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At least 37 records · Page 2

Fabrication of a novel 3D-printed perfusion bioreactor for complex cell culture models

We introduce a novel fabrication method for developing a 3D-printed perfusion bioreactor (3D-PBR) to facilitate the in situ growth and differentiation of human bone marrow (BM)-derived mesenchymal stem cells (MSCs) while enabling coculture with vascular cells. To recapitulate human physiology, in vitro platforms must incorporate several key features of their native target organ. This often entails a supportive 3D architecture for growing and differentiating multiple human cell types in situ under perfusion. Other essential characteristics include reproducibility, ease of customization, and biocompatibility. Our 3D-PBR combines these features and was fabricated using a biocompatible resin-based polymer, which was 3D-printed, followed by the addition of a permeable membrane to create a coculture microenvironment. MSCs were encapsulated in a collagen-fibrin gel alongside human endothelium within the 3D-PBR. The physical cues that our 3D-PBR provided facilitated the differentiation of MSCs into specific lineages, such as adipocytes and osteoblasts. Immunohistochemistry images demonstrated that cells grown in the 3D-PBR exhibited more physiologically relevant BM perivascular niche markers compared to static culture models. Our method utilizes emerging 3D printing techniques and alternative materials, departing from traditional PDMS-based soft lithography. These advancements in fabrication further enhance in vitro platforms for diverse cell culture models and vascular permeability assays.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of a Hybrid Domain Overlapping Coupling Between SAM and CFD Against the TALL-3D Transients

The System Thermal Hydraulics (STH) code SAM has been coupled to the Computational Fluid Dynamics (CFD) code Simcenter STAR-CCM+ utilizing a hybrid domain overlapping method with an explicit coupling in time. The coupling aims to extend the STH code’s applicability to scenarios where local momentum and energy transfers are important yet difficult for STH codes to capture, such as three-dimensional (3D) mixing. The coupling method’s numerical stability was verified in the past against two closed-loop configurations, and it was validated against a double T-junction experiment with 3D scalar mixing. In the present work, the coupling method is validated against the TALL-3D STH/CFD coupling benchmark facility. TALL-3D is a three-legged, liquid-metal facility with a large, pool-type enclosure (test section) that exhibits 3D flow effects to be modeled by a CFD code. The rest of the system exhibits approximately 1D behavior well-predicted by an STH code. First, the present STAR-CCM+ CFD model of the 3D test section is validated against experimental data. Then, the SAM-STARCCM+ coupled model is validated against six different TALL-3D steady states, including SAM standalone model results for comparison. Lastly, the SAM-STARCCM+ coupled model is validated against two TALL-3D transients, one exhibiting flow reversal in the test section and one exhibiting nonlinear, Limit Cycle Oscillations (LCO). For the first transient, the SAM-STARCCM+ coupled model properly predicts an increase in the test section’s inlet temperature during flow reversal, and this is not predicted by the SAM standalone model. Following flow reversal, the SAM-STARCCM+ coupled model better-predicts the initial flow recovery and following oscillations as the system approaches a final natural circulation state. For the second transient, no true final steady state is observed due to LCO. Neither the SAM-STARCCM+ coupled model nor the SAM standalone model can perfectly capture the experiment’s changing oscillation frequency during the transient. However, the SAM-STARCCM+ coupled model does reproduce the oscillatory feedback observed in the system. This is a significant achievement as the SAM-STARCCM+ coupled model only uses an explicit coupling in time, as opposed to a semi-implicit coupling. In comparison, previous STH/CFD coupling efforts of the TALL-3D facility required semi-implicit coupling to obtain similar results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A RELAP5-3D Model of the Lobo Lead Loop

The goal of our research is to build upon the capability of RELAP5-3D to model molten lead systems. Molten lead has several potential uses in future advanced reactors like the lead fast reactor or fusion reactors that utilize dual-coolant lead lithium blankets. This potential for use in future generations of reactors highlights the necessity to develop molten lead models to ensure that they can accurately predict the thermohydraulic behavior. We have developed a RELAP5-3D model of the Lobo Lead Loop facility, located at the University of New Mexico, to verify the accuracy of RELAP5-3D via comparison to existing computational fluid dynamics results and analytical calculations. It was found that RELAP5-3D accurately calculated radiative heat transfer (within < 1%) when compared to theoretical calculations. In addition, pressure drop calculations done in RELAP5-3D demonstrated reasonable agreement within 20 kPa, mostly within ~7-15%, when compared to the computational fluid dynamics model of the facility developed by the University of New Mexico, and captured the dependence of pressure drop on flow velocity accurately. Finally, a hypothetical loss of flow transient was imposed on the RELAP5-3D model to determine the feasibility of performing a similar experiment with the Lobo Lead Loop. It was found that such an experiment could be possible as the RELAP5-3D model indicated that the temperatures of the fluid would not exceed limiting temperatures of the structure (1658 K) nor the maximum temperature of the electromagnetic pump inlet (823 K). Although there is not experimental data to begin validation, the model will be readily available for future validation studies when the experimental data is generated, especially as the model continues to evolve over time. Furthermore, the results so far demonstrate a promising first step in the verification/validation of the RELAP5-3D model of the Lobo Lead Loop.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗

Geometry-complete diffusion for 3D molecule generation and optimization

Abstract Generative deep learning methods have recently been proposed for generating 3D molecules using equivariant graph neural networks (GNNs) within a denoising diffusion framework. However, such methods are unable to learn important geometric properties of 3D molecules, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which notably hinders their ability to generate valid large 3D molecules. In this work, we address these gaps by introducing the Geometry-Complete Diffusion Model (GCDM) for 3D molecule generation, which outperforms existing 3D molecular diffusion models by significant margins across conditional and unconditional settings for the QM9 dataset and the larger GEOM-Drugs dataset, respectively. Importantly, we demonstrate that GCDM’s generative denoising process enables the model to generate a significant proportion of valid and energetically-stable large molecules at the scale of GEOM-Drugs, whereas previous methods fail to do so with the features they learn. Additionally, we show that extensions of GCDM can not only effectively design 3D molecules for specific protein pockets but can be repurposed to consistently optimize the geometry and chemical composition of existing 3D molecules for molecular stability and property specificity, demonstrating new versatility of molecular diffusion models. Code and data are freely available on GitHub .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

RELAP5-3D validation studies based on the High Temperature Test facility

In the spring and summer of 2019, experiments were conducted at the High Temperature Test Facility (HTTF) that form the basis of an upcoming high-temperature gas-cooled reactor (HTGR) thermal hydraulics (T/H) benchmark. HTTF is an integral effects test facility for HTGR T/H modeling validation. This paper presents RELAP5-3D models of two of those experiments: PG-27, a pressurized conduction cooldown (PCC); and PG-29, a depressurized conduction cooldown (DCC). These models used the RELAP5-3D model of HTTF originally developed by Paul Bayless as a starting point. The sensitivity analysis and uncertainty quantification code, RAVEN was used to perform calibration studies for the steady-state portion of PG-27. Here we developed four PG-27 calibrations based on steady-state conditions. These calibrations all used an effective thermal conductivity equal to 36 % of the measured thermal conductivity, but they differed with respect to the frictional pressure drops and radial conduction models. These models all captured the trends in steady-state temperature distributions and transient temperature behavior well. All four calibrations show room for improvement in predicting the transient temperature rise. The smallest error in temperature rise during the transient was a 21 % underprediction, and the largest was a 48 % underprediction. The errors in transient temperature rise are largely a result of a mismatch in power density between the RELAP5-3D model and the experiment due to the location of active heater rods along the boundary between heat structures in the model. The best of these calibrations was applied to PG-29 to model the DCC. Once again, temperatures during the transient were underpredicted but trends in temperature were captured. The RELAP5-3D model captured trends in the data but could not reproduce measured temperatures exactly. This result is not attributed to deficiencies in the experimental data or to RELAP5–3D itself. Rather, this result likely arises due to the some of the assumptions and decisions made when the RELAP5-3D model was first developed, prior to the execution of HTTF experiments. An agreement in prediction of temperature trends but challenges reproducing HTTF temperatures within measurement uncertainty is consistent with previous analyses of HTTF in the literature. Future RELAP5-3D validation activities centered around HTTF may be able to provide greater insight into the code’s capabilities for HTGR modeling with a more finely nodalized model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring strain rate effects upon 3D materials using high speed in situ X-ray tomoscopy

Cellular materials are ubiquitous in our modern society. They may be stochastic gas-blown foams (e.g., polyurethane), foamed starches (e.g., cereals), or, in this case, 3D printed microlattices. Failure in these materials is often driven by surface or sub-surface defects, which may be nucleated at a surface roughness, an interior void, or inclusion interfaces that may not be typically observable. Obfuscating our understanding further, bulk materials are known to exhibit strain-rate-dependent mechanical response, making a subsurface understanding of damage even more critical. For the first time, an in situ uniaxial mechanical loading stage that simultaneously rotates specimens up to 18 Hz was fielded at a synchrotron for 3D tomographic imaging. This capability opens a plethora of materials science opportunities to explore strain rate effects in materials and examining deformation, fracture, and delamination’s (in composites) for a complete 3D picture (movie) of material response. We demonstrate the deformation of 3D printed polymer lattice structures, of three different material types, at 0.25, 1.1, and 2.2 s −1 strain rates. We successfully imaged the 3D deformation of these materials and can directly compare the same printed structure to the three material types at three strain rates, all in 3D. Material point method simulations were applied to one of the materials to better understand the role of voids on the 3D printed structure’s performance.

36 MATERIALS SCIENCE↗

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗

Experiments in 3D Printing Electric Motors

This paper catalogues a series of experiments we conducted to explore how to 3D print a DC electric motor. The individual parts of the electric motor were 3D printed but assembled by hand. First, we focused on a rotor with soft magnetic properties, for which we adopted ProtoPasta TM , which is a commercial off-the-shelf PLA filament incorporating iron particles. Second, we focused on the stator permanent magnets, which were 3D printed through binder jetting. Third, we focused on the wire coils, for which we adopted a form of laminated object manufacture of copper wire. The chief challenge was in 3D printing the coils, because the winding density is crucial to the performance of the motor. We have demonstrated that DC electric motors can be 3D printed and assembled into a functional system. Although the performance was poor due to the wiring problem, we showed that the other 3D printing processes were consistent with high performance. Nevertheless, we demonstrated the principle of 3D printing electric motors.

3D printed motor↗

Material property characterization of 3D printed polypropylene wood plastic composites

Abstract Wood flour (WF) at 10 wt.% and 20 wt.% loadings was used as a reinforcing filler to enhance the applicability of polypropylene (PP) for 3D printing. After performing printability tests of PP wood plastic composites (WPCs), the mechanical properties of both injection‐molded and 3D‐printed PP WPC specimens were explored. Test specimens were prepared from 3D printed hexagons for analyzing the mechanical properties. Adding WF to neat PP increased the storage modulus and the glass transition temperature while decreasing the degree of crystallinity and the coefficient of thermal expansion, while enhancing the printability of neat PP. The tensile strength, tensile modulus of elasticity, flexural strength, and flexural modulus of elasticity of injection‐molded neat PP improved by up to 21%, 59%, 30%, and 56%, respectively, with 20 wt.% WF. However, the impact strength of injection‐molded neat PP decreased by 85%, with 20 wt.% WF. After 3D printing, the tensile strength and tensile modulus of elasticity of printed neat PP increased by up to 84% and 60%, respectively, with 20 wt.% WF. The flexural strength and flexural modulus of elasticity of neat printed PP remained unchanged compared to those of PP filled with 20 wt.% WF, while the impact strength decreased by 87%. Highlights WF was used as a reinforcement in polypropylene designed for 3D printing A pilot‐scale, pellet‐fed 3D printer was used to print hollow hexagons, and then test specimens were fabricated from these hexagons for mechanical properties The tensile and flexural properties of 3D printed neat polypropylene improved, while the impact strength decreased after adding 20 wt.% WF to the neat PP.

Hwang, Sungjun↗

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗

A Deep, High-angular-resolution 3D Dust Map of the Southern Galactic Plane

We present a deep, high-angular-resolution 3D dust map of the southern Galactic plane over 239° < l < 6° and ∣ b∣ < 10° built on photometry from the DECaPS2 survey, in combination with photometry from VISTA Variables in the Via Lactea, the Two Micron All Sky Survey, and “Unofficial” Wide-field Infrared Survey Explorer and parallaxes from Gaia Data Release 3 where available. To construct the map, we first infer the distance, extinction, and stellar types of over 700 million stars using the brutus stellar inference framework with a set of theoretical MESA Isochrone and Stellar Tracks (MIST) stellar models. Our resultant 3D dust map has an angular resolution of 1′ , roughly an order of magnitude finer than existing 3D dust maps and comparable to the angular resolution of the Herschel 2D dust emission maps. We detect complexes at the range of distances associated with the Sagittarius-Carina and Scutum-Centaurus arms in the fourth quadrant, as well as more distant structures out to a maximum reliable distance of d ≈ 10 kpc from the Sun. The map is sensitive up to a maximum extinction of roughly A V ≈ 12 mag. We publicly release both the stellar catalog and the 3D dust map, the latter of which can easily be queried via the Python package dustmaps. When combined with the existing Bayestar19 3D dust map of the northern sky, the DECaPS 3D dust map fills in the missing piece of the Galactic plane, enabling extinction corrections over the entire disk ∣b∣ < 10°. Our map serves as a pathfinder for the future of 3D dust mapping in the era of LSST and Roman, targeting regimes accessible with deep optical and near-infrared photometry but often inaccessible with Gaia.

Milky Way galaxy↗

Design and scale-up of 3D printed bat houses with biomass-derived polymer composites

Biomass (e.g., pine sawdust, especially high–ash content pine sawdust) is commonly disposed of as waste. Combining biomass with polymers to make composite feedstocks for 3D printing has been explored as a method to reduce or repurpose the biomass waste. Although not all biocomposite properties are known, the wood-based polylactic acid (PLA) composite has promising qualities for applications in ecological settings. In this work, pine wood–PLA composite feedstock was used to 3D print supplemental roost structures for endangered tree-roosting bats, which often face a paucity of suitable naturally occurring roosts. This material combination was selected because it is estimated to degrade faster than the synthetic material systems that are used widely in supplemental bat roosting structures to aid in the conservation of tree roosting bats. The layered, rough surface created by the 3D printing process serves as a surface that bats can grip while roosting. Computer-aided design (CAD) models were generated based on natural roost structures, and a full-size bat house was successfully additively manufactured using a pellet-fed large-scale 3D printing system. The 3D printed hexagon exhibited a tensile strength of 22–23 MPa and a Young’s modulus of 3202–3218 MPa in the x-direction. It has been demonstrated that the 3D printed bat house can be installed on a tree in a stable fashion. This successful demonstration of a bat roost manufactured using a bioderived composite should promote its use in other fish and wildlife structures and broader industrial applications such as construction and automobiles.

3D printing↗

RELAP5-3D Capabilities for High-Temperature Gas-Cooled Reactor Analysis

RELAP5-3D is the premier systems thermal-hydraulic code in the world. The code has been used significantly for high-temperature gas-cooled reactor (HTGR) analyses over the last 10 years, but there has not been a comprehensive summary of RELAP5-3D capabilities and methods for HTGR modeling. In this paper, we provide a guide for how novice users can build models for prismatic HTGRs. This guide includes best practices for developing heat structures and setting up radiation and conduction heat transfer. We also provide a summary of relevant validation studies. These studies are divided into three categories: separate effects tests, integral effects tests, and nuclear reactor studies. We present a comprehensive review of RELAP5-3D HTGR applications for reactor modeling over the last 10 years. These applications include work for the Modular High-Temperature Gas-Cooled Reactor benchmark, design activities for a prismatic HTGR as part of the U.S. Department of Energy’s Advanced Demonstration and Test Reactor Options Study, and studies performed to design gas-cooled microreactors. Following the comprehensive literature review, we present a gap analysis highlighting capabilities of RELAP5-3D that are available and missing for a complete analysis of HTGR thermal hydraulics. We also discuss the limitations of existing code capabilities and potential improvements that could improve analyses. Current research efforts have yet to fully validate RELAP5-3D for a prismatic HTGR analysis; however, some of this is attributable to confounding factors in the available experimental data as opposed to code capabilities. In conclusion, this paper presents the most comprehensive review to date on RELAP5-3D capabilities, limitations, and applications for HTGR analysis.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Biochar–polymer composites for 3D printing: a review

Biochar, a bio-based co-product of biofuel production via thermochemical conversion, holds potential as a filler for polymer composites to reduce costs, improve thermomechanical properties, and aid in environmental remediation. 3D-printed biochar composites have received growing interest over the past few years but have experienced difficulties such as poor layer adhesion and nozzle clogging. Currently, no literature review examines 3D-printed biochar composites and related biochar properties in-depth. This work summarizes and discusses recent studies on 3D-printed polymer and biochar composites and examines their mechanical, thermal, and additional properties that result from each study. Technical challenges in printability, such as nozzle clogging from particle size and biochar aggregation, are also discussed. Furthermore, this work discusses the variability of biochar properties resulting from the pyrolysis conditions and feedstock choice in relation to potential 3D printing outcomes. In particular, several studies reported that high lignin feedstocks could be candidates for 3D printing. The post-processing approaches of the biochar via physical and chemical methods are also introduced. Ball milling appears to hold the most promise for physical treatments due to its tunability of particle size, surface area, and functional groups, while chemical treatments with acids or alkalis are used to tailor biochar porosity and wettability. Overall, it was determined that future research needs to be done relating biochar production and post-processing methods to resulting 3D printing parameters as the number of studies is limited.

Day, Rachel [Auburn University, Auburn, AL]↗

Directional finite difference method for directly solving 3D gyrokinetic field equations with enhanced accuracy

The gyrokinetic (GK) field equation is a three-dimensional (3D) elliptic equation, but it is often simplified to a set of two-dimensional (2D) equations by assuming that the field does not vary along a specific direction. However, this simplification can introduce inevitable 0th-order numerical errors, as nonlinear mode coupling in toroidal geometry can produce undesirable harmonic modes that violate the assumption. In this work, we propose a novel directional finite difference method (FDM) with a local coordinate transformation to better resolve the target field of interest. The directional FDM can accurately solve 3D GK field equations without simplifications, which can overcome the limitations of conventional methods. The accuracy and efficiency of different FDMs are analyzed in great detail for a variety of geometries, from simple 2D Cartesian coordinates to realistic 3D curvilinear coordinates. The 0th-order numerical errors of simplified 2D GK equations were found to be more problematic for low-harmonic modes and low aspect ratio geometries such as spherical tokamaks. On the other hand, the directional 3D FDM can accurately resolve a much wider range of harmonic modes aligned to the direction of interest, including the low-harmonic modes. In conclusion, we demonstrate that the directional 3D FDM is a highly effective algorithm for solving the 3D GK field equations, achieving accuracy improvements of 10 to 100 times or more, particularly for low-harmonic modes in spherical tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

3D interface size effects on slip transfer in Ti/Nb nanolaminates

Two-phase nanolaminates are well-renowned for achieving extraordinarily high strengths but at the sacrifice of reduced toughness and strain to failure. Recently ”thick” interfaces, or so called 3D interfaces, in Cu/Nb nanolaminates were experimentally shown to improve both of these mechanical properties. Here, in this work, we study the effect of 3D interfaces in the hexagonal close packed (HCP)/body centered cubic (BCC) Ti/Nb nanolaminate system. Nanoindentation hardness testing suggests increased strength with the introduction of a 3D Ti–Nb interface and a positive size effect with increases in 3D interface thickness from 5 nm to 20 nm. To understand this effect from a single dislocation perspective, we present a phase-field dislocation dynamics (PFDD) model for multi-phase HCP/BCC systems. We employ the model to simulate stress-driven transfer of single dislocations across 3D Ti/Nb interfaces of various thicknesses. Our results show that the critical stress for slip transfer increases with the thickness of the interface. This positive size effect is stronger for transfer from basal or prismatic dislocations in the Ti layer to 110$\langle$111$\rangle$ dislocations in the Nb layer than the reverse. For this Ti/Nb system, a critical thickness of 2 nm is identified at which the asymmetry in slip transfer is minimized. This work showcases 3D interfaces as a beneficial microstructure modification to strengthen as well as reduce anisotropy in nanocrystalline materials containing HCP phases.

Dislocations↗

3D nanolithography with metalens arrays and spatially adaptive illumination

The growing demand for advanced materials, miniaturized devices and integrated microsystems calls for the reliable fabrication of complex, multiscale, three-dimensional (3D) architectures, a need increasingly addressed through light-based and laser-based processes. However, owing to the field-of-view (FOV) limitations of conventional imaging optics, existing 3D laser nanofabrication techniques face fundamental challenges in throughput, proximity error and stitching defects on the path to scaling. Here, in this study, we present a scalable 3D nanofabrication platform that uses a metalens-generated focal spot array to parallelize two-photon lithography (TPL) beyond centimetre-scale write field areas. Metalenses are ideally suited for producing submicron-scale focal spots for high-throughput nanolithography, as they uniquely feature large numerical apertures (NAs), immersion media compatibility and large-scale manufacturability. We experimentally demonstrate a printing system that uses a 12-cm 2 metalens array to produce more than 120,000 cooperative focal spots, corresponding to a throughput exceeding 10 8 voxels s −1 . By programmatically patterning the focal spot array using a spatial light modulator (SLM), an adaptive parallel printing strategy is developed for precise greyscale linewidth modulation and choreographed printing of semiperiodic and fully aperiodic 3D geometries. We demonstrate parallel printing of replicated microstructures (>50 M microparticles per day), centimetre-scale 3D architectures with feature sizes down to 113 nm, and photonic and mechanical metamaterials. This work demonstrates the potential of 3D nanolithography towards wafer-scale production, showing how TPL could be used at scale for applications in microelectronics, biomedicine, quantum technology and high-energy laser targets.

Materials science↗