Modern Physics Letters B

A tunable narrowband metamaterial perfect absorber (NMPA) with single absorption peak at both normal incidence and oblique incidence is proposed. The spectral responses of the designed NMPA are calculated using finite-difference time-domain (FDTD) method. By using an Ag guided-mode resonance grating layer with great fill factor, the designed NMPA exhibits single resonance peak, which is converted to heat due to the strong surface plasmon resonance around the Ag grating and the Ag substrate. An NMPA sample is fabricated and the spectral responses are measured to verify the theoretical results. The experimental results are consistent with the theoretical ones.

In this paper, Wien’s displacement law as one of the most important laws of thermal radiation, for which Wien has won the Nobel Prize in Physics, is studied and derived from the perspective of phase transition by using catastrophe theory. This paper describes in detail how the control variable causes the phase transition of the system potential function and the main indexes for judging whether the phase transition occurs. By extending the control variable in the catastrophe theory affecting the thermal radiation into multi-parameters form, the function equilibrium curve of the blackbody radiation is solved, and then the two expressions of Wien’s displacement law including wavelength-temperature and wavelength-temperature are derived theoretically. Furthermore, a phase transition method is proposed to study the thermal radiation of blackbody. This not only provides a new perspective for the research of thermal radiation, but also provides a new idea for the study of other phase transitions.

Recently, Jiang et al. proposed a quantum cryptography protocol [Mod. Phys. Lett. B 32 (2018) 1850125] which can implement the equal exchange of secret information between the two parties with the help of semi-trusted third party. Here, it will be shown that the protocol is insecure and has the drawback of information leakage.

In order to study the hysteresis nonlinear characteristics of piezoelectric actuators, a novel hybrid modeling method based on Long-Short-Term Memory (LSTM) and Nonlinear autoregressive with external input (NARX) neural networks is proposed. First, the input–output curve between the applied voltage and the produced angle of a piezoelectric tip/tilt mirror is measured. Second, two hysteresis models named LSTM and NARX neural networks were, respectively, established mathematically, and then were tested and verified experimentally. Third, a novel adaptive weighted hybrid hysteresis model which combines LSTM and NARX neural networks was proposed through analyzing and comparing the unique characteristics of the above two hysteresis models. The proposed hybrid model combines LSTM’s ability to approximate nonlinear static hysteresis and NARX’s high dynamic-fitting ability. Experimental results show that the RMS errors of the hybrid model are smaller than those of LSTM model and NARX model. That is to say, the proposed hybrid model has a relatively high accuracy. Compared with the traditional differential equation-based and operator-based hysteresis models, the presented hybrid neural network method has higher flexibility and accuracy in modeling performance, and is a more promising method for modeling piezoelectric hysteresis.

We propose a novel bio-sensor structure composed of double sided-wall Bragg gratings and dual-slot-micro-ring waveguides. The slot waveguide is a better choice to interact the bio-material under investigation with the propagating light with in the slot region. The incident light field propagates clockwise through the slot micro-ring resonator, the reflection light field propagates counterclockwise in the slot Bragg grating. By optimizing the geometric parameters of the device, the spectral response is tailored to obtain a sharp resonant peak simulated by the finite- difference time-domain (FDTD) method. The spectrum can be tuned not only by geometrically changing the couple distance in slot Bragg grating resonator, but also by dynamically altering the depth and number of the Bragg grating. Furthermore, the device is easy to yield an extinction ratio of 11 dB, a FWHM of 1.1 nm and a quality factor of $1.422\times 10^3$. The device with a small footprint can enable integration with some photonic devices on a chip and have great promising for applications including tunable sensors, slow-light devices and optical communication.

Deterministic weighted networks have been widely used to model real-world complex systems. In this paper, we study the weighted iterated pentagonal networks. From the construction of the network, we derive recursive relations of all eigenvalues and their multiplicities of its normalized Laplacian matrix from the two successive generations of the weighted iterated pentagonal networks. As applications of spectra of the normalized Laplacian matrix, we study the Kemeny’s constant, the multiplicative degree-Kirchhoff index, and the number of weighted spanning trees and derive their exact closed-form expressions for the weighted iterated pentagonal networks.

In biological systems, gene expression is an important subject. In order to clarify the specific process of gene expression, mathematical tools are needed to simulate the process. The Boolean network (BN) is a good mathematical tool. In this paper, we study a Boolean network with intermittent perturbations. This is of great significance for studying genetic mutations in bioengineering. The expression of genes in the internal system of a living being is a very complicated process, and it is clear that the process is trans-ageal for humans. Through the intermittent control and pulse control of the BN, we can obtain the trajectory of gene expression better and faster, which will provide a very important theoretical basis for our next research.

The tendency to improve the properties of insulating materials by incorporating inorganic nanoparticles has become necessary in order to design new insulation systems. In this study, PVC/TiO₂-based nanocomposites with different loadings (3, 5 and 10 wt.%) of TiO₂ nanoparticles were prepared by the solution mixing method. The morphology of the prepared nanocomposites was studied by Atomic Force Microscope (AFM). Experimentally, it was found that as the concentration increases, the size of the surface structural elements and particle size increases. Photoluminescence (PL) analysis of samples shows improvement compared to the pristine polymer. Furthermore, PL intensity for nanocomposites increases depending on the concentration and saturation occurs at a certain amount of titanium dioxide nanoparticles. The increase in luminescence intensity till a certain nanoparticle content is due to the growth of the luminescent surface area. Further saturation is explained by the increase in particle size with no increase or a slight reduction in surface area. Dielectric properties of nanocomposites were studied. It was found that dielectric permittivity of the materials increases as the nanoparticle volume content increases and it reaches at its highest value for the nanocomposites with 3% nanoparticle content. The optical properties of the polymer and nanocomposite films were studied in the region 200 nm to 600 nm. It was found that the PVC/TiO₂ nanocomposites showed enhancement in the absorbance intensities which was more significant for the nanocomposites with higher nanoparticle content compared to the pristine polymer. Furthermore, absorption spectra were used to calculate the optical bandgap of the prepared nanocomposite films and redshift observed in the calculated values of bandgap for nanocomposites. Consequently, it was proved that by incorporating TiO₂ nanoparticles into the polymer matrix, the spectral region of the samples can be expanded resulting in broadened application of such systems in various fields of science and technology.

In Big data domain, platform dependency can alter the behavior of the business. It is because of the different kinds (Structured, Semi-structured and Unstructured) and characteristics of the data. By the traditional infrastructure, different kinds of data cannot be processed simultaneously due to their platform dependency for a particular task. Therefore, the responsibility of selecting suitable tools lies with the user. The variety of data generated by different sources requires the selection of suitable tools without human intervention. Further, these tools also face the limitation of recourses to deal with a large volume of data. This limitation of resources affects the performance of the tools in terms of execution time. Therefore, in this work, we proposed a model in which different data analytics tools share a common infrastructure to provide data independence and resource sharing environment, i.e. the proposed model shares common (Hybrid) Hadoop Distributed File System (HDFS) between three Name-Node (Master Node), three Data-Node and one Client-node, which works under the DeMilitarized zone (DMZ). To realize this model, we have implemented Mahout, R-Hadoop and Splunk sharing a common HDFS. Further using our model, we run $K$-means clustering, Naïve Bayes and recommender algorithms on three different datasets, movie rating, newsgroup, and Spam SMS dataset, representing structured, semi-structured and unstructured, respectively. Our model selected the appropriate tool, e.g. Mahout to run on the newsgroup dataset as other tools cannot run on this data. This shows that our model provides data independence. Further results of our proposed model are compared with the legacy (individual) model in terms of execution time and scalability. The improved performance of the proposed model establishes the hypothesis that our model overcomes the limitation of the resources of the legacy model.

This paper studies an inverse problem of reconstructing a sound-soft obstacle from a homogeneous medium. We deal with it in the framework of statistical inversion and adopt an iterative ensemble Kalman algorithm to reconstruct the boundary. Some numerical examples show that the algorithm is effective and it can recover the shape of the boundary using one or several of the incident waves.

Metasurfaces have recently emerged to realize flat optical components with various functions and providing potential capabilities in manufacturing active devices. In this paper, a doublet lens for mid-infrared wavelength with tunable focal length has been proposed. The designed metalens consists of two dielectric metalenses with different focal lengths patterned on a phase-change materials Ge₂Sb₁Te₄. The doublet lens is proved to have above 13% change in the focal length with the crystalline states shifting of the Ge₂Sb₁Te₄. And the designed doublet lens can be operated in mid-infrared region from 2.41 $\mu$m to 2.60 $\mu$m. In addition, chromatic calibration can be achieved by adjusting the crystalline phases of the Ge₂Sb₁Te₄. This compatible metalens promises potential for a wide range of applications in MIR region such as multi-spectrum imaging, optical coupling system and micrography.

The effect of magnetic field on the polarization effect of black phosphorene is studied. The ground state energy and the relevant energy bandgap formula of carrier and carrier–phonon interaction system is derived in turn, and the effect of applied magnetic field on ground state energy and bandgap is also investigated, by the method of variational method, LLP unitary transformation method and linear combination operator method. When the substrate is given, the ground state energy and the relevant bandgap of the carrier–phonon interaction system changes with the magnetic induction intensity, phonon energy and cutoff wave vector. It can be shown by numerical calculation: The ground state energy and the relevant bandgap of the Hole and the Hole–phonon interaction system in black phosphorene increases with increase in magnetic induction intensity $B$. The ground state energy of the Hole, Hole–phonon system and the relevant bandgap are different when the substrate is different. Under the action of a magnetic field, the ground state energy of the Hole and Hole–phonon system and bandgap decreases with increase in phonon energy and increases with increase in cutoff wave vector when the substrate is fixed.

Image captioning is a multidisciplinary artificial intelligence (AI) research task that has captures the interest of both image and natural language processing experts. Image captioning is a complex problem as it sometimes requires accessing the information that may not be directly visualized in a given scene. It possibly will require common sense interpretation or the detailed knowledge about the object present in image. In this paper, we have given a method that utilizes both visual and external knowledge from knowledge bases such as ConceptNet for better description the images. We demonstrated the usefulness of the method on two publicly available datasets; Flickr8k and Flickr30k.The results explain that the proposed model outperforms the state-of-the art approaches for generating image captions. At last, we will talk about possible future prospects in image captioning.

The evolution of atomic structures and its correlation with the kinetic fragility of liquid tantalum (Ta) during cooling were investigated through molecular dynamics simulations. Pair distribution function, angular distribution function, and largest standard cluster analysis were used to characterize the atomic configurations in the Ta metal system. Results revealed that canonical Kasper clusters with a coordination number of $\ge$12 play a critical role in the formation of Ta monoatomic metallic glasses. Similar to the pattern observed in many multi-component metallic glass-forming liquids, the three-stage evolution pattern of the self-diffusion coefficient could be observed during cooling. The fragile-to-strong (F–S) transition temperature of liquid Ta is identified to be $T_{\mathrm{\text{f-s}}}\approx 1.18T_g$. The possible structural reason for the strong-to-fragile liquid transition is correlated with the formation of abundant Kasper medium-range orders (MROs) and their zigzag competition with the loose configurations in liquid regions. The F–S transition is attributed to the success of MROs in the competition and their subsequent rapid growth.