Kurukshetra University

Programmable hydrogels have emerged as a new generation of intelligent biomaterials capable of integrating stimuli-responsiveness, biocompatibility, and regenerative functions for precise drug delivery. Unlike traditional passive hydrogels, these systems utilize dynamic covalent and supramolecular crosslinking to achieve reversible adaptability and spatiotemporal regulation of therapeutic release. This review systematically summarizes the molecular design principles, stimuli-responsive mechanisms (pH, redox, enzyme, thermal, mechanical, and light), and crosslinking strategies that enable programmability and biodegradability within hydrogel networks. The crucial design approaches, including hybrid network architectures, molecular imprinting, and bioresponsive linkers, are highlighted as central to achieving selective and adaptive functionality. Particular focus is placed on multi-stimuli and feedback-controlled systems that coordinate drug release with biological signals to enable autonomous, context-specific therapy. Recent progress shows the integration of molecular imprinting, bioresponsive linkers, and hybrid structures that improve structural stability while maintaining responsiveness. Applications in wound healing, angiogenesis, and tissue regeneration emphasize the role of programmable hydrogels as bio-instructive matrices that modulate the immune response, preserve redox balance, and promote scar-free healing. Furthermore, emerging technologies such as AI-guided material design, 4D bioprinting, and bioelectronic integration are accelerating the development of closed-loop and patient-specific therapeutic platforms. Despite these advances, significant challenges remain, particularly regarding scalability, reproducibility, long-term stability, and the predictability of in vivo performance, which continue to limit clinical translation. Overall, programmable hydrogels mark a significant shift from static carriers to dynamic, self-regulating biomaterials for advanced regenerative medicine.

This study presents the results of active and passive seismic surveys to delineate the site characteristics of Kurukshetra city, situated in the Indo-Gangetic alluvial plains of northern India. The ambient noise measurements were acquired at 160 sites using single station recordings, and Multichannel Simulation with One Receiver (MSOR) surveys were conducted at 18 sites distributed across the city. Our analysis reveals that the fundamental frequency (MSOR) ranges from 0.71 to 1.28 Hz, suggesting the presence of a thick and soft sedimentary cover overlaying the bedrock. For most sites, is less than 1.0 Hz and is characterized by broad, diffuse spectral peaks, suggesting a low impedance contrast at greater depths and a positive shear wave velocity gradient within the sedimentary column. A distinct low-frequency peak similar to 0.26 Hz is interpreted as the seismic response associated with the Quaternary-Tertiary boundary. The estimated site amplification ranges from 1.69 to 3.32 times, indicating moderate amplification of the deep alluvial basin. The calculated vulnerability index (K-g) ranges from 3.32-11.58, indicating enhanced liquefaction susceptibility, particularly in the southeastern sectors. Furthermore, 1-D shear wave velocity profile shows a systematic increase in velocity with depth at all measurement sites. The calculated Vs(30) values (170-282 m/s) classify the near-surface materials as NEHRP soil classes D and E, confirming the diminution of soft sediment within the upper 30 m. Sediment thickness is high in the northern and eastern parts of the city compared to the western side, indicating a west-to-east slope in the deep subsurface. The validity of the derived results is supported by recorded earthquake and SPT data. These findings will be instrumental in seismic hazard assessment and microzonation of the city.

Perovskite solar cells (PSCs) have been reported to have a power conversion efficiency (PCE) of 27.3%, although their instability in enduring moisture, heat, and light is a major hindrance in energy-related applications. In this work, we investigate the role of La-doped BaSnO3 (LBSO) as an electron transport layer (ETL) to improve the aging performance of PSCs and its suitability with a fixed hole transport layer (HTL) and various absorber layers for PSCs. The first-principles calculations are performed on pristine BaSnO3 and LBSO using the full potential linear augmented plane wave (FPLAPW) method within a time-efficient orbital-independent modified Becke-Jhonson (mBJ) approach. The calculated results indicate that La doping results in BaSnO3 being an n-type semiconductor with electronic properties appropriate for its application as an efficient ETL for PSCs. The optical absorption and reflectivity spectra govern the superiority of LBSO over BaSnO3, and LBSO is found to transmit the solar photons in the perovskite absorber layer in a better way. The numerical simulations also authenticate LBSO as a more suitable ETL than BaSnO3 in the PSCs having prominent absorber layers, including MAPbI3, FAPbI3, CsPbI3, Cs x FA1-x PbI3, and MAPb(I1-x Cl x )3, where MA = CH3NH3 + and FA = CH(NH2)2 +, combined with the PTAA HTL.

This study investigates the reflection of plane waves in a thermoelastic diffusion medium governed by the Moore–Gibson–Thompson (MGT) heat conduction model, incorporating both impedance boundary conditions and temperature-dependent material properties. The governing field equations are formulated by coupling mechanical, thermal, and diffusive effects, and Helmholtz decomposition is employed to identify distinct longitudinal (P), transverse shear (SV), thermal (T), and diffusive (P₀) wave modes. Analytical expressions for reflection coefficients are derived, enabling a detailed examination of wave–boundary interactions under varying physical parameters. The results reveal that impedance parameters and temperature-dependent properties significantly influence reflection amplitudes and mode conversion, while thermal diffusion enhances the contribution of diffusive wave modes. Furthermore, the interplay between thermal relaxation and diffusion is shown to alter wave propagation characteristics in a non-trivial manner. These findings provide new insights into thermo-diffusive wave behavior and establish a more comprehensive framework for modeling wave propagation in advanced engineering and geophysical materials.

The increasing global energy demand, along with the intermittent nature of solar and wind resources, necessitates hybrid renewable energy systems (HRES) combining PV, wind, and battery storage for reliable single-phase grid integration. Conventional FOPID controllers often suffer from sensitive tuning and suboptimal performance, and existing optimization methods lack a hybrid mechanism tailored to the rapidly varying environmental conditions of such systems, which results in reduced power quality and higher harmonic distortion. To address these gaps, this work proposes a novel SPU-HBO hybrid optimization algorithm, which integrates SSA and HBA to enhance convergence speed, solution accuracy, and robustness. The SPU-HBO is used to optimally tune the FOPID controller for grid-connected PV/Wind/Battery systems, which ensures stable operation under fast-changing conditions. The proposed method achieves superior power quality, significantly reducing THD and demonstrates improved dynamic performance and robustness compared to conventional optimization techniques such as SSA, HBA, GWO, and IPF. Accordingly, the convergence study shows the proposed SPU-HBO achieves a minimum cost of 0.22351, which outperforms GWO, SSA, HBA, PSO, GA, and WOA. Additionally, the proposed SPU-HBO algorithm achieves the lowest THD of 0.11% in grid voltage, compared to GWO (0.67%), HBA (0.12%), IPF (3.98%), and SSA (0.12%), which demonstrates superior harmonic reduction and improved power quality.