Digital Chemical Engineering

An Official Publication of the Institution of Chemical Engineers



Digital Chemical Engineering aims to provide a leading platform for publishing new and novel interdisciplinary research across the domains of chemical engineering and digital sciences and technologies. The emerging digital transformation in the chemical industry brings new challenges and opportunities, and is fundamentally changing the way of future chemical engineering research, innovation, education and enterprise. It is the vision of Digital Chemical Engineering to capture the breakthroughs during the transformation, and provide a timely discussion forum for researchers to disseminate results and exchange ideas.

The journal seeks to extend the boundaries of traditional chemical engineering and welcomes papers at the interface between chemical engineering and digitalization related disciplines. We are interested in contributions that advance the knowledge on data science, machine learning and computational sciences to tackle chemical engineering problems. The journal also publishes bespoke solutions and best practices for digital methodologies with a clear application background in the broad sense of chemical engineering, including materials, catalysis, processes, reactors, systems and society.

The journal covers fundamental research, applied research, and case studies, and welcomes contributions from both academia and industry.

Types of Paper
The journal welcomes the following types of papers:

Original research papers report on the outcomes of original research. There is no length limitation to papers of this type but authors are encouraged to be concise and make use of the facility to submit supplementary material for material that enhances the paper.

Case studies are usually from industrial users/researchers presenting successful application cases of implementing digital solutions to improve or enable products, processes or systems in practice. Papers of this type should include the overview of problems, discussion of implementation, and discussion of impact and improvement from the proposed approach. Authors should write in a style that ensures that the article is accessible to the broad readership of the journal. There are no length limitations to case studies.

Review papers of relevance to the core topics covered by the journal are welcomed. A review paper should provide a timely and critical assessment of previously published work.

Perspectives are short opinion papers addressing a key, emerging, research area. They should balance the personal view of the author and a reasoned discussion of recent results of great importance. While they often examine the evolution of the field, they are not meant as a mini-review, but as a scholarly discussion that helps to identify new trends and developments in a given field. Perspective manuscripts should contain no more than 5000 words, up to five figures and 60 references.

Short communications are short reports dealing with especially timely new ideas and specific points such as novel research techniques, fresh analysis of existing work or interesting aspects or results of work-in-progress. Short communications should not exceed the equivalent of 2000 words including illustrations and tables.

The journal also supports the publication of research data*. The areas and topics covered by the journal include but are not limited to:

Topics
Systems thinking
Big data analytics
Artificial intelligence
Blockchain
Process control
Sensors
Robotics
Automation
Virtual reality
Process simulation
Process modelling
Machine learning
Digital twins
Industry 4.0
Ethics
Data Science
Digital Economy
Process system engineering
Engineering and society
Life cycle assessment
Industrial symbiosis
Cyber-physical systems
Reaction Engineering

Sectors
Bio-resources
Catalysis
Circular Economy
Education
Energy
Food and Beverages
Health and Wellbeing
Manufacturing and Resources
Materials
Safety and Risk
Sustainability
Water

*Research data - Mendeley Data, enabling you to deposit any research data (including raw and processed data, video, code, software, algorithms, protocols, and methods) associated with your manuscript in a free-to-use, open access repository. The datasets will be listed and directly accessible to readers next to your published article online.