Path Catalog
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ALLPATHFoundationALLPATHFoundationPath Catalog
正在从 AllPath API 加载 Path Catalog…
Path Catalog
列表数据实时取自 GET /api/v1/paths，仅包含存在已发布版本的 Path。
共 7800 条 Path · 第 205 / 780 页
This learning path introduces high school students to the structure of the global energy system. Starting with basic energy concepts, it traces energy from primary sources through transformation to final consumption across major sectors, including industry, transport, and buildings.
This learning path introduces high school students to the fundamental concepts of energy systems, including definitions, boundaries, inputs/outputs, energy chains, and socio-technical perspectives. It builds from basic physics and systems thinking to a holistic understanding of energy systems.
A systematic learning path for graduate students and beginning researchers to develop essential skills for conducting research in energy storage. It covers research problem formulation, literature review, experimental design, data analysis, scientific communication, ethics, and reproducibility.
This advanced graduate-level path explores quantum phenomena in energy storage, focusing on quantum batteries, quantum dots, and quantum capacitors. It begins with essential quantum mechanics and solid-state physics, then progresses to theoretical models and applications, providing a comprehensive understanding for researchers.
This graduate-level learning path explores the principles, technologies, and economic aspects of gravity-based energy storage. It covers the fundamental physics, various system architectures (mass-based, mine shafts, tower systems), performance metrics, and cost considerations. Designed for graduate students and researchers, it builds from foundational mechanics to advanced system analysis.
This advanced graduate-level learning path provides a systematic study of liquid air energy storage (LAES) technology, from fundamental cryogenic thermodynamics to system integration and applications. Learners will analyze the liquefaction and regasification processes, evaluate round-trip efficiency, and explore integration with renewable energy and industrial waste heat. The path emphasizes rigorous thermodynamic analysis and system-level understanding.
This learning path explores the fundamentals and advanced topics of metal-air batteries, covering electrochemistry, challenges, catalysts, and energy density for Li-air, Zn-air, and Al-air systems. Designed for graduate students and researchers, it progresses from basic concepts to advanced research directions, emphasizing the interdisciplinary nature of the field.
This path equips graduate students and researchers with the knowledge to apply machine learning to battery management systems (BMS). It covers battery fundamentals, key ML techniques for state estimation, predictive modeling, optimization, and anomaly detection, culminating in a capstone project that demonstrates an integrated AI-based BMS application.
This advanced professional learning path equips engineers and managers with the knowledge to design viable business models for energy storage projects. It covers market structures, revenue streams, value stacking, and economic analysis, culminating in the creation of a project-specific business model.
This advanced professional learning path equips engineers with the skills to apply data analytics to energy storage systems, focusing on state-of-health (SOH) estimation, predictive maintenance, and performance optimization. It bridges battery domain knowledge with machine learning and data engineering practices, culminating in a capstone project.