Isobaric vapor-liquid equilibria (VLE) are experimentally measured for the binary systems of dimethyl carbonate (DMC)+ ethylene carbonate and methanol + ethylene carbonate at 101.325kPa. The thermodynamic consistency ...Isobaric vapor-liquid equilibria (VLE) are experimentally measured for the binary systems of dimethyl carbonate (DMC)+ ethylene carbonate and methanol + ethylene carbonate at 101.325kPa. The thermodynamic consistency of these experimental data is tested with an available statistic method. Interaction parameters of the carbonate group -OCOO- with the group -CH3, ACH, CH3OH and CH3COO- in UNIFAC model are determined using the experimental and literature VLE data. The results show that the calculated VLE data using the new UNIFAC parameters agree excellently with the experimental data in this work and in literature. These results are useful in the research on DMC and diphenyl carbonate synthesis by transesterification in design of reactor and distillation tower.展开更多
Starting from the fact that water is quite arguably the source of life, the authors agreed to set up a project on water and name it： ＂REFLECTION＂. Particular focus was placed on the following issues： water in natu...Starting from the fact that water is quite arguably the source of life, the authors agreed to set up a project on water and name it： ＂REFLECTION＂. Particular focus was placed on the following issues： water in nature, importance of water in human life, physical and chemical properties of water, protection of water in nature. The aim of the project was to make students aware of the importance of water for health as well as to help them develop a rational relationship towards drinking water. In order to find answers to the issues raised, the authors designed worksheets, PowerPoint presentations, educational games （ecological postcards, dominoes, memory games, etc.）. The authors even tried our hand at making a comic strip. Students learned about the influence of water on health, as well as about water content in particular foods. The long-term goal of the project is to introduce children to scientific approach and methodology. Through active participation and dialogue, students discover cooperative learning and acquire skills that will be beneficial to them as well as to the wider community. Working on the project, students＇ evidence that the role of an individual is a key one in building a better world. This insight helps develop their civic skills and attitudes that serve as the starting point for environmental education. The authors made numerous adaptations and implemented individual approach with the goal of training students for independent work and life according to their personal abilities in line with the principles of inclusive education. Students conduct experiments following step-by-step instructions on specially adapted worksheets. Each student gets positive feedback and experiences the joy of success that leads to the development of self-confidence and love of work and learning.展开更多
Hexagonal boron nitride （h-BN） is often prepared by epitaxial growth on metals, and stability of the formed BN/metal interfaces in gaseous environment is a key issue for physicochemical properties of the BN overlaye...Hexagonal boron nitride （h-BN） is often prepared by epitaxial growth on metals, and stability of the formed BN/metal interfaces in gaseous environment is a key issue for physicochemical properties of the BN overlayers. As an illustration here, the structural change of a BN/Ru（0001） interface upon exposure to 02 has been investigated using in situ photoemission electron microscopy （PEEM） and ambient pressure X-ray photoelectron spectroscopy （AP-XPS）. We demonstrate the occurrence of oxygen intercalation of the BN overlayers in 02 atmosphere, which decouples the BN overlayer from the substrate. Comparative studies of oxygen intercalation at BN/Ru（0001） and graphene/Ru（0001） surfaces indicate that the oxygen intercalation of BN overlayers happens more easily than graphene. This finding will be of importance for future applications of BN-based devices and materials under ambient conditions.展开更多
The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate predictio...The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate prediction of chemical poisoning of honey bees is a challenging task owing to a lack of understanding of chemical toxicity and introspection. Deep learning(DL) shows potential utility for general and highly variable tasks across fields. Here, we developed a new DL model of deep graph attention convolutional neural networks(GACNN) with the combination of undirected graph(UG) and attention convolutional neural networks(ACNN) to accurately classify chemical poisoning of honey bees. We used a training dataset of 720 pesticides and an external validation dataset of 90 pesticides, which is one order of magnitude larger than the previous datasets. We tested its performance in two ways: poisonous versus nonpoisonous and GACNN versus other frequently-used machine learning models. The first case represents the accuracy in identifying bee poisonous chemicals. The second represents performance advantages. The GACNN achieved ~6% higher performance for predicting toxic samples and more stable with ~7%Matthews Correlation Coefficient(MCC) higher compared to all tested models, demonstrating GACNN is capable of accurately classifying chemicals and has considerable potential in practical applications.In addition, we also summarized and evaluated the mechanisms underlying the response of honey bees to chemical exposure based on the mapping of molecular similarity. Moreover, our cloud platform(http://beetox.cn) of this model provides low-cost universal access to information, which could vitally enhance environmental risk assessment.展开更多
文摘Isobaric vapor-liquid equilibria (VLE) are experimentally measured for the binary systems of dimethyl carbonate (DMC)+ ethylene carbonate and methanol + ethylene carbonate at 101.325kPa. The thermodynamic consistency of these experimental data is tested with an available statistic method. Interaction parameters of the carbonate group -OCOO- with the group -CH3, ACH, CH3OH and CH3COO- in UNIFAC model are determined using the experimental and literature VLE data. The results show that the calculated VLE data using the new UNIFAC parameters agree excellently with the experimental data in this work and in literature. These results are useful in the research on DMC and diphenyl carbonate synthesis by transesterification in design of reactor and distillation tower.
文摘Starting from the fact that water is quite arguably the source of life, the authors agreed to set up a project on water and name it： ＂REFLECTION＂. Particular focus was placed on the following issues： water in nature, importance of water in human life, physical and chemical properties of water, protection of water in nature. The aim of the project was to make students aware of the importance of water for health as well as to help them develop a rational relationship towards drinking water. In order to find answers to the issues raised, the authors designed worksheets, PowerPoint presentations, educational games （ecological postcards, dominoes, memory games, etc.）. The authors even tried our hand at making a comic strip. Students learned about the influence of water on health, as well as about water content in particular foods. The long-term goal of the project is to introduce children to scientific approach and methodology. Through active participation and dialogue, students discover cooperative learning and acquire skills that will be beneficial to them as well as to the wider community. Working on the project, students＇ evidence that the role of an individual is a key one in building a better world. This insight helps develop their civic skills and attitudes that serve as the starting point for environmental education. The authors made numerous adaptations and implemented individual approach with the goal of training students for independent work and life according to their personal abilities in line with the principles of inclusive education. Students conduct experiments following step-by-step instructions on specially adapted worksheets. Each student gets positive feedback and experiences the joy of success that leads to the development of self-confidence and love of work and learning.
文摘Hexagonal boron nitride （h-BN） is often prepared by epitaxial growth on metals, and stability of the formed BN/metal interfaces in gaseous environment is a key issue for physicochemical properties of the BN overlayers. As an illustration here, the structural change of a BN/Ru（0001） interface upon exposure to 02 has been investigated using in situ photoemission electron microscopy （PEEM） and ambient pressure X-ray photoelectron spectroscopy （AP-XPS）. We demonstrate the occurrence of oxygen intercalation of the BN overlayers in 02 atmosphere, which decouples the BN overlayer from the substrate. Comparative studies of oxygen intercalation at BN/Ru（0001） and graphene/Ru（0001） surfaces indicate that the oxygen intercalation of BN overlayers happens more easily than graphene. This finding will be of importance for future applications of BN-based devices and materials under ambient conditions.
基金This work was supported in part by the National Key Research and Development Program of China(2017YFD0200506)the National Natural Science Foundation of China(21837001 and 21907036).
文摘The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate prediction of chemical poisoning of honey bees is a challenging task owing to a lack of understanding of chemical toxicity and introspection. Deep learning(DL) shows potential utility for general and highly variable tasks across fields. Here, we developed a new DL model of deep graph attention convolutional neural networks(GACNN) with the combination of undirected graph(UG) and attention convolutional neural networks(ACNN) to accurately classify chemical poisoning of honey bees. We used a training dataset of 720 pesticides and an external validation dataset of 90 pesticides, which is one order of magnitude larger than the previous datasets. We tested its performance in two ways: poisonous versus nonpoisonous and GACNN versus other frequently-used machine learning models. The first case represents the accuracy in identifying bee poisonous chemicals. The second represents performance advantages. The GACNN achieved ~6% higher performance for predicting toxic samples and more stable with ~7%Matthews Correlation Coefficient(MCC) higher compared to all tested models, demonstrating GACNN is capable of accurately classifying chemicals and has considerable potential in practical applications.In addition, we also summarized and evaluated the mechanisms underlying the response of honey bees to chemical exposure based on the mapping of molecular similarity. Moreover, our cloud platform(http://beetox.cn) of this model provides low-cost universal access to information, which could vitally enhance environmental risk assessment.
