Harnessing the Power of Artificial Intelligence in Materials Science: An Overview
Adedotun Adetunla, Esther T. Akinlabi, Tien‐Chien Jen, Samuel-Soma M. Ajibade
Abstract
The integration of artificial intelligence (AI) into the realm of material science has ushered in a new era, by changing the process of material discovery and design. Leveraging advanced computational methods, machine learning algorithms, and predictive modeling, AI accelerates the identification of novel materials with tailored properties. From quantum simulations to high-throughput experimentation, AI-driven techniques enable rapid screening and prediction of material behaviors, significantly reducing the time and resources traditionally required for innovation. This synergy has paved the way for the creation of smart and adaptive materials, responsive to external stimuli and tailored for specific applications across industries. The marriage of AI and material science extends beyond discovery, encompassing efficient process optimization, manufacturing improvements, and the management of vast datasets through materials informatics. Challenges, including ethical considerations, data privacy, and responsible AI practices, must be navigated for sustainable integration. Looking forward, the collaborative potential of AI and material science promises continuous advancements. Ongoing research in machine learning, deep learning, and materials informatics anticipates breakthroughs in material applications, pushing the boundaries of innovation and sustainability. The union of AI and material science not only reshapes the landscape of scientific discovery but also holds the key to unlocking unprecedented opportunities for intelligent materials that will define the technological future.