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Char gasification is a feasible technology to recycle CO2 and utilize biomass energy. However, the impact of different species of biomass on the gasification is still unclear. For the assessment of the feedstock effect on CO2 gasification, the present work prepared over 40 different wood char samples on a high temperature (around 1523 K) flame reactor, which simulate the rapid heating rates experienced in industrial reactors. Then, the curves of conversion (X) and conversion rate (dX/dt) versus temperature, and the conversion rate versus fractional conversion were derived from the linear non-isothermal thermogravimetric analysis. Three models (volumetric model, grain model, and random pore model) are examined for their goodness of fit between the model and experimental data, and their estimated activation energy. Finally, links between different biomass property parameters and different reactivity indexes were investigated. The results obtained show that different feedstocks result in different gasification reactivities of the resultant chars, with T50 and Tmax varying in a wide range of about 170 K and 200 K. But when conversion is plotted against dimensionless temperature, regardless of the feedstock origin, all the experimental plots can be described by only one curve for X = 0.2–0.95. We attributed the slightly superior prediction of the RPM to the increased amount of adjustable kinetic parameters, but lower E values were obtained by using RPM. In addition to the potassium content, the cellulose and lignin contents of the feedstock were found to have relatively high correlation with the char reactivity indexes. [ABSTRACT FROM AUTHOR]

Abundant genetic variation among the geographical provenances of Juglans mandshurica. The biomass and allometry of 3-year-old J. mandshurica seedlings were studied among 21 Chinese provenances to understand the variations in biomass allocation in depth. Standardized major axis (SMA) regression analysis was used to analyze the allometry relationship between the organs and whole plants or between the organs of plants from different provenances. Pearson correlation analysis determined the correlation of various biomass traits and the geographical and climatic factors of provenances. Significant variations (p < 0.001) in seedling biomass and its distribution were observed among the different provenances. The root, stem, leaf, aboveground, and total biomasses of Hongshi, Ji'an, Fangzheng, and Kuandian provenances were the highest, but their root allocation and root–shoot ratios were all lower. This phenomenon is just the opposite in the Lushuihe provenance. An extremely marked positive correlation (p < 0.001) was detected among the root, stem, leaf, aboveground, and total biomasses, but there were significant negative correlations (p < 0.001) among the biomass allocation ratios (except between root allocation and root–shoot ratios). The organs, aboveground, and total biomasses were mainly positively affected by annual mean precipitation except for leaf biomass. The allometric growth relationship between the organs or between the organs (except roots) and whole plants of J. mandshurica changed remarkably among the provenances (p < 0.05). The organ–biomass allocation in J. mandshurica seedlings conspicuously varied among the different provenances, which was mainly caused by the genetic variations in the seeds. This study provided the basis for the selection of optimal provenances for J. mandshurica seedlings. [ABSTRACT FROM AUTHOR]

A recent report published in Nature Metabolism identified that glutamine synthetase (GS), the only enzyme in mammals to produce glutamine from glutamate, can directly control cancer cell mitosis by governing the APC/C complex via a metabolism-independent mechanism. It reported that GS can directly interact with the nuclear pore protein NUP88 to abolish its binging with CDC20, therefore licensing the activation of APC/CCDC20 to permit proper metaphase to anaphase transition of mitosis. These findings illustrated a dual-function mode of action of GS in cancer cells, in which GS’s metabolic and non-metabolic functions coordinate with the concentration change of glutamine in the tumor microenvironment (TME) to ensure cell survival or proliferation, respectively. These findings revealed the multi-faceted roles of glutamine synthetase in tumor development and underscored the potential to target non-canonical functions of glutamine synthetase for cancer treatment.

Epoxy resin is a widely used polymer material, while its low mechanical properties and thermal stability limit its use in extreme environments such as high temperature and high pressure. In order to improve the performance of EP, this study assessed the enhancement of mechanical properties and thermal stability of EP by stearic acid‐modified n‐CeO2 and its mechanism. Laser particle size analyzers, transmission electron microscopes, and other instruments were used to characterize n‐CeO2. Universal testing machines, thermogravimetric analyzers, and other instruments were used to test n‐CeO2/EP nanocomposites. The results show that fatty acids effectively coated the surface of n‐CeO2, reducing its central particle size from 0.248 μm to 0.193 μm and improving its dispersion and compatibility. The tensile, flexural, impact strength, maximum decomposition temperature, and glass transition temperature (Tg) increased by 382%, 554%, 698%, 5%, and 10%, respectively with 2 wt% filler content. The scanning electron microscopy (SEM) images showed that the addition of n‐CeO2 induced plastic deformation and crack formation in the EP matrix, which enhanced the toughness of the composite material. This study provided the effective methods and basis for the preparation of high‐performance n‐CeO2/EP nanocomposites. Highlights: Nano cerium dioxide was modified to improve its dispersion by using stearic acid.High‐performance nanocomposites were prepared by using modified nanoparticles.The stiffness and toughness of the epoxy resin were enhanced by adding n‐CeO2.Thermal stability and heat resistance of the epoxy resin were improved by doping n‐CeO2.SEM images of the impact section showed that n‐CeO2 can prevent crack propagation. [ABSTRACT FROM AUTHOR]

The emission of carbon dioxide (CO2) by thermal power plants is the main factor leading to the greenhouse effect. The measurement of CO2 is of great significance to carbon emission data statistics. In this paper, a measurement system based on tunable diode laser absorption spectroscopy (TDLAS) was built to measure the spectrum of CO2 near 1579 nm. To simplify the experimental system, a direct absorption signal fitting method is proposed to replace etalons for time‐frequency conversion. The method was applied to the measurement of four different concentrations of CO2 in the range of 7%–16%, and the measurement results were compared with the multipeak method, another etalon‐free method. The results show that the mean relative error of the measurement results is 4.23%, which is 1.76% lower than the measurement results of the multipeak method. The experimental research provides a feasible idea to simplify the CO2 measurement system based on TDLAS. [ABSTRACT FROM AUTHOR]

Accurately predicting trends in NOx emission is essential for effectively controlling pollution in municipal solid waste incineration (MSWI) power plants. However, the MSWI process exhibits notable dynamic nonlinearity, time series characteristics, and fluctuations that are distinct from those present in fossil fuel combustion processes. Therefore, the model must possess excellent capabilities in handling time series and nonlinear features while achieving adaptive updates to account for complex working conditions. To address these issues, we have developed a robust prediction model for NOx emission trends using the bi‐directional long short‐term memory (Bi‐LSTM) deep learning algorithm. This model encompasses maximum information coefficient and expert experience for input variables selection, parameter optimization using the linear inertial weight particle swarm algorithm (LDWPSO), and an adaptive update strategy based on probabilistic statistics. The prediction performance of this model was compared to that of the traditional and widely used backpropagation neural network (BPNN), extreme learning machine (ELM), and LSTM. Furthermore, we verified the adaptive update effect of the proposed model using additional data. The results demonstrate that the proposed model exhibits robust prediction and adaptive capabilities. This study's originality is presenting a satisfactory trend prediction for NOx emission from the MSWI process using an adaptive LDWPSO‐(Bi‐LSTM) model. It will be essential for the optimization and control of NOx emissions from the MSWI process. [ABSTRACT FROM AUTHOR]

In this issue of Cell Metabolism , Li et al. report that the highly expressed aldehyde dehydrogenase 1 family member A3 interacts with pyruvate kinase M2 (PKM2) in glioblastoma cells. Consequently, PKM2 tetramerization and activation promote lactate production, leading to the lactylation and nuclear translocation of XRCC1 for DNA damage repair and therapeutic resistance. [ABSTRACT FROM AUTHOR]