Molecular dynamics simulations in biomaterials science: Atomistic modeling across bioactive glasses and ceramics, polymers, metals and composites

Abstract

Over the last decade, molecular dynamics (MD) simulations have become an important tool in biomaterials research by linking atomic-scale interactions to macroscopic biological and mechanical performance. This review examines the application of MD across major biomaterial classes, including bioactive glasses and ceramics, polymers and hydrogels, metallic biomaterials, composites, and biological interfaces. For inorganic biomaterials, MD has clarified structure-property relationships, ion transport, hydration, and early dissolution processes. For polymers and hydrogels, it has provided insight into chain conformation, swelling, degradation, crosslinking, and responses to physiological environments. In metallic systems and composites, MD has helped explain interfacial adhesion, load transfer, deformation mechanisms, and corrosion-related behavior, while at biointerfaces it has revealed key aspects of protein adsorption and membrane interactions. This review summarizes the recent advancements in the methods for studying the properties of biomaterials through computer simulation and, specifically, highlights the latest developments in the field of reactive molecular dynamics (rMD). This class of methodologies has developed various schemes beyond the traditional view of materials as being represented by a fixed topology (the arrangement of the atoms), including the use of multiple surfaces within the same framework (multisurface reactions) and different schemes to accelerate the polymer crosslinking. Examples of these strategies encompass the use of template-based reactions and coarse-grained or multiscale approaches to create models, along with using machine-learning techniques to create potentials. All of these new methodologies increase the range of chemical, time, and length scales accessible to simulations and increase the ability to predict how a biomaterial will dissolve, mineralize, crosslink, degrade and respond dynamically at the interface with another one. Overall, these developments show that MD is evolving from a mainly interpretive technique into a predictive framework for the rational design and optimization of next-generation biomaterials.