Backward Direction Research Articles

Programming Anisotropic Functionality of 3D Microdenticles by Staggered-Overlapped and Multilayered Microarchitectures.

Natural sharkskin features staggered-overlapped and multilayered architectures of riblet-textured anisotropic microdenticles, exhibiting drag reduction and providing a flexible yet strong armor. However, the artificial fabrication of three-dimensional (3D) sharkskin with these unique functionalities and mechanical integrity is a challenge using conventional techniques. In this study, it is reported on the facile microfabrication of multilayered 3D sharkskin through the magnetic actuation of polymeric composites and subsequent chemical shape fixation by casting thin polymeric films. The fabricated hydrophobic sharkskin, with geometric symmetry breaking, achieves anisotropic drag reduction in frontal and backward flow directions against the riblet-textured microdenticles. For mechanical integrity, hard-on-soft multilayered mechanical properties are realized by coating the polymeric sharkskin with thin layers of zinc oxide and platinum, which have higher hardness and recovery behaviors than the polymer. This multilayered hard-on-soft sharkskin exhibits friction anisotropy, mechanical robustness, and structural recovery. Furthermore, coating the MXene nanosheets provides the fabricated sharkskin with a low electrical resistance of ≈5.3 Ω, which leads to high Joule heating (≈229.9°C at 2.75V). The proposed magnetomechanical actuation-assisted microfabrication strategy is expected to facilitate the development of devices requiring multifunctional microtextures.

Q-compensated wavefield depth extrapolation-based migration using a viscoacoustic wave equation

In a viscoacoustic medium, intrinsic attenuation causes seismic wavefields to attenuate in amplitude and become dispersed in phase, leading to distorted structural imaging and inaccurate migrated amplitudes. To address this problem, viscoacoustic reverse time migration corrects for dispersion and amplitude attenuation effects in wavefield propagation in forward and backward directions. To provide a parallel alternative approach, the time fractional derivative viscoacoustic wave equation in the depth domain is solved and a Q-compensated wavefield depth extrapolation scheme is established to compensate for viscoacoustic effects during recursive wavefield depth extrapolation. This approach decouples the amplitude attenuation and phase dispersion effects from the viscoacoustic vertical wavenumber. To suppress high wavenumber components and address the problem of exponential amplitude growth during wavefield depth extrapolation, we limit the imaginary part of the vertical wavenumber in the frequency wavenumber domain and use an adaptive stabilization solution. Numerical experiments of impulse responses in a viscoacoustic isotropic medium demonstrate that our proposed scheme can observe calculated wavefields exhibiting amplitude attenuation and phase dispersion effects in comparison to wavefields of the acoustic medium, indicating good agreement with theoretical expectations. We also demonstrate the capability of our proposed scheme to recover imaging amplitudes through a variety of numerical experiments, such as imaging of three-layer, Marmousi, and BP gas reservoir models. The results indicate that our proposed scheme can recover amplitude attenuation and phase dispersion effects more accurately than acoustic migration. We also use marine seismic data featuring natural gas hydrates to indicate that our proposed Q-compensated scheme can generate an enhanced imaging result, especially for the bottom simulating reflectors, compared with the conventional imaging algorithm without Q-compensation.

Comparison of ground reaction force and contact time during various-direction lunges between badminton shoes without and with a lateral forefoot wedge sole

This study compared the ground reaction force (GRF), GRF ratio, and contact time between badminton shoes without and with a lateral forefoot wedge sole during lunges in three directions. Fifteen collegiate athletes wore forefoot wedge shoes (5° incline) and control shoes without a lateral forefoot wedge sole (in random order) and performed three typical badminton lunge movements (forward, lateral, and backward directions). A total of nine GRF, GRF ratio, and contact time parameters were analyzed. A paired t test was performed to assess the differences between two shoes. The significance level was set at p < 0.0056 (0.05/9) based on Bonferroni correction to avoid chances of type 1 errors. In the forward lunge, the forefoot wedge shoes resulted in a significantly higher average vertical ground reaction force (GRFv, 3.9%), average horizontal GRF (GRFh, 7.8%) in the braking phase and higher average GRFh (3.9%) in the propulsion phase than the control shoes. In the lateral lunge, the forefoot wedge shoes resulted in a significantly shorter total contact time (−4.6%) than the control shoes in the backward lunge, the forefoot wedge shoes resulted in a significantly higher GRFh to GRFv ratio (6.4%) in the braking phase compared with the control shoes. Thus, shoes with a lateral forefoot wedge sole can effectively enhance mechanical performance in direction changes during forward and backward badminton lunges, and shorter the contact time during lateral badminton lunges. Shoes with a lateral forefoot wedge sole can be considered when designing athletic footwear.

The quality of visual entrainment correlates with forward traveling wave properties in human cortex

AbstractBackgroundFlickering light stimulation has been shown to entrain the brain’s oscillatory activity at the input frequency and synchronize different cortical regions in that frequency (Herrmann et al., 2001; Lahijanian et al., 2021). Brain entrainment at gamma frequency has been proposed and shown promising results as a non‐pharmaceutical therapeutic approach for Alzheimer’s disease (Cimenser et al., 2021). Studying the effects of such stimulation on the brain’s neural activity can help explain the mechanisms that underlie the reported improvements. It is known that neural oscillations form traveling waves across the brain during various cognitive functions (Bhattacharya et al., 2022). In this study, we use different flickering light frequencies as entrainment input and investigate the spatiotemporal pattern of neural activity modulated by visual entrainment which appears as a traveling wave across the posterior‐frontal pathway.MethodEEG data recorded from young healthy adults were analyzed during multi‐trial flickering light stimulation at 10, 15, 20, 22, and 30Hz frequencies. In order to analyze the quality of posterior‐frontal waves, the spatiotemporal phase pattern was measured over the head midline. The wave quality was defined as the consistency of the spatiotemporal phase pattern during consecutive time intervals, and the quality of entrainment was defined as the intensity of the power spectral density at the input frequency.ResultDuring the resting state, different wave patterns traveling across the frontoparietal link are canceled out. However, visual stimulation invigorates the forward wave from the sensory (posterior – visual) region to the upstream area (frontal lobe) at the target frequency compared to the baseline. Meanwhile, in contrast to the forward wave, traveling wave in the backward direction does not show noticeable presence at the stimulation frequency. Furthermore, as the entrainment quality increases, the wave pattern consistency is improved for all stimulating frequencies (Figs. 1, 2).ConclusionThe forward wave induced during non‐invasive visual stimulation represents long‐range activity along the posterior‐frontal pathway known to be activated during sensory processing and inference. The observed correlation between the wave’s quality and the quality of entrainment at the target frequency points to the mechanism underlying the therapeutic effects of gamma entrainment.

Are acoustics enough? Semantic effects on auditory salience in natural scenes

Auditory salience is a fundamental property of a sound that allows it to grab a listener's attention regardless of their attentional state or behavioral goals. While previous research has shed light on acoustic factors influencing auditory salience, the semantic dimensions of this phenomenon have remained relatively unexplored owing both to the complexity of measuring salience in audition as well as limited focus on complex natural scenes. In this study, we examine the relationship between acoustic, contextual, and semantic attributes and their impact on the auditory salience of natural audio scenes using a dichotic listening paradigm. The experiments present acoustic scenes in forward and backward directions; the latter allows to diminish semantic effects, providing a counterpoint to the effects observed in forward scenes. The behavioral data collected from a crowd-sourced platform reveal a striking convergence in temporal salience maps for certain sound events, while marked disparities emerge in others. Our main hypothesis posits that differences in the perceptual salience of events are predominantly driven by semantic and contextual cues, particularly evident in those cases displaying substantial disparities between forward and backward presentations. Conversely, events exhibiting a high degree of alignment can largely be attributed to low-level acoustic attributes. To evaluate this hypothesis, we employ analytical techniques that combine rich low-level mappings from acoustic profiles with high-level embeddings extracted from a deep neural network. This integrated approach captures both acoustic and semantic attributes of acoustic scenes along with their temporal trajectories. The results demonstrate that perceptual salience is a careful interplay between low-level and high-level attributes that shapes which moments stand out in a natural soundscape. Furthermore, our findings underscore the important role of longer-term context as a critical component of auditory salience, enabling us to discern and adapt to temporal regularities within an acoustic scene. The experimental and model-based validation of semantic factors of salience paves the way for a complete understanding of auditory salience. Ultimately, the empirical and computational analyses have implications for developing large-scale models for auditory salience and audio analytics.

On-chip interference of scattering from two individual molecules

Integrated photonic circuits offer a promising route for studying coherent cooperative effects of a controlled collection of quantum emitters. However, spectral inhomogeneities, decoherence, and material incompatibilities in the solid state make this a nontrivial task. Here, we demonstrate efficient coupling of a pair of Fourier-limited organic molecules embedded in a polyethylene film to a TiO2 microdisc resonator on a glass chip. Moreover, we tune the resonance frequencies of the emitters with respect to that of the microresonator by employing nanofabricated electrodes. For two molecules separated by a distance of about 8 µm and an optical phase difference of about π/2, we report on a large collective extinction of the incident light in the forward direction and the destructive interference of its scattering in the backward direction. Our work sets the ground for coherent coupling of several quantum emitters via a common mode and realization of polymer-based hybrid quantum photonic circuits.

RNN-BIRNN-LSTM based spectrum sensing for proficient data transmission in cognitive radio

With the advancements that are taking place in the wireless communications field, the number of users who are utilizing resources is also increasing; as a result, the wireless spectrum is scarce. In this article, RNN-BIRNN-LSTM with Gaussian noise (RBRLG)-based spectrum sensing (SS) for QAM16, CPFSK, QPSK, and BPSK modulation schemes has been proposed. Recurrent Neural Networks for sequential data use recurrent connections to capture temporal dependencies; BIRNN extends RNN by processing input in both forward and backward directions, capturing past and future context; and finally, LSTM, using specialized memory cells, efficiently manages long-term dependencies in sequential data. In order to create a spectrum sensing model, RNN units, BIRNN units, and LSTM units were cascaded in this paper. Open-source dataset RadioML2016.10B has been used for the investigation. The experimental results show that the proposed RBRLG-based SS has higher accuracy on the dataset especially at -20 dB, a lower probability of miss detection percentage of 7.19 %, and a lower sensing error (SE) percentage of 10.80 % for QAM16. The evaluation of performance indicators for our suggested model, such as the F1 Score, Jaccard Index, and Matthew's correlation coefficient, demonstrates that the proposed model provides improved SS performance.

Induction of ice VII structure with secondary shock compression by backward Raman scattering in plasmas

Forward stimulated Raman scattering and backward stimulated Raman scattering (BSRS) are measured when an intense 532 nm nanosecond pulsed laser is focused into water and heavy water. The investigation reveals a significant observation: the formation of the ice VII structure exclusively occurs in the backward direction when optical breakdown takes place, provided that the input energy falls below 90 mJ for liquid water or 75 mJ for heavy water. This phase transition is attributed to secondary shock compression, which comes from energy transfer and compression between the BSRS in plasmas with the pump laser. The optical breakdown experiment under pre-pressure reveals that the shock compression in the back direction is approximately 2.3 times that of the forward direction. This research is useful for shock compression and dynamics in plasmas.

Modeling Long-Distance Forward and Backward Diffusion Processes in Tracer Transport Using the Fractional Laplacian on Bounded Domains

Recent studies have emphasized the importance of the long-distance diffusion model in characterizing tracer transport occurring within both subsurface and surface environments, particularly in heterogeneous systems. Long-distance diffusion, often referred to as nonlocal diffusion, signifies that tracer particles may experience a considerably long distance in either the forward or backward direction along preferential channels during the transport. The classical advection–diffusion (ADE) model has been widely used to describe tracer transport; however, they often fall short in capturing the intricacies of nonlocal diffusion processes. The fractional operator has gained recognition among hydrologists due to its potential to capture distinct mechanisms of transport and storage for tracer particles exhibiting nonlocal dynamics. However, the hypersingularity of the fractional Laplacian operator presents considerable difficulties in its numerical approximation in bounded domains. This study focuses on the development and application of the fractional Laplacian-based model to characterize nonlocal tracer transport behavior, specifically considering both forward and backward diffusion processes on bounded domains. The Riesz fractional Laplacian provides a mathematical framework for describing tracer diffusion processes on a bounded domain, and a novel finite difference method (FDM) is introduced as an effective numerical solver for addressing the fractional Laplacian-based model. Applications reveal that the fractional Laplacian-based model can effectively capture the observed nonlocal tracer transport behavior in a heterogeneous system, and nonlocal tracer transport exhibits dynamic characteristics, influenced by the evolving heterogeneity of the media at various temporal scales.

Identifying Phage Sequences From Metagenomic Data Using Deep Neural Network With Word Embedding and Attention Mechanism.

Phages are the functional viruses that infect bacteria and they play important roles in microbial communities and ecosystems. Phage research has attracted great attention due to the wide applications of phage therapy in treating bacterial infection in recent years. Metagenomics sequencing technique can sequence microbial communities directly from an environmental sample. Identifying phage sequences from metagenomic data is a vital step in the downstream of phage analysis. However, the existing methods for phage identification suffer from some limitations in the utilization of the phage feature for prediction, and therefore their prediction performance still need to be improved further. In this article, we propose a novel deep neural network (called MetaPhaPred) for identifying phages from metagenomic data. In MetaPhaPred, we first use a word embedding technique to encode the metagenomic sequences into word vectors, extracting the latent feature vectors of DNA words. Then, we design a deep neural network with a convolutional neural network (CNN) to capture the feature maps in sequences, and with a bi-directional long short-term memory network (Bi-LSTM) to capture the long-term dependencies between features from both forward and backward directions. The feature map consists of a set of feature patterns, each of which is the weighted feature extracted by a convolution filter with convolution kernels in the CNN slide along the input feature vectors. Next, an attention mechanism is used to enhance contributions of important features. Experimental results on both simulated and real metagenomic data with different lengths demonstrate the superiority of the proposed MetaPhaPred over the state-of-the-art methods in identifying phage sequences.

Experimental investigation of two-phase heat transfer in saw-tooth copper microchannels

Due to the confinement effect, vapor backflow is ubiquitous in flow boiling process in microscale confined domains. This, in turn, severely deteriorate the flow boiling performances. To solve this dilemma, many microchannel configurations have been exploited to regulate two-phase flows such as inlet orifices and auxiliary channels. However, the inlet orifices would lead to significant increase of flow resistance, scarifying the pumping power. In this study, periodic symmetric saw-tooth structure is designed and fabricated along sidewalls of parallel copper microchannels to effectively suppress the vapor backflow without the cost of pressure drop. The effects of this periodic symmetric saw-tooth structure on suppression of vapor backflow and two-phase flow mixing are studied in both forward and reverse directions. The flow boiling performances of this saw-tooth microchannel configuration was experimentally investigated for total inlet flow rates ranging from 30 to 70 ml/min (mass flux ranging from 183.3 kg/m2·s to 427.7 kg/m2·s). The experimental results and visualization study demonstrate that the successful suppression of vapor backflow in the forward direction and enhancement of two-phase flow mixing in the backward direction can dramatically enhance flow boiling performance. Significant boost on both HTC and CHF is demonstrated. A CHF of 217 W/cm2 is demonstrated at 70 ml/min in the forward direction. Also, significant difference in CHF is observed between the two flow directions as the further increase of flow rates. Compared to conventional plain wall microchannels, the CHF and HTC of this study can be significantly enhanced by ∼77.4 % and ∼250 %, respectively. Note that this improved boiling performance is achieved without sacrificing pressure drops.

Analysis and Application of the Electromagnetic Wave Propagation, Fields, and Dispersion Relation in an Elliptical Chiro Plasma Waveguide Immersed in Magnetized Plasma

AbstractThis research proposes and investigates an elliptical waveguide filled with chiro plasma as its core and magnetized plasma as its clad region. The clad region is in the constant infinite magnetic field, and its direction is the same as the wave propagation in the chiro plasma elliptical waveguide. The electromagnetic wave propagation in the considered waveguide is studied. The expressions for electromagnetic field components in the chiro plasma core and magnetized plasma cladding are derived. The dispersion relations for the hybrid modes are calculated considering appropriate boundary conditions at the chiro plasma and magnetized plasma interface. The behavior of the energy flux and the dispersion curves are numerically and graphically studied. It is seen that the magnitude of the power density decreases with the increase of the cyclotron frequency and it increases with the increase of the plasma frequency and supports power flow in the backward direction for the considered mode. Furthermore, it is shown higher values of the chirality parameter cause the magnitude of the power flux to increase in the backward direction.

A multimaterial sensor with Janus characteristics based on enhanced particle swarm optimization algorithm

This paper presents an enhanced particle swarm optimization (EPSO) algorithm for optimizing the parameters of a layered photonic structure. By dynamically adjusting the thickness and refractive index of each dielectric layer, the phase and absorption properties of the transmitted electromagnetic waves (EWs) can be modified, effectively achieving high absorption rates by incorporating defects formed by the Kerr nonlinear material. The proposed EPSO algorithm facilitates the identification of the global optimal solution, resulting in the formation of sharp absorption peaks with values exceeding 0.9 for incident EWs from various directions. Leveraging the Janus properties, the EW exhibits distinct physical characteristics when incident from the front and back directions, enabling the creation of sensors tailored for thickness, angle, and pressure sensing. The forward angle sensing demonstrates a high sensitivity (S) of 0.32 nm/degree, a quality factor (Q) of 543.9, and a figure of merit (FOM) of 0.32 degree−1. Both pressure and thickness can be sensed in both forward and backward directions, with S of 5.46 nm/GPa and 10.24 nm/GPa, mean Q of 563.9 and 316.7, and FOM of 5.5 GPa−1 and 3.3 GPa−1, respectively. Thus, it can be stated that the proposed EPSO holds promising prospects for optical sensor design.

Thermal boundary resistance and thermal rectification in VACNT arrays integrated with SnZn alloys

Thermal rectification (TR) phenomena in carbon nanotubes (CNTs) have been previously foreseen through theoretical predictions; however, its experimental realization in bulk CNT arrays remains relatively unexplored. Herein, we have synthesized vertically aligned carbon nanotube (VACNT) arrays of ∼ 4.5 mm in length on a 4-inch silicon wafer by a combined bubble-assisted chemical vapor deposition method. By integrating these VACNT arrays with SnZn alloys, we have successfully developed devices capable of functioning across a wide temperature range spanning from 200 °C to 400 °C. Notably, the thermal boundary resistances (TBR) between the VACNTs and SnZn alloy exhibit pronounced dependence on the alloy's composition, exhibiting variations ranging from 0.12 cm2KW−1 to 1.12 cm2KW−1. Of particular significance, the TBRs of Sn50Zn50/VACNT compounds in the forward direction were found to fall within the range of 0.63–0.98 cm2KW−1 in the temperature range from120 °C to 180 °C, while in the backward direction, they exhibited values in the range of 0.13–0.34 cm2KW−1. These contrasting TBR values highlight a marked thermal rectification performance with a substantial TR coefficient between 0.49 and 0.66. Our comprehensive investigation sheds valuable insights into the TR effects within VACNTs and metal/alloy interfaces, presenting a promising avenue for the development of future thermal logic circuits and thermal transistors.

Mobility and erosion of granular flows travelling on an erodible substrate: Insights from the small-scale flume experiments

Rock avalanches are extremely rapid, flow-like movements of dry debris mass with extreme destructive potential. Among the dynamical aspects of rock avalanches still inadequately understood, the flow along an erodible substrate stands out as a particularly significant one. We carried out a series of flume experiments to investigate the mobility and the erosion of granular flows on an erodible substrate. It was found that granular flows with a large total mass could evolve into a stable multi-layer flow when suffering the enhanced basal resistance (e.g., loose and dry erodible substrate). Without the variation of the properties of erodible material, the increase of total mass (from 5 kg to 15 kg) as well as the reduction of grain size (from 4 to 8 mm to 1–2 mm) has a positive influence on the mobility of the granular flows (max. 12% and max. 3.4% growths in runout distance, respectively), emphasizing the important roles of both the event magnitude and the internal friction. Total mass and the grain size have prominent influences also on the erosion effect of granular flow. An increase in flow mass causes an enhancement of the eroded depth and of the expansion in both backward and forward directions, while grain size enhanced only forward expansion in addition to the eroded depth. Altogether, the experiments indicate that an erodible substrate may have dramatic effects on the dynamics of an experimental granular flow. When applied to the field, they point to the importance of the nature of the basal material onto which a natural landslide collapses.

On space-time media that compute their own inverse

We show that it is possible to design a space-time medium such that the time scattering anticipates the space scattering in the medium and produces the exact inverse for the space scattering. Probing such a medium with a single broadband pulse thus also results in a single broadband pulse on the other side of the space-time heterogeneity. The transmission coefficient of such systems is unity. The reflection coefficient is non-zero, however, as both the time and spatial boundaries scatter waves in the backward direction. The time boundaries thus add energy. To construct a single pulse on the other side of a stack bounded by n interfaces, 2(n−1)−1 additional well-scaled and well-timed pulses need to be emitted following the main pulse, to cancel multiple reflections in the forward direction. Scattering at a time boundary doubles the number of wavepackets propagating in a medium. Furthermore, time refraction and reflection coefficients have the form required to produce well-scaled pulses. The required 2(n−1)−1 pulses can thus be efficiently generated by a single pulse interacting with n time boundaries. The contrasts across the time boundaries are the spatial contrasts in reverse. The time “thicknesses” of the boundaries are a simple function of the layer velocities.

Time-domain Brillouin scattering theory for probe light and acoustic beams propagating at an angle and acousto-optic interaction at material interfaces

A theory has been developed to interpret time-domain Brillouin scattering (TDBS) experiments involving coherent acoustic pulse (CAP) and light pulse beams propagating at an angle to each other. It predicts the influence of the directivity pattern of their acousto-optic interaction on TDBS signals when heterodyne detection of acoustically scattered light is in backward direction to incident light. The theory reveals relationships between the carrier frequency, amplitude and duration of acoustically induced ”wave packets” in light transient reflectivity signals, and factors such as CAP duration, widths of light and sound beams, and their interaction angle. It describes the transient dynamics of these wave packets when the light and CAP encounter material interfaces, and how the light scattering by the incident CAP transforms into scattering by the reflected and transmitted CAPs. The theory suggests that single-point TDBS experiments can determine not only depth positions of buried interfaces but also their local inclinations/orientations.

Robust multi-step wind speed forecasting based on a graph-based data reconstruction deep learning method

Against global warming, wind energy has increasingly become a stable form of power supply. Accurate prediction of wind speed is crucial for turbine control and wind farm dispatch, contributing to stable and continued wind energy utilization. However, it is very difficult to accomplish satisfactory wind speed forecasting, especially multi-step forecasting, due to the stochastic, random and volatile characteristic of wind speed series with complex fluctuations. This study is elaborated to propose a novel method based on “data graph” reconstruction and long short term memory (LSTM) network, to achieve accurate and robust multi-step wind speed forecasting. To obtain implicit correlations between wind speed series, the time series data are reconstructed into matrices like “data graphs”. To achieve better computing efficiency and forecasting accuracy, the convolutional neural network (CNN) is adopted to extract the features in the “data graphs”. Then the extracted data graph features are imported into the bidirectional-LSTM (bi-LSTM) network module, which takes the input in forward and backward directions, respectively, to extract more temporal information. For adequate performance assessment, experiments are carried out on data sets of an actual wind farm located in a mountainous region in China. The results show that the proposed method outperforms classic meta-model based and hybrid-model based methods in accuracy, stability and computing efficiency. The results reveal that the data graph reconstruction combined with the CNN is able to extract the hidden features of the wind speed time series data. The proposed CNN-bi-LSTM method effectively improve the multi-step wind speed prediction accuracy.

Asymmetric phase modulation of light with parity-symmetry broken metasurfaces

The design of wavefront-shaping devices is conventionally approached using real-frequency modeling. However, since these devices interact with light through radiative channels, they are by default non-Hermitian objects having complex eigenvalues (poles and zeros) that are marked by phase singularities in a complex frequency plane. Here, by using temporal coupled mode theory, we derive analytical expressions allowing to predict the location of these phase singularities in a complex plane and as a result, allowing to control the induced phase modulation of light. In particular, we show that spatial inversion symmetry breaking—implemented herein by controlling the coupling efficiency between input and output radiative channels of two-port components called metasurfaces—lifts the degeneracy of reflection zeros in forward and backward directions, and introduces a complex singularity with a positive imaginary part necessary for a full 2π-phase gradient. Our work establishes a general framework to predict and study the response of resonant systems in photonics and metaoptics.

Non-reciprocal electromagnetic metasurface based on the nonlinearity of a liquid metamaterial.

In this Letter, we propose the design of a non-reciprocal electromagnetic metasurface, which uses a highly nonlinear liquid metamaterial as a source of non-reciprocity. We show that the proposed metasurface, whose thickness is comparable to the wavelength, can exhibit a difference between the transmission coefficients in the forward and backward directions of up to 0.95. Moreover, the particularly high nonlinearity of the liquid metamaterial enables the radiation power required to induce the nonlinear effects to be considerably reduced compared with natural materials. The feasibility of the proposed metasurface has been verified by numerical simulations.