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A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching
Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.
Designing 3D Printed Micro-Actuators for Functionalized Fiber Optics.
Abstract not provided.
Design of 3D eye-safe middle range vibrometer
Laser Doppler Vibrometer and Range Meter (3D-MRV) is designed for middle range distances [1–100 meters]. 3D-MRV combines more than one laser in one device for a simultaneous real time measuring the distance and movement of the targets. The first laser has a short pulse (t∼30psec) and low energy (E∼200nJ) for distance measurement and the second one is a CW (continuous wave) single frequency laser for the velocity measurement with output power (P∼30mW). Both lasers perform on the eye-safe wavelength 1.5 μm. 3D-MRV uses the same mono-static optical transmitting and receiving channel for both lasers including an output telescope and a scanning angular system. 3D-MRV has an optical polarization switch to combine linear polarized laser beams from two lasers into one optical channel. The laser beams from both lasers by turns illuminate the target and the scattered laser radiation is collected by the telescope on a photo detector. The electrical signal from photo detector is used for measuring the distance to the target and its movement. For distance measurement the time of flight method is employed. For targets movement the optical heterodyne method is employed. The received CW laser radiation is mixed on a photo detector with the frequency-shifted laser radiation that is taken from CW laser and passed through an acousto-optic cell. The electrical signal from a photo detector on the difference frequency and phase has information about movement of the scattered targets. 3D-MVR may be used for the real time picturing of vibration of the extensive targets like bridges or aircrafts.
Systems and methods for automated nozzle design and 3D printing
A present disclosure relates to a system for automatic design and manufacturing of 3D printing units and 3D products. The system is configured to obtain specification of a target structure corresponding to a 3D product; automatically determine a design and a printing path of a 3D printing unit based on the specification of the target structure, wherein the 3D printing unit is a micronozzle unit configured to print the target structure of the 3D product; automatically determine a manufacturing procedure to print the 3D printing unit based on the specification of the target structure; and instruct a 3D printer to print the 3D printing unit according to the manufacturing procedure and the printing path of the 3D printing unit.
Physics basis for design of 3D coils in tokamaks
Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. In this work generalized perturbed equilibrium code is used to determine optimally efficient spectrum for driving total, core, and edge neoclassical toroidal viscosity torque. These fundamental modes of 3D control are shown to have consistent outboard structures across a wide variety of plasma scenarios and machines. Given these target spectra, the currents and 3D geometry of multiple coils can be optimized to increase efficient drive for the physics of interest without undesired secondary effects. Here, this nonlinear optimization is demonstrated using the flexible optimized coils using space-curves code. The optimized coils are individually distorted in space, creating toroidal 'arrays' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. Importantly, efficient coupling can be maintained even when enforcing large distances between coils and the plasma during the geometric optimization of coil designs. Finally, the physics-driven optimization presented here thus provides a practical path to utilizing coils built on the exterior of the vacuum chamber in future reactors to obtain the powerful 3D field benefits demonstrated on current machines with close, internal coils.
MADE3D: Enabling the Next-Generation High-Torque- Density Wind Generators by Additive Design and 3D Printing
Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments - especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technologies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.
MADE3D: Enabling the next generation of high-torque density wind generators by additive design and 3D printing
Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments—especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technolgies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.
Algorithmic design for 3D printing at building scale
Here, this paper addresses the use of algorithmic design paired with additive manufacturing and their potential impact on architectural design and fabrication of a full-sized building, as demonstrated with the AMIE project. AMIE (Additive Manufacturing and Integrated Energy) was collaboration to 3d print a building and vehicle. Both the car and building were designed to generate, store and share energy in an effort to reduce or eliminate reliability on the power grid. This paper is intended to outline our methodology in successfully designing for these innovative strategies, with a focus on the use of computational design tools as a catalyst for design optimization, integrated project delivery, rapid prototyping and fabrication of building elements using additive manufacturing.
Optimal design of 3D borehole seismic arrays for microearthquake monitoring in anisotropic media during stimulations in the EGS collab project
Multiple U.S. national laboratories, universities and industrial collaborators are conducting collaborative research under the EGS Collab project supported by the U.S. Department of Energy, to understand the fracture creation and imaging during fracturing in enhanced geothermal systems. Microearthquake hypocenter locations and focal mechanisms are used to monitor hydraulic fracturing growth and characterization at the EGS Collab experimental site at the Sanford Underground Research Facility using seismic receivers in multiple monitoring wells. In this study, we develop a methodology for optimal design a 3D borehole seismic array for cost-effective seismic monitoring in anisotropic media using not only the relationship between receiver distributions and standard deviation errors of microearthquake hypocenter locations, but also that between receiver distributions and focal-mechanism inversion errors. Our results indicate that microearthquake hypocenter locations and focal mechanisms can be reasonably well reconstructed for the EGS Collab Experiment I using six monitoring wells, including four fracture-parallel monitoring wells and two orthogonal wells. Lastly, eight seismic receivers evenly distributed in four parallel monitoring wells or twelve receivers in all six monitoring wells are required for hypocenter location, and twelve receivers evenly distributed in six wells or sixteen receivers in four wells are needed for focal-mechanism inversion.
Automated Sequence Design of 3D Polyhedral Wireframe DNA Origami with Honeycomb Edges
3D polyhedral wireframe DNA nanoparticles (DNA-NPs) fabricated using scaffolded DNA origami offer complete and independent control over NP size, structure, and asymmetric functionalization on the 10–100 nm scale. However, the complex DNA sequence design needed for the synthesis of these versatile DNA-NPs has limited their widespread use to date. While the automated sequence design algorithms DAEDALUS and vHelix-BSCOR apply to DNA-NPs synthesized using either uniformly dual or hybrid single-dual duplex edges, respectively, these DNA-NPs are relatively compliant mechanically and are therefore of limited utility for some applications. Further, these algorithms are incapable of handling DNA-NP edge designs composed of more than two duplexes, which are needed to enhance DNA-NP mechanical stiffness. As an alternative, here we introduce the scaffolded DNA origami sequence design algorithm TALOS, which is a generalized procedure for the fully automated design of wireframe 3D polyhedra composed of edges of any cross section with an even number of duplexes, and apply it to DNA-NPs composed uniformly of single honeycomb edges. We also introduce a multiway vertex design that enables the fabrication of DNA-NPs with arbitrary edge lengths and vertex angles and apply it to synthesize a highly asymmetric origami object. Sequence designs are demonstrated to fold robustly into target DNA-NP shapes with high folding efficiency and structural fidelity that is verified using single particle cryo-electron microscopy and 3D reconstruction. Furthermore, in order to test its generality, we apply TALOS to design an in silico library of over 200 DNA-NPs of distinct symmetries and sizes, and for broad impact, we also provide the software as open source for the generation of custom NP designs.
Electrode Cage for Hydrogen Production
3D design documents for 3D printing. The holes in the electrode cage are designed to condense hydrogen into progressively larger bubbles, and to direct the flow of hydrogen from the cathode up and out of the bioreactor so it is kept away from the anode and collected as nearly pure hydrogen.
Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE
This work introduces a three-dimensional (3D) invariant graph-to-string transformer variational autoencoders (VAE) (Vagrant) for generating molecules with accurate density functional theory (DFT)-level properties. Vagrant learns to model the joint probability distribution of a 3D molecular structure and its properties by encoding molecular structures into a 3D-aware latent space. Directed navigation through this latent space implicitly optimizes the 3D structure of a molecule, and the latent embedding can be used to condition a generative transformer to predict the candidate structure as a one-dimensional (1D) sequence. Additionally, we introduce two novel sampling methods that exploit the latent characteristics of a VAE to improve performance. Here, we show that our method outperforms comparable 3D autoregressive and diffusion methods for predicting quantum chemical property values of novel molecules in terms of both sample quality and computational efficiency.
Exploiting negative Poisson's ratio to design 3D-printed composites with enhanced mechanical properties
Auxetic materials exhibiting a negative Poisson's ratio are shown to have better indentation resistance, impact shielding capability, and enhanced toughness. Here, we report a class of high-performance composites in which auxetic lattice structures are used as the reinforcements and the nearly incompressible soft material is employed as the matrix. This coupled geometry and material design concept is enabled by the state-of-the-art additive manufacturing technique. Guided by experimental tests and finite element analyses, we systematically study the compressive behavior of the 3D printed auxetics reinforced composites and achieve a significant enhancement of their stiffness and energy absorption. This improved mechanical performance is due to the negative Poisson's ratio effect of the auxetic reinforcements, which makes the matrix in a state of biaxial compression and hence provides additional support. This mechanism is further supported by the investigation of the effect of auxetic degree on the stiffness and energy absorption capability. The findings reported here pave the way for developing a new class of auxetic composites that significantly expand their design space and possible applications through a combination of rational design and 3D printing.
Advanced Design and 3D Printing Strategies With Alginate‐Nanoclay Nanocomposites: From Microstructure to Bioprinting
Nanocomposites made from alginate and nanoclay are extensively applied for diverse biomedical applications. However, the lack of a clear understanding of the interactions between alginate and nanoclay makes it difficult to rationally design the nanocomposites for different material extrusion-based 3D bioprinting strategies. Here, a combined analytical model is proposed to accurately predict the interaction mechanisms between alginate and nanoclay through small-angle neutron scattering. These mechanisms are summarized into a phase diagram that can guide the design of alginate-nanoclay nanocomposites for different bioprinting applications. The rheological properties of various nanocomposites are measured to validate the proposed interaction mechanisms at the macroscale. Accordingly, three representative extrusion-based bioprinting strategies are linked with the nanocomposite design and applied to freeform fabricate complex structures. In conclusion, a roadmap is summarized to bridge the gap between biomaterial design and bioprinting processes, enabling the rapid and rational selection of biomaterial formula based on available 3D printing methods, and vice versa.
THE KMOS{sup 3D} SURVEY: DESIGN, FIRST RESULTS, AND THE EVOLUTION OF GALAXY KINEMATICS FROM 0.7 ≤ z ≤ 2.7
We present the KMOS{sup 3D} survey, a new integral field survey of over 600 galaxies at 0.7 < z < 2.7 using KMOS at the Very Large Telescope. The KMOS{sup 3D} survey utilizes synergies with multi-wavelength ground- and space-based surveys to trace the evolution of spatially resolved kinematics and star formation from a homogeneous sample over 5 Gyr of cosmic history. Targets, drawn from a mass-selected parent sample from the 3D-HST survey, cover the star formation-stellar mass (M {sub *}) and rest-frame (U – V) – M {sub *} planes uniformly. We describe the selection of targets, the observations, and the data reduction. In the first-year of data we detect Hα emission in 191 M {sub *} = 3 × 10{sup 9}-7 × 10{sup 11} M {sub ☉} galaxies at z = 0.7-1.1 and z = 1.9-2.7. In the current sample 83% of the resolved galaxies are rotation dominated, determined from a continuous velocity gradient and v {sub rot}/σ{sub 0} > 1, implying that the star-forming ''main sequence'' is primarily composed of rotating galaxies at both redshift regimes. When considering additional stricter criteria, the Hα kinematic maps indicate that at least ∼70% of the resolved galaxies are disk-like systems. Our high-quality KMOS data confirm the elevated velocity dispersions reported in previous integral field spectroscopy studies at z ≳ 0.7. For rotation-dominated disks, the average intrinsic velocity dispersion decreases by a factor of two from 50 km s{sup –1}at z ∼ 2.3 to 25 km s{sup –1}at z ∼ 0.9. Combined with existing results spanning z ∼ 0-3, we show that disk velocity dispersions follow an evolution that is consistent with the dependence of velocity dispersion on gas fractions predicted by marginally stable disk theory.
3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling
Driving range and fast charge capability of electric vehicles are heavily dependent on the 3D microstructure of lithium-ion batteries (LiBs) and substantial fundamental research is required to optimise electrode design for specific operating conditions. Here we have developed a full microstructure-resolved 3D model using a novel X-ray nano-computed tomography (CT) dual-scan superimposition technique that captures features of the carbon-binder domain. This elucidates how LiB performance is markedly affected by microstructural heterogeneities, particularly under high rate conditions. The elongated shape and wide size distribution of the active particles not only affect the lithium-ion transport but also lead to a heterogeneous current distribution and non-uniform lithiation between particles and along the through-thickness direction. Building on these insights, we propose and compare potential graded-microstructure designs for next-generation battery electrodes. To guide manufacturing of electrode architectures, in-situ X-ray CT is shown to reliably reveal the porosity and tortuosity changes with incremental calendering steps.