• Energy Research
• 2016-2025close
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Abstract Lignin is considered as a renewable and sustainable resource for producing value-added aromatic chemicals and functional carbon materials. Herein, we develop a one-step catalyst-free depolymerization strategy to convert lignin into aryl monomers and carbon nanospheres simultaneously. Importantly, microwave-assisted depolymerization (MAD) in conjunction with dichloromethane (CH2Cl2) vapors is developed. The total mass yield of guaiacols reached the highest amount of 225.1 mg/g at 600 °C, and the highest yields of phenols (49.0 mg/g) and aromatic hydrocarbons (155.1 mg/g) were obtained at 700 °C. Hydrogen radicals and hydrogen chloride (HCl) are in-situ formed from CH2Cl2, significantly decreasing the activation barrier and reforming pyrolysis vapors to promote the formation of aryl monomers. Interestingly, uniform carbon nanospheres with an average size of 140 nm were produced as co-products at 700 °C. The microwave “hot-spots”, allied with the continuous surface erosion and the decrease in surface energy of lignin-derived carbon precursors by CH2Cl2 vapor, can be considered the driving force for the ultimate formation of carbon nanospheres. The CH2Cl2/MAD system produces aryl monomers (26.8 wt% yield) and carbon nanospheres (36.6 wt% yield) at 700 °C. We provide a facile, intriguing and scalable approach to convert lignin to valuable aryl monomers and sustainable carbon materials that can be applied in the chemistry, energy and environmental fields.

Abstract Lignin is considered as a renewable and sustainable resource for producing value-added aromatic chemicals and functional carbon materials. Herein, we develop a one-step catalyst-free depolymerization strategy to convert lignin into aryl monomers and carbon nanospheres simultaneously. Importantly, microwave-assisted depolymerization (MAD) in conjunction with dichloromethane (CH2Cl2) vapors is developed. The total mass yield of guaiacols reached the highest amount of 225.1 mg/g at 600 °C, and the highest yields of phenols (49.0 mg/g) and aromatic hydrocarbons (155.1 mg/g) were obtained at 700 °C. Hydrogen radicals and hydrogen chloride (HCl) are in-situ formed from CH2Cl2, significantly decreasing the activation barrier and reforming pyrolysis vapors to promote the formation of aryl monomers. Interestingly, uniform carbon nanospheres with an average size of 140 nm were produced as co-products at 700 °C. The microwave “hot-spots”, allied with the continuous surface erosion and the decrease in surface energy of lignin-derived carbon precursors by CH2Cl2 vapor, can be considered the driving force for the ultimate formation of carbon nanospheres. The CH2Cl2/MAD system produces aryl monomers (26.8 wt% yield) and carbon nanospheres (36.6 wt% yield) at 700 °C. We provide a facile, intriguing and scalable approach to convert lignin to valuable aryl monomers and sustainable carbon materials that can be applied in the chemistry, energy and environmental fields.

Lower-cost alternatives to platinum electrocatalysts are being explored for the sustainable production of hydrogen, but often trial-and-error approaches are used for their development. Now, principles are elucidated that suggest pathways to rationally design efficient metal-free electrocatalysts based on doped graphene.

Lower-cost alternatives to platinum electrocatalysts are being explored for the sustainable production of hydrogen, but often trial-and-error approaches are used for their development. Now, principles are elucidated that suggest pathways to rationally design efficient metal-free electrocatalysts based on doped graphene.

Abstract Data from many real-world applications can be high dimensional and features of such data are usually highly redundant. Identifying informative features has become an important step for data mining to not only circumvent the curse of dimensionality but to reduce the amount of data for processing. In this paper, we propose a novel feature selection method based on bee colony and gradient boosting decision tree aiming at addressing problems such as efficiency and informative quality of the selected features. Our method achieves global optimization of the inputs of the decision tree using the bee colony algorithm to identify the informative features. The method initializes the feature space spanned by the dataset. Less relevant features are suppressed according to the information they contribute to the decision making using an artificial bee colony algorithm. Experiments are conducted with two breast cancer datasets and six datasets from the public data repository. Experimental results demonstrate that the proposed method effectively reduces the dimensions of the dataset and achieves superior classification accuracy using the selected features.

Abstract Data from many real-world applications can be high dimensional and features of such data are usually highly redundant. Identifying informative features has become an important step for data mining to not only circumvent the curse of dimensionality but to reduce the amount of data for processing. In this paper, we propose a novel feature selection method based on bee colony and gradient boosting decision tree aiming at addressing problems such as efficiency and informative quality of the selected features. Our method achieves global optimization of the inputs of the decision tree using the bee colony algorithm to identify the informative features. The method initializes the feature space spanned by the dataset. Less relevant features are suppressed according to the information they contribute to the decision making using an artificial bee colony algorithm. Experiments are conducted with two breast cancer datasets and six datasets from the public data repository. Experimental results demonstrate that the proposed method effectively reduces the dimensions of the dataset and achieves superior classification accuracy using the selected features.

With growing health risks from climate change and a trend of increasing carbon emissions from coal, it is time for China to take action. The rising frequency and severity of extreme weather events in China, such as record-high temperatures, low rainfall, severe droughts, and floods in many regions (along with the compound and ripple effects of these events on human health) have underlined the urgent need for health-centred climate action. The rebound in the country's coal consumption observed in 2022 reflected the great challenge faced by China in terms of its coal phase-down, over-riding the country's gains in reducing greenhouse gas (GHG) emissions. Timely and adequate responses will not only reduce or avoid the impacts of climate-related health hazards but can also protect essential infrastructures from disruptions caused by extreme weather. Health and climate change are inextricably linked, necessitating a high prioritisation of health in adaptation and mitigation efforts. The 2023 China report of the Lancet Countdown continues to track progress on health and climate change in China, while now also attributing the health risks of climate change to human activities and providing examples of feasible and effective climate solutions. This fourth iteration of the China report was spearheaded by the Lancet Countdown regional centre in Asia, based at Tsinghua University in Beijing, China. Progress is monitored across 28 indicators in five domains: from climate change impacts, exposures, and vulnerability (section 1); to the different elements of action, including adaption (section 2) and mitigation, and their health implications (section 3); to economics and finance (section 4); and public and political engagement (section 5). This report was compiled with the contribution of 76 experts from 26 institutions both within and outside of China. The impending global stocktake at the UN Framework Convention on Climate Change 28th Conference of the Parties (COP28), the UN initiative on early warning systems (which ...

With growing health risks from climate change and a trend of increasing carbon emissions from coal, it is time for China to take action. The rising frequency and severity of extreme weather events in China, such as record-high temperatures, low rainfall, severe droughts, and floods in many regions (along with the compound and ripple effects of these events on human health) have underlined the urgent need for health-centred climate action. The rebound in the country's coal consumption observed in 2022 reflected the great challenge faced by China in terms of its coal phase-down, over-riding the country's gains in reducing greenhouse gas (GHG) emissions. Timely and adequate responses will not only reduce or avoid the impacts of climate-related health hazards but can also protect essential infrastructures from disruptions caused by extreme weather. Health and climate change are inextricably linked, necessitating a high prioritisation of health in adaptation and mitigation efforts. The 2023 China report of the Lancet Countdown continues to track progress on health and climate change in China, while now also attributing the health risks of climate change to human activities and providing examples of feasible and effective climate solutions. This fourth iteration of the China report was spearheaded by the Lancet Countdown regional centre in Asia, based at Tsinghua University in Beijing, China. Progress is monitored across 28 indicators in five domains: from climate change impacts, exposures, and vulnerability (section 1); to the different elements of action, including adaption (section 2) and mitigation, and their health implications (section 3); to economics and finance (section 4); and public and political engagement (section 5). This report was compiled with the contribution of 76 experts from 26 institutions both within and outside of China. The impending global stocktake at the UN Framework Convention on Climate Change 28th Conference of the Parties (COP28), the UN initiative on early warning systems (which ...