Elaborate Architectures Research Articles

Ultrafine Homologous Ni2P–Co2P Heterostructures via Space‐Confined Topological Transformation for Superior Urea Electrolysis

AbstractConstructing effective electrocatalysts based on ultrafine heterostructures is a promising strategy for boosting catalytic performance by exposing active sites and increasing specific surface area. However, the fabrication of catalytically active heterostructures with elaborate architectures is still poorly developed owing to synthetic challenges, and the intrinsic mechanism of heterogeneous interfaces remains unclear because of insufficient evidence regarding real active sites. In this study, ultrafine homologous Ni2P–Co2P heterostructures (Ni2P–Co2P/C) are created using a topological transformation strategy from a Ni–Co layered double hydroxide/carbon (Ni–Co LDH/C) interconnected structure in a single nanosheet. When employed as catalysts in urea oxidation reaction (UOR), the Ni2P–Co2P/C heterostructures exhibit superior activity and stability, attributed to the optimized geometric and electronic structures of the catalytic sites. Specifically, it takes an ultralow potential of 1.27 V to reach a current density of 10 mA cm−2 with a small Tafel slope of 28.71 mV dec−1. The operando analyses and calculation results reveal that cobalt incorporation can reduce the generation potential of the surface reconstructive active species and optimize the absorption/desorption energy of the intermediates. Overall, this study proposes an efficient and cost‐effective UOR electrocatalyst and offers a new high‐performance homologous heterostructure design for widespread application.

Why are there African huts at the zoo? The racialized spectacle of conservation

ABSTRACTWith 700 million annual global visitors, zoos transmit widely consumed stories about human relationships with nature and animals. In recent decades, zoos have framed their mission around wildlife conservation. Yet just as zoos pivoted to conservation, they simultaneously re-introduced ‘native village’ exhibits: African huts, thatched roofs, and Thai tuktuks. This article examines the Denver Zoo in Colorado, arguing that the zoo produces a racialized spectacle of conservation. Drawing on quantitative and photographic documentation of the zoo’s signage and architecture, I describe how the African and Asian exhibits at the zoo are the only sections representing human culture, and feature elaborate architectures, artwork, and descriptions of stereotypically rural and primitive people. These representations ‘naturalize race’ by portraying these cultures as closer to nature. Zoo exhibits simultaneously reproduce Malthusian narratives of environmental decline, blaming African and Asian populations for harming wildlife through overpopulation, deforestation, and illegal poaching. White Western conservationists are portrayed as educating local tribes in proper beliefs and scientific management. Meanwhile, exhibits erase how colonial exploitation, capitalism, and conservation itself have destabilized human-ecological relationships across the globe. This article contributes to broader literatures on the spectacle of neoliberal global conservation, demonstrating the racialization of this spectacle.

Bioinspired fish-scale-like magnesium composites strengthened by contextures of continuous titanium fibers: Lessons from nature

Abstract Natural fish scales demonstrate outstanding mechanical efficiency owing to their elaborate architectures and thereby may serve as ideal prototypes for the architectural design of man-made materials. Here bioinspired magnesium composites with fish-scale-like orthogonal plywood and double-Bouligand architectures were developed by pressureless infiltration of a magnesium melt into the woven contextures of continuous titanium fibers. The composites exhibit enhanced strength and work-hardening ability compared to those estimated from a simple mixture of their constituents at ambient to elevated temperatures. In particular, the double-Bouligand architecture can effectively deflect cracking paths, alleviate strain localization, and adaptively reorient titanium fibers within the magnesium matrix during the deformation of the composite, representing a successful implementation of the property-optimizing mechanisms in fish scales. The strength of the composites, specifically the effect of their bioinspired architectures, was interpreted based on the adaptation of classical laminate theory. This study may offer a feasible approach for developing new bioinspired metal-matrix composites with improved performance and provide theoretical guidance for their architectural designs.

Modeling of 3D Blood Flows with Physics-Informed Neural Networks: Comparison of Network Architectures

Machine learning-based modeling of physical systems has attracted significant interest in recent years. Based solely on the underlying physical equations and initial and boundary conditions, these new approaches allow to approximate, for example, the complex flow of blood in the case of fluid dynamics. Physics-informed neural networks offer certain advantages compared to conventional computational fluid dynamics methods as they avoid the need for discretized meshes and allow to readily solve inverse problems and integrate additional data into the algorithms. Today, the majority of published reports on learning-based flow modeling relies on fully-connected neural networks. However, many different network architectures are introduced into deep learning each year, each with specific benefits for certain applications. In this paper, we present the first comprehensive comparison of various state-of-the-art networks and evaluate their performance in terms of computational cost and accuracy relative to numerical references. We found that while fully-connected networks offer an attractive balance between training time and accuracy, more elaborate architectures (e.g., Deep Galerkin Method) generated superior results. Moreover, we observed high accuracy in simple cylindrical geometries, but slightly poorer estimates in complex aneurysms. This paper provides quantitative guidance for practitioners interested in complex flow modeling using physics-based deep learning.

Deep learning for behaviour classification in a preclinical brain injury model.

The early detection of traumatic brain injuries can directly impact the prognosis and survival of patients. Preceding attempts to automate the detection and the assessment of the severity of traumatic brain injury continue to be based on clinical diagnostic methods, with limited tools for disease outcomes in large populations. Despite advances in machine and deep learning tools, current approaches still use simple trends of statistical analysis which lack generality. The effectiveness of deep learning to extract information from large subsets of data can be further emphasised through the use of more elaborate architectures. We therefore explore the use of a multiple input, convolutional neural network and long short-term memory (LSTM) integrated architecture in the context of traumatic injury detection through predicting the presence of brain injury in a murine preclinical model dataset. We investigated the effectiveness and validity of traumatic brain injury detection in the proposed model against various other machine learning algorithms such as the support vector machine, the random forest classifier and the feedforward neural network. Our dataset was acquired using a home cage automated (HCA) system to assess the individual behaviour of mice with traumatic brain injury or non-central nervous system (non-CNS) injured controls, whilst housed in their cages. Their distance travelled, body temperature, separation from other mice and movement were recorded every 15 minutes, for 72 hours weekly, for 5 weeks following intervention. The HCA behavioural data was used to train a deep learning model, which then predicts if the animals were subjected to a brain injury or just a sham intervention without brain damage. We also explored and evaluated different ways to handle the class imbalance present in the uninjured class of our training data. We then evaluated our models with leave-one-out cross validation. Our proposed deep learning model achieved the best performance and showed promise in its capability to detect the presence of brain trauma in mice.

Catalyst-free nitro-coupling synthesis of azo-linked conjugated microporous polymers with superior aqueous energy storage capability

Developing methods to construct conjugated microporous polymers (CMPs) with desirable structures is a crucial undertaking. However, obtaining azo-CMPs with extended azaacene cores is immensely challenging. Herein, we disclose the facile synthesis of diquinoxalino[2,3-a:2′,3′-c]-phenazine-core CMP (3Qn-CMP; core diameter, ∼1.6 nm) via the one-step hydrothermal homocoupling of nitro monomers in a mixture solution of N,N-dimethylformamide (or N,N-dimethylacetamide) and water (1:3, v/v). A 3Qn-CMP/rGO hybrid is readily prepared from CMP spheres (diameter, 0.5–1.5 µm) anchored on reduced graphene oxide (rGO) nanosheets (∼3 layers) by synergizing the one-pot synthesis of (rGO) for intercalation and self-assembly. The highly porous hybrid features dual redox active sites with azo and imine linkages and efficient charge conduction. 3Qn-CMP and 3Qn-CMP/rGO exhibit outstanding energy storage capacity, current density tolerance (1–50 A g−1), and long-term cycling stability in aqueous acidic electrolytes. 3Qn-CMP and 3Qn-CMP/rGO also produce high specific capacitances of 615.4 and 847.8 F g−1, respectively, at 1 A g−1. Approximately 99.1% of this capacitance can be retained over 50,000 continuous charge/discharge cycles at 50 A g−1. To the best of our knowledge, our hybrid outperforms most organic molecules or CMP-/rGO-based composites reported in the literature in terms of capacitance and cycling durability. This work provides a general strategy to access a new library of CMPs and hybrids with multilevel elaborate architectures tailored for target applications, such as electrochemical energy storage and catalysis.

Nanoscale Bouligand Multilayers: Giant Circular Dichroism of Helical Assemblies of Plasmonic 1D Nano-Objects.

Chirality is found at all length scales in nature, and chiral metasurfaces have recently attracted attention due to their exceptional optical properties and their potential applications. Most of these metasurfaces are fabricated by top-down methods or bottom-up approaches that cannot be tuned in terms of structure and composition. By combining grazing incidence spraying of plasmonic nanowires and nanorods and Layer-by-Layer assembly, we show that nonchiral 1D nano-objects can be assembled into scalable chiral Bouligand nanostructures whose mesoscale anisotropy is controlled with simple macroscopic tools. Such multilayer helical assemblies of linearly oriented nanowires and nanorods display very high circular dichroism up to 13 000 mdeg and giant dissymmetry factors up to g ≈ 0.30 over the entire visible and near-infrared range. The chiroptical properties of the chiral multilayer stack are successfully modeled using a transfer matrix formalism based on the experimentally determined properties of each individual layer. The proposed approach can be extended to much more elaborate architectures and gives access to template-free and enantiomerically pure nanocomposites whose structure can be finely tuned through simple design principles.

Sketch-specific data augmentation for freehand sketch recognition

Sketch recognition remains a significant challenge due to the limited training data and the substantial intra-class variance of freehand sketches for the same object. Conventional methods for this task often rely on the availability of the temporal order of sketch strokes, additional cues acquired from different modalities and supervised augmentation of sketch datasets with real images, which also limit the applicability and feasibility of these methods in real scenarios.In this paper, we propose a novel sketch-specific data augmentation (SSDA) method that leverages the quantity and quality of the sketches automatically. From the aspect of quantity, we introduce a Bezier pivot based deformation (BPD) strategy to enrich the training data. Towards quality improvement, we present a mean stroke reconstruction (MSR) approach to generate a set of novel types of sketches with smaller intra-class variances. Both of these solutions are unrestricted from any multi-source data and temporal cues of sketches. Furthermore, we show that some recent deep convolutional neural network models that are trained on generic classes of real images can be better choices than most of the elaborate architectures that are designed explicitly for sketch recognition. As SSDA can be integrated with any convolutional neural networks, it has a distinct advantage over the existing methods. Our extensive experimental evaluations demonstrate that the proposed method achieves the state-of-the-art results (84.27%) on the TU-Berlin dataset, outperforming the human performance by a remarkable 11.17% increase. Finally, more experiments show the practical value of our approach for the task of sketch-based image retrieval.

Prepare with care: Low contact resistance of pentacene Field-Effect transistors with clean and oxidized gold electrodes

In recent years, a number of researchers have voiced concerns regarding the increasing amount of publications which report record performance characteristics of organic field-effect transistors (OFETs). These devices often make use of elaborate architectures, ranging from surface treatment by self-assembled monolayers to contact-limited doping, injection layer introduction etc. While these techniques are claimed to improve the device performance, they often result in poorly defined device interfaces, such as that of the organic semiconductor with the dielectric and electrode surfaces, which render a rigorous theoretical description of the interface effects close to impossible. Furthermore, the effects of ambient exposure of prepared devices are often neglected during the analysis. In this work we introduce a completely high vacuum-based manufacturing and electrical characterization of OFETs using commercially available gold bottom-contact bottom-gate FET structures, which enables a rigorous exclusion of any air contact of the devices. Using the example of the prototypical and widely studied organic semiconductor pentacene, we compare various initial cleaning procedures of the FET-structures prior to the vacuum deposition of pentacene films on the device characteristics and complement the electrical in situ analysis by ex situ AFM measurements of the pentacene film morphology. We demonstrate that O 2 plasma cleaning with subsequent thermal annealing under vacuum conditions results in well-defined interfaces of the pentacene film with clean surface of gold electrodes, which exhibit a remarkably low width-normalized contact resistance of 1.19 kΩcm. Additionally, we show that the formation of gold oxide on top of the electrodes as a result of O 2 plasma cleaning without subsequent heating is beneficial for the charge carrier injection, resulting in a contact resistance of only 0.16 kΩcm – to the best of our knowledge, one of the lowest yet reported values for pentacene-gold systems. In addition, the comparative rigorous vacuum-based processing and analysis allows in particular to study also the effects of controlled exposure to ambient air – even for a short time – as well as aging under different storage conditions on the device performance. • Full HV OFET fabrication and characterization process chain is introduced. • HV process chain allows rigorous characterization of the charge carrier injection. • Reference for a PEN OFET with clean Au electrodes is demonstrated. • Gold oxide improves the charge carrier injection in PEN OFETs. • Ambient exposure and HV storage of OFETs affects the device characteristics.

Novel aqueous rechargeable nickel-bismuth batteries based on porous Bi2MoO6 microspheres and CoxNi1-xMoO4@NiCo-layered double hydroxide heterostructure nanoarrays

Aqueous rechargeable batteries represent one promising candidate for new energy storage and conversion systems because of their good safety, low cost, high energy density based on Faradic reactions, and high power density originated from the high ionic conductivity of aqueous electrolyte. Herein, a novel aqueous rechargeable nickel-bismuth battery was developed with highly porous Bi2MoO6 microspheres as anode active materials and delicately designed binder-free Co0.5Ni0.5MoO4@NiCo-layered double hydroxide heterostructure nanoarrays as the cathode for the first time. The Bi2MoO6 anode active materials exhibit outstanding electrochemical performances (such as high capacity of 163.2 mAh/g at 1 A/g and superior rate capability of 79.6% at 15 A/g) owing to their porous structure. To obtain the improved cathode, substitution of Co for Ni species of CoXNi1-XMoO4 as ‘core’ materials and growing time of NiCo-layered double hydroxide onto the ‘core’ materials were optimized systematically. The optimal cathode (Co0.5Ni0.5MoO4@NCLDH-12) affords appreciably enhanced electrochemical performances with the high capacity of 386.7 mAh/g at 1 A/g and good rate capability of 64.9% at 15 A/g owing to its advantages in composition and architecture. Desirably, the nickel-bismuth battery can deliver the acceptable maximum energy density of 41.5 W h/kg and power density of 3896.2 W/kg, respectively. The excellent electrochemical performances can be put down to the elaborate architectures of electrodes and synergistic effect between active materials. This current research would enrich the chemistry systems of present aqueous rechargeable batteries and also pave the way to effectively construct promising electrode active materials for aqueous rechargeable nickel-bismuth batteries.

Discrete Supramolecular Stacks Based on Multinuclear Tweezer-Type Rhodium Complexes.

By taking advantage of self-complementary π-π stacking and CH-π interactions, a series of discrete quadruple stacks were constructed through the self-aggregation of U-shaped dirhodium metallotweezer complexes featuring various planar polyaromatic ligands. By altering the conjugate stacking strength and bridging ligands, assemblies with a range of topologies were obtained, including a binuclear D-shaped macrocycle, tetranuclear open-ended cagelike frameworks, and duplex metallotweezer stacking structures. Furthermore, a rare stacking interaction resulting in selective C-H activation was observed during the self-assembly process of these elaborate architectures.

UV-curable, 3D printable and biocompatible silicone elastomers

A biocompatible silicone elastomer that can be UV-cured and 3D printed via thiol-ene photopolymerization between vinyl and thiol functionalized polysiloxanes is explored in this study. The in-situ photo-rheology demonstrates that the photo-crosslinking of silicone elastomer occurs instantaneously upon exposure to UV radiation and its gelation time is influenced synergically by thiol-ene molar ratio, photoinitiator dosage and UV irradiation intensity. Differential scanning photo-calorimeter results indicate that UV-initiated thiol-ene photoreaction preferably follows a second-order reaction kinetics and its activation energy is approximately 23.3 kJ/mol. Moreover, antibacterial assay shows thiol-ene UV-cured silicone elastomer can inhibit the growth of Gram-positive (S. aureus) and Gram-negative (E. coli) bacteria to some extent. Cytotoxicity and biocompatibility results reveal that this silicone elastomer also has good biocompatibility, and it used as wound dressing is conducive to the recovery of wounds. Furthermore, due to excellent spatiotemporal controllability of thiol-ene photoreaction, various elaborate architectures are fabricated by photo-patterning. On the other hand, this UV-curable formulation can also be 3D printed into various structures with smooth surface and good accuracy. These results propose that thiol-ene UV-curable silicone elastomer will be a promising material in biomedical applications as wound dressings or customized soft tissue scaffolds through 3D printing.

Submicron Co9S8/CoS/Carbon Spheres Derived from Bacteria for the Electrocatalytic Oxygen Reduction Reaction

AbstractSynthesizing non‐noble metal electrocatalysts with both high activity and high stability for the oxygen reduction reaction (ORR) is of great significance in the fuel cell and metal‐air battery industries. Herein, a facile method is explored to fabricate submicron Co9S8/CoS/C spheres by using Streptococcus thermophiles as a template. The electrocatalytic activity for the ORR with an onset and half‐wave potential of 0.87 and 0.79 V, respectively, vs. RHE approaches that of commercial Pt/C catalyst. The durability and methanol tolerance are better than those of the commercial catalyst. The good performance could be attributed to the coupling effect between Co9S8/CoS and the bio‐carbon substrate, as well as the robust submicron sphere morphology. Benefiting from the structural diversity of bacteria, this method can be extended to the synthesis of sulfide catalysts with other elaborate architectures.

Leaf-inspired multiresponsive MXene-based actuator for programmable smart devices.

Natural leaves, with elaborate architectures and functional components, harvest and convert solar energy into chemical fuels that can be converted into energy based on photosynthesis. The energy produced leads to work done that inspired many autonomous systems such as light-triggered motion. On the basis of this nature-inspired phenomenon, we report an unprecedented bilayer-structured actuator based on MXene (Ti3C2T x )-cellulose composites (MXCC) and polycarbonate membrane, which mimic not only the sophisticated leaf structure but also the energy-harvesting and conversion capabilities. The bilayer actuator features multiresponsiveness, low-power actuation, fast actuation speed, large-shape deformation, programmable adaptability, robust stability, and low-cost facile fabrication, which are highly desirable for modern soft actuator systems. We believe that these adaptive soft systems are attractive in a wide range of revolutionary technologies such as soft robots, smart switch, information encryption, infrared dynamic display, camouflage, and temperature regulation, as well as human-machine interface such as haptics.

Evolution of Co3O4 Nanocubes through Stepwise Oriented Attachment.

Uniformly sized building units are generally required to construct highly elaborate architectures over a wide range. Defined nanocubes of Co3O4 evolved from deformed precursor nanograins 2-5 nm in diameter through direct oriented attachment in a nonpolar medium. Uniformly sized primary nanocubes ∼8 nm on a side with {100} faces were formed by adjusting the coverage of the oxide nanograins with oleic acid. Larger nanocubes 20-40 nm on a side were produced with further direct oriented attachment of the primary nanocubes. Ordered arrays, such as superlattices, were found to be constructed by the indirect oriented attachment of the primary and larger nanocubes covered with organic molecules.

Evaporation-driven manipulation of nanoscale brickwork structures for the design of 1D, 2D, and 3D microarrays of rectangular building blocks

As children play with wooden building blocks, we would like to construct elaborate architectures through the one-by-one accumulation of nanocrystals.

Ecological suicide in microbes.

The growth and survival of organisms often depend on interactions between them. In many cases, these interactions are positive and caused by a cooperative modification of the environment. Examples are the cooperative breakdown of complex nutrients in microbes or the construction of elaborate architectures in social insects, where the individual profits from the collective actions of her peers. However, organisms can similarly display negative interactions by changing the environment in ways that are detrimental for them, for example by resource depletion or the production of toxic byproducts. Here we find an extreme type of negative interactions, in which Paenibacillus sp. bacteria modify the environmental pH to such a degree that it leads to a rapid extinction of the whole population, a phenomenon we call ecological suicide. Modification of the pH is more pronounced at higher population densities, and thus ecological suicide is more likely with increasing bacterial density. Correspondingly, promoting bacterial growth can drive populations extinct whereas inhibiting bacterial growth by the addition of harmful substances – like antibiotics – can rescue them. Moreover, ecological suicide can cause oscillatory dynamics, even in single-species populations. We find ecological suicide in a wide variety of microbes, suggesting that it could play a significant role in microbial ecology and evolution.

Dawn of the in vivo RNA structurome and interactome.

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure-function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases.

Molecular basis for photoreceptor outer segment architecture.

To serve vision, vertebrate rod and cone photoreceptors must detect photons, convert the light stimuli into cellular signals, and then convey the encoded information to downstream neurons. Rods and cones are sensory neurons that each rely on specialized ciliary organelles to detect light. These organelles, called outer segments, possess elaborate architectures that include many hundreds of light-sensitive membranous disks arrayed one atop another in precise register. These stacked disks capture light and initiate the chain of molecular and cellular events that underlie normal vision. Outer segment organization is challenged by an inherently dynamic nature; these organelles are subject to a renewal process that replaces a significant fraction of their disks (up to ∼10%) on a daily basis. In addition, a broad range of environmental and genetic insults can disrupt outer segment morphology to impair photoreceptor function and viability. In this chapter, we survey the major progress that has been made for understanding the molecular basis of outer segment architecture. We also discuss key aspects of organelle lipid and protein composition, and highlight distributions, interactions, and potential structural functions of key OS-resident molecules, including: kinesin-2, actin, RP1, prominin-1, protocadherin 21, peripherin-2/rds, rom-1, glutamic acid-rich proteins, and rhodopsin. Finally, we identify key knowledge gaps and challenges that remain for understanding how normal outer segment architecture is established and maintained.

Cyclic voltammogram on ridge/pore array architectured electrode inspired by butterfly-wings

Abstract Porous architectured electrodes are intensely investigated for promoting electrochemical performance. Besides the high surface area, mass transport plays an irreplaceable role in the architecture assisting effect, which is, however, far beyond expression due to the complexity and irregularity of various electrode materials. Here, we took advantage of elaborate architectures from butterfly wings and obtained carbon electrode with ridge/pore array hierarchical architecture (ridge/pore-C) using a carbonizing-graphite coating method. A basic one-electron transfer process using the redox couple ferri/ferrocyanide as a benchmark under cyclic voltammetric conditions was conducted. The peak potential separation for ridge/pore-C was decreased by 117 mV compared to its non-architectured counterpart, with obvious enhancement of peak current density, indicating prominent beneficial impact on electrochemical responses. Further finite element simulation demonstrated the additional lateral diffusion within the ridge domain and partial thin layer diffusion within the pore array domain of ridge/pore-C, and simultaneously verified the experimental results. By constructing and investigating the well-organized porous architecture for affecting cyclic voltammogram, this work provides a prototype and cost-effective method for structural design of efficient electrodes by drawing inspiration from nature.