Functionally Graded Porous Scaffold (FGPS) becomes an attractive candidate for bone graft due to its combination of better mechanical and biological requirements with the scaffold gradient to better ...mimic host tissue. This paper focuses on the graded change requirements of bio-porous scaffolds in terms of physical and mechanical properties. Gradients in three patterns (density, heterostructure and cell-size gradients) with Gyroid and Diamond unit cells were proposed based on Triply Periodic Minimal Surfaces (TPMS), and fabricated by Selective Laser Melting (SLM) using Ti-6Al-4V. Among them, cell-size gradient was described for the first time, realizing a variation of graded pore size on a specific way. Morphological properties of porous samples were characterized by micro-CT and SEM, followed by compressive tests for determining their mechanical behaviors. It was found that the TPMS method is an effective way to achieve gradients in multiple patterns which are comparable to natural tissue with respect to both continuous topology and interconnectivity. The porous surface area and pore size, could be controlled by the cell-size gradient without relatively density alteration, stabilizing the modulus and strength within 11% and 20%, respectively. Both Gyroid and Diamond structures possess a superior strength (152.6 MPa, 145.7 MPa) and comparable elastic modulus (3.8GPa) with natural cortical bone.
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•Cell-size gradient porous scaffold was designed based on triply periodic minimal surfaces (TPMS).•Cell-size gradient can adjust surface area and pore size of scaffolds without relative density alteration.•TPMS is a feasible way to achieve gradient scaffolds in multiple patterns with continuous topology and interconnectivity.•The studied scaffolds of TC4 have a superior strength and comparable elastic modulus with cortical bone.
A common difficulty in applications of machine learning is the lack of any general principle for guiding the choices of key parameters of the underlying neural network. Focusing on a class of ...recurrent neural networks—reservoir computing systems, which have recently been exploited for model-free prediction of nonlinear dynamical systems—we uncover a surprising phenomenon: the emergence of an interval in the spectral radius of the neural network in which the prediction error is minimized. In a three-dimensional representation of the error versus the time and spectral radius, the interval corresponds to the bottom region of a “valley.” Such a valley arises for a variety of spatiotemporal dynamical systems described by nonlinear partial differential equations, regardless of the structure and the edge-weight distribution of the underlying reservoir network. We also find that, while the particular location and size of the valley depend on the details of the target system to be predicted, the interval tends to be larger for undirected than for directed networks. The valley phenomenon can be beneficial to the design of optimal reservoir computing, representing a small step forward in understanding these machine-learning systems.
There has been tremendous development in linear controllability of complex networks. Real-world systems are fundamentally nonlinear. Is linear controllability relevant to nonlinear dynamical ...networks? We identify a common trait underlying both types of control: the nodal "importance". For nonlinear and linear control, the importance is determined, respectively, by physical/biological considerations and the probability for a node to be in the minimum driver set. We study empirical mutualistic networks and a gene regulatory network, for which the nonlinear nodal importance can be quantified by the ability of individual nodes to restore the system from the aftermath of a tipping-point transition. We find that the nodal importance ranking for nonlinear and linear control exhibits opposite trends: for the former large-degree nodes are more important but for the latter, the importance scale is tilted towards the small-degree nodes, suggesting strongly the irrelevance of linear controllability to these systems. The recent claim of successful application of linear controllability to Caenorhabditis elegans connectome is examined and discussed.
Platinum is the most efficient catalyst for hydrogen evolution reaction in acidic conditions, but its widespread use has been impeded by scarcity and high cost. Herein, Pt atomic clusters (Pt ACs) ...containing Pt-O-Pt units were prepared using Co/N co-doped carbon (CoNC) as support. Pt ACs are anchored to single Co atoms on CoNC by forming strong interactions. Pt-ACs/CoNC exhibits only 24 mV overpotential at 10 mA cm
and a high mass activity of 28.6 A mg
at 50 mV, which is more than 6 times higher than commercial Pt/C with any Pt loadings. Spectroscopic measurements and computational modeling reveal the enhanced hydrogen generation activity attributes to the charge redistribution between Pt and O atoms in Pt-O-Pt units, making Pt atoms the main active sites and O linkers the assistants, thus optimizing the proton adsorption and hydrogen desorption. This work opens an avenue to fabricate noble-metal-based ACs stabilized by single-atom catalysts with desired properties for electrocatalysis.
Characterized by high thermal-electrical conductivity and reasonable specific strength, lattice structures of copper alloy have great potential in industrial applications. However, they have been ...rarely studied due to their complicated structures and difficulty in fabrication. Based on the ability of selective laser melting to produce near net shape parts with any complex geometry directly, Cu-Cr-Zr copper alloy lattice structures with high density were manufactured and studied for the first time. A series of lattice structures were designed by a mathematical approach named Triply Periodic Minimal Surfaces and their mechanical properties, microstructures and deformation behaviors were systematically studied. The effects of cell size and volume fraction on their mechanical properties and energy absorptions were analyzed and evaluated. The results demonstrate that the mechanical and energy absorption properties of the lattice structures varied dramatically with the changes of cell size and volume fraction. Due to the good plasticity of the copper alloy, stress-strain curves of the lattice structures exhibit a long stress plateau without stress collapses, which is very beneficial for energy absorption. The deformation of the lattice structures occurred uniformly and was caused by the struts bending without cell breaking and struts fracturing.
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•Cu-Cr-Zr copper alloy lattice structures were well fabricated via selective laser melting for the first time.•The compression deformations of the lattice structures occurred uniformly without cell breaking and strut fracturing.•The stress-strain curves exhibit a long and rising stress plateaus without stress collapses.•Properties of the lattice structures with lower volume fraction are more sensitive to cell size.•Explicit equations depict the relations of the volume fractions and the mechanical properties.
A considerable amount of platinum (Pt) is required to ensure an adequate rate for the oxygen reduction reaction (ORR) in fuel cells and metal‐air batteries. Thus, the implementation of atomic Pt ...catalysts holds promise for minimizing the Pt content. In this contribution, atomic Pt sites with nitrogen (N) and phosphorus (P) co‐coordination on a carbon matrix (PtNPC) are conceptually predicted and experimentally developed to alter the d‐band center of Pt, thereby promoting the intrinsic ORR activity. PtNPC with a record‐low Pt content (≈0.026 wt %) consequently shows a benchmark‐comparable activity for ORR with an onset of 1.0 VRHE and half‐wave potential of 0.85 VRHE. It also features a high stability in 15 000‐cycle tests and a superior turnover frequency of 6.80 s−1 at 0.9 VRHE. Damjanovic kinetics analysis reveals a tuned ORR kinetics of PtNPC from a mixed 2/4‐electron to a predominately 4‐electron route. It is discovered that coordinated P species significantly shifts d‐band center of Pt atoms, accounting for the exceptional performance of PtNPC.
Phosphorus‐coordinated atomic Pt‐Nx sites are theoretically predicted and experimentally realized, offering enhanced kinetics for four‐electron electrochemical oxygen reduction. Exceptional activity is attributed to the tuning of the d‐band electron center via local coordination asymmetry. This chemistry provides an effective guideline for atomic Pt catalysts in batteries and fuel cells.
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•A high-fidelity CFD model that predicts the SLM process of Cu-Cr-Zr alloy.•Implementation of ray-tracing method coupled with temperature-dependent absorption.•In-situ laser ...absorptivity measurements.•Good consistency between simulations and experiments.•Underlying mechanisms of laser reflection.
Despite of the promising capabilities of selective laser melting (SLM), the poor formability of copper and its alloys is a critical challenge for industrial applications, which is widely-believed attributed to the high reflectivity of copper. Due to the difficulty of observing laser reflections, current understanding on the laser reflection mechanisms is still vague and unclear. This work constructs a high-fidelity CFD model coupled with a ray-tracing method to visualize the flow kinetics and reflection behavior during SLM Cu-Cr-Zr alloy. Considering the material specificity of copper, a temperature-dependent absorption rule is introduced to overcome the simulation deviation caused by the widely-used Fresnel absorption, showing good agreement with experiments in terms of track width and depth. The in-situ absorptivity measurement experiments are further conducted to compare with simulations with the error less than 2%. Additionally, different reflection mechanisms for continuous and distorted tracks are revealed. At relatively high linear energy density (LED), the global absorptivity undergoes a rise and a decrease in the initial stage, and finally gets stable. At low LED level, the surface tension drives the melt pool to form isolated balls and exposed plat surface, which is responsible for the intense absorptivity oscillation as the balling effect occurs.
Complex and nonlinear ecological networks can exhibit a tipping point at which a transition to a global extinction state occurs. Using real-world mutualistic networks of pollinators and plants as ...prototypical systems and taking into account biological constraints, we develop an ecologically feasible strategy to manage/control the tipping point by maintaining the abundance of a particular pollinator species at a constant level, which essentially removes the hysteresis associated with a tipping point. If conditions are changing so as to approach a tipping point, the management strategy we describe can prevent sudden drastic changes. Additionally, if the system has already moved past a tipping point, we show that a full recovery can occur for reasonable parameter changes only if there is active management of abundance, again due essentially to removal of the hysteresis. This recovery point in the aftermath of a tipping point can be predicted by a universal, two-dimensional reduced model.
Complex networked systems ranging from ecosystems and the climate to economic, social, and infrastructure systems can exhibit a tipping point (a “point of no return”) at which a total collapse of the ...system occurs. To understand the dynamical mechanism of a tipping point and to predict its occurrence as a system parameter varies are of uttermost importance, tasks that are hindered by the often extremely high dimensionality of the underlying system. Using complex mutualistic networks in ecology as a prototype class of systems, we carry out a dimension reduction process to arrive at an effective 2D system with the two dynamical variables corresponding to the average pollinator and plant abundances. We show, using 59 empirical mutualistic networks extracted from real data, that our 2D model can accurately predict the occurrence of a tipping point, even in the presence of stochastic disturbances. We also find that, because of the lack of sufficient randomness in the structure of the real networks, weighted averaging is necessary in the dimension reduction process. Our reduced model can serve as a paradigm for understanding and predicting the tipping point dynamics in real world mutualistic networks for safeguarding pollinators, and the general principle can be extended to a broad range of disciplines to address the issues of resilience and sustainability.
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