Distributed electrified heating for efficient hydrogen production.

This study introduces a distributed electrified heating approach that is able to innovate chemical engineering involving endothermic reactions. It enables rapid and uniform heating of gaseous reactants, facilitating efficient conversion and high product selectivity at specific equilibrium. Demonstrated in catalyst-free CH4 pyrolysis, this approach achieves stable production of H2 (530 g h-1 L reactor -1) and carbon nanotube/fibers through 100% conversion of high-throughput CH4 at 1150 °C, surpassing the results obtained from many complex metal catalysts and high-temperature technologies. Additionally, in catalytic CH4 dry reforming, the distributed electrified heating using metallic monolith with unmodified Ni/MgO catalyst washcoat showcased excellent CH4 and CO2 conversion rates, and syngas production capacity. This innovative heating approach eliminates the need for elongated reactor tubes and external furnaces, promising an energy-concentrated and ultra-compact reactor design significantly smaller than traditional industrial systems, marking a significant advance towards more sustainable and efficient chemical engineering society.

Digital transformation, productive services agglomeration and innovation performance.

Innovation is a necessary guarantee for sustainable development. Stepping into the digital age, digital transformation has triggered the innovation revolution. This paper takes 30 provinces in China from 2012 to 2022 as the research sample, we verify whether digital transformation has improved innovation performance. Based on the Solow growth model and agglomeration economics theory, we also explore the moderating role and threshold effect of agglomeration in productive service industry between digital transformation and innovation performance. To achieve this, we apply the methods of machine learning and text analysis to construct an evaluation index of regional digital transformation and measure it. The paper finds that China's digital transformation index is increasing, but there is a digital divide between regions. We also determine that digital transformation significantly and positively contributes to the level of innovation performance. Considering the threshold effect of agglomeration in productive service industry, the impact of digital transformation on innovation performance exhibits non-linear characteristics, As the level of agglomeration continues to exceed the threshold, the innovation-driven effect of digital transformation increases. The research results help clarify the relationship between digital transformation and innovation performance, and provide favorable policy directions for regional governments to identify digital divides and make reasonable industrial layouts. Thus, it can promote the construction of digital China and innovation power, injecting strong innovation force into the realization of SDGs.

Bio-based anode material production for lithium-ion batteries through catalytic graphitization of biochar: the deployment of hybrid catalysts.

Producing sustainable anode materials for lithium-ion batteries (LIBs) through catalytic graphitization of renewable biomass has gained significant attention. However, the technology is in its early stages due to the bio-graphite's comparatively low electrochemical performance in LIBs. This study aims to develop a process for producing LIB anode materials using a hybrid catalyst to enhance battery performance, along with readily available market biochar as the raw material. Results indicate that a trimetallic hybrid catalyst (Ni, Fe, and Mn in a 1:1:1 ratio) is superior to single or bimetallic catalysts in converting biochar to bio-graphite. The bio-graphite produced under this catalyst exhibits an 89.28% degree of graphitization and a 73.95% conversion rate. High-resolution transmission electron microscopy (HRTEM) reveals the dissolution-precipitation mechanism involved in catalytic graphitization. Electrochemical performance evaluation showed that the trimetallic hybrid catalyst yielded bio-graphite with better electrochemical performances than those obtained through single or bimetallic hybrid catalysts, including a good reversible capacity of about 293 mAh g-1 at a current density of 20 mA/g and a stable cycle performance with a capacity retention of over 98% after 100 cycles. This study proves the synergistic efficacy of different metals in catalytic graphitization, impacting both graphite crystalline structure and electrochemical performance.

Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes.

Feedstock properties play a crucial role in thermal conversion processes, where understanding the influence of these properties on treatment performance is essential for optimizing both feedstock selection and the overall process. In this study, a series of van Krevelen diagrams were generated to illustrate the impact of H/C and O/C ratios of feedstock on the products obtained from six commonly used thermal conversion techniques: torrefaction, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, pyrolysis, and gasification. Machine learning methods were employed, utilizing data, methods, and results from corresponding studies in this field. Furthermore, the reliability of the constructed van Krevelen diagrams was analyzed to assess their dependability. The van Krevelen diagrams developed in this work systematically provide visual representations of the relationships between feedstock and products in thermal conversion processes, thereby aiding in optimizing the selection of feedstock and the choice of thermal conversion technique.

Development of functional connectome gradients during childhood and adolescence.

Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network, capturing a functional spectrum that ranges from perception and action to abstract cognition. However, how this gradient pattern develops and whether its development is linked to cognitive growth, topological reorganization, and gene expression profiles remain largely unknown. Using longitudinal resting-state functional magnetic resonance imaging data from 305 children (aged 6-14 years), we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence, including emergence as the principal gradient, expansion of global topography, and focal tuning in primary and default-mode regions. These gradient changes are mediated by developmental changes in network integration and segregation, and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes. Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.

Pyrolysis of engineered beach-cast seaweed: Performances and life cycle assessment.

The blooming of beach-cast seaweed has caused environmental degradation in some coastal regions. Therefore, a proper treating and utilizing method of beach-cast seaweed is demanded. This study investigated the potential of producing power or biofuel from pyrolysis of beach-cast seaweed and the effect of the ash-washing process. First, the raw and washed beach-cast seaweeds (RS and WS) were prepared. Thereafter, thermogravimetric analysis (TG), bench-scale pyrolysis experiment, process simulation, and life cycle assessment (LCA) were conducted. The TG results showed that the activation energies of thermal decomposition of the main organic contents of RS and WS were 44.23 and 58.45 kJ/mol, respectively. Three peak temperatures of 400, 500, and 600 °C were used in the bench-scale pyrolysis experiments of WS. The 600 °C case yielded the most desirable gas and liquid products. The bench-scale pyrolysis experiment of RS was conducted at 600 °C as well. Also, an LCA was conducted based on the simulation result of 600 °C pyrolysis of WS. The further process simulation and LCA results show that compare to producing liquid biofuel and syngas, a process designed for electricity production is most favored. It was estimated that treating 1 ton of dry WS can result in a negative cumulative energy demand of -2.98 GJ and carbon emissions of -790.89 kg CO2 equivalence.

The impact of digital economy on total factor carbon productivity: the threshold effect of technology accumulation.

This research focuses on the impact of the digital economy on total factor carbon productivity. Based on the panel data of China's provinces from 2009 to 2019, this paper incorporates undesired output, namely carbon emissions, into the evaluation index system, and uses the SBM-ML index to measure regional total factor carbon productivity, and uses the RAGA-PP model to measure the digital economy development index, which includes three dimensions: digital infrastructure, digital industry development, and digital economic environment. Moreover, this paper incorporates the heterogeneous threshold of technological accumulation into the framework of the impact mechanism of total factor carbon productivity and builds a threshold model to examine the impact of the digital economy on total factor carbon productivity under different technological accumulation thresholds. The research shows that, first, during the sample period, total factor carbon productivity fluctuated around the frontier, showing a certain upward trend, with significant regional heterogeneity. Second, the digital economy has a promotional effect on the total factor carbon productivity level in China and can become the new energy for the country to improve the level of green development. Third, the impact of the digital economy on total factor carbon productivity presents a significant heterogeneous threshold effect of technological accumulation, along with the increasing level of technology accumulation, the effective coefficient of the digital economy on total factor carbon productivity is increasing, and the level of significance is increasing. Last, the low-carbon driving mechanism of the digital economy has temporal and spatial heterogeneity of regional technology accumulation levels. The conclusions of this paper provide an effective reference for exploring the realization mechanism of regional total factor carbon productivity improvement, ecological civilization construction, and high-quality economic development.

Research on the impact of energy technology innovation on total factor ecological efficiency.

Promoting sustainable economic development from the perspective of energy technology is crucial, given limited energy resources and severe environmental pollution. Based on the panel data of China's provinces from 2000 to 2017, we empirically explore the complex relation among energy technology innovation, regional economic growth, and total factor ecological efficiency. We innovatively introduce ecological footprint as one of the input indicators of total factor ecological efficiency measured using slack-based measure-data envelopment analysis, thereby comprehensively quantifying sustainable economic development. Moreover, we adopt spatial econometric and threshold regression models to empirically assess the relation between energy technology innovation and total factor ecological efficiency. We infer the following conclusions. First, both China's provincial ecological efficiency and energy technology innovation possess significant spatial positive correlation, manifesting a spatial geographical distribution agglomerated by similar characteristics. Second, the regional energy technology innovation has a remarkable spatial effect on ecological efficiency, displaying a U-shaped trend. Compared with the direct effect, the spatial spillover effect is more intense, along with a much stronger long-term influence. Third, under the regulation of regional economic growth, two inflection points exist in the effect of energy technology innovation on ecological efficiency. Energy technology innovation is not conducive to total factor ecological efficiency under low regional economic growth. No significant relation exists between the two core variables under medium regional economic growth. Furthermore, energy technology innovation positively influences total factor ecological efficiency only when regional economic growth reaches a certain peak.

Atriplex canescens: A new host for Cistanche deserticola.

Cistanche deserticola has been historically used in traditional Chinese medicine for supplementing kidney (yang) function, benefiting blood and essence, and moistening intestines in order to pass stool. Its host, Haloxylon ammodendron, is an important pioneer plant used for windbreaks and sand dune fixation, which are strategies used for the control desertification. For a long time, it has been considered that C. deserticola can only parasitize H. ammodendron. In this study, morphological identification, gene barcoding identification and inoculation experiment were carried out, we finally found that C. deserticola can also parasitize Atriplex canescens. A. canescens is a species of Chenopodiaceae with a wide range of adaptability. Compared with H. ammodendron, it has more biomass and a wider range of ecological adaptability, making it more suitable for the industrial production of C. deserticola. In addition, we also found that the concentration of active components was higher in C. deserticola parasitized on A. canescens than in those parasitized on H. ammodendron; this finding further suggests that the application of C. deserticola on a larger scale warrants further exploration.

Does renewable energy consumption contribute to the development of low-carbon economy? Evidence from China.

Stimulating renewable energy consumption has become a major strategic choice for China to both fulfill the international commitment to reduce carbon emissions and realize the high-quality growth of the domestic economy. On account of the provincial data during the period of 2000 to 2017, we creatively incorporate the ecological footprint into the measurement of low-carbon economy development level through super-efficient SBM model, so as to infer the coordinated development level of 3E system more precisely. Based on the factor substitution effect, energy path dependence effect, and scale effect, the complex nonlinear relationship between the two core research objects is further probed by constructing the threshold regressive model. On the foundation of theoretical research, the consumption of renewable energy, the intensity of energy use, and the level of regional economic development are respectively selected as the moderating variables of the model. Further, we divide different intervals of threshold values to distinguish the differences in the effects caused by regional heterogeneity. The following conclusions are drawn ultimately: There is an apparent threshold effect between renewable consumption and the advancement of the low-carbon economy. Only when renewable itself reaches a higher level of consumption can it show a significant advantage in green economic development. In addition, to make full use of renewable resources to boost the low-carbon and green economy, it is necessary to reduce the economy's dependence on energy, that is, to decrease the intensity of energy use while maintaining the process of improving coordination of regional economy.

Application of Threshold Regression Analysis to Study the Impact of Clean Energy Development on China's Carbon Productivity.

Facing the pressures of international carbon emission reduction, the transformation into a low-carbon economy has become a common issue of all countries. The core of developing a low-carbon economy is to increase carbon productivity, which can be measured as the economic benefits of unit carbon emissions. Therefore, using province-level panel data in China from 2009 to 2017, we analyze the carbon productivity level of each region, and empirically investigate the threshold effect of clean energy development on carbon productivity under different technological innovation levels. The results show that the carbon productivity is rising, and China's economic development pattern has been shifting towards low-carbon and sustainable development. Furthermore, the driving force of clean energy development on carbon productivity is not monotonously increasing (decreasing) but is a "double threshold effect" of technological innovation capability. Finally, based on the research conclusions and realistic requirements of China's low-carbon economic transformation, this paper proposes improving carbon productivity from the aspects of innovation capability improvement and institutional guarantee.

Source attribution and structure classification-assisted strategy for comprehensively profiling Chinese herbal formula: Ganmaoling granule as a case.

Chinese herbal formula (CHF) has extremely complex chemical composition. Herein, a source attribution and structure classification-assisted strategy was established based on reductionism for rapidly and comprehensively profiling CHF, and Ganmaoling granule (GMLG) was selected as a representative case to illustrate such a strategy and to confirm its applicability. Firstly, comprehensive data acquisition was achieved using neutral losses along with full scan on a liquid chromatography coupled with hybrid ion trap-time of flight mass spectrometer (LC-IT-TOF-MS). Then, the detected precursor and product ions were paired to construct a list of ion transitions for profiling GMLG and its constituent herbs using the scheduled multiple reaction monitoring (sMRM) mode on a LC coupled with hybrid triple quadrupole-linear ion trap mass spectrometer (LC-Q-Trap-MS). The mass parameters of sMRM were optimized using an online optimization strategy to achieve the highest sensitivity, and the automated source attribution was performed with the assistant of the "Quantitate" function of Analyst software. The target peaks were then structurally classified into seven classes through integrating the mass defect filtering (MDF) and diagnostic fragment ion filtering (DFIF), and identified by combination of the mass fragmentation rules and a 'structure extension' approach. Using this strategy, 261 components, including 148 trace ones (with the intensity lower than 100,000 cps), were tentatively characterized. The findings demonstrated that such a comprehensive source attribution and structure classification-assisted strategy is qualified to be an efficient approach for rapidly and globally characterizing the chemical profile of CHF.

[Quantitative analysis of calycosin glycoside and formononetin in Radix astragali from different sources].

OBJECTIVE: To establish the quantitative methods for calycosin glycoside and formononetin in Radix Astragali, and the samples from different sources were analyzed, in order to supply the basis for the quality control of Radix Astragali. METHOD: The content of calycosin glycoside and formononetin in 59 samples of Radix Astragali from eight with different provinces was analyzed by HPLC-DAD. RESULT: The contents of calycosin glycoside and formononetin in Radix Astragali from different sources, with different cultivating method or in different ages differed markedly, and the results showed that the quality of samples from Shannxi, Innermongolia and Shanxi were better than other sources, and the semi-wild samples were better than other cultiving samples, moreover the shorter age, the better quality. CONCLUSION: This simple, accurate and reproducible method could use to determine the contents of isoflavanoids in Radix Astragali.