Thermal desorption and pyrolysis direct analysis in real time mass spectrometry of Nafion membrane

Perfluorosulfonic acid ionomer membranes have been widely used as proton conducting membranes in various electrochemical processes such as polymer electrolyte fuel cells and water electrolysis. While their thermal stability has been studied by thermogravimetry and analysis of low molecular weight products, their decomposition mechanism is little understood. In this study a newly developed methodology of thermal desorption and pyrolysis in combination with direct analysis in real time mass spectrometry is applied for Nafion membrane. An ambient ionization source and a high-resolution time-of-flight mass spectrometer enabled unambiguous assignment of gaseous products. Thermal decomposition is initiated by side chain detachment above 350°C, which leaves carbonyls on the main chain at the locations of the side chains. Perfluoroalkanes are released above 400°C by main chain scission and their further decomposition products dominate above 500 °C. DFT calculation of reaction energies and barrier heights of model compounds support proposed decomposition reactions.     

Mitochondrial and Autophagic Regulation of Adult Neurogenesis in the Healthy and Diseased Brain

Adult neurogenesis is a highly regulated process during which new neurons are generated from neural stem cells in two discrete regions of the adult brain: the subventricular zone of the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Defects of adult hippocampal neurogenesis have been linked to cognitive decline and dysfunction during natural aging and in neurodegenerative diseases, as well as psychological stress-induced mood disorders. Understanding the mechanisms and pathways that regulate adult neurogenesis is crucial to improving preventative measures and therapies for these conditions. Accumulating evidence shows that mitochondria directly regulate various steps and phases of adult neurogenesis. This review summarizes recent findings on how mitochondrial metabolism, dynamics, and reactive oxygen species control several aspects of adult neural stem cell function and their differentiation to newborn neurons. It also discusses the importance of autophagy for adult neurogenesis, and how mitochondrial and autophagic dysfunction may contribute to cognitive defects and stress-induced mood disorders by compromising adult neurogenesis. Finally, I suggest possible ways to target mitochondrial function as a strategy for stem cell-based interventions and treatments for cognitive and mood disorders.     

Analysis of surface and interior degradation of gas diffusion layer with accelerated stress tests for polymer electrolyte membrane fuel cell

The effects of surface and interior degradation of the gas diffusion layer (GDL) on the performance and durability of polymer electrolyte membrane fuel cells (PEMFCs) have been investigated using three freeze-thaw accelerated stress tests (ASTs). Three ASTs (ex-situ, in-situ, and new methods) are designed from freezing ?30 °C to thawing 80 °C by immersing, supplying, and bubbling, respectively. The ex-situ method is designed for surface degradation of the GDL. Change of surface morphology from hydrophobic to hydrophilic by surface degradation of GDL causes low capillary pressure which decreased PEMFC performance. The in-situ method is designed for the interior degradation of the GDL. A decrease in the ratio of the porosity to tortuosity by interior degradation of the GDL deteriorates PEMFC performance. Moreover, the new method showed combined effects for both surface and interior degradation of the GDL. It was identified that the main factor that deteriorated the fuel cell performance was the increase in mass transport resistance by interior degradation of GDL. In conclusion, this study aims to investigate the causes of degraded GDL on the PEMFC performance into the surface and interior degradation and provide the design guideline of high-durability GDL for the PEMFC.     

Stem Photosynthesis—A Key Element of Grass Pea (Lathyrus sativus L.) Acclimatisation to Salinity

Grass pea (Lathyrus sativus) is a leguminous plant of outstanding tolerance to abiotic stress. The aim of the presented study was to describe the mechanism of grass pea (Lathyrus sativus L.) photosynthetic apparatus acclimatisation strategies to salinity stress. The seedlings were cultivated in a hydroponic system in media containing various concentrations of NaCl (0, 50, and 100 mM), imitating none, moderate, and severe salinity, respectively, for three weeks. In order to characterise the function and structure of the photosynthetic apparatus, Chl a fluorescence, gas exchange measurements, proteome analysis, and Fourier-transform infrared spectroscopy (FT-IR) analysis were done inter alia. Significant differences in the response of the leaf and stem photosynthetic apparatus to severe salt stress were observed. Leaves became the place of harmful ion (Na⁺) accumulation, and the efficiency of their carboxylation decreased sharply. In turn, in stems, the reconstruction of the photosynthetic apparatus (antenna and photosystem complexes) activated alternative electron transport pathways, leading to effective ATP synthesis, which is required for the efficient translocation of Na⁺ to leaves. These changes enabled efficient stem carboxylation and made them the main source of assimilates. The observed changes indicate the high plasticity of grass pea photosynthetic apparatus, providing an effective mechanism of tolerance to salinity stress.     

Investigation of thermal residual stresses during laser ablation of tantalum carbide coated graphite substrates using micro-Raman spectroscopy and COMSOL multiphysics

Laser ablation of high-temperature ceramic coatings results in thermal residual stresses due to which the coatings fail by cracking and debonding. Hence, the measurement of such residual stresses during laser ablation process holds utmost importance from the view of performance of coatings in extreme conditions. The present research aims at investigating the effect of laser parameters such as laser pulse energy, scanning speed and line spacing on thermal residual stresses induced in tantalum carbide-coated graphite substrates. Residual stresses were measured using micro-Raman spectroscopy and correlated with Raman peak shifts. Transient thermal analysis was performed using COMSOL Multiphysics to model the single ablated track and residual stresses were reported at low, moderate and high pulse energy regimes. The results showed that the initial laser conditions caused higher tensile residual stresses. Moderate pulse energy regime comprised higher compressive residual stresses due to off centre overlapping of the laser pulses. Higher pulse energy (250 μJ), higher scanning speed (1000 mm/s) and moderate line spacing (20 μm) caused accumulation of tensile residual stresses during the final stage of laser ablation. The deviation of experimental residual stresses from COMSOL numerical model was attributed to unaccounted additional stresses induced during thermal spraying process and deformation potentials in the numerical model.     

Magnetic field-enhanced photocatalytic nitrogen fixation over defect-rich ferroelectric Bi2WO6

Photocatalytic N₂ fixation is a promising and sustainable manufacturing process of ammonia (NH₃); however, the NH₃ production rate by this method is very low, thus severely restricting further application of this sustainable technology. Therefore, developing an efficient photocatalyst for N₂ fixation under mild conditions is urgently required. Herein, ferroelectric Bi₂WO₆ materials with different surface oxygen defects were prepared, and the concentration of corresponding defects was controlled by adjusting the thermal reduction time. The abundant oxygen defects in Bi₂WO₆ can provide more reactive sites to promote the effective adsorption of N₂, and the photogenerated charge carrier can be efficiently separated benefiting from the internal electric field. These would weaken the N₂ triple bond and reduce the activation energy barrier for the conversion of N₂ to NH₃ under mild conditions. In the absence of sacrificial agents and cocatalysts, the optimized Bi₂WO₆ with oxygen defects shows an indigenous NH₃ yield of 132.175 μmol·g^-1·L^-1·h^-1, which is more than two times higher than that of the original Bi₂WO₆. Surprisingly, the Bi₂WO₆ with oxygen defects produced more than eight times NH₃ (471.13 μmol·g^-1·L^-1·h^-1) than that of the original Bi₂WO₆ when assisted by an external magnetic field, thus providing a new perspective for further enhancing the N₂ fixation performance.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

Adaptation to Endoplasmic Reticulum Stress Enhances Resistance of Oral Cancer Cells to Cisplatin by Up-Regulating Polymerase η and Increasing DNA Repair Efficiency

Endoplasmic reticulum (ER) stress response is an adaptive program to cope with cellular stress that disturbs the function and homeostasis of ER, which commonly occurs during cancer progression to late stage. Late-stage cancers, mostly requiring chemotherapy, often develop treatment resistance. Chemoresistance has been linked to ER stress response; however, most of the evidence has come from studies that correlate the expression of stress markers with poor prognosis or demonstrate proapoptosis by the knockdown of stress-responsive genes. Since ER stress in cancers usually persists and is essentially not induced by genetic manipulations, we used low doses of ER stress inducers at levels that allowed cell adaptation to occur in order to investigate the effect of stress response on chemoresistance. We found that prolonged tolerable ER stress promotes mesenchymal–epithelial transition, slows cell-cycle progression, and delays the S-phase exit. Consequently, cisplatin-induced apoptosis was significantly decreased in stress-adapted cells, implying their acquisition of cisplatin resistance. Molecularly, we found that proliferating cell nuclear antigen (PCNA) ubiquitination and the expression of polymerase η, the main polymerase responsible for translesion synthesis across cisplatin-DNA damage, were up-regulated in ER stress-adaptive cells, and their enhanced cisplatin resistance was abrogated by the knockout of polymerase η. We also found that a fraction of p53 in stress-adapted cells was translocated to the nucleus, and that these cells exhibited a significant decline in the level of cisplatin-DNA damage. Consistently, we showed that the nuclear p53 coincided with strong positivity of glucose-related protein 78 (GRP78) on immunostaining of clinical biopsies, and the cisplatin-based chemotherapy was less effective for patients with high levels of ER stress. Taken together, this study uncovers that adaptation to ER stress enhances DNA repair and damage tolerance, with which stressed cells gain resistance to chemotherapeutics.     

5A06-O aluminium–magnesium alloy sheet warm hydroforming and optimization of process parameters

The uniaxial tensile test of the 5A06-O aluminium–magnesium (Al–Mg) alloy sheet was performed in the temperature range of 20–300 °C to obtain the true stress–true strain curves at different temperatures and strain rates. The constitutive model of 5A06-O Al–Mg alloy sheet with the temperature range from 150 to 300°C was established. Based on the test results, a unique finite element simulation platform for warm hydroforming of 5A06-O Al–Mg alloy was set up using the general finite element software MSC.Marc to simulate warm hydroforming of classic specimen, and a coupled thermo-mechanical finite element model for warm hydroforming of cylindrical cup was built up. Combined with the experiment, the influence of the temperature field distribution and loading conditions on the sheet formability was studied. The results show that the non-isothermal temperature distribution conditions can significantly improve the forming performance of the material. As the temperature increases, the impact of the punching speed on the forming becomes particularly obvious; the optimal values of the fluid pressure and blank holder force required for forming are reduced.     

Identifying catalyst layer compositions of proton exchange membrane fuel cells through machine-learning-based approach

Membrane electrode assembly (MEA) is considered a key component of a proton exchange membrane fuel cell (PEMFC). However, developing a new MEA to meet desired properties, such as operation under low-humidity conditions without a humidifier, is a time- and cost-consuming process. This study employs a machine-learning-based approach using K-nearest neighbor (KNN) and neural networks (NN) in the MEA development process by identifying a suitable catalyst layer (CL) recipe in MEA. Minimum redundancy maximum relevance and principal component analysis were implemented to specify the most important predictor and reduce the data dimension. The number of predictors was found to play an essential role in the accuracy of the KNN and NN models although the predictors have self-correlations. The KNN model with a K of 7 was found to minimize the model loss with a loss of 11.9%. The NN model constructed by three corresponding hidden layers with nine, eight, and nine nodes can achieve the lowest error of 0.1293 for the Pt catalyst and 0.031 for PVA as a good additive blending in the CL of the MEA. However, even if the error is low, the prediction of PVA seems to be inaccurate, regardless of the model structure. Therefore, the KNN model is more appropriate for CL recipe prediction.