1.

Record Nr.

UNINA9910557427803321

Autore

Quartarone Eliana

Titolo

Recent Advances in Post-Lithium Ion Batteries

Pubbl/distr/stampa

Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021

Descrizione fisica

1 electronic resource (116 p.)

Soggetti

Research & information: general

Technology: general issues

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

Lithium ion batteries (LIBs) are efficient storage systems for portable electronic devices, electrical power grids, and electrified transportation due to their high-energy density and low maintenance requirements. After their launch into the market in 1990s, they immediately became the dominant technology for portable systems. The development of LiBs for electric drive vehicles has been, in contrast, rather incremental. There are several critical issues, such as an energy density, system safety, cost, and environmental impact of the battery production processes, that remain challenges in the automotive field. In order to strengthen the LiB’s competitiveness and affordability in vehicle technology, the necessity of game-changer batteries is urgent. Recently, a novel approach going beyond Li batteries has become rapidly established. Several new chemistries have been proposed, leading to better performances in terms of energy density, long-life storage capability, safety, and sustainability. However, several challenges, such as a thorough understanding of mechanisms, cell design, long-term durability, and safety issues, have not yet been fully addressed. This book collects some recent developments and emerging trends in the field of “post-lithium” batteries, covering both fundamental and applied aspects of next-generation batteries



2.

Record Nr.

UNINA9910557435103321

Autore

Zhang Yudong

Titolo

Deep Learning in Medical Image Analysis

Pubbl/distr/stampa

Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021

Descrizione fisica

1 electronic resource (458 p.)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis.