Sri Vaishnavi Thummalapalli

Fabricating thin, fully dense oxide ceramic electrolytes without polymer binders remains a central manufacturing bottleneck for all‐solid‐state lithium batteries (ASSBs). Conventional pressing routes yield (LLZTO) pellets exceeding 500 m in thickness, and the 15 –30 wt.% polymer binders require deposit grain‐boundary carbon during sintering, suppressing ionic conductivity by 10% –40%. Here, we demonstrate binder‐free direct ink writing (DIW) of LLZTO using a ternary ‐terpineol/ethylene glycol/ceramic capillary suspension, in which trace ethylene glycol (2 vol.%) generates a percolating pendular‐bridge network that imparts a recoverable yield stress of Pa and Pa without any polymer. The optimized 65 vol.% (85.9 wt.%) LLZTO ink exhibits pronounced shear‐thinning behavior. Sintering at 1300/4 h yields 95.8% relative density at 254 m thickness with an intrinsic bulk ionic conductivity of 17.3 and a cycle‐median bulk value of 11.8 mS , consistent with the upper range of Ta‐stabilized cubic LLZO.

Inkjet printing enables scalable fabrication of nanomaterial-based devices, but stable droplet formation and reproducible deposition remain challenging for emerging nanosheet inks. In this work, we develop a model-guided inkjet printing framework that monitors and optimizes droplet generation based on fluid properties and nozzle dynamics. Unlike previous MXene inkjet printing studies that primarily rely on empirical parameter tuning and focus on ink formulation or device performance, the proposed framework employs a physics-based analytical model that quantitatively links waveform parameters, fluid properties, nozzle dynamics, and droplet behavior. This predictive approach enables rational waveform design for stable single-droplet ejection, minimizes satellite droplet formation, and reduces the need for extensive experimental calibration. MXene (Ti3C2Tx) nanosheets dispersed in ethanol are used as a representative conductive ink to demonstrate the capability of the optimized printing approach. Under model-guided printing conditions, the system achieves reliable pattern formation and enables fabrication of printed MXene devices that exhibit measurable responses to several gases relevant to agricultural environments. These results demonstrate that analytical-model-guided monitoring and optimization of the inkjet printing process provides a predictive and generalizable strategy for reproducible printing of nanomaterial-based devices.

Hierarchical porous materials enable next‐generation protective, thermal, and biomedical devices by leveraging multiscale architectures with tunable mechanical and thermal properties. Current 3D printing techniques mainly yield periodic lattices and support limited polymer types, restricting patterning possibilities and scalability. Stochastic foam architectures, with heterogeneous and interconnected pores, mimic biological structures for improved energy dissipation and functional adaptability. However, scalable additive manufacturing of such foams remains scarcely explored. Here, a direct ink writing (DIW) strategy couples static mixer‐enabled reactive extrusion and in situ polymerization to manufacture stochastic polyurethane (PU) foams at ambient conditions, eliminating post‐processing. Precise control over pore size (0.2 µm to 1.2 mm), porosity (65–95%), and open‐cell architecture delivers thermal conductivities down to 0.067 W m ⁻¹ K ⁻¹ and elastic recovery exceeding 90% after 5000 cycles. A multi‐agent artificial intelligence framework enables the patterning of spatially organized, bioinspired motifs into print‐ready CAD geometries, resulting in architecturally structured foams with tailored anisotropy and spatial thermal management. Flow‐rate modulation further tunes morphology, optimizing the balance between stiffness and damping. This manufacturing platform integrates stochastic pore formation, AI‐guided patterning, and mechanical–thermal optimization to realize scalable, customizable materials for impact protection, wearable thermotherapy, and adaptive healthcare, advancing digital manufacturing, smart materials, and personalized function.

The disposal of wind turbine blade (WTB) waste poses a significant environmental challenge due to its high volume and complex composition. This study introduces an innovative approach to address this issue by repurposing WTB-derived glass fibers (GF) into high-performance polyacrylonitrile (PAN)-GF composite fibers through a scalable dry-jet wet spinning and forced assembly process. By integrating alternating layers of PAN and PAN-GF, layer thickness was precisely controlled to the micrometer scale, ensuring enhanced GF dispersion and improved orientation through shear stress at layer interfaces. The individual layer thickness in the multilayered PAN-GF fibers decreased progressively with an increasing number of layers, with 32-layered fibers exhibiting comparatively thicker layers, while 256-layered fibers demonstrated significantly thinner layers. The effects of WTB-GF incorporation on the thermal and mechanical properties of PAN fibers were examined using tensile testing and thermogravimetric analysis (TGA). Using GF loadings of 1–4 wt %, the 256-layered composite fibers demonstrated remarkable mechanical improvements, with stiffness (modulus) increasing by 54.7% from 15.10 to 23.37 GPa and tensile strength rising by 27.2% from 521.71 to 663.66 MPa compared to pure PAN fibers. TGA results indicate that increasing the GF content leads to higher residual weight at 900 °C, reflecting enhanced thermal stability and greater char yield. The 256-layered 10PAN-4GF fibers showed the highest residual mass (41.23 wt %), highlighting the significant contribution of GF reinforcement to thermal stabilization. Heat treatment further transformed these precursor fibers into carbonized fibers (CF) with exceptional thermal stability and performance under extreme conditions. This process highlights a sustainable pathway for reusing WTB waste and producing advanced composite fibers, making them ideal candidates for demanding applications such as aerospace and space exploration.

This article explores the environmental sustainability of recycling decommissioned wind turbine blades to produce polyacrylonitrile fiber. By comparing greenhouse gas emissions across various scales of production in different regions, including the US and Europe, the study highlights how cleaner energy grids, such as those in France, can substantially reduce the carbon footprint. The carbonization and graphitization stages, identified as highly energy-intensive, underscore the need for energy-efficient techniques and alternative energy sources. The study reveals significant reductions in greenhouse gas emissions with scalable production, demonstrating US production emissions reduced to 3.89 kg CO₂ equiv/kg fiber and European production to 3.28 kg CO₂ equiv/kg fiber from a lab scale of at least one order of magnitude higher. The findings emphasize the importance of sustainable raw materials, green chemistry, and renewable energy in enhancing the sustainability of carbon fiber production and promoting a circular economy in wind energy.

This study introduces a biomimetic approach to 3D printing multilayered hierarchical porous membranes (MHMs) using Direct Ink Writing (DIW) technology. Fabricated through a fast layer-by-layer printing process with varying concentrations of pore-forming agents, the produced MHMs mimic the hierarchical pore structure and filtration capabilities of natural soil systems. As a result, the 3D-printed MHMs achieved an impressive oil rejection rate of 99.02% and demonstrated exceptional reusability, maintaining a flux recovery ratio of 99.48% even after hours of continuous filtration. Moreover, the 3D-printed MHMs exhibit superior hierarchical porous architecture and mechanical integrity compared to traditional flat sheet single-layered membranes. This study presents a significant advancement for scalable 3D printing of customized multilayer membranes with tailored porosity and high-performance filtration properties. The simplicity, versatility, and cost-effectiveness of the presented manufacturing method offer a pathway for advanced design and on-demand membrane production.

3D printing, also known as additive manufacturing, holds immense potential for rapid prototyping and customized production of functional health‐related devices. With advancements in polymer chemistry and biomedical engineering, polymeric biomaterials have become integral to 3D‐printed biomedical applications. However, there still exists a bottleneck in the compatibility of polymeric biomaterials with different 3D printing methods, as well as intrinsic challenges such as limited printing resolution and rates. Therefore, this review aims to introduce the current state‐of‐the‐art in 3D‐printed functional polymeric health‐related devices. It begins with an overview of the landscape of 3D printing techniques, followed by an examination of commonly used polymeric biomaterials. Subsequently, examples of 3D‐printed biomedical devices are provided and classified into categories such as biosensors, bioactuators, soft robotics, energy storage systems, self‐powered devices, and data science in bioplotting. The emphasis is on exploring the current capabilities of 3D printing in manufacturing polymeric biomaterials into desired geometries that facilitate device functionality and studying the reasons for material choice. Finally, an outlook with challenges and possible improvements in the near future is presented, projecting the contribution of general 3D printing and polymeric biomaterials in the field of healthcare.

As a treatment for the widely spread cardiovascular diseases (CVD), bypass vascular grafts have room for improvement in terms of mechanical property match with native arteries. A 3D‐printed nozzle is presented, featuring unique internal structures, to extrude artificial vascular grafts with a flower‐mimicking geometry. The multilayer‐structured graft wall allows the inner and outer layers to interfere sequentially during lateral expansion, replicating the nonlinear elasticity of native vessels. Both experiment and simulation results verify the necessity and benefit of the flower‐mimicking structure in obtaining the self‐toughening behavior. The gelation study of natural polymers and the utilization of sacrificial phase enables the smooth extrusion of the multiphase conduit, where computer‐assisted image analysis is employed to quantify manufacturing fidelity. The cell viability tests demonstrate the cytocompatibility of the gelatin methacryloyl (GelMA)/sodium alginate grafts, suggesting potential for further clinical research with further developments. This study presents a feasible approach for fabricating bypass vascular grafts and inspires future treatments for CVD.

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.

Additive manufacturing known as 3D printing has transformed the material landscape, with intricate structures and rapid prototyping for modern production. While nanoscale 3D printing has made significant progress, a critical challenge remains in the rapid, high-throughput tailoring of complex nanostructures. Here, we present a 3D printing-facilitated, light-driven assembly technology for rapid surface patterning consisting of complex particle nanonetworks with balanced fabrication resolution and processing scalability. This innovative approach seamlessly integrates top-down 3D printing (i.e., fused deposition modeling (FDM)) of digitally encoded patterns with bottom-up nanoparticle assembly (i.e., plasmonic light-driven techniques). The manufacturing-structure relationship of the generated nanonetworks within macroscale cylindrical patterning is investigated through programmatic modulation of critical processing parameters, including polymer rheology, chain-mode plasmonic resonances, nanoparticle dimensions, and peak optical intensity. The capacity of nanoscale 3D printing with optical adjustment can not only achieve high-resolution patterning but also offer precise control over large-scale geometries for applications in optical sensing.