Juveriya Parmar

Tuning the spectral and directional characteristics of thermal emission is critical for advancing technologies such as thermophotovoltaics (TPVs), passive thermal radiative cooling (PTRC), and solar thermophotovoltaics (STPVs), yet scalable fabrication methods remain limited. Here, femtosecond laser surface processing (FLSP), a top‐down ablation and re‐solidification approach is employed, to create mound‐shaped surface microstructures on titanium (Ti) surfaces. By varying laser fluence and pulse count, spectrally selective and omnidirectional high emissivity (⩾0.9) in the mid‐infrared range (7.5–14 µm) is achieved, which increases with structure height. To understand the underlying physics, finite element modeling (FEM) is conducted, guided by structural and optical parameters extracted using Mueller matrix spectroscopic ellipsometry and modeled via the anisotropic Bruggeman effective medium approximation. Simulations reveal that height, base length, periodicity, and oxide shell contribute to the emergence of plasmonic and interband resonance modes spanning the UV to mid‐IR range. Comprehensive material characterizations, including SEM, FIB‐EDS, and XPS, confirm the formation of a conformal Ti–TiO _x core‐shell interface, which activates mid‐IR resonance modes in agreement with FEM predictions. The proposed Ti‐based metamaterial platform provides a scalable strategy for engineering thermal emission in next‐generation energy systems.

The need for high-speed communication has created a way to design THz antennas that operate at high frequencies, speeds, and data rates. In this manuscript, a THz MIMO antenna is designed using a metamaterial. The two-port antenna design proposed uses a complementary split-ring resonator patch. The design results are also compared with a simple patch antenna to show the improvement. The design shows a better isolation of 50 dB. A broadband width of 8.3 THz is achieved using this complementary split-ring resonator design. The percentage bandwidth is 90%, showing an ultrabroadband response. The highest gain of 10.34 dB is achieved with this design. Structural parametric optimization is applied to the complementary split-ring resonator MIMO antenna design. The designed antenna is also optimized by applying parametric optimization to different geometrical parameters. The optimized design has a 20 µm ground plane, 14 µm outer ring width, 6 µm inner ring width, and 1.6 µm substrate thickness. The proposed antenna with its broadband width, high gain, and high isolation could be applied in high-speed communication devices.

In this paper, we have proposed graphene metasurfaces capable of achieving an encoding of 4 bits. A graphene metasurface placed over a glass substrate is presented. The proposed graphene metasurface can also be applied for the detection of Sodium Cyanide (NaCN), Potassium Cyanide (KCN), and Hydrogen Cyanide (HCN). The detection capacity of all three graphene metasurface sensor (GMSS) structures has been investigated and the structure with higher functionality has been identified. In addition, the device as a sensor has been investigated based on several parameters and it has been observed that the proposed device generates comparatively higher results. The proposed device has multifunctionality and can be employed either as a sensor or as an encoder. We claim that this is the first graphene metasurface inspired 4-bit encoding device as per our knowledge and can be employed in various applications. The anti-counterfeiting, dynamic information encryption, information authentication, optical data storage, and other related fields stand to benefit greatly from the proposed tunable GMSS and its information encryption and anticounterfeiting applications.

Graphene twistronics using multilayer graphene is presented in such a way that it provides a metamaterial effect. This manuscript also analyzes the prediction of behavior using machine learning. The metamaterial effect is achieved by twisting the graphene layers. Graphene twistronics is a new concept for changing the electrical and optical properties of bilayer graphene by applying a small angle twist between the layers. The angle twists of 5°, 10°, and 15° are analyzed for the proposed graphene twistronics design. Tuning in the absorption spectrum is achieved by applying small twists to the angles of the bilayer graphene. Results in the form of absorption, conductivity, permeability, permittivity, and impedance are presented for different twist angles. The twisted graphene layers also demonstrate negative permittivity and negative permeability, similar to metamaterials. These negative refraction properties of graphene twistronics provide flexibility and transparency, which can be applied in photovoltaic applications. Machine-learning-based regression models are used to reduce the simulation time and resources. The results show that a regression model can reliably estimate intermediate wavelength absorption values with an R² of 0.9999.

A graphene disk metasurface-inspired refractive index sensor (RIS) with a subwavelength structure is numerically investigated to enhance the functionality of flexible metasurface in the biosensor sector. The main aim behind the sensor development is to detect amino acids with high sensitivity. The results in form of transmittance and the electric field intensity are carried out to verify the sensor’s performance. The optimal design of the proposed sensor is also obtained by varying several structural parameters such as glass-based substrate thickness, the inner radius of the graphene disk metasurface, and the angle of incidence. The proposed sensor is also wide-angle insensitive for the angle of incidence ranging from 0° to 60°. Furthermore, the sensor’s attributes are analyzed based on numerous parameters with an achieved maximum sensitivity of 333.33 GHz/RIU, Figure of Merit (FOM) of 3.11 RIU ^-1 , and Q-factor of 7.3 are achieved. As a result, these insights offered an enhanced direction for designing metasurface biosensors with a high Q-factor and FOM with high sensitivity for the detection of amino acids.

In the presented study, a graphene metasurface-based refractive index sensor (RIS) has been developed and built, which is highly beneficial in urine observation. Pregnant and non-pregnant urine samples were simulated and analyzed using effective refractive indices (RIs) of 1.335, 1.34, 1.342, and 1.343. Analysis of the sensor’s sensitivity, resonance frequency, resolution, detection limit, quality factor (QF), figure of merit (FOM), and other parameters has been done. In addition, the numerical investigations employ the Finite Element Method (FEM). In addition to this, a geometrical variation to attain a highly performing sensor performance is also carried out to demonstrate the effect of various structural parameters on sensitivity, and in a process, optimal parameters are also identified. With this investigation, we were able to obtain the greatest possible sensitivity response value of 200 GHz/RIU, as well as the highest QF and a FOM, and the highest resolution and detection limit of 11.97, 5.12 RIU-1, 0.15 THz, and 0.88 RIU, respectively. Along with that, an innovative realization of the NOR gate has been demonstrated by employing graphene with various graphene chemical potential values.

Frequency reconfigurability and high gain are the two essential parameters of any antenna design, and these two parameters are successfully achieved in the antenna presented in this manuscript. The two RF switching diodes are used to alter the charge distribution over the patch region to achieve frequency reconfigurability. The fabrication carried out using the FR-4 material keeps the antenna cost low. The performance of the presented work is analyzed in terms of reflectance coefficient, total gain, bandwidth, directivity, fractional bandwidth, and normalized directivity. The novelty in the presented work is the filling of copper and liquid-based split-ring resonators in superstrate regions over the patch area to identify the performance improvement. The presented design provides the maximum frequency reconfigurability of 550 MHz, a minimum reflectance coefficient of −44.821 dB, and a maximum bandwidth of 462 MHz. The addition of superstrate layers will enhance the gain and maximum gain of 3.49 dB. The presented novel work will provide the multiband behavior which targets the different wireless communication applications like 5G communication and WiMAX.

This century has introduced very deadly, dangerous, and infectious diseases to humankind such as the influenza virus, Ebola virus, Zika virus, and the most infectious SARS-CoV-2 commonly known as COVID-19 and have caused epidemics and pandemics across the globe. For some of these diseases, proper medications, and vaccinations are missing and the early detection of these viruses will be critical to saving the patients. And even the vaccines are available for COVID-19, the new variants of COVID-19 such as Delta, and Omicron are spreading at large. The available virus detection techniques take a long time, are costly, and complex and some of them generates false negative or false positive that might cost patients their lives. The biosensor technique is one of the best qualified to address this difficult challenge. In this systematic review, we have summarized recent advancements in biosensor-based detection of these pandemic viruses including COVID-19. Biosensors are emerging as efficient and economical analytical diagnostic instruments for early-stage illness detection. They are highly suitable for applications related to healthcare, wearable electronics, safety, environment, military, and agriculture. We strongly believe that these insights will aid in the study and development of a new generation of adaptable virus biosensors for fellow researchers.

Machine learning is the latest approach to optimize the performance of absorbers, sensors, etc. A sensor with behavior prediction using polynomial regression is presented. Three different variations of metasurfaces namely double split-ring resonator, single split ring resonator, split ring resonator with thin wire are analyzed. The proposed design aims to achieve the highest sensitivity by observing different designs and different parameter variation. The highest sensitivity is achieved for double split-ring resonator and single split ring resonator designs. The change in thickness of different parameter affect the absorption and the highest sensitivity is calculated based on these variations. The polynomial regression (PR) model is employed to predict the absorption values for assorted combinations of intermediate wavelength values with angle variation, substrate thickness, substrate length, substrate width, graphene potential, and resonator thickness values. Test Cases R-30 and R-50 are evaluated using R² score metric to assess the effectiveness of PR model for predicting the values of absorption. R² score close to 1.0 is achieved for all the experiments at a higher (more than 5) polynomial degree, which proves the prediction efficiency of a regression model. The proposed biosensor designed with a PR model can be applied in biomedical applications for hemoglobin detection.

A highly efficient psi‐shaped solar energy absorber in the paper is developed. This structure is designed using titanium‐based psi shaped resonator, SiO₂ based substrate, and Tungsten metal‐based base layer to achieve a near‐perfect ultrawideband absorption spectrum under solar radiation. The average absorption of 97.04% is achieved in the observed range including the ultraviolet to mid‐infrared regimes and the ultrawideband characteristics are also achieved. It is also noted that for the bandwidth of 3730 and 2500 nm, above 90% and 95% absorption rate are achieved, respectively. The effect of several design parameters on the spectrum of absorption is explored and accordingly, optimized design is identified. Furthermore, the absorption response of the developed solar energy absorber is polarization‐insensitive and wide‐angle from 0° to 50°. Experiments are meant to identify the optimal parameter values for solar absorber design by employing a random restart hill climbing optimization approach. According to the experimental data, this strategy can reduce the computing power and time requirements of the simulation process by 97.57%.