Roshna S H

Dr. Roshna S H is a scientist by profession with more than five years of teaching experience at graduate and postgraduate levels. She has obtained a Ph.D. from IIT Madras after M.Sc., M. Phil in Physics. She has also cleared CSIR-NET and GATE with top ranks. She is a constant content creator through publications in peer-reviewed international journals and by writing concept based blog articles. She has research experiences in diverse areas spans from atmospheric science to optics as well as spintronics and magnetism. She has obtained awards and recognitions at various international platforms for her contributions as scientific articles and oral presentations. Dr. Roshna completed her Ph.D. with exposure at American physical society, Material research society, University of Oxford, etc. She focuses on communicating the concepts with utmost clarity in the simplest possible way.

Generative AI

The Boundless Creativity of Generative AI: From Art to Science

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Generative Artificial Intelligence (AI) stands at the forefront of innovation, reshaping the boundaries of creativity and technology. It represents a paradigm shift in AI research, enabling machines to autonomously produce original content across various domains, including artwork, music, literature, and design. This technology emerged from the intersection of deep learning, neural networks, and computational creativity. …

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Machine Learning in Material Science

Machine Learning in Material Science Research

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In recent years, the integration of machine learning (ML) techniques with material science research has catalyzed innovation, revolutionizing traditional approaches to material discovery, characterization, and optimization. This article explores the diverse applications of ML in material science, highlighting its transformative impact on various research domains. Areas in Material Science where Machine Learning is Used Prediction …

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Math for data science

Essential Math for Data Science : A Guide to Beginner’s

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Data science has become an indispensable field in today’s digital age, revolutionizing industries with its ability to derive valuable insights from vast amounts of data. While proficiency in programming languages and data manipulation tools is crucial, having a solid foundation in mathematics is equally essential for success in this field. In this article, we’ll explore …

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Stable diffusion models

Stable Diffusion Models in Deep Learning

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Stable diffusion models stand out for their ability to capture intricate data distributions while maintaining stability during training and inference. Unlike traditional approaches that may suffer from issues like mode collapse or vanishing gradients, stable diffusion models offer a robust solution for tasks ranging from image generation to data denoising. The title image depicting a …

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Exploring the Depths of Crystallography: Advanced X-ray Characterization Through Reciprocal Space Mapping

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The two or three-dimensional mapping of crystals in reciprocal space is known as reciprocal space mapping (RSM). The RSM is performed by a coupled scan of $2\theta-\omega$  for a set of $\omega$ values. These maps, centered around reciprocal lattice spots, offer insights beyond those obtained from single line scans, such as high-resolution rocking curves. In epitaxial …

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Pulsed Laser Deposition Technique for Thin Film Growth

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The pulsed laser deposition (PLD) method is a widely known thin film growth technique for its potential in growing highly crystalline oxide thin films with near stoichiometry on an ultra-thin scale. Various thin film deposition techniques are used to prepare thin films and superlattices such as sputtering, molecular beam epitaxy, PLD, thermal evaporation method, chemical …

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Density Functional Theory: A Key to Unlocking Quantum Insights

Density Functional Theory: A Key to Unlock Quantum Insights

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Density Functional Theory (DFT) stands as a cornerstone in the realm of quantum mechanics, serving as a powerful tool for understanding the electronic structure and properties of materials. In this article, we will embark on a journey to demystify DFT, exploring its fundamental principles, applications in material science and physics, and the practical aspects of …

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Transform Negativity into Resilience and Positivity

Transform Negativity into Resilience and Positivity

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Negativity is an inevitable part of life, but how we respond to it can profoundly impact our well-being. In this article, we’ll explore effective strategies to transform negativity into resilience and positivity. Additionally, we’ll delve into practical ways to handle negative people, fostering a mindset that empowers and uplifts Acknowledge and Redirect: The first step …

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Impulse-Momentum Theorem Demystified

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In the realm of physics, certain principles serve as the bedrock upon which our understanding of motion and its governing laws is built. One such fundamental concept is the Impulse-Momentum Theorem. This theorem, which lies at the intersection of classical mechanics and Newtonian dynamics, provides invaluable insights into the behavior of objects in motion and …

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Machine Learning in Physics

Machine Learning in Physics

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In the domain of physics, the incorporation of machine learning (ML) has emerged as a transformative force. As we venture into the forefront of scientific inquiry, ML algorithms provide a powerful arsenal for dissecting intricate data, revealing underlying patterns, and formulating predictions. This article delves into the application of machine learning in physics, examining its …

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