Understanding mechanical responses of materials under load and other forms of stimulus are crucially important to applications including high performance actuators for soft robotics, lightweight but high strength structural materials, energy absorbers, and energy efficient buildings. With the aim for strong yet predictable/programmable mechanical responses, numerous efforts have been devoted to improving the mechanical properties of materials, through intrinsic fine-tuning of material chemistry and properties, extrinsic geometrical optimizations, and global topological designs. One effective approach is to assemble materials into ordered liquid crystal (LC) phases, in which the properties of individual building blocks can be constructively added up in a controlled manner. LC phases of anisotropic carbon nanomaterials including carbon nanotubes (CNTs) and graphene derivatives are of particular interest due to the excellent physical properties of the nanoscale building blocks. In this Thesis, we focus on the controlled assembly of carbon-based nanomaterials into LC phases, understanding their interactions and ordering, then exploit their applications, including high performance robotic artificial muscles and lightweight high strength load-bearing materials.Specifically, meter-long CNT/liquid crystal elastomer composite filaments are fabricated as light and electrically responsive artificial muscle actuators. Through the molecular interactions between the LC molecules and incorporated nanomaterials, the alignment of LC molecules along the filament long axis is enhanced, the mechanical properties, actuation strength and speed are also boosted. The maximum work capacity of the filament can be comparable to biological muscles, with demonstrated potential integration with different robotic systems. To further improve the performance, especially the response speed of the artificial muscles, strong and ultrafast artificial muscles from reduced graphene oxide (rGO)/conducting polymer composite fibers are created. The wet-spun fibers with well aligned, closely packed rGO sheets can achieve ultra-fast (80 ms) and reversible bending. Yarn actuators based on rGO fiber actuators and non-conductive nylon yarns demonstrate 75 J/kg work capacity and 924 W/kg power density, well exceed those of biological muscles. Further, exploiting the ordering of graphene oxide (GO) lyotropic liquid crystals (LLCs), a new dynamic wrinkling system on freely suspended poly(vinyl alcohol) (PVA) soap films templated by 3D printed wireframes during their liquid-to-solid phase transition is developed and utilized to align GO LLCs on flat and curved surfaces. Via varying the size, thickness, and surface energy of the wireframe, molecular weight, concentration, and thickness of the PVA soap solution, and the environmental conditions, a broad range of pattern are generated. Finally, the GO LLCs alignment guided by wrinkling of PVA soap films are extended to shellular triply periodic minimal surfaces (TPMS) for lightweight and high strength architectured materials. An up to 50 times increase of mass normalized compressive stiffness is observed with less than 20% of weight increase. The better understanding of the interaction, assembly, and ordering of anisotropic carbon nanomaterials – LC systems can potentially pave the way for the next generation of multifunctional smart materials with controllable and programmable intrinsic properties.