Mahatma Gandhi College

Existing magneto‑photo‑thermoelastic models for semiconductor media typically treat key effects in isolation, and therefore cannot simultaneously represent microstructural porosity, long‑range nonlocal stress interactions, and memory‑dependent thermal transport. This limitation hinders realistic prediction of coupled heat, deformation, and carrier dynamics in advanced semiconductor structures. This study develops a unified analytical framework to quantify the coupled magneto‑photo‑thermoelastic response of porous semiconductor cylinders while accounting, in a single formulation, for porosity, nonlocal elasticity, and thermal memory, while preserving finite thermal‑wave propagation. Nonlocal elasticity is integrated with a memory‑dependent three‑phase‑lag (3PL) heat‑conduction theory, and the Moore–Gibson–Thompson (MGT) equation is included to ensure finite thermal‑wave speeds under strong multi physics coupling. The resulting governing equations are solved in the Laplace domain, and time‑domain responses are obtained via numerical Laplace inversion. Parametric simulations are performed in Wolfram Mathematica. The computed fields show pronounced sensitivity to the governing physical parameters. In particular, porosity and the nonlocal length‑scale parameter strongly affect thermal stress and carrier‑density distributions, producing distinct shifts in response trends as these parameters vary. The memory‑dependent formulation also enables improved modulation of the coupled thermo‑mechanical wave profiles. By unifying porosity, nonlocality, and thermal memory in a finite‑speed transportmodel, the proposed framework resolves an important multiphysics modeling gap and provides a versatile basis for the analysis and design ofsemiconductor‑based technologies such as energy‑harvesting systems, optoelectronic devices, and precision thermal‑management applications.

The prevalent TiO2 photocatalysts have some glaring limitations, viz., (i) their inactivity under visible light irradiation and (ii) the irreversible temperature-dependent transformation of photocatalytically active anatase phase into inactive rutile. In this study, we employed a facile method to develop visible-light sensitive coloured rutile photocatalysts to tackle these issues. Here, we executed a surface modification technique on sol-gel derived, crystalline rutile TiO2 using sodium borohydride (NaBH4). This was done in favourable atmospheric conditions, rendering it cost-effective and scalable. A series of rutile TiO2 samples, with colour varied from white to black, were prepared by changing the amount of NaBH4. Surface-modified samples exhibited crystalline core and disordered shell heterostructure. The pristine rutile sample was rich in Ti3+ and doubly charged oxygen vacancy V-o(++), respectively corresponding to shallow and deep defect states. In contrast, the surface-modified samples are rich in photocatalytically active shallow-trapped surface Ti3+ and singly charged oxygen vacancy (V-o(+)) defects, which act as colour centers. Hence, the photocatalytic activities of the surface-modified rutile TiO2 enhanced significantly upon white LED irradiation. Amongst a series of surface-modified samples, rR3 (treated with 0.1 g of NaBH4) showed the highest visible-light photocatalytic degradation rate constant (10.35 x 10(-3) min(-1)) for methylene blue (MB) dye. In addition to MB, sample rR3 showed better degradation of rhodamine B (RhB) and phenol than the pure rutile and commercial photocatalyst Degussa P25 under visible-light irradiation. Since rutile is the thermodynamically stable form of TiO2, surface-modified samples could be effective in hightemperature applications, especially without the assistance of regularly utilized UV radiation.

The increasing demand for effective energy storage solutions has spurred research into innovative materials with exceptional properties. Among these, two-dimensional (2D) materials have become popular alternatives due to their unique mechanical, chemical, and electrical characteristics. This review highlights recent advances in using 2D materials-such as graphene, MXenes, and transition metal dichalcogenides (TMDs) for energy storage devices like batteries and supercapacitors. Graphene, known for its high conductivity and surface area, enhances charge storage when used as an anode. MXenes, a newer class with variable compositions, provide high capacitance for both anodes and cathodes. The large surface area and capacitance of graphene, along with the flexibility of MXenes, offer promising advantages. Additionally, combining 2D materials with carbon nanotubes and metal nanoparticles further improves storage performance. New hybrid architectures and composites that incorporate 2D materials optimise energy storage devices, increasing metrics such as energy density and cycling stability. Moreover, integrating 2D materials into flexible, wearable devices addresses the needs of portable electronics and IoT. The review links the structure, synthesis, and characterisation to the electrochemical behavior of each material and also captures recent advances in the last decade related to battery and supercapacitor applications. In addition, the review includes two tables that compare the performance of each type of material as well as an increased focus on emerging hybrid structures for next-generation energy storage systems.

This study proposes a unified kernel-based mathematical framework for analyzing fractional magneto-thermoelastic diffusion within a spherical semiconductor cavity subjected to complex magnetic excitation and governed by non-Fourier heat conduction. The formulation incorporates three distinct fractional operators, Riemann–Liouville, Caputo–Fabrizio, and Atangana–Baleanu, within a single, tunable unified kernel structure that not only captures nonlocal interactions and memory-dependent behavior but also interpolates smoothly across infinite, tempered, and finite memory regimes. This innovation enables consistent modeling of multiphysical semiconductor systems, distinguishing the present work from prior isolated kernel approaches. The governing equations are derived from generalized thermoelastic theory incorporating three-phase-lag heat conduction, solved analytically via Laplace transformation and numerically inverted using Talbot's method. A detailed parametric study investigates the influence of kernel configuration, fractional orders, magnetic field intensity, and phase-lag parameters on the evolution of thermal, mechanical, and diffusive fields. The results demonstrate three key findings such as, kernel configuration strongly influences stress attenuation and carrier dynamics, nonlocality significantly modifies thermal wave speed, and phase-lag parameters govern diffusion relaxation behavior. These findings highlight the versatility of the unified kernel framework and provide valuable insights for nanoscale material design, semiconductor device optimization, and advanced nonlocal modeling.