4D Printing: Transformative Advances and Multidimensional Applications in Engineering and Additive Manufacturing

This review article comprehensively explores the transformative potential of 4D printing technology across additive manufacturing, art, architecture, and construction. By introducing time as an active design dimension, 4D printing enables materials and structures to adapt, transform, and evolve in response to external stimuli, thereby extending the capabilities of conventional 3D printing. The motivation for this review arises from the rapid evolution of 4D printing materials, processes, and transformation strategies, which have outpaced their systematic consolidation and critical assessment in the existing literature. Unlike prior reviews that primarily emphasize smart material classifications or application‐specific demonstrations, the present work integrates fundamental transformation mechanisms with process‐dependent material behavior and engineering performance considerations. The review critically examines core principles of 4D printing, with particular attention to light‐based vat photopolymerization processes, as well as to material extrusion techniques employing thermoplastic filaments and viscoelastic inks. The influence of process parameters on anisotropy, crystallinity, and functional response is systematically discussed across both 3D and 4D printing contexts. In addition, the review synthesizes emerging applications in interactive art, responsive architectural systems, and adaptive construction components, highlighting how programmed material behavior enables controlled changes in shape, color, or properties in response to environmental stimuli. Beyond application demonstrations, the article provides a critical assessment of unresolved challenges, including durability under cyclic actuation, scalability, repeatability, and the need for standardized characterization frameworks. The review concludes by outlining research directions required to transition 4D printing from experimental prototypes toward reliable, large‐scale, and performance‐driven implementations.