Artificial Intelligence: An Innovative Solution to the Optimization and Discovery of Functional Materials
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Materials Processes".
Deadline for manuscript submissions: 10 February 2026 | Viewed by 1307
Special Issue Editors
Interests: machine learning; computational materials science; electrochemistry; catalysis; corrosion and protection
Interests: AI; solid-state electrolyte; electrocatalysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Driven by the advances in artificial intelligence (AI), the discovery and optimization of functional materials have reached an unprecedented rate and scale. In recent years, AI has demonstrated success in accelerating the discovery and design of various functional materials ranging from polymers to crystals and nanomaterials. AI plays a critical role in the development of computer-aided robotics, machine learning force-fields, Bayesian optimization, generative models and data-driven approaches. Innovation of next-generation functional materials highly relies on AI-driven methods.
This Special Issue “Artificial Intelligence: An Innovative Solution to the Optimization and Discovery of Functional Materials” welcomes articles that report novel development or applications of AI techniques for the optimization and discovery of functional materials with improved properties.
Rooted in the field of functional materials, to the following topics are included in this Special Issue:
- Machine learning accelerated simulations;
- AI for elucidating experimental data;
- Inverse materials design;
- Automated synthesis.
Dr. Cheng Zeng
Prof. Dr. Menghao Yang
Guest Editors
Manuscript Submission Information
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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. Processes 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 2400 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
- functional materials
- artificial intelligence
- materials informatics
- data-driven approach
- Bayesian optimization
- inverse materials design
- high-throughput screening
- machine learning force-field
- automated experimentation
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