The main motivation for replacing lithium-ion batteries with lithium metal batteries is to achieve a higher energy density by using the metallic lithium anode. One of the major challenges with ...rechargeable lithium metal batteries is the formation of lithium dendrites and dead lithium during repeated cycling. Another challenge is the formation of the unstable solid electrolyte interphase (SEI) on the surface of the lithium metal electrode, which can reduce battery efficiency and cycle life. In the present work, two different lithium silicates (Li2Si2O5 and Li2SiO3) are successfully synthesized and implemented as an artificial SEI layer via a simple dry coating method. The lithium silicate coating acts as a protective barrier that prevents direct contact between the lithium metal and the electrolyte, which can cause undesirable side reactions and reduce the efficiency and lifetime of the battery. The lithium silicate artificial SEI layer improves the stability of lithium metal batteries by reducing unwanted surface reactions, optimizing ion transport kinetics, and protecting the lithium metal anode from mechanical deformation and unstable SEI formation during extended cycling. This laminated lithium anode structure can be an effective design for the future development of rechargeable lithium metal batteries.
Display omitted
•Three lithium silicate precursors were utilized to create a stable artificial SEI layer, improving battery efficiency and cycle life.•Li2Si2O5 and Li2SiO3 were successfully synthesized via solid-state or hydrothermal reactions.•Lithium silicate-based artificial SEIs improve the stability of Li stripping/deposition and ion transport kinetics.•Lithium silicate-based artificial SEIs protect Li metal anodes from mechanical deformation and undesired dendrite formation during cycling.
This investigation explores the differentiated electrochemical behavior of silicon (Si) anodes in lithium-ion batteries (LIBs) under different operating protocols defined by specific voltage windows ...and capacity control strategies. Our investigation reveals distinctive responses of the Si anode to different state of charge (SoC) ranges, translating delivered capacity into significant variations in cycle life. While predominantly mostly lithiated Si anodes at 0.01–0.32 V subjected to voltage-controlled operation with an SoC between 75 % and 100 % exhibit poor cycle life, a similar situation with predominantly mostly delithiated anodes at 0.23–1.5 V and an SoC of 0–25 % also results in inferior cycle performance. Conversely, predominantly partially lithiated Si anodes at 0.01–0.5 V under voltage-controlled conditions with an SoC range of 65–100 % show superior cycle life performance. However, predominantly partially delithiated Si anodes at 0.1–1.5 V, voltage controlled with an SoC of 0–40 %, lead to a cycle life with obvious degradation. Likewise, Si anodes subjected to full lithiation followed by delithiation at 1200 mA h g−1, controlled by delithiation capacity, demonstrate excellent cycle life within a SoC range of 65–100 %. On the contrary, full delithiation followed by lithiation at 1200 mA h g−1 results in less favorable cycle life within an SoC range of 0–35 %. In short, maintaining the lithiation state at a higher level, i.e. a high SoC, throughout the cycle allows Si anodes to maintain low impedance, resulting in outstanding cycle performance. These results provide important insights into tailoring operating parameters to optimize Si anode cycle performance in LIBs.
Display omitted
In recent years, learning materials have gradually been applied to flipped classrooms. Teachers share learning materials, and students can preview the learning materials before class. During class, ...the teacher can discuss students' questions from their notes from previewing the learning materials. The social media platform Facebook provides access to learning materials and diversified interactions, such as sharing knowledge, annotating learning materials, and establishing common objectives. Previous studies have explored the effect of flipped classrooms on students' learning engagement, attitudes, and performance. In this paper, we apply educational data mining to explore the relationship between students' viewing behaviors in accessing learning materials and their performance in flipped classrooms. The participants are classified into an experimental group and a control group to engage in flipped classroom activities. The experimental group uses the social media platform Facebook for flipped learning, and the control group uses a learning management system for flipped learning. The results show that there is a significant difference in the learning performance between the two groups, with the average score of the experimental group being higher than that of the control group. Furthermore, we find that the viewing behaviors and performance of the students within the experimental group differ significantly.
Pair programming (PP) can help improve students’ computational thinking (CT), but the trajectory of CT skills and the differences between high-scoring and low-scoring students in PP are unknown and ...need further exploration. In this study, a total of 32 fifth graders worked on Scratch tasks in 16 pairs. The group discourse of three learning topics (comprising 9 projects) was collected. After the audio files were transcribed, 1,303 conversations were obtained. They were analyzed via Epistemic Network Analysis (ENA) Webkit, which can reveal the trajectory of students’ CT development via analyzing codes of discourse related to CT in PP. Three Scratch learning topics were assessed based on the Dr. Scratch platform to acquire the level of students’ CT and to determine the low- and high-scoring groups. Results indicated that CT concepts and CT practices were always closely related in PP and CT practices, and CT perspectives could be gradually and closely related after a long period of CT training. A significant difference between the two groups’ CT structures was found. The high-scoring group had more fragments of CT practice and connecting of CT perspectives, while the low-scoring group showed more fragments of CT concepts and expressing of CT perspectives. This research provides insights into cultivating primary school students’ CT using Scratch in the context of PP. The findings can provide suggestions for instructors to design instructional interventions to facilitate students’ CT skills via PP learning. Instructors can improve CT skills by guiding students to constantly ask questions, and specifying the role swap between driver and navigator in PP. Besides, instructors could give more consideration to the development of CT perspectives, and especially the ability to question.
The Miocene Lincang leaf assemblage is used in this paper as proxy data to reconstruct the palaeoclimate of southwestern Yunnan (SW China) and the evolution of monsoon intensity. Three quantitative ...methods were chosen for this reconstruction, i.e. Leaf Margin Analysis (LMA), Climate Leaf Analysis Multivariate Program (CLAMP), and the Coexistence Approach (CA). These methods, however, yield inconsistent results, particularly for the precipitation, as also shown in European and other East Asian Cenozoic floras. The wide range of the reconstructed climatic parameters includes the Mean Annual Temperature (MAT) of 18.5–24.7
°C and the Mean Annual Precipitation (MAP) of 1213–3711
mm. Compared with the modern Lincang climate (MAT, 17.3
°C; MAP, 1178.7
mm), the Miocene climate is slightly warmer, wetter and has a higher temperature seasonality. A detailed comparison on the palaeoclimatic variables with the coeval Late Miocene Xiaolongtan flora from the eastern part of Yunnan allows us to investigate the development and interactions of both South Asian and East Asian monsoons during the Late Miocene in southwest China, now under strong influence of these monsoon systems. Our results suggest that the monsoon climate has already been established in southwest Yunnan during the Late Miocene. Furthermore, our results support that both Southeast Asian and East Asian monsoons co-occurred in Yunnan during the Late Miocene.
Digital reality technologies (such as AR, VR, and MR) have recently become a key component of promoting creative and cultural industries (CCIs) worldwide to transform static cultural heritage ...exhibits into more engaging, entertaining, and immersive experiences. These technologies present an exciting example of studying how consumers would respond to the potential invasion of privacy due to these technologies. This literature review study mainly focuses on one essential branch of CCIs: museums and their applications of digital reality technologies. Because many of these location-based AR applications by museums are inherently sensitive to users’ locational information, there is also a rising concern of the potential infringement of personal privacy (RQ1). A thorough examination of existing literature on how consumers respond to privacy concerns related to the museum’s AR applications will help uncover how scholars have approached and studied these crucial issues in the literature (RQ2). Unlike traditional literature review analyses, we employed a text mining of retrieved 715 studies articles from
Business Source Complete
and
Engineering Village
(E.I.) databases to answer our two research questions. Our study found that privacy and user(s) /visitor(s) has dramatically increased since 2017, echoing the rising concerns of other privacy-invasive technologies. Most notably, key phrases extracted from the literature corpus include “security and privacy,” “privacy and security,” “privacy risks,” “privacy concerns,” “privacy issues,” “user privacy,” “location privacy,” “privacy protection,” and “privacy preserving” that are most pertinent to the rapid implementation of AR technology in the museum sector. Discussions and implications are provided.
The first case of 2009 pandemic influenza A (H1N1) virus infection in China was documented on May 10. Subsequently, persons with suspected cases of infection and contacts of those with suspected ...infection were tested. Persons in whom infection was confirmed were hospitalized and quarantined, and some of them were closely observed for the purpose of investigating the nature and duration of the disease.
During May and June 2009, we observed 426 persons infected with the 2009 pandemic influenza A (H1N1) virus who were quarantined in 61 hospitals in 20 provinces. Real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) testing was used to confirm infection, the clinical features of the disease were closely monitored, and 254 patients were treated with oseltamivir within 48 hours after the onset of disease.
The mean age of the 426 patients was 23.4 years, and 53.8% were male. The diagnosis was made at ports of entry (in 32.9% of the patients), during quarantine (20.2%), and in the hospital (46.9%). The median incubation period of the virus was 2 days (range, 1 to 7). The most common symptoms were fever (in 67.4% of the patients) and cough (69.5%). The incidence of diarrhea was 2.8%, and the incidence of nausea and vomiting was 1.9%. Lymphopenia, which was common in both adults (68.1%) and children (92.3%), typically occurred on day 2 (range, 1 to 3) and resolved by day 7 (range, 6 to 9). Hypokalemia was observed in 25.4% of the patients. Duration of fever was typically 3 days (range, 1 to 11). The median length of time during which patients had positive real-time RT-PCR test results was 6 days (range, 1 to 17). Independent risk factors for prolonged real-time RT-PCR positivity included an age of less than 14 years, male sex, and a delay from the onset of symptoms to treatment with oseltamivir of more than 48 hours.
Surveillance of the 2009 H1N1 virus in China shows that the majority of those infected have a mild illness. The typical period during which the virus can be detected with the use of real-time RT-PCR is 6 days (whether or not fever is present). The duration of infection may be shortened if oseltamivir is administered.
Comfortable leisure and entertainment is expected through multimedia. Web multimedia systems provide diversified multimedia interactions, for example, sharing knowledge, experience and information, ...and establishing common watching habits. People use information technology (IT) systems to watch multimedia videos and to perform interactive functions. Moreover, IT systems enhance multimedia interactions between users. To explore user behaviors in viewing multimedia videos by key points in time, multimedia video watching patterns are analyzed by data mining techniques. Data mining methods were used to analyze users' video watching patterns in converged IT environments. After the experiment, we recorded the processes of clicking the Web multimedia video player. The system logs of using the video player are classified into four variables, playing time, active playing time, played amount, and actively played amount. To explore the four variables, we apply the k-means clustering technique to organize the similar playing behavior patterns of the users into three categories: actively engaged users, watching engaged users, and long engaged users. Finally, we applied statistical analysis methods to compare the three categories of users' watching behaviors. The results showed that there were significant differences among the three categories.
To understand students' learning behaviors, this study uses machine learning technologies to analyze the data of interactive learning environments, and then predicts students' learning outcomes. This ...study adopted a variety of machine learning classification methods, quizzes, and programming system logs, found that students' learning characteristics were correlated with their learning performance when they encountered similar programming practice. In this study, we used random forest (RF), support vector machine (SVM), logistic regression (LR), and neural network (NN) algorithms to predict whether students would submit on time for the course. Among them, the NN algorithm showed the best prediction results. Education-related data can be predicted by machine learning techniques, and different machine learning models with different hyperparameters can be used to obtain better results.
In Taiwan, classroom lectures are gradually shifting from traditional to diverse digital learning environments through social network websites. Facebook is being used to provide a space for sharing ...and discussing learning materials and knowledge for teachers and students. In this paper, we focus on the effects of applying Big Six approaches to Facebook on students’ learning performance and behavior in a project innovation and implementation course. The participants were 72 first-year students in a college located in north Taiwan. The experimental participants who took the course were divided into two classes: the experimental group and the control group. While the experimental group used Facebook combined with Big Six approaches, the control group used traditional classroom tools combined with Big Six approaches. The experimental results show that the learning performance and creativity development of students from the experimental group are enhanced after using Facebook with Big Six approaches indicating a great social interaction and discussion cycle. On the other hand, students from the control group were only guided by the teacher. Owing to the lack of interactions between the Internet and the social learning community, there is no obvious enhancement in students’ learning performance and creativity. In addition, we found that the teacher practiced the tips for guiding experimental students to solve the encountered problem, and then the students replied to the classmate’s questions.
PDF
