AI for Molecular Dynamics
Learn to simulate the dance of atoms using Python, data science, and modern machine learning. Transform raw simulation trajectories into thermodynamic insights and train deep neural networks that run physical simulations at unprecedented speed.
Like Duolingo, but for AI for Molecular Dynamics. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
23 levels across 3 sections, about 46 minutes end to end, roughly 9 days at five minutes a day. It moves through Simulating and Wrangling Molecular Motion, Statistical Foundations and Landscape Mapping, and Machine Learning and Deep Learning Potentials. It starts from scratch.
Free forever · No credit card · iPhone & Android
Key ideas in AI for Molecular Dynamics
- Net force on each atom is computed from surrounding interactions
- Acceleration is calculated by dividing force by atomic mass
- Positions advance using updated velocities across a tiny discrete timestep
- Electron cloud overlap causes sharp repulsion when atoms get too close
- Weak dispersion forces pull atoms together at intermediate distances
- Forces drop essentially to zero once atoms are far apart
- Nested Python loops compute pairwise distances sequentially and incur high interpreter overhead
- NumPy executes array-wide operations in compiled C routines simultaneously
- Calculating all N-by-N atom pairs at once prevents simulation slowdowns
- The sequence of calculations required to update atom positions in a single molecular dynamics simulation step
- Periodic boundaries treat the box as wrapping infinitely in all directions
- An atom leaving one boundary re-enters from the opposite boundary
- Wrapping particles prevents them from dissipating into empty vacuum
- Total energy should stay nearly constant in an isolated molecular system
- A timestep that is too large allows atoms to overlap, generating unrealistically massive forces
- Energy drift or sudden spikes warn that the numerical simulation is 'exploding'
You've tried the other tabs
Thirty open tabs. Four facts you actually kept.
You watched. You nodded. By Sunday it was gone.
One answer, then back to scrolling.
Eight weeks. You meant to finish. You didn't.
Tomo gives AI for Molecular Dynamics the Duolingo treatment: levels, streaks, and quick quizzes that test what you just learned. That game loop is what the tabs above never had, so it's the one you actually finish.
Here's what playing it feels like
A real question from this course. Take your best guess.
When your simulation knows the net force on an atom, how does it find that atom's acceleration?
Get it right to open this lesson and 22 more in the app.
Where AI for Molecular Dynamics takes you
- 1
Simulating and Wrangling Molecular Motion
- Animating Molecules with Python
- Wrangling Molecular Trajectory Data
- 2
Statistical Foundations and Landscape Mapping
- Extracting Statistical Mechanics from Trajectories
- Mapping Molecular Landscapes with Dimensionality Reduction
- 3
Machine Learning and Deep Learning Potentials
- Predicting Molecular Properties with Machine Learning
- Training Deep Neural Network Potentials
- Accelerating Rare Events with Generative AI
3 sections · 7 units · 23 levels. Built to play, not to enroll.
Tomo is in ChatGPT
Tomo is also a ChatGPT plugin: the same playable courses, built and played inside your chat.
Add Tomo to ChatGPT- What to ask
- “Make me a Tomo course on black holes.” “Turn this chat into a Tomo course.”
- What you get
- Quick questions with instant feedback, hearts and stars, ready to play in about a minute.
- Where it goes
- No sign-up to start. Connect your Tomo account and your streak carries on in the app.
You pick the voice
AI for Molecular Dynamics is taught in the Pirate style: arr, learning be an adventure!. Want a different feel? In the app you can spin up the same topic in any of Tomo's teaching styles. Same facts, totally different vibe.
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Start AI for Molecular Dynamics today.
Download Tomo, search AI for Molecular Dynamics, and play your first lesson in under a minute.