Thoughts on Physics,
Materials & Beyond

Sharing research insights, tutorials, and reflections on condensed matter physics, magnetocaloric materials, and the journey of scientific discovery.

16 Posts
4 Topics

A Dose, Four Times a Day

Four small ways my body has of leaning in close and saying: this one matters, hold onto it. A reflection on D.O.S.E. — dopamine, oxytocin, serotonin, endorphins — and the quiet moments of being alive that we so often walk right past.

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My Motivation for Scientific Research

An honest reflection on why I do research — not for the publications, not for the credentials, but for the quiet click when something finally makes sense. From DFT at Academia Sinica to grinding powders in a Vietnamese lab, and why the detour is not wasted.

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XRD Peak Finding: From Raw .xy Data to Bragg Reflections

A practical guide to identifying and locating peaks in raw XRD data — from noise reduction and baseline correction to automated peak detection algorithms and manual refinement. With worked examples on real diffractogram data.

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XRD Peak Fitting: Gaussian, Lorentzian, and Voigt Profiles

Understanding the physics behind diffraction peak shapes — why Gaussian, Lorentzian, and pseudo-Voigt profiles arise, how to choose among them, and step-by-step fitting with Python. Includes FWHM extraction and goodness-of-fit diagnostics.

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Williamson-Hall Analysis: Separating Size from Strain

How to use Williamson-Hall plots to disentangle crystallite size broadening from microstrain broadening in XRD data. Covers the Scherrer equation's limits, the W-H linearization, and fitting strategies for nanocrystalline materials.

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The $25,000,000,000 Eigenvector: The Linear Algebra Behind Google

How Larry Page and Sergey Brin turned a linear algebra concept into a $25 billion company. From hyperlinks as votes and the random surfer model to the Perron–Frobenius theorem, power iteration, and why PageRank is really just finding a dominant eigenvector.

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Neural Network Potentials: Bridging Quantum Accuracy and Classical Speed

From Behler–Parrinello symmetry functions to equivariant graph neural networks like NequIP and MACE — how machine learning is revolutionizing molecular simulations, with real examples from peptide and saccharide conformer searches.

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Density Functional Theory: A Gentle Introduction

From the exponential wall of the many-body Schrödinger equation to Kohn–Sham orbitals and Jacob's Ladder of exchange-correlation functionals — a complete conceptual roadmap for newcomers to DFT, with physical intuition first and equations second.

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Wave Diffraction and the Reciprocal Lattice: The Natural Language of Crystallography Vietnamese

From the intuitive Bragg law to Fourier analysis, reciprocal lattice vectors, and Brillouin zones — a unified picture of diffraction built on physical intuition first, equations second. Based on Kittel Chapter 2.

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Wave Diffraction and the Reciprocal Lattice: The Natural Language of Crystallography

From the intuitive Bragg law to Fourier analysis, reciprocal lattice vectors, and Brillouin zones — a unified picture of diffraction built on physical intuition first, equations second. Based on Kittel Chapter 2.

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Your Body Has Been Screaming. But Are You Listening?

A raw, personal reflection on burnout, the illusion of productivity, and the moment I realized no success is worth it if you're no longer healthy enough to enjoy it. This isn't about slowing down — it's about survival.

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Understanding Arrott Plots: A Practical Guide for Experimentalists

A step-by-step walkthrough of modified Arrott plots for determining the order of magnetic phase transitions and extracting critical exponents. Includes worked examples from real manganite data and common pitfalls to avoid.

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Why Nano-sized Manganites Behave Differently: Surface Effects and Magnetic Ordering

Exploring how reducing particle size to the nanoscale changes the fundamental magnetic behavior of perovskite manganites. From dead magnetic layers to core-shell models — what the latest research tells us about finite-size effects.

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The Future of Magnetic Refrigeration: Are We Close to a Breakthrough?

Reflections on the current state of magnetocaloric research and the remaining challenges before practical magnetic cooling becomes a reality. A look at where the field stands and what breakthroughs are still needed.

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Building a Nest: My Desire for Marriage and Babies

A personal reflection on the meaning of life, inheritance, and the deep human desire to leave something behind — not just material wealth, but values, stories, and love passed on to the next generation.

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Calculating Magnetic Entropy Change with Python: From Raw M(H) Data to ΔSM Curves

A practical coding tutorial showing how to process isothermal magnetization data and calculate the magnetic entropy change using Maxwell's relation. Complete with Python code, visualization tips, and error analysis.

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