rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: The
    title: science of AI for energy storage
  name:
    name part: Spellman, Frank R.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2026
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: The Science of AI for Energy Storage presents a comprehensive exploration of the intersection between artificial intelligence (AI) and energy storage technologies. This book provides a detailed analysis of energy storage systems, including mechanical, electrochemical, chemical, electrical, and thermal solutions, while emphasizing the transformative role of AI and machine learning in optimizing these technologies. By integrating foundational principles with cutting-edge advancements, the book delivers a robust framework for understanding the design, application, and sustainability of modern energy storage systems. Written in the author's hallmark conversational yet scientifically rigorous style, the work bridges the gap between theory and practice, offering invaluable insights for energy professionals, engineers, policymakers, and academics. Explores the transformative role of artificial intelligence (AI) and machine learning in optimizing energy storage systems, including batteries, supercapacitors, and pumped hydro storage. Examines a wide range of storage technologies-mechanical, electrochemical, chemical, electrical, and thermal-ensuring a thorough understanding of current and future solutions. Highlights the role of energy storage in achieving sustainability goals and addresses the challenges of integrating AI to meet growing global energy demands efficiently.
  note: Frank R. Spellman.
  note: Includes bibliographical references.
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Energy storage
  subject:
    topic: Intelligence artificielle
    topic: Applications industrielles
  subject:
    topic: Énergie
    topic: Stockage
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Energy storage
  classification: TJ165
  classification: 621.3126
  related item:
    identifier: (OCoLC)1527588350
  identifier: 9781040648490
  identifier: 1040648495
  identifier: 9781003637851
  identifier: 100363785X
  identifier: 9781040594049
  identifier: 1040594042
  identifier: 1041069200
  identifier: 9781041069201
  identifier: 9781003637851 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 251118
    record change date: 20260209202848.3
    record identifier: in00005684538
    language of cataloging:
      language term: eng