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Tissue engineering is an interdisciplinary field combining biology, chemistry, and engineering to create implantable structures that support healing and regeneration. Autografts, tissues taken from a patient’s own body, are commonly used due to their high compatibility and minimal disease transmission risk. However, autografts are limited by the small amount of tissue that can be harvested. Allografts, or transplants from one person to another, provide a more natural alternative to synthetic or metal implants, yet their use is constrained by limited donor availability, high rejection rates, and significant operating costs. Although synthetic polymer, ceramic, and metallic implants have gained popularity due to their affordability and durability, they often lead to chronic pain, restricted movement, and eventual reimplantation because of issues like surface wear and reduced lubrication. Advances in artificial intelligence (AI), machine learning (ML), and 3D printing are opening new possibilities in tissue engineering. Researchers are now exploring natural polymers as an alternative to synthetic materials by focusing on the structural complexities and sustainability of native tissues. For example, type I collagen (Col), the most abundant protein in human connective tissues, shows promise as a replacement for titanium in bone tissue engineering due to its excellent mechanical properties, biocompatibility, and ability to support bone growth (osteogenesis). When combined with hydroxyapatite (HAp), Col-HAp composites can closely mimic the natural organic-inorganic structure of bone, providing both the chemical and physical properties needed to promote tissue healing and regeneration. However, the extraction and processing of collagen pose challenges, as they can degrade its natural properties and complicate the 3D printing of implants. This perspective examines the processing, characterization, and manufacturability of Col, its composites, and other robust biomaterials for bone tissue engineering, aiming to replicate the mechanical behavior of human limbs under both static and dynamic conditions. It also explores how AI and ML can enhance the precision and reproducibility of Col composite printing and enable generative scaffold design to foster vascularization, cell viability, and tissue growth. Finally, this work underscores the advancements in novel and customized 3D bioprinting systems designed to address patient-specific requirements, promote higher cell proliferation, and fabricate complex scaffold structures with improved structural properties. 

Abstract Biopolymers and bioinspired materials contribute to the construction of intricate hierarchical structures that exhibit advanced properties. The remarkable toughness and damage tolerance of such multilevel materials are conferred through the hierarchical assembly of their multiscale (i.e., atomistic to macroscale) components and architectures. Here, the functionality and mechanisms of biopolymers and bio‐inspired materials at multilength scales are explored and summarized, focusing on biopolymer nanofibril configurations, biocompatible synthetic biopolymers, and bio‐inspired composites. Their modeling methods with theoretical basis at multiple lengths and time scales are reviewed for biopolymer applications. Additionally, the exploration of artificial intelligence‐powered methodologies is emphasized to realize improvements in these biopolymers from functionality, biodegradability, and sustainability to their characterization, fabrication process, and superior designs. Ultimately, a promising future for these versatile materials in the manufacturing of advanced materials across wider applications and greater lifecycle impacts is foreseen. 

Carbon–carbon (C–C) composites are highly sought-after in aviation, automotive, and defense sectors due to their outstanding thermal & thermo-mechanical properties even surpassing those of alloys and other composites for exterme operations. 

Abstract This paper presents a scalable and straightforward technique for the immediate patterning of liquid metal/polymer composites via multiphase 3D printing. Capitalizing on the polymer's capacity to confine liquid metal (LM) into diverse patterns. The interplay between distinctive fluidic properties of liquid metal and its self‐passivating oxide layer within an oxidative environment ensures a resilient interface with the polymer matrix. This study introduces an inventive approach for achieving versatile patterns in eutectic gallium indium (EGaIn), a gallium alloy. The efficacy of pattern formation hinges on nozzle's design and internal geometry, which govern multiphase interaction. The interplay between EGaIn and polymer within the nozzle channels, regulated by variables such as traverse speed and material flow pressure, leads to periodic patterns. These patterns, when encapsulated within a dielectric polymer polyvinyl alcohol (PVA), exhibit an augmented inherent capacitance in capacitor assemblies. This discovery not only unveils the potential for cost‐effective and highly sensitive capacitive pressure sensors but also underscores prospective applications of these novel patterns in precise motion detection, including heart rate monitoring, and comprehensive analysis of gait profiles. The amalgamation of advanced materials and intricate patterning techniques presents a transformative prospect in the domains of wearable sensing and comprehensive human motion analysis. 

Thein situHF acid etching of Ti₃AlC₂yielded multilayered Ti₃C₂. Sonication delaminated nanosheets, suspended in DI water, post rheological optimization 3D printed using DIW platform to produce conductive patterns of MXene.