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Additive manufacturing processes such as 3D printing use time-consuming, stepwise layer-by-layer approaches to object fabrication. We demonstrate the continuous generation of monolithic polymeric parts up to tens of centimeters in size with feature resolution below 100 micrometers. Continuous liquid interface production is achieved with an oxygen-permeable window below the ultraviolet image projection plane, which creates a \"dead zone\" (persistent liquid interface) where photopolymerization is inhibited between the window and the polymerizing part. We delineate critical control parameters and show that complex solid parts can be drawn out of the resin at rates of hundreds of millimeters per hour. These print speeds allow parts to be produced in minutes instead of hours.

A new bioprinting system produces large tissue constructs with enough structural stability for surgical implantation. A challenge for tissue engineering is producing three-dimensional (3D), vascularized cellular constructs of clinically relevant size, shape and structural integrity. We present an integrated tissue–organ printer (ITOP) that can fabricate stable, human-scale tissue constructs of any shape. Mechanical stability is achieved by printing cell-laden hydrogels together with biodegradable polymers in integrated patterns and anchored on sacrificial hydrogels. The correct shape of the tissue construct is achieved by representing clinical imaging data as a computer model of the anatomical defect and translating the model into a program that controls the motions of the printer nozzles, which dispense cells to discrete locations. The incorporation of microchannels into the tissue constructs facilitates diffusion of nutrients to printed cells, thereby overcoming the diffusion limit of 100–200 μm for cell survival in engineered tissues. We demonstrate capabilities of the ITOP by fabricating mandible and calvarial bone, cartilage and skeletal muscle. Future development of the ITOP is being directed to the production of tissues for human applications and to the building of more complex tissues and solid organs.

The increasing demands for efficient and clean energy-storage systems have spurred the development of Li metal batteries, which possess attractively high energy densities. For practical application of Li metal batteries, it is vital to resolve the intrinsic problems of Li metal anodes, i.e., the formation of Li dendrites, interfacial instability, and huge volume changes during cycling. Utilization of solid-state electrolytes for Li metal anodes is a promising approach to address those issues. In this study, we use a 3D garnet-type ion-conductive framework as a host for the Li metal anode and study the plating and stripping behaviors of the Li metal anode within the solid ion-conductive host. We show that with a solid-state ion-conductive framework and a planar current collector at the bottom, Li is plated from the bottom and rises during deposition, away from the separator layer and free from electrolyte penetration and short circuit. Owing to the solid-state deposition property, Li grows smoothly in the pores of the garnet host without forming Li dendrites. The dendrite-free deposition and continuous rise/fall of Li metal during plating/stripping in the 3D ion-conductive host promise a safe and durable Li metal anode. The solid-state Li anode shows stable cycling at 0.5 mA cm−2 for 300 h with a small overpotential, showing a significant improvement compared with reported Li anodes with ceramic electrolytes. By fundamentally eliminating the dendrite issue, the solid Li metal anode shows a great potential to build safe and reliable Li metal batteries.

We present large scale facial model (LSFM)—a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. To build such a large model we introduce a novel fully automated and robust Morphable Model construction pipeline, informed by an evaluation of state-of-the-art dense correspondence techniques. The dataset that LSFM is trained on includes rich demographic information about each subject, allowing for the construction of not only a global 3DMM model but also models tailored for specific age, gender or ethnicity groups. We utilize the proposed model to perform age classification from 3D shape alone and to reconstruct noisy out-of-sample data in the low-dimensional model space. Furthermore, we perform a systematic analysis of the constructed 3DMM models that showcases their quality and descriptive power. The presented extensive qualitative and quantitative evaluations reveal that the proposed 3DMM achieves state-of-the-art results, outperforming existing models by a large margin. Finally, for the benefit of the research community, we make publicly available the source code of the proposed automatic 3DMM construction pipeline, as well as the constructed global 3DMM and a variety of bespoke models tailored by age, gender and ethnicity.

Fish in schooling formations navigate complex flow fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behavior has been associated with evolutionary advantages including energy savings, yet the underlying physical mechanisms remain unknown. We show that fish can improve their sustained propulsive efficiency by placing themselves in appropriate locations in the wake of other swimmers and intercepting judiciously their shed vortices. This swimming strategy leads to collective energy savings and is revealed through a combination of high-fidelity flow simulations with a deep reinforcement learning (RL) algorithm. The RL algorithm relies on a policy defined by deep, recurrent neural nets, with long–short-term memory cells, that are essential for capturing the unsteadiness of the two-way interactions between the fish and the vortical flow field. Surprisingly, we find that swimming in-line with a leader is not associated with energetic benefits for the follower. Instead, “smart swimmer(s)” place themselves at off-center positions, with respect to the axis of the leader(s) and deform their body to synchronize with the momentum of the oncoming vortices, thus enhancing their swimming efficiency at no cost to the leader(s). The results confirm that fish may harvest energy deposited in vortices and support the conjecture that swimming in formation is energetically advantageous. Moreover, this study demonstrates that deep RL can produce navigation algorithms for complex unsteady and vortical flow fields, with promising implications for energy savings in autonomous robotic swarms.

A method for 3D differentiation of human pluripotent stem cells yields brain cortical spheroids with functional neurons and astrocytes. The spheroids can be sliced for imaging and electrophysiological studies. The human cerebral cortex develops through an elaborate succession of cellular events that, when disrupted, can lead to neuropsychiatric disease. The ability to reprogram somatic cells into pluripotent cells that can be differentiated in vitro provides a unique opportunity to study normal and abnormal corticogenesis. Here, we present a simple and reproducible 3D culture approach for generating a laminated cerebral cortex–like structure, named human cortical spheroids (hCSs), from pluripotent stem cells. hCSs contain neurons from both deep and superficial cortical layers and map transcriptionally to in vivo fetal development. These neurons are electrophysiologically mature, display spontaneous activity, are surrounded by nonreactive astrocytes and form functional synapses. Experiments in acute hCS slices demonstrate that cortical neurons participate in network activity and produce complex synaptic events. These 3D cultures should allow a detailed interrogation of human cortical development, function and disease, and may prove a versatile platform for generating other neuronal and glial subtypes in vitro .

Fused Deposition Modeling (FDM) is capable of producing complicated geometries and a variety of thermoplastic or composite products. Thus, it is critical to carry out the relationship between the process parameters, the finished part’s quality, and the part’s mechanical performance. In this study, the optimum printing parameters of FDM using oil palm fiber reinforced thermoplastic composites were investigated. The layer thickness, orientation, infill density, and printing speed were selected as optimization parameters. The mechanical properties of printed specimens were examined using tensile and flexural tests. The experiments were designed using a Taguchi experimental design using a L9 orthogonal array with four factors, and three levels. Analysis of variance (ANOVA) was used to determine the significant parameter or factor that influences the responses, including tensile strength, Young’s modulus, and flexural strength. The fractured surface of printed parts was investigate using scanning electron microscopy (SEM). The results show the tensile strength of the printed specimens ranged from 0.95 to 35.38 MPa, the Young’s modulus from 0.11 to 1.88 GPa, and the flexural strength from 2.50 to 31.98 MPa. In addition, build orientation had the largest influence on tensile strength, Young’s modulus, and flexural strength. The optimum printing parameter for FDM using oil palm fiber composite was 0.4 mm layer thickness, flat (0 degree) of orientation, 50% infill density, and 10 mm/s printing speed. The results of SEM images demonstrate that the number of voids seems to be much bigger when the layer thickness is increased, and the flat orientation has a considerable influence on the bead structure becoming tougher. In a nutshell, these findings will be a valuable 3D printing dataset for other researchers who utilize this material.

A three-dimensional (3D) topological insulator (TI) is a quantum state of matter with a gapped insulating bulk yet a conducting surface hosting topologically protected gapless surface states. One of the most distinct electronic transport signatures predicted for such topological surface states (TSS) is a well-defined half-integer quantum Hall effect (QHE) in a magnetic field, where the surface Hall conductivities become quantized in units of (1/2) e 2 / h ( e being the electron charge, h the Planck constant) concomitant with vanishing resistance. Here, we observe a well-developed QHE arising from TSS in an intrinsic TI of BiSbTeSe 2 . Our samples exhibit surface-dominated conduction even close to room temperature, whereas the bulk conduction is negligible. At low temperatures and high magnetic fields perpendicular to the top and bottom surfaces, we observe well-developed integer quantized Hall plateaux, where the two parallel surfaces each contribute a half-integer e 2 / h quantized Hall conductance, accompanied by vanishing longitudinal resistance. When the bottom surface is gated to match the top surface in carrier density, only odd integer QH plateaux are observed, representing a half-integer QHE of two degenerate Dirac gases. This system provides an excellent platform to pursue a plethora of exotic physics and novel device applications predicted for TIs, ranging from magnetic monopoles and Majorana particles to dissipationless electronics and fault-tolerant quantum computers. Experimentalists have observed the predicted half-integer quantum Hall effect using the topological insulator BiSbTeSe 2 , which exhibits topological surface states at room temperature, with each surface contributing a half quantum of Hall conductance.

For adhering to three-dimensional (3D) surfaces or objects, current adhesion systems are limited by a fundamental trade-off between 3D surface conformability and high adhesion strength. This limitation arises from the need for a soft, mechanically compliant interface, which enables conformability to nonflat and irregularly shaped surfaces but significantly reduces the interfacial fracture strength. In this work, we overcome this trade-off with an adhesion-based soft-gripping system that exhibits enhanced fracture strength without sacrificing conformability to nonplanar 3D surfaces. Composed of a gecko-inspired elastomeric microfibrillar adhesive membrane supported by a pressure-controlled deformable gripper body, the proposed soft-gripping system controls the bonding strength by changing its internal pressure and exploiting the mechanics of interfacial equal load sharing. The soft adhesion system can use up to ∼26% of the maximum adhesion of the fibrillar membrane, which is 14× higher than the adhering membrane without load sharing. Our proposed load-sharing method suggests a paradigm for soft adhesion-based gripping and transfer-printing systems that achieves area scaling similar to that of a natural gecko footpad.

Conservation of cultural heritage is nowadays a very important aspect of our lives. Thanks to such legacy we gain knowledge about our ancestors, methods of production and ways of their life. The rapid development of 3D technology allows for more and more faithful reflection of this area of life. The rich cultural heritage, both tangible and intangible, can be preserved for future generations due to the use of advanced 3d technologies. They provide the means of documenting, recovering and presenting items of cultural heritage. Not only buildings or monuments are taken into account. An important aspect of our culture is intangible cultural heritage (ICH), including acting, crafting or storytelling, passed down from generation to generation. Due to the rapid development of civilisation and the migration of people, this type of culture is often forgotten. That is why the preservation of ICH is an important element of today world. The main aim of this study, on the basis of the gathered papers, is to identify: (1) the general state of use of 3D digital technologies in ICH; (2) the topics and themes discussed; (3) the technologies used in the study; (4) locations of research centres conducting such studies; and (5) the types of research carried out. The methodology consists of the following main steps: defining study questions, searching query development, selection of publications in Scopus, Web of Knowledge and IEEE Xplore, finally the study execution and the analysis of the obtained results. The results show that for ICH the most often used technologies are: 3D visualisation, 3D modelling, Augmented Reality, Virtual Reality and motion capture systems.