Fabricating polymeric composites with desirable characteristics for electronic applications is a complex and costly process. Digital light processing (DLP) 3D printing emerges as a promising technique for manufacturing intricate structures. In this study, polymeric samples are fabricated with a conductivity difference exceeding three orders of magnitude in various portions of a part by employing grayscale DLP (g‐DLP) single‐vat single‐cure 3D printing deliberate resin design. This is realized through the manipulation of light intensity during the curing process. Specifically, the rational resin design with added lithium ions results in the polymer cured under the maximum UV‐light intensity exhibiting higher electrical resistance. Conversely, sections that are only partially cured retains uncured monomers, serving as a medium that facilitates ion mobility, consequently leading to higher conductivity. The versatility of g‐DLP allows precise control of light intensity in different regions during the printing process. This characteristic opens up possibilities for applications, notably the low‐cost, facile, and rapid production of complex electrical circuits and sensors. The utilization of this technique makes it feasible to fabricate materials with tailored conductivity and functionality, providing an innovative pathway to advance the accelerated and facile creation of sophisticated electronic devices.

The design and engineering of liquid crystal elastomers (LCE) composites for enhanced multifunctionality and responsiveness is highly desired. Here, a hollow LCE (h‐LCE) fiber fabricated via coaxial spinning, enabling the straightforward yet effective creation of functional LCE composites, is reported. Inspired by the fiber‐tubule architecture in skeletal muscles, the hollow fiber features an LCE outer shell for programmable actuation and an inner channel allowing for the integration of a variety of functional media. Thus, the h‐LCE fiber can serve as a versatile platform for multifunctionalities in LCE composites. With this unique design strategy, h‐LCE fibers are fabricated with lengths exceeding 3 meters in the lab with outer and inner diameters as small as 250 mm and 120 µm, respectively. The versatility of these h‐LCE fibers across various applications are further demonstrated, from fast‐response stiffness‐tunable actuators by integrating water flow as triggering media and shape memory polymer (SMP) for enhanced mechanical properties, to electrically driven actuating systems through the incorporation of liquid metal, and actuating light‐guides by combining SMP and PDMS optical fiber. The conception of h‐LCE fiber not only advances the design of multifunctional LCE composites but also paves the way for their application in soft robotics, artificial muscles, and beyond.

Polymer packaging plays a crucial role in food preservation but poses major challenges in recycling and environmental persistence. To address the need for sustainable, high-performance alternatives, we employed a polymer informatics workflow to identify single- and multi-layer drop-in replacements for polymer-based packaging materials. Machine learning (ML) models, trained on carefully curated polymer datasets, predicted eight key properties across a library of approximately 7.4 million ring-opening polymerization (ROP) polymers generated by virtual forward synthesis (VFS). Candidates were prioritized by the enthalpy of polymerization, a critical metric for chemical recyclability. This screening yielded thousands of promising candidates, demonstrating the feasibility of replacing diverse packaging architectures. We then experimentally validated poly(p-dioxanone) (poly-PDO), an existing ROP polymer whose barrier performance had not been previously reported. Validation showed that poly-PDO exhibits strong water barrier performance, mechanical and thermal properties consistent with predictions, and excellent chemical recyclability (∼95% monomer recovery), thereby meeting the design targets and underscoring its potential for sustainable packaging. These findings highlight the power of informatics-driven approaches to accelerate the discovery of sustainable polymers by uncovering opportunities in both existing and novel chemistries. Beyond identifying potential replacements, this work establishes a generalizable framework for navigating vast polymer design spaces under competing performance constraints. The results illustrate how data-driven polymer design can bridge the gap between sustainability concepts and experimentally realizable materials for real-world packaging applications.

Grayscale digital light processing (g-DLP) has emerged as a significant advancement in multimaterial additive manufacturing, providing high precision and versatility in the fabrication of complex, multifunctional structures. By modulating ultraviolet (UV) light intensity at the pixel level, g-DLP enables spatially resolved tuning of mechanical, optical, and electrical properties within a single part using a single resin vat. This approach addresses the traditional limitations of digital light processing (DLP), such as a single set of material properties, while preserving the key features of high resolution, smooth surface quality, and efficient layer-by-layer fabrication. This perspective paper introduces the foundational mechanisms and key technological breakthroughs that have positioned g-DLP as a multimaterial manufacturing technique. A diverse array of applications is discussed, including the fabrication of integrated fiber and matrix composites to achieve enhanced mechanical performance, the precise modulation of optical properties, multicolor printing from a single resin vat, the development of functional electronic components with tailored conductivity, and 4D printing for dynamic, stimuli-responsive systems. By leveraging pixel-level control of material properties, g-DLP not only broadens the scope of design possibilities but also delivers a combination of efficiency, customization, and multifunctionality. It enables the creation of advanced materials and devices for next-generation applications.