High-performance flexible power sources have gained attention, as they enable the realization of next-generation bendable, implantable, and wearable electronic systems. Although the rechargeable lithium-ion battery (LIB) has been regarded as a strong candidate for a high-performance flexible energy source, compliant electrodes for bendable LIBs are restricted to only a few materials, and their performance has not been sufficient for them to be applied to flexible consumer electronics including rollable displays. In this paper, we present a flexible thin-film LIB developed using the universal transfer approach, which enables the realization of diverse flexible LIBs regardless of electrode chemistry. Moreover, it can form high-temperature (HT) annealed electrodes on polymer substrates for high-performance LIBs. The bendable LIB is then integrated with a flexible light-emitting diode (LED), which makes an all-in-one flexible electronic system. The outstanding battery performance is explored and well supported by finite element analysis (FEA) simulation.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/nl302254v | DOI Listing |
Sci Rep
December 2024
Health and Sports Medicine Department, Faculty of Sports Sciences and Health, University of Tehran, North Karegar St, P.O.B: 1439813117, Tehran, Iran.
Although the connection between muscular strength and flatfoot condition is well-established, the impact of corrective exercises on these muscles remains inadequately explored. This study aimed to assess the impact of intrinsic- versus extrinsic-first corrective exercise programs on muscle morphometry and navicular drop in boys with flexible flatfoot. Twenty-five boys aged 10-12 with flexible flatfoot participated, undergoing a 12-week corrective exercise program, with a shift in focus at six weeks.
View Article and Find Full Text PDFSci Rep
December 2024
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
Autonomous vehicles, often known as self-driving cars, have emerged as a disruptive technology with the promise of safer, more efficient, and convenient transportation. The existing works provide achievable results but lack effective solutions, as accumulation on roads can obscure lane markings and traffic signs, making it difficult for the self-driving car to navigate safely. Heavy rain, snow, fog, or dust storms can severely limit the car's sensors' ability to detect obstacles, pedestrians, and other vehicles, which pose potential safety risks.
View Article and Find Full Text PDFSci Rep
December 2024
School of Management Science and Engineering, Shandong Jianzhu University, Jinan, 250101, China.
This study seeks to improve urban supply chain management and collaborative governance in the context of public health emergencies (PHEs) by integrating fuzzy theory with the Back Propagation Neural Network (BPNN) algorithm. By combining these two approaches, an early warning mechanism for supply chain risks during PHEs is developed. The study employs Matlab software to simulate supply chain risks, incorporating fuzzy inference techniques with the adaptive data modeling capabilities of neural networks for both training and testing.
View Article and Find Full Text PDFSci Rep
December 2024
Advanced Research Institute for Digital-Twin Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Statistical Science, Duke University, Durham, 27708-0251, USA.
The article is motivated by an application to the EarlyBird cohort study aiming to explore how anthropometrics and clinical and metabolic processes are associated with obesity and glucose control during childhood. There is interest in inferring the relationship between dynamically changing and high-dimensional metabolites and a longitudinal response. Important aspects of the analysis include the selection of the important set of metabolites and the accommodation of missing data in both response and covariate values.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!