Artificial intelligence integration in materials science

Abstract

The pervasive integration of Artificial Intelligence (AI) in materials science has transformed the design, functionality, properties and structures of innovative, as well as traditional molecules and crystalline. The new AI-powered laboratories promise to address persistent problems facing humans such cost reduction and productivity improvement in research and development. AI accelerates the discovery of resilient and durable chemical structures capable of providing humans with quality lasting products. More importantly, AI allows researchers to devise new bioactive materials making drugs more potent and affordable. The present research offers readers a succinct comprehensive overview of the progress in Ai application within materials science. Findings demonstrate that AI has improved chemoinformatics, imaging and drug discovery. Moreover, the implementation of AI has resulted in advancing additive manufacturing through transforming 3D printing design and optimization processes. The study documents an increasing trend in developing specific AI tools for advancing materials science such as ChatMOF, MatKG, BioinspiredLLM, MatterGen, and SpectATNet. Notwithstanding the progress in AI’s implementation within materials science, there are important limits to the process represented by data quality, availability and accessibility. Future directions of research in the discipline include developing autonomous research assistant models and laboratories, improving the flexibility and responsiveness of AI systems to mimic human decision-making, and advancing interdisciplinary collaborations to enhance AI-enabled materials discovery.