Gang Liu – författare

With the recently well developed areas of Internet of Thing, consumer wearable gadgets and artificial intelligence, flexible and stretchable electronic devices have spurred great amount of interest from both the global scientific and industrial communities. As an emerging technology, flexible and stretchable electronics requires the scale-span fabrication of devices involving nano-features, microstructures and macroscopic large area manufacturing. The key factor behind covers the organic, inorganic and nano materials that exhibit completely different mechanical and electrical properties, as well as the accurate interfacial control between these components. Based on the fusion of chemistry, physics, biology, materials science and information technology, this review volume will try to offer a timely and comprehensive overview on the flexible and stretchable electronic materials and devices. The book will cover the working principle, materials selection, device fabrication and applications of electronic components of transistors, solar cells, memories, sensors, supercapacitors, circuits and etc.

With the recently well developed areas of Internet of Thing, consumer wearable gadgets and artificial intelligence, flexible and stretchable electronic devices have spurred great amount of interest from both the global scientific and industrial communities. As an emerging technology, flexible and stretchable electronics requires the scale-span fabrication of devices involving nano-features, microstructures and macroscopic large area manufacturing. The key factor behind covers the organic, inorganic and nano materials that exhibit completely different mechanical and electrical properties, as well as the accurate interfacial control between these components. Based on the fusion of chemistry, physics, biology, materials science and information technology, this review volume will try to offer a timely and comprehensive overview on the flexible and stretchable electronic materials and devices. The book will cover the working principle, materials selection, device fabrication and applications of electronic components of transistors, solar cells, memories, sensors, supercapacitors, circuits and etc.

This book offers a comprehensive overview of the epidemiology, etiology, and pathophysiology of chronic obstructive pulmonary disease (COPD). It addresses the limitations of existing drug delivery methods and explores advanced delivery systems to overcome these challenges, providing an exhaustive account of their intricate mechanisms. The introductory chapters elucidate pathways responsible for COPD progression, followed by a detailed analysis of established biomarkers and potential targets in contemporary COPD therapy. Subsequent chapters provide insights into ongoing treatment modalities, their efficacy, drawbacks, and prospective solutions to counter the setbacks of COPD therapy. The subsequent section covers state-of-the-art drug delivery technologies and novel drug formulations designed to enhance drug deposition and absorption in COPD lungs. It further explores a methodical yet coordinated explanation of targeted personalized therapies and emerging approaches, including nanoparticles, polymeric carriers, and vesicular delivery systems. Toward the end, the book discusses ongoing and completed clinical trials encompassing the management of COPD through advanced drug delivery approaches. It serves as a valuable resource for professionals, scientists, academicians, and clinicians specializing in respiratory health.

This book offers a comprehensive overview of the epidemiology, etiology, and pathophysiology of chronic obstructive pulmonary disease (COPD). It addresses the limitations of existing drug delivery methods and explores advanced delivery systems to overcome these challenges, providing an exhaustive account of their intricate mechanisms. The introductory chapters elucidate pathways responsible for COPD progression, followed by a detailed analysis of established biomarkers and potential targets in contemporary COPD therapy. Subsequent chapters provide insights into ongoing treatment modalities, their efficacy, drawbacks, and prospective solutions to counter the setbacks of COPD therapy. The subsequent section covers state-of-the-art drug delivery technologies and novel drug formulations designed to enhance drug deposition and absorption in COPD lungs. It further explores a methodical yet coordinated explanation of targeted personalized therapies and emerging approaches, including nanoparticles, polymeric carriers, and vesicular delivery systems. Toward the end, the book discusses ongoing and completed clinical trials encompassing the management of COPD through advanced drug delivery approaches. It serves as a valuable resource for professionals, scientists, academicians, and clinicians specializing in respiratory health.

This book presents a comprehensive range of topics in deep learning for polymer discovery, from fundamental concepts to advanced methodologies.  These topics are crucial as they address critical challenges in polymer science and engineering. With a growing demand for new materials with specific properties, traditional experimental methods for polymer discovery are becoming increasingly time-consuming and costly. Deep learning offers a promising solution by enabling rapid screening of potential polymers and accelerating the design process.  The authors begin with essential knowledge on polymer data representations and neural network architectures, then progress to deep learning frameworks for property prediction and inverse polymer design. The book then explores both sequence-based and graph-based approaches, covering various neural network types including LSTMs, GRUs, GCNs, and GINs. Advanced topics include interpretable graph deep learning with environment-based augmentation, semi-supervised techniques for addressing label imbalance, and data-centric transfer learning using diffusion models.  The book aims to solve key problems in polymer discovery, including accurate property prediction, efficient design of polymers with desired characteristics, model interpretability, handling imbalanced and limited labeled data, and leveraging unlabeled data to improve prediction accuracy.