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Abstract Fused deposition modeling 3D printing provides a cost-effective and streamlined method for producing electrochemical sensors, overcoming the challenges associated with material selection, complex fabrication processes, and reproducibility issues. This study introduces an innovative approach utilizing a dual-printer setup to simplify the manufacturing of sensor electrodes. A critical enhancement in this process is the surface modification with reduced graphene oxide (rGO), which not only improves the electrochemical characteristics but also induces a wrinkled structure on the 3D printed surface. These wrinkles significantly increase the surface area, directly boosting the electrode’s electrochemical performance. Comprehensive characterization of the electrode surfaces, both before and after rGO modification, demonstrates a substantial increase in sensitivity, with a fortyfold improvement observed in hydrogen peroxide (H₂O₂) amperometric measurements. This breakthrough paves the way for advanced applications in 3D printed electrochemical sensors. 

Abstract Polycrystalline yttrium aluminum garnet (YAG) ceramic doped with neodymium (Nd), referred to as Nd:YAG, is widely used in solid‐state lasers. However, conventional powder metallurgy methods suffer from expenses, time consumption, and limitations in customizing structures. This study introduces a novel approach for creating Nd:YAG ceramics with 3D free‐form structures from micron (∼70 µm) to centimeter scales. Firstly, sol‐gel synthesis is employed to form photocurable colloidal solutions. Subsequently, by utilizing a home‐built micro‐continuous liquid interface printing process, precursors are printed into 3D poly(acrylic acid) hydrogels containing yttrium, aluminum, and neodymium hydroxides, with a resolution of 5.8 µmpixel⁻¹at a speed of 10 µm s⁻¹. After the hydrogels undergo thermal dehydration, debinding, and sintering, polycrystalline Nd:YAG ceramics featuring distinguishable grains are successfully produced. By optimizing the concentrations of the sintering aids (tetraethyl orthosilicate) and neodymium trichloride (NdCl₃), the resultant samples exhibit satisfactory photoluminescence, emitting light concentrated at 1064 nm when stimulated by a 532 nm laser. Additionally, Nd:YAG ceramics with various 3D geometries (e.g., cone, spiral, and angled pillar) are printed and characterized, which demonstrates the potential for applications, such as laser and amplifier fibers, couplers, and splitters in optical circuits, as well as gain metamaterials or metasurfaces. 

Abstract Ti/TiN coatings are used in a wide range of engineering applications due to their superior properties such as high hardness and toughness. Doping Al into Ti/TiN can further enhance properties and lead to even higher performance. Therefore, studying the atomic‐level behavior of the TiAl/TiAlN interface is important. However, due to the large number of possible combinations for the 50 mol% Al‐doped Ti/TiN system, it is time‐consuming to use the DFT‐based Monte Carlo methods to find the optimal TiAl/TiAlN system with a high work of adhesion. In this study, we use a graph convolutional neural network as an interatomic potential, combined with reinforcement learning, to improve the efficiency of finding optimal structures with a high work of adhesion. By inspecting the features of structures in neural networks, we found that the optimal structures follow a certain pattern of doping Al near the interface. The electronic structure and bonding analysis indicate that the optimal TiAl/TiAlN structures have higher bonding strength. We expect our approach to significantly accelerate the design of advanced ceramic coatings, which can lead to more durable and efficient materials for engineering applications. 

Abstract Graphene-based electrodes have been extensively investigated for supercapacitor applications. However, their ion diffusion efficiency is often hindered by the graphene restacking phenomenon. Even though holey graphene is fabricated to address this issue by providing ion transport channels, those channels could still be blocked by densely stacked graphene nanosheets. To tackle this challenge, this research aims at improving the ion diffusion efficiency of microwave-synthesized holey graphene films by tuning the water interlayer spacer towards the improved supercapacitor performance. By controlling the vacuum filtration during graphene-based electrode fabrication, we obtain dry films with dense packing and wet films with sparse packing. The SEM images reveal that 20 times larger interlayer distance is constructed in the wet film compared to that in the dry counterpart. The holey graphene wet film delivers a specific capacitance of 239 F/g, ~82% enhancement over the dry film (131 F/g). By an integrated experimental and computational study, we quantitatively show that the interlayer spacing in combination with the nanoholes in the basal plane dominates the ion diffusion rate in holey graphene-based electrodes. Our study concludes that novel hierarchical structures should be further considered even in holey graphene thin films to fully exploit the superior advantages of graphene-based supercapacitors. 

Abstract High‐performance electrical conductors at higher temperatures are increasingly needed in aerospace, electric vehicles, and military applications. This study develops an innovative multilayered graphene–metal composite conductor, significantly surpassing the maximum temperature limit of conventional copper (≈90 °C for commercial wires). This approach involves integrating fine copper (Cu) wire with functional shells to exploit the high electrical conductivity and chemical inertness of silver (Ag) and graphene (G), as well as excellent anti‐oxidation of nickel (Ni). Three different composite conductors, namely, NiGCu, NiAgCu, and NiAgGCu, are synthesized, characterized, and compared to quantify their overall performance and investigate the functionality of each shell. This work highlights the importance of the G layer. For example, NiAgGCu has 29.3% lower resistivity than NiAgCu, 34% lower resistivity than NiGCu, and 18.7% higher current density limit than NiAgCu after exposure to 550–850 °C. Both molecular dynamics (MD) and finite elements (FE) simulations are performed to reveal the detailed mechanisms of unprecedented thermal stability. These theoretical studies suggest that the embedded continuous graphene layer, even with its unavoidable defects, is attributed to significant performance enhancements up to 850 °C. The results present possible strategies to address current technical bottlenecks for high‐performance electrical conductors in harsh environments. 

Gyroid structure, a nature inspired cellular architecture, is under extensive exploration recently due to its structure continuity, uniform stress distribution under compression, and stable collapse mechanism during deformation. However, when combining with a functional gradient, the Gyroid structure can perform much different mechanical behavior from its homogeneous counterpart. Herein, bottom-up computational modeling is performed to investigate the mechanics of functional gradient nano-gyroid structure made of copper (Cu). Our work reveals that its mechanical properties degrade with a density that is much slower than those of homogeneous gyroid structure. The scaling of yield strength [Formula: see text] to the relative density [Formula: see text] for the functional gradient gyroid structure is in the factor of 1.5. Moreover, the layer-by-layer collapsing mechanism yields significantly better mechanical energy absorption ability. This study not only leads to insightful understanding of the deformation mechanisms in nonuniform gyroid structures but also promotes the development of the functional gradient cellular materials. 

Abstract Nanodiamonds (NDs) have been widely explored for applications in drug delivery, optical bioimaging, sensors, quantum computing, and others. Room-temperature nanomanufacturing of NDs in open air using confined laser shock detonation (CLSD) emerges as a novel manufacturing strategy for ND fabrication. However, the fundamental process mechanism remains unclear. This work investigates the underlying mechanisms responsible for nanomanufacturing of NDs during CLSD with a focus on the laser-matter interaction, the role of the confining effect, and the graphite-to-diamond transition. Specifically, a first-principles model is integrated with a molecular dynamics simulation to describe the laser-induced thermo-hydrodynamic phenomena and the graphite-to-diamond phase transition during CLSD. The simulation results elucidate the confining effect in determining the material’s responses to laser irradiation in terms of the temporal and spatial evolutions of temperature, pressure, electron number density, and particle velocity. The integrated model demonstrates the capability of predicting the laser energy threshold for ND synthesis and the efficiency of ND nucleation under varying processing parameters. This research will provide significant insights into CLSD and advance this nanomanufacturing strategy for the fabrication of NDs and other high-temperature-high-pressure synthesized nanomaterials towards extensive applications.