of the measured onset temperature is reported for the case of high scanning rates and the use of small samples. Based on a conventional heat transfer model of a DSC a general relation of the heating rate and sample mass dependence of the onset temperature is derived. The reason of this unusual behavior is that the time for the melting event is less than the equilibration time of the DSC. The approach presented can be used to correct the onset temperatures in the case of non-linear behavior, which may occur in conventional DSC and Fast DSC (using chip sensors).
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