Applications of molecular dynamics in nanomaterial design and characterization - A review

Abstract

Molecular dynamics (MD) simulations have become game changers in nanomaterial research, providing detailed understanding of how materials behave, are designed, or characterized at the atomic scale. In addition, MD is a powerful method for predicting mechanical, thermal, and electronic properties of nanomaterials in different environments. The aim includes but is not limited to fundamental concepts, state-of-the-art developments, and the use of MD in conjunction with machine learning and quantum mechanics. Herein, we aim to give a comprehensive overview of the contributions of MD to the engineering of nanomaterial properties for catalytic, energy storage, drug delivery and other applications. Using a comprehensive review of literature this review underscores the ability of MD simulation to capture complex phenomena for example, phase transitions, molecular interactions and surface changes. The major strengths of MD (such as intricate modeling of atomic interactions) and weaknesses (e.g., computational needs and experimental validation issues) are highlighted by critical analysis. Recent advances, such as improved multiscale modeling and computational algorithms and real-time simulations, shed light onto MD processes of revolutionizing nanotechnology. In conclusion, the present review highlights the critical role assigned to MD simulations to foster the development of nanosized materials, connecting experimental and theoretical efforts. The MD community is urged to merge their field with emerging technologies, whereby existing issues can be surmounted and innovations towards the design of sustainable, high-performance materials can take place. It is the ultimate "reference work" for those who would like to harness the power that MD has for the future of nanotechnology and showcases unique applications of MD that may revolutionize both science and industry. This review summarizes the latest innovations in MD simulations, ranging from integration of artificial intelligence and real−time modeling to emerging applications in drug delivery, catalysis, and sustainable materials design.