Acoustic metamaterials (AMMs) are a type of artificial materials that make use of appropriate structural designs and exhibit exotic properties not found in natural materials, such as negative effective material parameters (e.g., bulk modulus, mass density, and refractive index). These interesting properties offer novel means for sound manipulation and thus have drawn a great deal of attention. Over the past two decades, tremendous progress has been made in the fundamental research of AMMs, which has not only promoted the development of modern acoustics but also shown the potential of AMMs for engineering applications. Here, we review recent developments in AMMs with a focus on their future engineering, especially in the most promising fields of sound absorption/isolation, acoustic imaging, cloaking, and so on, furthermore, we outline the opportunities and challenges they are encountering.
Propagation of light beams in turbid media such as underwater environments, fog, clouds, or biological tissues finds increasingly important applications in science and technology, including bio-imaging, underwater and free-space communication technologies. While many of these applications traditionally relied on conventional, linearly polarized Gaussian beams, light possesses many degrees of freedom that are still largely unexplored, such as spin angular momentum (SAM) and orbital angular momentum (OAM). Here, we present nonlinear light–matter interactions of such complex light beams with ″rotational″ degrees of freedom in engineered nonlinear colloidal media. By making use of both variational and perturbative approach, we consider non-cylindrical optical vortices, elliptical optical vortices, and higher-order Bessel beams integrated in time (HOBBIT) to predict the dynamics and stability of the evolution of these beams. These results may find applications in many scenarios involving light transmission in strongly scattering environments.
Mechanical metamaterials can be defined as a class of architected materials that exhibit unprecedented mechanical properties derived from designed artificial architectures rather than their constituent materials. While macroscale and simple layouts can be realized by conventional top-down manufacturing approaches, many of the sophisticated designs at various length scales remain elusive, due to the lack of adequate manufacturing methods. Recent progress in additive manufacturing (AM) has led to the realization of a myriad of novel metamaterial concepts. AM methods capable of fabricating microscale architectures with high resolution, arbitrary complexity, and high feature fidelity have enabled the rapid development of architected metamaterials and drastically reduced the design-computation and experimental-validation cycle. This paper first provides a detailed review of various topologies based on the desired mechanical properties, including stiff, strong, and auxetic (negative Poisson's ratio) metamaterials, followed by a discussion of the AM technologies capable of fabricating these metamaterials. Finally, we discuss current challenges and recommend future directions for AM and mechanical metamaterials.
Inspired by the design philosophy of information metasurfaces based on the digital coding concept, a planar 4-bit reconfigurable antenna array with low profile of 0.15 λ0 (where λ0 is the wavelength) is presented. The array is based on a digital coding radiation element consisting of a 1-bit magnetoelectric (ME) dipole and a miniaturized reflection-type phase shifter (RTPS). The proposed 1-bit ME dipole can provide two digital states of “0” and “1” (with 0° and 180° phase responses) over a wide frequency band by individually exciting its two symmetrical feeding ports. The designed RTPS is able to realize a relative phase shift of 173°. By digitally quantizing its phase in the range of 157.5°, additional eight digital states at intervals of 22.5° are obtained. To achieve low sidelobe levels, a 1:16 power divider based on the Taylor line source method is employed to feed the array. A prototype of the proposed 4-bit antenna array has been fabricated and tested, and the experimental results are in good agreement with the simulations. Scanning beams within a ±45° range were measured with a maximum realized gain of 13.4 dBi at 12 GHz. The sidelobe and cross-polarization levels are below –14.3 and –23 dB, respectively. Furthermore, the beam pointing error is within 0.8°, and the 3-dB gain bandwidth of the broadside beam is 25%. Due to its outstanding performance, the array holds potential for significant applications in radar and wireless communication systems.
Subwavelength manipulation of light waves with high precision can enable new and exciting applications in spectroscopy, sensing, and medical imaging. For these applications, miniaturized spectrometers are desirable to enable the on-chip analysis of spectral information. In particular, for imaging-based spectroscopic sensing mechanisms, the key challenge is to determine the spatial-shift information accurately (i.e., the spatial displacement introduced by wavelength shift or biological or chemical surface binding), which is similar to the challenge presented by super-resolution imaging. Here, we report a unique “rainbow” trapping metasurface for on-chip spectrometers and sensors. Combined with super-resolution image processing, the low-setting 4× optical microscope system resolves a displacement of the resonant position within 35 nm on the plasmonic rainbow trapping metasurface with a tiny area as small as 0.002 mm2. This unique feature of the spatial manipulation of efficiently coupled rainbow plasmonic resonances reveals a new platform for miniaturized on-chip spectroscopic analysis with a spectral resolution of 0.032 nm in wavelength shift. Using this low-setting 4× microscope imaging system, we demonstrate a biosensing resolution of 1.92 × 109 exosomes per milliliter for A549-derived exosomes and distinguish between patient samples and healthy controls using exosomal epidermal growth factor receptor (EGFR) expression values, thereby demonstrating a new on-chip sensing system for personalized accurate bio/chemical sensing applications.
Metamaterials constructed from origami units of different types and behaviors could potentially offer a broader scope of mechanical properties than those formed from identical unit types. However, the geometric design rules and property programming methods for such metamaterials have yet to be extensively explored. In this paper, we propose a new kind of origami metasheet by incorporating a family of different square-twist units. The tessellation rule of these metasheets is established to allow compatible mountain–valley crease assignments and geometric parameters among neighboring units. We demonstrate through experiments that the energy, initial peak force, and maximum stiffness of the metasheets can be obtained by a summation of the properties of the constitutional units. Based on this, we are able to program the mechanical properties of the metasheets over a wide range by varying the types and proportions of the units, as well as their geometric and material parameters. Furthermore, for a metasheet with a fixed number of units, all the geometrically compatible tessellations can be folded out of the same pre-creased sheet material by simply changing the mountain–valley assignments, thereby allowing the properties of the metasheet to be re-programmed based on specific requirements. This work could inspire a new class of programmable origami metamaterials for current and future mechanical and other engineering applications.
This paper reports on analysis of an experimental study that aimed to determine the apparent gas permeability in cracked concrete. There is a lack of research on this topic in the international literature, due to the difficulty of performing reliable experimental testing for gas permeability. The principal interest of this work is to present new and reliable experimental results. Analytical functions between the evolution of the apparent crack permeability and the apparent crack opening are also proposed. These functions appear to be relevant in consideration of Poiseuille theory.
This study investigates the effects of nanofillers on the interfacial transition zone (ITZ) between aggregate and cement paste by using nanoindentation and statistical nanoindentation techniques. Moreover, the underlying mechanisms are revealed through micromechanical modeling. The nanoindentation results indicate that incorporating nanofillers increases the degree of hydration in the ITZ, reduces the content of micropores and low-density calcium silicate hydrate (LD C-S-H), and increases the content of high-density C-S-H (HD C-S-H) and ultrahigh-density C-S-H (UHD C-S-H). In particular, a new phase, namely nano-core-induced low-density C-S-H (NCILD C-S-H), with a superior hardness of 2.50 GPa and an indentation modulus similar to those of HD C-S-H or UHD C-S-H was identified in this study. The modeling results revealed that the presence of nanofillers increased the packing density of LD C-S-H and significantly enhanced the interaction (adhesion and friction) among the basic building blocks of C-S-H gels owing to the formation of nano-core-shell elements, thereby facilitating the formation of NCILD C-S-H and further improving the performance of the ITZ. This study provides insight into the effects of nanofillers on the ITZ in concrete at the nanoscale.
The use of coral aggregate concrete (CAC) as a novel construction material has attracted significant attention for the construction of reef engineering structures. To investigate the static splitting-tensile behaviors of CAC under the influence of two factors, namely specimen geometry and bearing strip size, a three-dimensional (3D) mesoscale modeling approach with consideration for aggregate randomness in shape and distribution was adopted in this study. We established 12 different specimen models with two specimen shapes (i.e., a cube with an edge length of 150 mm and a cylinder with dimensions of ϕ150 mm × 300 mm) and six strip widths (i.e., 6, 9, 12, 15, 18, and 20 mm) for calculation. The effects of specimen geometry and strip width on the splitting-tensile properties of CAC, such as failure processes, final failure patterns, and splitting-tensile strength (fst), are analyzed and discussed systematically. The results indicate the high reliability of the developed mesoscale modeling approach and reveal the optimal computational parameters for simulating and predicting the splitting-tensile properties of CAC. The fst values of CAC are associated with both the specimen geometry and width of the bearing strip. The fst values of the cube model are slightly higher than those of the cylinder model for the same bearing strip size, representing geometry effects that can be explained by differences in fracture area. Additionally, the fst value of CAC gradually increases with the relative width of the bearing strip ranging from 0.04 to 0.13. Based on the elastic solution theory, the variation area of CAC fst values with the relative width of the bearing strip was determined preliminarily, which has great significance for studying the tensile performance of CAC.
In this study, through experimental research and an investigation on large datasets of the durability parameters in ocean engineering, the values, ranges, and types of distribution of the durability parameters employed for the durability design in ocean engineering in northern China were confirmed. Based on a modified theoretical model of chloride diffusion and the reliability theory, the service lives of concrete structures exposed to the splash, tidal, and underwater zones were calculated. Mixed concrete proportions meeting the requirement of a service life of 100 or 120 years were designed, and a cover thickness requirement was proposed. In addition, the effects of the different time-varying relationships of the boundary condition (Cs) and diffusion coefficient (Df) on the service life were compared; the results showed that the time-varying relationships used in this study (i.e., Cs continuously increased and then remained stable, and Df continuously decreased and then remained stable) were beneficial for the durability design of concrete structures in marine environment.
An earthquake is usually followed by a considerable number of aftershocks that play a significant role in earthquake-induced landslides. During the aftershock, the cracking process in rocks becomes more complex because of the formation of faults. In order to investigate the effects of seismic loading on the cracking processes in a specimen containing a single flaw, a numerical approach based on the bonded-particle model (BPM) was adopted to study the seismic loading applied in two orthogonal directions. The results reveal that no transmission and reflection phenomena were observable in the small specimens (76 mm × 152 mm) because they were considerably smaller than the wavelength of the P-wave. Furthermore, under seismic loading, the induced crack was solely tensile in nature. Repeated axial seismic loading did not induce crack propagation after the first axial seismic loading. Cracks began to propagate only when the seismic loading direction was changed from axial to lateral, and then back to axial, ultimately resulting in the failure of the specimen.
To develop an efficient way to overcome the contradiction among flame retardancy, smoke suppression, and thermal insulation in expanded polystyrene (EPS) foams, which are widely used insulation materials in buildings, a novel “green” porous bio-based flame-retardant starch (FRS) coating was designed from starch modified with phytic acid (PA) that simultaneously acts as both a flame retardant and an adhesive. This porous FRS coating has open pores, which, in combination with the closed cells formed by EPS beads, create a hierarchically porous structure in FRS–EPS that results in superior thermal insulation with a lower thermal conductivity of 27.0 mW‧(m·K)−1. The resultant FRS–EPS foam showed extremely low heat-release rates and smoke-production release, indicating excellent fire retardancy and smoke suppression. The specific optical density was as low as 121, which was 80.6% lower than that of neat EPS, at 624. The FRS–EPS also exhibited self-extinguishing behavior in vertical burning tests and had a high limiting oxygen index (LOI) value of 35.5%. More interestingly, after being burnt with an alcohol lamp for 30 min, the top side temperature of the FRS–EPS remained at only 140 °C with ignition, thereby exhibiting excellent fire resistance. Mechanism analysis confirmed the intumescent action of FRS, which forms a compact phosphorus-rich hybrid barrier, and the phosphorus-containing compounds that formed in the gas phase contributed to the excellent flame retardancy and smoke suppression of FRS–EPS. This novel porous biomass-based FRS system provides a promising strategy for fabricating polymer foams with excellent flame retardancy, smoke suppression, and thermal insulation.
Understanding the immunological characteristics of monocytes—including the characteristics associated with fibrosis—in severe coronavirus disease 2019 (COVID-19) is crucial for understanding the pathogenic mechanism of the disease and preventing disease severity. In this study, we performed single-cell transcriptomic sequencing of peripheral blood samples collected from six healthy controls and 14 COVID-19 samples including severe, moderate, and convalescent samples from three severely/critically ill and four moderately ill patients. We found that the monocytes were strongly remodeled in the severely/critically ill patients with COVID-19, with an increased proportion of monocytes and seriously reduced diversity. In addition, we discovered two novel severe-disease-specific monocyte subsets: Mono 0 and Mono 5. These subsets expressed amphiregulin (AREG), epiregulin (EREG), and cytokine interleukin-18 (IL-18) gene, exhibited an enriched erythroblastic leukemia viral oncogene homolog (ErbB) signaling pathway, and appeared to exhibit pro-fibrogenic and pro-inflammation characteristics. We also found metabolic changes in Mono 0 and Mono 5, including increased glycolysis/gluconeogenesis and an increased hypoxia inducible factor-1 (HIF-1) signaling pathway. Notably, one pre-severe sample displayed a monocyte atlas similar to that of the severe/critical samples. In conclusion, our study discovered two novel severe-disease-specific monocyte subsets as potential predictors and therapeutic targets for severe COVID-19. Overall, this study provides potential predictors for severe disease and therapeutic targets for COVID-19 and thus provides a resource for further studies on COVID-19.
Highlights
•Pan-genomic and phylogenetic characterizations of 109 L. fermentum strains were performed.
•No co-evolutionary relationship exists between L. fermentum strains and the geographical origins of their host Immunomodulatory properties of L. fermentum were strain-dependent.
•Some specific genes may account for the anti-inflammatory and immunoregulation of L. fermentum strains.
Emerging evidence shows that some Lactobacillus fermentum strains can contribute to the prevention and treatment of ulcerative colitis (UC). In this study, 105 isolates of L. fermentum strains were separated from fecal samples of populations in different regions in China and their draft genomes were sequenced. Pan-genomic and phylogenetic characterizations of these strains and four model strains (L. fermentum 3872, CECT5716, IFO3956, and VRI003) were performed. Phylogenetic analysis indicated that there was no significant adaptive evolution between the genomes of L. fermentum strains and the geographical location, sex, ethnicity, and age of the hosts. Three L. fermentum strains (FWXBH115, FGDLZR121, and FXJCJ61) from different branches of the phylogenetic tree and strain type L. fermentum CECT5716 were selected and their anti-inflammatory and immune modulatory activities in a dextran sulphate sodium (DSS)-induced colitis mouse model were further investigated. Both L. fermentum FXJCJ61 and CECT5716 significantly alleviated UC by reducing all colitis-associated histological indices, maintaining mucosal integrity, and stimulating replenishment of short-chain fatty acids (SCFAs), while the other two strains failed to offer similar protection. The anti-inflammatory mechanisms of L. fermentum FXJCJ61 and CECT5716 were related to the inhibition of nuclear factor kappa-B (NF-κB) signaling pathway activation and enhancement of interleukin 10 (IL-10) production. Comparative genomic analysis of these strains identified candidate genes that may contribute to the anti-inflammatory effects of specific L. fermentum strains.
The immune response after implantation is a primary determinant of the tissue-repair effects of three-dimensional (3D)-printed scaffolds. Thus, scaffolds that can subtly regulate immune responses may display extraordinary functions. Inspired by the angiogenesis promotion effect of humoral immune response, we covalently combined mesoporous silica microrod (MSR)/polyethyleneimine (PEI)/ovalbumin (OVA) self-assembled vaccines with 3D-printed calcium phosphate cement (CPC) scaffolds for local antigen-specific immune response activation. With the response activated, antigen-specific CD4+ T helper 2 (Th2) cells can be recruited to promote early angiogenesis. The silicon (Si) ions from MSRs can accelerate osteogenesis, with an adequate blood supply being provided. At room temperature, scaffolds with uniformly interconnected macropores were printed using a self-setting CPC-based printing paste, which promoted the uniform dispersion and structural preservation of functional polysaccharides oxidized hyaluronic acid (OHA) inside. Sustained release of OVA was achieved with MSR/PEI covalently attached to scaffolds rich in aldehyde groups as the vaccine carrier. The vaccine-loaded scaffolds effectively recruited and activated dendritic cells (DCs) for antigen presentation and promoted the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) in vitro. When embedded subcutaneously in vivo, the vaccine-loaded scaffolds increased the proportion of Th2 cells in the spleen and locally recruited antigen-specific T cells to promote angiogenesis in and around the scaffold. Furthermore, the result in a rat skull defect-repair model indicated that the antigen-specific vaccine-loaded scaffolds promoted the regeneration of vascularized bone. This method may provide a novel concept for patient-specific implant design for angiogenesis promotion.
Nitrogen removal is a critical process in water treatment plants (WTPs) and wastewater treatment plants (WWTPs). The recent discovery of a novel bacterial process, complete ammonia oxidation (comammox, CMX), has refuted a century-long perception of the two-step conversion of NH3 to NO3–. Compared with canonical nitrifiers, CMX bacteria offer undeniable advantages, such as a high growth yield propensity and adaptability to nutrient- and growth-limiting conditions, which collectively draw attention to validate the aptness of CMX bacteria to wastewater treatment. As there has been no comprehensive review on the relevance of CMX bacteria for sustainable water and wastewater treatment, this review is intended to discuss the roles and applications of CMX in the removal of nitrogen and pollutants from water and wastewater. We took into account insights into the metabolic versatilities of CMX bacteria at the clade and subclade levels. We focused on the distribution of CMX bacteria in engineered systems, niche differentiation, co-occurrence and interactions with canonical nitrifiers for a better understanding of CMX bacteria in terms of their ecophysiology. Conceptualized details on the reactor adaptability and stress response of CMX bacteria are provided. The potential of CMX bacteria to degrade micropollutants either directly or co-metabolically was evaluated, and these insights would be an indispensable advantage in opening the doors for wider applications of CMX bacteria in WWTPs. Finally, we summarized future directions of research that are imperative in improving the understanding of CMX biology.
Deployable space structure technology is an approach used in building spacecraft, especially when realizing deployment and folding functions. Once in orbit, the structures are released from the fairing, deployed, and positioned. With the development of communication, remote-sensing, and navigation satellites, space-deployable structures have become cutting-edge research topics in space science and technology. This paper summarizes the current research status and development trend of spacedeployable structures in China, including large space mesh antennas, space solar arrays, and deployable structures and mechanisms for deep-space exploration. Critical technologies of space-deployable structures are addressed from the perspectives of deployable mechanisms, cable-membrane form-finding, dynamic analysis, reliable environmental adaptability analysis, and validation. Finally, future technology developments and trends are elucidated in the fields of mesh antennas, solar arrays, deployable mechanisms, and on-orbit adjustment, assembly, and construction.
Heterogeneous cellular networks (HCNs) are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity. However, the densified multi-tier network architecture introduces excessive intra- and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks. In this article, a dynamic spectrum control (DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity. Specifically, the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families, which represent the transmission decisions, by performing iterative and orthogonal sequence transformations. Based on the sequence families, multiple users can dynamically occupy different frequency slots for data transmission simultaneously. In addition, the collision probability of the data transmission is analyzed, which results in closed-form expressions of the reliable transmission probability and the secrecy probability. Then, the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities. Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance. Finally, the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.
Existing biomimetic robots can perform some basic rat-like movement primitives (MPs) and simple behavior with stiff combinations of these MPs. To mimic typical rat behavior with high similarity, we propose parameterizing the behavior using a probabilistic model and movement characteristics. First, an analysis of fifteen 10min video sequences revealed that an actual rat has six typical behaviors in the open
field, and each kind of behavior contains different bio-inspired combinations of eight MPs. We used the softmax classifier to obtain the behavior-movement hierarchical probability model. Secondly, we specified the MPs using movement parameters that are static and dynamic. We obtained the predominant values of the static and dynamic movement parameters using hierarchical clustering and fuzzy C-means
clustering, respectively. These predominant parameters were used for fitting the rat spinal joint trajectory using a second-order Fourier series, and the joint trajectory was generalized using a back propagation neural network with two hidden layers. Finally, the hierarchical probability model and the generalized joint trajectory were mapped to the robot as control policy and commands, respectively. We implemented the six typical behaviors on the robot, and the results show high similarity when compared with the behaviors of actual rats.
Stochastic differential equations (SDEs) are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources. The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system's dynamics. The practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data resources. This study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning (SBL) technique to search for a parsimonious, yet physically necessary representation from the space of candidate basis functions. More importantly, we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series data. The effectiveness of the proposed framework is demonstrated using real data on stock and oil prices, bearing variation, and wind speed, as well as simulated data on well-known stochastic dynamical systems, including the generalized Wiener process and Langevin equation. This framework aims to assist specialists in extracting
stochastic mathematical models from random phenomena in the natural sciences, economics, and engineering fields for analysis, prediction, and decision making.