Energy and AI

|

Elsevier
United Kingdom
ENGINEERING
/
English
Gold OA
T2
Scopus, Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (ESCI), SCImago Journal Rank (SJR) and SNIP

Publishing Information

/
Single-blind

Founding year

2020

Publishing Frequency

4 issues per year

Number of articles per year

105

(2024)

Acceptance Rate

81%

(2023)

Open Access

CC BY | CC BY-NC | CC BY-NC-ND

Content

Original research article; Review article; Other (specify); Short Communication
No
Reproducible research
Open
Official Journal of Tianjin University Energy and AI provides a fast and authoritative open access platform to disseminate the latest research progress in the cross-disciplinary area of energy and artificial intelligence (AI). The journal focuses on innovative applications of AI that address the critical challenges in energy systems, energy materials, energy chemistry, energy utilization & conversion, and energy & society, as well as other important pressing issues in energy research. The journal also considers papers on the development of bespoke AI technologies and methodologies for advancing energy, decarbonization and sustainable development, such as data-driven approaches, optimization algorithms and AI ethics. Energy and AI aims to become a leading journal for cutting-edge research at the interface between energy and AI. Papers purely focusing on a single aspect of energy or AI are not suitable for the journal. The journal considers full length, short communications, perspective and review articles, and publishes 4 volumes per year. Focal points of the journal include, but are not limited to: Automation of science discovery related to energy materials and chemistry Digital twinning or big data analytics of complex energy processes/systems Data-driven design of energy materials, devices and systems Internet-of-things and cyber-physical energy systems AI for human factors in energy related activities Virtual reality applied to energy and environment Autonomous systems for energy efficiency maximalization Hardware for data collections in energy systems Data Science for energy applications Hybrid data-driven and physical modelling for energy related problems Intelligent control of energy systems AI, energy and society AI safety, reliability and ethics within energy applications AI for life-cycle assessment or energy and decarbonization roadmaps Energy robotics This journal welcomes contributions that support and advance the UN's sustainable development goals, in particular SDG 7 (Affordable and clean energy)