Asian Journal of Research and Reviews in Physics

Recent Advances in Carbon Doped ZnO Thin Films Correlating Structural Evolution with Optical Performance

Zainab Hussein Mutar, Muatazbullah Ibrahim Abdullah — Thu, 09 Jul 2026 00:00:00 +0000

Carbon-doped zinc oxide (ZnO) thin films have garnered significant attention in recent years due to their ability to simultaneously modify the structural, electronic, and optical properties of zinc oxide. The introduction of carbon leads to the development of numerous defect configurations within the ZnO lattice, as well as significant changes in crystallinity, lattice stress, defect density, and electronic band structure. These modifications are crucial for enhancing the optical properties of ZnO thin films and for their application in high-tech optoelectronic devices. This review aims to provide a detailed account of the latest advancements in carbon-doped ZnO thin films and the relationship between structural changes and optical properties. It discusses different carbon insertion modes (substitutional and interstitial) and outlines the main techniques for film preparation. The review also provides a detailed analysis of the effects of carbon doping on crystal structure, crystal size, lattice parameters, microstress, and defect generation. Furthermore, the optical transmittance and absorption properties, optical bandgap geometry, refractive index, and absorption coefficient of the embedded carbon were investigated. A literature review revealed that carbon doping is an effective method for modifying the electronic structure of zinc oxide (ZnO) by introducing defective states and adjusting the bandgap, thereby enhancing visible light absorption and photovoltaic functions. These achievements have paved the way for the application of ZnO thin films in diverse fields, including photodetectors, solar cells, gas sensors, transparent electronics, and photocatalytic systems. Finally, some remaining challenges and future research directions were highlighted, emphasizing the importance of precise defect control, improved synthesis processes, and advanced characterization techniques for developing next-generation ZnO technologies.

Role of Laser Pulse Shape Asymmetry in Electron Acceleration from Underdense Plasmas

Deep Kumar Kuri — Wed, 08 Jul 2026 00:00:00 +0000

Temporal asymmetry in the shape of a linearly polarised laser pulse can influence electron acceleration during interaction with underdense plasmas. This study numerically investigates electron acceleration for Gaussian, positive-skew and negative-skew laser pulses using a one-dimensional fluid model. The positive-skew pulse is characterised by a sharp rise and slow fall, whereas the negative-skew pulse has a slow rise and sharp fall. The model solves Maxwell equations, the electron continuity equation and the electron momentum equations to compare laser propagation, wakefield generation, electron energy gain and harmonic production under different pulse-shape conditions. The results show that the positive-skew pulse generates a strong intensity gradient at the laser front, producing a strong ponderomotive force and an immediate increase in electron energy. However, the negative-skew pulse allows electron oscillations to persist for a longer duration near the laser pulse, resulting in a stronger wakefield of approximately 650 GV/m and the highest electron energy gain of approximately 0.25 MeV. During propagation through the plasma, the laser pulse splits into harmonic components, and odd harmonics up to the 29th order are observed. No substantial difference in spectral intensity is found among the Gaussian, positive-skew and negative-skew cases. These findings indicate that temporal pulse asymmetry can influence wakefield evolution and electron acceleration in underdense plasmas.

Heat and Mass Transfer on MHD Blood Flow with Casson Fluid and Slip Effect Past a Porous Wounded Surface using Power Series Solution and Undetermined Coefficient Method on Perturbation Technique

Ekakitie Omamoke, Isaac Funakpo, David-Onah, Serian Ikiomoye — Thu, 09 Jul 2026 00:00:00 +0000

This study presents an analytical investigation of heat and mass transfer in magnetohydrodynamic (MHD) blood flow modelled as a Casson fluid past a porous wounded surface under slip, suction/injection and chemical reaction effects. The governing dimensional equations for momentum, energy and concentration transport were transformed into non-dimensional form using appropriate similarity variables and physical parameters. A perturbation procedure was applied to reduce the coupled system, and approximate analytical expressions for velocity, temperature and concentration distributions were derived using the method of undetermined coefficients and a power series solution. The effects of the magnetic field parameter, Casson fluid parameter, suction/injection, porosity, Prandtl number, Schmidt number, heat source parameter, chemical reaction rate, thermal Grashof number, solutal Grashof number and slip length were examined graphically and through transport quantities. The results indicate that the magnetic field parameter, Schmidt number, porosity, chemical reaction parameter, heat source parameter, Casson parameter and suction reduce the velocity profile, whereas the Prandtl number, thermal Grashof number, solutal Grashof number and slip length enhance it within the model assumptions. Temperature decreases with suction and Prandtl number and increases with the heat source parameter. Concentration decreases with suction, chemical reaction parameter and Schmidt number. Skin friction, Nusselt number and Sherwood number describe the sensitivity of momentum, heat and mass transport to the governing parameters. The study provides a theoretical framework for coupled MHD, thermal and concentration transport in Casson blood flow near a porous wounded surface without experimental validation.

Optimizing Real-time Signal Processing in Particle Physics Using Machine Learning Algorithms for High-energy Particle Detection

Sujata Nema, R. K. Nagarch, Parmeshwar Dayal Lodhi, Shailendra Jain — Fri, 10 Jul 2026 00:00:00 +0000

Real-time signal processing is essential in high-energy particle physics, where detector systems produce large volumes of waveform data under strict latency and storage constraints. This study examines the use of machine learning algorithms for waveform-based event classification in high-energy particle detection, with emphasis on signal-background discrimination and trigger-oriented processing. Detector responses are represented as one-dimensional time-series waveforms that encode temporal structure, amplitude variation, noise components and non-linear behaviour. The manuscript evaluates the relevance of convolutional neural networks, long short-term memory networks and a hybrid CNN-LSTM approach for extracting discriminative features from these complex signals. The analysed dataset contains labelled signal and background events, allowing supervised classification after preprocessing steps such as normalisation, filtering, outlier treatment and interpolation to improve signal quality and model robustness. The proposed CNN-LSTM model correctly identified 116 of 120 signal events and 115 of 120 background events in the test set, with a reported accuracy of 96.25%. Comparative performance indicates that the hybrid model outperformed decision tree, random forest, support vector machine, CNN and LSTM models in the reported analysis. These findings suggest that deep learning can support efficient waveform classification and may assist real-time trigger decisions when integrated with suitable low-latency hardware frameworks. However, further validation using larger benchmark datasets, transparent training protocols, hardware-based latency assessments across different event classes, noise levels, and realistic detector operating conditions is required before operational implementation in particle-physics experiments.

Preparation, Characterization and Holographic Interferometric Study of Electrodeposited CuS, CuSe and CuTe Thin Films

V. P. Malekar, V. J. Fulari, V. G. Kurundkar — Fri, 10 Jul 2026 00:00:00 +0000

Holography is an advanced optical technique that enables three-dimensional recording and reconstruction of information using coherent electromagnetic waves. Among its applications, holographic interferometry is a useful non-destructive method for evaluating surface deformation, residual stress and the mechanical behaviour of thin films through the analysis of interference fringe patterns. In the present study, double-exposure holographic interferometry, coupled with mathematical modelling, was used to determine the stress, mass, fringe width and thickness of electrodeposited thin films. Copper chalcogenide thin films were synthesised by electrodeposition under varying deposition times and electrolyte normalities to investigate their influence on film growth, material deposition and substrate deformation. The study was carried out systematically to understand the relationship between deposition parameters and the resulting physical properties of the films. The experimental results showed that, with increasing deposition time, the number of fringes increased from 3 to 8, 4 to 10 and 3 to 10; film thickness increased from 0.949 to 2.531, 1.265 to 3.164 and 0.942 to 3.164 μm; deposited mass increased from 1.865 to 4.975, 3.184 to 7.959 and 2.830 to 9.435 mg; substrate stress decreased from 0.101 to 0.037, 0.075 to 0.030 and 0.101 to 0.030 dyne/cm2; and fringe width decreased from 0.105 to 0.040, 0.314 to 0.051 and 0.127 to 0.045 cm for copper sulphide, copper selenide and copper telluride thin films, respectively. These results indicate enhanced film growth and reduced deformation effects at longer deposition durations. The structural, optical and surface characteristics of the deposited thin films were analysed using X-ray diffraction (XRD), ultraviolet-visible optical absorption spectroscopy and contact angle measurements. These characterisation techniques provided information on the crystallinity, optical behaviour and wettability of the synthesised films.