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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.

In this study, the decomposition of a martensite/austenite (M/A) microconstituent in bainitic steels was analyzed using differential scanning calorimetry (DSC) data in conjunction with Kissinger’s and Johnson–Mehl–Avrami–Kolmogorov (JMAK)’s formulas. In bainitic steel subjected to austempering heat treatment, the presence of an M/A microstructure adversely affects the mechanical properties. According to the kinetic equations derived, it is observed that after tempering the sample at 600 °C for 4000 s, the generation of each phase reaches its maximum. The SEM images taken before and after tempering reveal extensive decomposition of the M/A constituent in the microstructure. The proportion of the M/A microstructure decreased significantly from about 10% before tempering to less than 1% after. Additionally, the content of residual austenite also reduced nearly to zero. These observations are consistent with the predictions of the kinetic equations.

During ICTAC2020, a workshop was held on “Good laboratory practice in thermal analysis and calorimetry” for young researchers and beginners under the aegis of the Education Committee of ICTAC. Thermal analysis (TA) covers relationship between large number of sample properties and the temperature. Naturally, there is some technique for each property of the sample bringing versatility in TA. This review is devoted to the Workshop and has been refined for the benefit of the readers so that it helps them in obtaining useful qualitative and quantitative information about the effects of heat treatments on materials of all kinds. Recent trends in DSC, TG-FTIR, TG-MS, DMA, kinetics and nanocalorimetry have also been covered in this article.

PurposeThis study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.Design/methodology/approachThe research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.FindingsFour broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.Research limitations/implicationsThe proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.Practical implicationsThe proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.Originality/valueThis research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

Background: Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in downstream radiation dose differences. Although auto-segmentation algorithms offer a potentially time-saving solution, the challenges in defining, quantifying, and achieving expert performance remain. Objective: Adopting a deep learning approach, we aim to demonstrate a 3D U-Net architecture that achieves expert-level performance in delineating 21 distinct head and neck organs at risk commonly segmented in clinical practice. Methods: The model was trained on a data set of 663 deidentified computed tomography scans acquired in routine clinical practice and with both segmentations taken from clinical practice and segmentations created by experienced radiographers as part of this research, all in accordance with consensus organ at risk definitions. Results: We demonstrated the model’s clinical applicability by assessing its performance on a test set of 21 computed tomography scans from clinical practice, each with 21 organs at risk segmented by 2 independent experts. We also introduced surface Dice similarity coefficient, a new metric for the comparison of organ delineation, to quantify the deviation between organ at risk surface contours rather than volumes, better reflecting the clinical task of correcting errors in automated organ segmentations. The model’s generalizability was then demonstrated on 2 distinct open-source data sets, reflecting different centers and countries to model training. Conclusions: Deep learning is an effective and clinically applicable technique for the segmentation of the head and neck anatomy for radiotherapy. With appropriate validation studies and regulatory approvals, this system could improve the efficiency, consistency, and safety of radiotherapy pathways.

Zeolitic imidazolate frameworks (ZIFs) are interesting materials for use in several aspects: energy storage material, gas sensing, and photocatalysis. The thermal stability and pyrolysis process are crucial in determining the active phase of the material. A deep understanding of the pyrolysis mechanism is in demand. Therefore, the thermodynamics and combustion process with different heating rates was examined, and the kinetic parameters were computed employing thermogravimetric tests. Based on the TG analysis of combustion, pyrolysis moves to the high-temperature region with an increase in heating rate. The decomposition process can be separated into the dehydration (300–503 K) and the pyrolysis reaction (703–1100 K). Three points of the decomposition process are performed by dynamical analysis owing to shifts of slopes, but the combustion process has only one stage. The Zeolitic imidazolate framework’s structure properties were examined using TDDFT-DFT/DMOl3 simulation techniques. Dynamical parameters, for instance, the possible mechanism, the pre-exponential factor, and the apparent activation energy are obtained through comparison using the Kissinger formula. The thermodynamics analysis of the Zn1-xCox-ZIF-8 materials is an effective way to explore the temperature influence on the process of pyrolysis, which can benefit several environment purifications, photocatalyst, and recent applications.

The application range of existing real scale mobile thermal storage units with phase change materials (PCM) is restricted by the low phase change temperature of 58 ∘ C for sodium acetate trihydrate, which is a commonly used storage material. Therefore, only low temperature heat sinks like swimming pools or greenhouses can be supplied. With increasing phase change temperatures, more applications like domestic heating or industrial process heat could be operated. The aim of this study is to find alternative PCM with phase change temperatures between 90 and 150 ∘ C . Temperature dependent thermophysical properties like phase change temperatures and enthalpies, densities and thermal diffusivities are measured for the technical grade purity materials xylitol (C 5 H 12 O 5 ), erythritol (C 4 H 10 O 4 ) and magnesiumchloride hexahydrate (MCHH, MgCl 2 · 6H 2 O). The sugar alcohols xylitol and erythritol indicate a large supercooling and different melting regimes. The salt hydrate MgCl 2 · 6H 2 O seems to be a suitable candidate for practical applications. It has a melting temperature of 115.1 ± 0.1 ∘ C and a phase change enthalpy of 166.9 ± 1.2 J / g with only 2.8 K supercooling at sample sizes of 100 g . The PCM is stable over 500 repeated melting and solidification cycles at differential scanning calorimeter (DSC) scale with only small changes of the melting enthalpy and temperature.

Hydrogels based on sodium alginate (SA) and partially neutralised poly(acrylic acid) were obtained by radical polymerisation. The hydrogels were cross-linked with N,N′-methylenebisacrylamide (MBA), simultaneously grafting the resulting polymer onto SA. The findings of the FTIR spectroscopy showed that all of the hydrogels were effectively synthesized and sodium alginate was chemically bonded with the poly(sodium acrylate) matrix. DSC analysis of the melting heat and glass transition parameters indicated that the hydrogel structure had changed as a result of the cross-linking process. Sodium alginate and MBA were tested at different concentrations to determine how they affected the hydrogel properties. A very high content of the biopolymer, i.e., sodium alginate, was used in our research, up to 33 wt%. This resulted in durable and stable hydrogels with a very high ability to uptake water, comparable to hydrogels based on synthetic polymers only. The ability to swell is inversely proportional to the quantity of MBA present. By increasing the amount of sodium alginate in the hydrogel, the ability of the hydrogel to absorb water is reduced. However, water uptake remains relatively high at 350 g·g−1, even for the hydrogel with the highest SA content.

The objective of this review paper is to survey the phase transition kinetics with a focus on the temperature dependence of the rates of crystallization and melting, as well as on the activation energies of these processes obtained via the Arrhenius kinetic treatment, including the treatment by isoconversional methods. The literature is analyzed to track the development of the basic models and their underlying concepts. The review presents both theoretical and practical considerations regarding the kinetic analysis of crystallization and melting. Both processes are demonstrated to be kinetically complex, and this is revealed in the form of nonlinear Arrhenius plots and/or the variation of the activation energy with temperature. Principles which aid one to understand and interpret such results are discussed. An emphasis is also put on identifying proper computational methods and experimental data that can lead to meaningful kinetic interpretation.

The cold-pressed oil from Japanese quince seeds (JQSO) is notable for its favorable fatty acid profile, low oxidation rate, and bioactive compounds like antioxidants, sterols, and carotenoids. This study offers a detailed molecular-level physical characterization of JQSO and its minor components using differential scanning calorimetry (DSC), Langmuir monolayer studies, and various spectroscopic methods, including UV–vis absorption, fluorescence, and FTIR. DSC analysis identified five peaks related to triglyceride (TG) fractions and provided insights into the melting and crystallization behavior of JQSO. The Langmuir monolayer studies revealed high compressibility, indicative of superior emulsification properties. Viscoelastic modulus measurements suggested strong intermolecular interactions, contributing to the oil’s resilience under stress—an attribute typical of oils high in saturated or monounsaturated fatty acids. Spectroscopic methods confirmed the presence of phenolic acids, tocopherols, carotenoids, and their derivatives. The total fluorescence spectra highlighted prominent peaks at 290 nm/330 nm and 360 nm/440 nm, while the total synchronous fluorescence spectra revealed key excitation–emission regions (10–50 nm/300 nm and 40–140 nm/360 nm), corroborating the presence of tocopherols, phenols, polyphenols, flavones, and carotenoids. No evidence of chlorophyll was detected. The ATR-FTIR spectra validated the presence of fatty acids and triacylglycerols, emphasizing a high degree of esterification and the dominance of unsaturated fatty acids in oil structures. The methods used provided the opportunity to perform a label-free, fast, and reliable determination of the properties of JQSO. The findings confirmed that crude, cold-pressed JQSO retains its valuable bioactive components, aligning with previous research on its chemical and physical properties.