In the domain of materials science and engineering, the mechanical properties of metals and alloys play a pivotal role in determining structural stability, wear resistance, and longevity of components. The underlying deformation mechanisms, particularly deformation twinning, significantly influence these properties. Deformation twinning involves the homogeneous shear of atomic layers within crystal lattices, creating distinct twin boundaries that separate regions of mirror-image symmetry. While slip is the predominant deformation mechanism for metals, twinning constitutes a crucial avenue, especially for materials with few independent slip systems. Understanding and characterizing deformation twinning is essential for both fundamental research and practical applications, influencing aspects from work hardening to crack initiation and propagation.

Certain conditions, such as low stacking fault energy, high strain rates, or low temperatures, can significantly promote deformation twinning. This phenomenon enhances a material's strength and ductility, making it a vital factor in material behavior. Deformation twins act as obstacles for dislocation glide, reducing the mean free path of dislocations, commonly referred to as the "dynamic Hall-Petch effect." In the context of steels, twinning-induced plasticity (TWIP) steels exhibit unique behavior, lying above the range classically referred to as the "material banana."

Traditional experimental methods often fall short in capturing the dynamic temporal evolution of twin structures during deformation processes. Molecular dynamics (MD) simulations offer a powerful avenue for investigating these dynamic processes at atomic scales. However, MD simulations have long lacked a suitable tool for systematically identifying and analyzing twins automatically or semi-automatically. To address this gap, this study introduces an innovative algorithm built upon the OVITO platform. This algorithm automates the identification of coherent twin boundaries, establishes connections between related twin boundaries, and tracks the temporal evolution of the identified twin structures. It offers quantifiable data and facilitates detailed investigations into individual twins.

By applying this algorithm to study the deformation behavior of a copper single crystal subjected to shear, the study successfully tracked and analyzed various twin boundaries, providing insights into their genesis and growth over multiple timesteps. The orientation analysis reliably validated twins, showcasing the algorithm's accuracy and utility in elucidating the intricate mechanisms that underlie twinning. This research addresses the critical need for a powerful tool to study deformation twinning through MD simulations, empowering researchers to explore fundamental aspects of twinning and gain deeper insights into material behavior and its implications for mechanical performance.