Birsa Institute of Technology Sindri (BIT Sindri), formerly Bihar Institute of Technology Sindri, is an affiliated engineering college in Sindri, Jharkhand, India. Established in 1949, BIT Sindri is one of the oldest engineering and technological institute in India.
Hydrothermal and plant extracted green synthesis method was employed to synthesize MoS2 and CuO nanoparticles respectively. Subsequently, CuO/MoS2 nanocomposites were synthesized by incorporation of CuO into MoS2. The FESEM, XRD, UV-DRS and TGA techniques were used to examine the properties of materials.The FESEM showed a layered MoS2 nanosheets were decorated with CuO nanoparticles, which confirms an effective interfacial interaction and uniform dispersion in the hybrid structure. The UV analysis revealed an improvement in visible light absorption of the composites over pure MoS2. Optical bandgap values were also determined as 1.75 eV for bare MoS2 and 1.66 eV for CuO and the composites showed slightly lower bandgap of 1.70 to 1.67 eV. TGA analysis revealed enhanced thermal stability of the composites whereby the MC (1:2) sample exhibited the superior thermal stability.
Cyber-Physical Systems (CPS) are becoming more and more complex, which requires autonomous architectures that can optimize themselves in closed-loop fashion. The paper suggests a Scalable Agentic AI Architecture (SAAA) that is intended to be used to estimate autonomous states and reason and actuate in non-stationary environments. The framework is based on a Distributed Multi-Agent System (MAS) which combines Hierarchical Reinforcement Learning (HRL) with low-latency edge-level responsiveness. The architecture uses the ability to provide temporal abstraction and decentralized policy gradients to provide robustness and fault tolerance in a heterogeneous environment of digital-physical nodes. A self-referential feedback loop allows the ongoing policy adaptation to different operational constraints and stochastic perturbations without the human-in-the-loop interventions. Quantitative comparisons of benchmark CPS situations show increased accuracy of decisions, reduced control latency and greater resiliency compared to centralized and fixed-point heuristics.
This paper addresses robust combined frequency and voltage regulation in a highly nonlinear, amphibious (aquatic and terrestrial), two-area hybrid power system (AHPS). The AHPS comprises multiple sources—thermal, dish–Stirling solar thermal (DSTS), hydro, pumped hydro, and gravity hydro units—connected to a 50-Hz grid. During operation, solar radiation fluctuations and load changes lead to significant variations in key model parameters (e.g., K_p,T_p,T_sc,T_rh,T_w,T_1,T_2) , which can cause undesirable frequency and voltage deviations. To tackle this challenge, a dynamic parameter-based modelling framework is developed for the AHPS, and a new fractional-order tilt-integral sliding mode controller (FOTI-SMC) is proposed for coordinated frequency–voltage regulation. The proposed FOTI-SMC is systematically compared with five benchmark controllers—classical PID, fractional TID, FOPID, FOTID, and nonlinear FOPISMC—whose parameters are tuned using five optimization classes (evolutionary, swarm-based, physics-based, human-inspired) and the bio-inspired Tasmanian Devil Optimization (TDO) algorithm. The TDO-tuned FOTI-SMC achieves a peak overshoot of only 1.18 for frequency deviation in area-1 (∆f1), significantly outperforming the GA-tuned PID. The proposed scheme also realizes faster recovery, with settling times reduced to 15.787s for ∆f1 and 12.052s for ∆f2, voltage deviations (∆V1 ∆V2), and tie-line power (∆Ptie). Under realistic operating scenarios involving simultaneous variations in load, solar insolation, and modelling parameters, the TDO-FOTI-SMC maintains superior robustness, restricting overshoots to 1.517 for ∆f1 and 0.931 for ∆f2. Real-time validation on an OPAL-RT OP4510 platform confirms that the proposed TDO-optimized FOTI-SMC offers the most effective frequency–voltage regulation and disturbance rejection among all tested configurations.
The Modular Multilevel Converter (MMC) is a promising technology for medium-and high-voltage applications due to its advantages, which include a modular structure, scalability, and high-quality output waveforms. The performance of the MMC depends on its control strategy, which addresses converter challenges such as circulating current, submodule (SM) capacitor voltage balancing, and achieving a low Total Harmonic Distortion (THD) output voltage waveform. Space Vector Pulse Width Modulation (SVPWM) provides higher DC Bus utilisation, lower THD, and greater switching flexibility compared to carrier-based PWM methods. This paper presents a simple battery-balancing strategy for modular multilevel converters (MMCs) integrating a battery pack for electric vehicle (EV) applications, using SVPWM. It provides cell-balancing control for each arm of the converter to equalise the cells' state of charge. The results show the effectiveness of the provided technique for Battery management systems and EV speed control. The provided technique has been validated using MATLAB/Simulink for MMC with 2 SMs per arm, but it can be extended to any number of submodules.
This study presents a breast cancer cell detector based on a dual cavity dielectric modulated (DM) silicon on insulator (SOI) junctionless field-effect transistor (DM-SOI-JL-FET), designed to detect various breast cancer cell types by incorporating a nanocavity structure. The nanocavity is created by etching the oxide region beneath the left and right sides of the gate. Also, the cavity thickness was optimized with respect to off-state current. Detection is achieved through analysing variations in the dielectric constant of the gate oxide when different breast cancer cells, such as MCF7-10 A, HS578T, MDA-MD-231, MCF7, and T47D, are placed inside the cavity. Sensitivity (S) is calculated as the ratio of the off-state current ( I_OFF ) in the absence of breast cancer cells to the off-state current in the presence of cancer cells. Additionally, variations in key electrical parameters, including drain current, energy band diagram, transconductance, and surface potential, are also evaluated with respect to different cancer cells. The results demonstrate that sensitivity increases with increase in the dielectric constant of the cancer cells. The sensitivity values for different cancer cells are as follows: MCF7-10 A (14.09), MDA-MD-231 (91.37), HS578T (99.24), MCF7 (109.91), and T47D (118.58). This method enhances the breast cancer cell detection, demonstrating the potential of the DM-SOI-JL-FET detector for highly sensitive breast cancer diagnostics.
