1.

Record Nr.

UNINA9910298611603321

Autore

Lei Ting

Titolo

Design, Synthesis, and Structure-Property Relationship Study of Polymer Field-Effect Transistors / / by Ting Lei

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015

ISBN

3-662-45667-2

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (124 p.)

Collana

Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053

Disciplina

621.381

621.3815284

Soggetti

Optical materials

Electronics - Materials

Polymers

Electronics

Microelectronics

Renewable energy resources

Optical and Electronic Materials

Polymer Sciences

Electronics and Microelectronics, Instrumentation

Renewable and Green Energy

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction -- Side Chain Effects and Design of Isoindigo-Based Polymers -- Ambipolar Polymer Field-Effect Transistors Based on Functionalized Isoindigo -- BDOPV-A Strong Electron-Deficient Building Block for Polymer Field-Effect Transistors -- Summary and Outlook.

Sommario/riassunto

The book summarizes Ting Lei’s PhD study on a series of novel conjugated polymers for field-effect transistors (FETs). Studies contain many aspects of polymer FETs, including backbone design, side-chain engineering, property study, conformation effects and device fabrication. The research results have previously scattered in many important journals and conferences worldwide. The book is likely to be



of interest to university researchers, engineers and graduate students in materials sciences and chemistry who wish to learn some principles, strategy, and applications of polymer FETs.

2.

Record Nr.

UNINA9910983328203321

Autore

Luger George F

Titolo

Artificial Intelligence : principles and practice

Pubbl/distr/stampa

Cham : , : Springer, , 2025

©2025

ISBN

9783031574375

3031574370

Edizione

[1st ed.]

Descrizione fisica

1 online resource (639 pages)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Sommario/riassunto

This book provides a complete introduction to Artificial Intelligence, covering foundational computational technologies, mathematical principles, philosophical considerations, and engineering disciplines essential for understanding AI. Artificial Intelligence: Principles and Practice emphasizes the interdisciplinary nature of AI, integrating insights from psychology, mathematics, neuroscience, and more. The book addresses limitations, ethical issues, and the future promise of AI, emphasizing the importance of ethical considerations in integrating AI into modern society. With a modular design, it offers flexibility for instructors and students to focus on specific components of AI, while also providing a holistic view of the field.  Taking a comprehensive but concise perspective on the major elements of the field; from historical background to design practices, ethical issues and more, Artificial Intelligence: Principles and Practice provides the foundations needed for undergraduate or graduate-level courses.  The important design paradigms and approaches to AI are explained in a clear, easy-to-



understand manner so that readers will be able to master the algorithms, processes, and methods described.  The principal intellectual and ethical foundations for creating artificially intelligent artifacts are presented in Parts I and VIII. Part I offers the philosophical, mathematical, and engineering basis for our current AI practice. Part VIII presents ethical concerns for the development and use of AI. Part VIII also discusses fundamental limiting factors in the development of AI technology as well as hints at AI's promising future. We recommended that PART I be used to introduce the AI discipline and that Part VIII be discussed after the AI practice materials. Parts II through VII present the three main paradigms of current AI practice: the symbol-based, the neural network or connectionist, and the probabilistic.  Generous use of examples throughout helps illustrate the concepts, and separate end-of-chapter exercises are included. Teaching resources include a solutions manual for the exercises, PowerPoint presentation, and implementations for the algorithms in the book.