How Accurate Are Machine Learning Potentials, Really?
Five top models differ by 11% on energy error and by 83% on thermal conductivity error. Which means the question has no single answer — here is what to ask…
Reading the Iron-Carbon Phase Diagram in 10 Minutes
Three lines and one point are all you need from the Fe-C diagram. Learn to read a cooling path, apply the lever rule, and predict a steel's microstructure.
8 Python Libraries Every Materials Researcher Should Know
The eight libraries that do the heavy lifting in computational materials science, what each is actually for, and the catch with every one of them.
What Is a Unit Cell? Crystallography From Scratch
A unit cell is the smallest repeating box that builds a whole crystal. How to count its atoms, work out its packing, and connect it to density you can measure.
Your First LAMMPS Simulation, Step by Step
Install LAMMPS, run a real melt simulation, and understand every line of the input script. A first molecular dynamics run you can finish in twenty minutes.
Annealing vs Normalizing vs Tempering
Three heat treatments, three different goals. What each does to steel's microstructure, the temperatures that matter, and how to tell which one you need.
The Liberty Ships That Broke in Half
Wartime ships cracked in calm water and cold weather. The story of why is the clearest lesson in materials engineering ever paid for in steel and lives.
Density Functional Theory, Explained Without the Math
DFT predicts what materials do, from first principles, using electron density instead of wavefunctions. Here is how it works and what it gets wrong.
What Is a Machine-Learned Interatomic Potential?
An MLIP gives you near-DFT accuracy at close to classical-MD speed. Here is how these potentials work, where the speed comes from, and how they fail.
BCC vs FCC vs HCP: Why Crystal Structure Decides Ductility
BCC steel has 48 slip systems and shatters in the cold. FCC copper has 12 and never does. Here is the packing-and-slip physics that decides which.