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September 28, 2025 HotTopics EFL Bio-3D Printing and Biofabrication 477

These ten studies in Science and Nature outline key future directions for 3D printing, spanning structural materials, novel applications, and sustainable processes.

As top-tier international academic journals, papers published in Nature and Science have long been regarded as important indicators of breakthrough advancements and cutting-edge achievements across various fields. With the first half of 2025 now behind us, EFL has compiled a summary of 3D printing-related research published in these two journals over the past six months.

Among the ten articles published in the main issues of Science and Nature in the first half of 2025, the focus areas include: two on structural innovation, one on high-performance material printing, two on the recycling of printing materials, one on metal 3D printing processes, two on novel 3D printing applications (perovskite solar cells and robot control), one on acoustic 3D printing technology, and one on 3D vascular network path algorithms. To some extent, these achievements are outlining the future development trajectory of 3D printing technology.

I. Science: 3D Printed Architectured Materials with Multi-Locked Networks (PAMs)
A research team from the California Institute of Technology proposed a design concept for 3D printed architectured materials with multi-locked networks (PAMs). The study was published in Science, with Chinese scholar Wenjie Zhou as the author, currently a postdoctoral researcher at Caltech.

II. Science: 3D Printing of High-Performance Thermoelectric Materials

The research team transformed continuous lattice topologies into discrete interlocking structures of ring- or cage-shaped particles, tuning the material's properties by altering particle geometry and connection topology. Additive manufacturing techniques were employed to fabricate PAMs samples, which underwent uniaxial compression, shear, and rheological testing. Results indicated that PAMs exhibit non-Newtonian fluid characteristics under small loads, while under large strains, their behavior resembles that of lattices and foams with nonlinear stress-strain relationships. At the microscopic scale, PAMs can change shape in response to electrostatic charges. This research validates the feasibility of the PAMs design framework, laying the foundation for creating architected materials with tailored mechanical properties and responsive control.

Source: https://doi.org/10.1126/science.adr9713

A team led by Professor Maria Ibáñez from the Institute of Science and Technology Austria (ISTA) and Dr. Shengduo Xu, a Chinese scholar, has addressed these challenges by employing extrusion-based 3D printing to fabricate high-performance thermoelectric materials. The research team developed an ink formulation that ensures the structural integrity of the 3D-printed object and enables effective particle bonding during the sintering process. This approach achieved record-high room-temperature dimensionless figure of merit (zT) values of 1.42 for p-type bismuth antimony telluride [(Bi, Sb)₂Te₃] and 1.3 for n-type silver selenide (Ag₂Se). The resulting thermoelectric cooler achieved a cooling temperature gradient of 50°C in air. Furthermore, this scalable and cost-effective method bypasses energy- and time-intensive steps such as ingot preparation and subsequent machining, offering a transformative solution for producing thermoelectric devices and heralding a new era of efficient and sustainable thermoelectric technology.

Source: https://doi.org/10.1126/science.adn9741

III. Science: Mitigating Porosity Defects in Additive Manufacturing via Magnetic Field Manipulation

This study demonstrates a reproducible and scalable method for fabricating high-performance thermoelectric coolers (TECs) using 3D-printed materials. Via extrusion-based 3D printing, high-performance thermoelectric materials were prepared, achieving room-temperature zT values of 1.42 for p-type (Bi, Sb)₂Te₃ and 1.3 for n-type Ag₂Se. The key to achieving high performance lay in a tailored ink formulation, designed to promote the formation of interparticle interfacial bonding during the removal of the liquid medium for both materials. The resulting high-porosity materials exhibited excellent thermoelectric properties. By integrating the printed thermoelectric materials into a 32-pair device, cooling performance comparable to state-of-the-art thermoelectric coolers was achieved.

Source: https://www.science.org/doi/10.1126/science.ads0426

A research team led by Professor Peter D. Lee from the Department of Mechanical Engineering at University College London and Professor Andrew Kao from the University of Greenwich collaborated on a study. By employing high-speed synchrotron X-ray imaging, combined with comparative experiments and quantitative analysis, they systematically revealed the mechanism by which magnetic fields modulate keyhole stability during laser welding and laser powder bed fusion. The study found that the protrusions caused by flow vortices on the keyhole's rear wall are a key factor leading to keyhole instability, and the application of a transverse magnetic field can suppress this instability by driving secondary thermoelectromagnetic hydrodynamics (TEMHD) flow. The related research was published in Science under the title "Magnetic modulation of keyhole instability during laser welding and additive manufacturing." This work successfully addresses the long-standing lack of clarity regarding the mechanism of static magnetic fields in this field and provides a theoretical basis for optimizing laser welding and additive manufacturing processes. Chinese scholar XIANQIANG FAN is the first author and co-corresponding author of this paper.

In the fields of laser welding and laser powder bed fusion (LPBF), while current research has made progress, it still faces challenges. The understanding of the mechanisms related to magnetic field control is not yet deep, and a lack of direct observation of key processes under magnetic influence limits in-depth investigation into keyhole dynamics and melt pool flow. Although applying magnetic fields can suppress keyhole porosity, the effectiveness varies across different materials and process parameters, and the complex interaction between magnetic fields and material properties is not fully understood.

In the future, further in-depth research is needed on the mechanism of magnetic field action under different materials and process parameters to optimize magnetic field application strategies. Simultaneously, more advanced observation techniques should be explored to overcome current limitations in imaging speed and melt pool size, enabling real-time and precise observation of key processes. This will help establish more comprehensive theoretical models, provide a more solid theoretical foundation for optimizing laser welding and LPBF technologies, promote the continuous development of this field, and expand its application in more complex manufacturing scenarios.

Source: https://www.science.org/doi/10.1126/science.ado8554

IV. Science: Dissociative network design for high-performance photopolymers

A research team led by Professors Tao Xie and Ning Zheng from Zhejiang University has developed a dynamic dissociative photochemistry method. This method utilizes stepwise photopolymerization to form dithioacetal bonds, enabling reversible conversion between the polymer network and photoreactive oligomers, thereby achieving circular 3D printing. This approach not only achieves 100% recycling efficiency but also allows for modular adjustment of the polymer network's backbone, facilitating the production of various high-performance polymer materials. The related work was published in Science under the title "Circular 3D printing of high-performance photopolymers through dissociative network design."

Circular 3D photoprinting and its applications.

The recyclable light-printing material developed in this study effectively addresses the issues of high resin costs and increasing waste in 3D printing. By leveraging the principle of dissociative photochemistry, the research successfully overcomes the contradiction between complete recyclability and high mechanical performance, removing a major obstacle for the practical application of this material. This chemical principle is not limited to dithioacetals and may also extend to other dynamic chemical systems. Moreover, based on the dynamic dissociation equilibrium between the polymer network and its oligomeric fragments, it breaks through the traditional closed-loop recycling model of polymer-monomer conversion, broadening the pathways for closed-loop plastic recycling. In practical applications, this material is particularly suitable for use in dental aligners and sacrificial molds for metal casting, significantly reducing plastic waste while lowering production costs. Overall, this research provides innovative ideas and feasible solutions for the sustainable development of 3D printing materials and is expected to drive green transformation in related industries.

Source:
https://www.science.org/doi/10.1126/science.ads3880

V. 《Science》: Image-Guided Acoustic 3D Printing for Deep Tissues

Professor Wei Gao's team from the California Institute of Technology, in collaboration with multiple institutions, conducted this joint research. They developed an imaging-guided deep-penetration acoustic volumetric printing (DAVP) platform. By utilizing low-temperature sensitive liposomes (LTSLs) loaded with crosslinking agents combined with focused ultrasound, they achieved precise, rapid, and on-demand crosslinking of various functional biomaterials. This platform integrates bubble (GV)-based ultrasound imaging to enable real-time monitoring of the printing process, ensuring accurate positioning and the precision of in-situ crosslinking. The related research, titled "Imaging-guided deep tissue in vivo sound printing," was published in Science. It provides a new and effective approach to addressing the challenges in biological 3D printing and demonstrates significant application potential in areas such as localized drug delivery and tissue replacement.

This study utilizes low-temperature sensitive liposomes (LTSLs) loaded with crosslinking agents to achieve ultrasound-guided in vivo sound printing, enabling the precise, high-speed, and high-resolution fabrication of functional biological structures within deep tissues. The research designed various bioinks, encompassing conductive, drug-loaded, cell-laden, and bioadhesive formulations, employing different crosslinking chemical approaches. Real-time ultrasound imaging ensured accurate targeting and controlled in-situ crosslinking. Both in vitro and in vivo studies confirmed the high biocompatibility of the prepolymers and the printed hydrogels. As a proof of concept, this study successfully performed in vivo printing in mouse bladders and rabbit leg muscles, demonstrating the potential of this technology for targeted therapeutic interventions and tissue replacement.

Source:
https://www.science.org/doi/10.1126/science.adt0293

VI. 《Science》: 3D Printed Laminar Dryers Enable "Breathable" Production of Perovskite Solar Modules

To overcome the aforementioned challenges, a collaborative team including Dr. Zheng Wang, a young faculty member from the College of Civil Engineering and Architecture at Zhejiang Sci-Tech University, Dr. Buyi Yan from Hangzhou Qianshuo Optoelectronics, and Professor Yang Yang from Zhejiang University, developed the Laminar-flow-Assisted Drying (LAD) technology. The team utilized 3D printing to customize LAD structures, simulating the uniform convective drying characteristics of spin-coating processes. By integrating this with slot-die coating, they achieved rapid and uniform drying of 0.79 m² perovskite films. This method addresses issues of solvent retention and thickness inhomogeneity in compressible foam ink during large-area drying, enabling the modules to simultaneously achieve high conversion efficiency (champion module: 15%) and stability (passing three sets of IEC reliability tests).

The related research, titled "3D laminar flow–assisted crystallization of perovskites for square meter–sized solar modules," was published in Science.

This study developed a Laminar-flow-Assisted Drying (LAD) technology, which combines 3D-printed structures with three-dimensional laminar airflow to achieve uniform drying of square-meter-scale perovskite films. By optimizing the internal flow path design of the LAD, the issues of short airflow duration and excessive solvent residue in traditional vacuum flash evaporation were resolved, enabling perovskite solar modules (PSMs) to achieve both 15% full-area efficiency and excellent stability (passing three sets of IEC reliability tests). Outdoor testing demonstrated that in a 0.5 MWp system, PSMs achieved 29% higher annual energy output compared to silicon-based modules, with a first-year degradation rate of <2% and a projected T90 lifetime of 9 years. The study found that the stable laminar flow characteristics of the LAD completely remove high-boiling-point solvents and reduce film defects, while its temperature coefficient advantage (-0.144%/°C) allows it to maintain high power generation efficiency in high-temperature environments. This technology enables the translation of laboratory efficiency to large-scale production, providing critical process support for the commercialization of single-junction perovskite modules.

Source:
https://www.science.org/doi/10.1126/science.adt5001

VII. 《Science》: Rapid Prototyping Technology for 3D-Printed Cardiac Vascular Networks

Currently, a major challenge in human large-scale biofabrication of organs is inadequate vascularization and perfusion, particularly the extreme difficulty in designing and printing vascular networks capable of sufficient perfusion for arbitrarily complex geometries. Existing methods, such as lattice-based designs, struggle to replicate natural vascular topology and hemodynamics, failing to meet the metabolic demands of clinically relevant cell densities. Meanwhile, algorithms like Constrained Constructive Optimization (CCO) have limitations including long construction times, limited ability to handle non-convex shapes, and an inability to predict multi-scale hemodynamics.

To address this, a team led by Professors Mark A. Skylar-Scott and Alison L. Marsden from Stanford University introduced a model-driven design platform. This platform integrates the CCO method, multi-fidelity computational fluid dynamics simulations, and 3D bioprinting technology. It enables the rapid generation of organ-scale synthetic vascular networks, overcoming the efficiency and geometric adaptability issues of existing algorithms, and enhances cell viability within biofabricated tissues.

The related research, titled "Rapid model-guided design of organ-scale synthetic vasculature for biomanufacturing," was published in Science on June 12, 2025.

This study demonstrates that the future of engineering organ-scale tissues relies on robust software infrastructure to design and validate vascular networks based on physics-driven functional objectives. The research presents a comprehensive model-driven pipeline that efficiently generates vasculature within arbitrary geometries, creating watertight models suitable for biomanufacturing and digital twins for advanced multi-fidelity hemodynamic simulations. Although the study also proposes a method for biomanufacturing perfusable vascular trees, constructing large, complex trees with smaller diameter vessels remains slow, and printing inaccuracies may lead to discontinuities or blockages that impede perfusion. In the long term, engineered tissues are expected to replace damaged or diseased organs in patient-specific interventions, and validating such biofabricated constructs will require simulation-optimized designs prior to resource-intensive manufacturing. The model-driven pipeline developed in this study can create complex synthetic vascular models within minutes on standard computing hardware, expanding the potential for broader hemodynamic analysis and design optimization in future applications of synthetic vascular structures for biomanufacturing and patient-specific modeling.

Source:
https://www.science.org/doi/10.1126/science.adj6152

VIII. 《Nature》: New Breakthrough in Degradable Plastics
Traditional thermosetting materials are derived from petroleum and are difficult to recycle. Existing methods for preparing degradable cross-linked polymers are often complex, resource-intensive, and insufficient for replacing conventional materials. A research team from Cornell University, USA, published a paper in Nature. They utilized the bio-based monomer 2,3-dihydrofuran (DHF) to prepare degradable thermosets via orthogonal polymerization. Through ring-opening metathesis polymerization and cationic polymerization experiments, they controlled reaction conditions to produce materials with diverse properties that are degradable and recyclable. This research validates the feasibility of using DHF to produce such materials, offering a new direction for the development of thermosetting materials. In the future, this may promote their application in fields like 3D printing, contributing to sustainable development.

Source: https://doi.org/10.1038/s41586-024-08386-w

IX. 《Nature》: Modular Chiral Origami Metamaterials

Mechanical metamaterials are macroscopic structures with specific geometric arrangements that exhibit unusual mechanical properties and deformation modes. Chiral metamaterials can achieve special deformation effects such as strain-twist coupling. However, existing metamaterials face challenges including coupled dual motions, an inability to independently control them, and limited deformation (strain ≤ 2%). A team led by Professor Glaucio H. Paulino from Princeton University constructed modular chiral metamaterials composed of auxetic planar tessellations and origami-inspired pillar arrays, achieving decoupled actuation. This structure can exhibit responses not found in nature: they twist under compression and compress when twisted. This design can be used to create materials for various applications, including thermal regulation, robotics, and packaging.

The related research, titled "Modular chiral origami metamaterials," was published in Nature. The first author of this study is Chinese scholar Tuo Zhao, who earned his bachelor's degree from Dalian University of Technology and is currently a postdoctoral researcher at Princeton University.

This study explores modular chiral metamaterials capable of limited multimodal deformations—such as twisting, contraction, and height variation—under single-degree-of-freedom actuation. The multimodal deformations are associated with the non-rigid origami behavior of the Kresling pattern and the modular nature of chiral origami. This super-modular system enables reconfigurable multistability, tunable load capacity, scalability, and multi-physics integration. The research outcomes can be applied to areas such as thermal regulation, elucidate theoretical concepts like mechanical hysteresis, and extend to interdisciplinary studies, such as on-demand programmed assembly, deformation, and performance control for microrobots.

Source:
https://doi.org/10.1038/s41586-025-08851-0

X. 《Nature》: A General Control Method for 3D-Printed Heterogeneous Robots Using Deep Network-Inferred Visual Motion Jacobian Fields

In the field of robotics, imitating the complex structures and functions of natural organisms has long been a challenge. While modern manufacturing technologies have expanded hardware feasibility, bio-inspired robots are often soft or multi-material, lack sensing capabilities, and exhibit material properties that change with use, making traditional modeling and control methods difficult to apply.

A collaborative team from the MIT Computer Science and Artificial Intelligence Laboratory, led by Professors Sizhe Lester Li and Vincent Sitzmann, proposed a method that uses deep neural networks to map robot video streams to visual motion Jacobian fields. This approach enables robot control using only a single camera, independent of the robot's material, actuation, or sensing characteristics, and is trained self-supervised by observing the execution of random commands. The work successfully controlled robots with diverse actuation methods, materials, and costs, achieving precise closed-loop control and recovering their causal dynamic structure. The related findings, titled "Controlling diverse robots by inferring Jacobian fields with deep networks," were published in Nature.

Source:
https://doi.org/10.1038/s41586-025-09170-0