Overview

This special issue focuses on the integration of Artificial Intelligence (AI) in process and design across various domains with flavor of applied science/engineering. The issue will explore how AI-driven methodologies can enhance efficiency, sustainability, resilience and innovation in various processes, chemical engineering, manufacturing, and business strategies. The goal is to bridge the gap between academic advancements and industry needs by incorporating both technical research and industry perspectives.

The special issue will have 3 types of content:

• Technical papers from academics (target at least 6).
• Business case studies or perspective of business professors and industry players (target at least 4)
• An Op-ed from editors on insights about the issue and key insights and gaps in using AI.

Impact and Expected Contributions

This special issue aims to serve as a comprehensive resource for researchers, engineers, and business leaders exploring AI’s transformative potential in materials science and process engineering. By integrating technical research with industry perspectives, the issue will foster interdisciplinary collaboration and highlight practical pathways for AI adoption in real-world applications.

Scope and Topics

The special issue welcomes original research articles, technical reviews, and industry insights on the following themes:

1. AI for Design of Experiments (DOE)

• AI-assisted experiment planning for materials discovery and optimization.
• Machine learning models for adaptive, autonomous and secure experimentation.
• Applications across chemistry, manufacturing, electronics processes and all disciplines of engineering.

2. AI for Chemical and Manufacturing Process Optimization

• AI-driven process control and automation.
• Predictive modeling for reaction kinetics and synthesis.
• AI-enhanced quality control and defect detection in manufacturing.

3. Digital Twins for Materials and Processing

• AI-powered virtual models for predictive simulations and real-time data driven decisions.
• Digital twin applications in additive manufacturing and advanced materials design.
• Integration of IoT and AI for smart material processing and monitoring.

4. AI for Sustainability

• AI-driven strategies for de-assembly, recycling, and circular economy initiatives.
• Predictive analytics for lifecycle assessment and environmental impact assesment and reduction.
• Sustainable manufacturing and green processes enabled by edge AI and Robotics.

5. Industry Perspectives and Business Case Studies

• Insights from key industry experts on the adoption of AI in design, processes, and manufacturing.
• Business case analyses from academic leaders in management and technology.
• Challenges in AI adoption and strategies to bridge the gap between academia and industry including ethics, security and resilience.

Submission Guidelines

• Technical Papers: Original research and review articles should follow the journal’s standard format and guidelines.
• Industry Insights & Perspective Articles: Limited to 2-3 pages, these articles will feature insights from industry leaders and academic experts in management, focusing on AI’s role in industrial transformation and the collaboration needed to align academic research with industry requirements.

Timeline

• Call for Papers Announcement: 15 April 2025
• Submission Deadline: 31 October 2025
• Review Process Completion: 31 March 2026
• Publication of Special Issue: June 2026