AI Revolutionizing Materials Science and Engineering
A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 20 January 2025 | Viewed by 69
Special Issue Editor
Interests: performance of materials; characterisation of materials; testing of materials; failure investigation; materials selection; materials in design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Materials science and engineering (MSE) play a pivotal role in scientific progress in all fields of development and this Special Issue of Materials delves into the transformative power artificial intelligence (AI) holds across the field to accelerate research, deepen learning, broaden accessibility, and allow unprecedented rates of innovation.
While cornerstone factors such as a detailed understanding of the relationships between a material’s structure, properties, and performance will still remain at the heart of research and teaching, accessing and using this knowledge and indeed our ability to create new materials are already changing. The way future materials scientists and engineers will develop the complex cross-disciplinary understanding needed by the industries of tomorrow is predicted to undergo a revolutionary change and our universities need to be ready to support them.
In research, AI offers a paradigm shift by enabling researchers to leverage vast datasets and sophisticated algorithms to develop new materials that will solve the world’s most pressing problems. In teaching, AI offers the potential to broaden access, enhance inclusivity, and provide bespoke feedback and assessment that were not previously possible. At this point, it is not yet clear just how profound the changes are going to be; all that is clear is that AI is here, and we need to understand both the risks and opportunities it presents to the materials research communities.
The following is a list of possible topics which would fit well into this Special Issue:
- Accelerating material discovery: AI can analyze complex material property relationships, predict novel material compositions with desired functionalities, and guide experimental efforts more efficiently;
- Enhancing material characterization: AI-powered tools can analyze data from characterization techniques like electron microscopy and spectroscopy, extracting deeper insights and automating tedious tasks;
- Optimizing material processing: Machine learning algorithms can analyze process parameters and material responses, leading to the development of optimized processing techniques for tailored material properties;
- Materials performance: Understanding the performance and integrity of materials, taking in real-time data and predicting the health of assets in concert with asset integrity management systems;
- Materials selection: Never before have we had the tools to process and use the vast amount of data which exists on the performance of materials in any application or environment;
- Teaching and learning for the next generation of materials scientists and engineers: AI tools offer unprecedented opportunities to enhance pedagogy and support the next generation graduates.
Dr. Andrew Spowage
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Materials is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- AI tools
- accelerated material discovery
- enhanced material characterization
- optimized material processing
- materials performance
- materials selection
