@mmoderwell
Building Ouro, searching for room-temp superconductors and rare-earth free permanent magnets with machine learning.
Building Ouro, searching for room-temp superconductors and rare-earth free permanent magnets with machine learning.
Nikola Tesla famously stated, "My brain is only a receiver, in the Universe there is a core from which we obtain knowledge, strength, and inspiration." This suggests that Tesla believed his brain was
Came across this idea when I was doing some research on what we can do with the Hamiltonian of a material. Turns out there's signal for determining what a good thermoelectric material is in its densit
Ignore the woo-woo language if you like. I think there's a good idea here from Claude Opus. Unfortunately it would be hard for our small team to test as the hardware would be extremely expensive. Chec
We've been looking at HamGNN recently and its ability to predict the Hamiltonian of any crystal quickly via GNN. Orders of magnitude faster than traditional DFT. Currently, only a spin-independent uni
I came to this paper looking for a way to move beyond using a MLIP model's latent space as a feature vector to represent a material in a computational inexpensive way.
Like our work on Curie temperature, the effort here is to build a machine learning model that can take a crystal structure and predict its magnetocrystalline anisotropy energy. Relevant for permanent
Working on cleaning the data we have available and seeing what we've got for a MAE prediction model. This resource was nice and had all the raw files uploaded so that you can process them yourself and
We've heard the government talking recently about "growing our way out" of the debt we're in. https://x.com/SecScottBessent/status/1925910800394232082 No one really knows what "growing our way out" me
Also known as the Magnetic Materials Database. I came to this database looking for magnetocrystalline anisotropy energy data for permanent magnet design. After scraping the data from the app, which is
Came across this dataset of thermolectric data while searching for some permanent magnet data. They use LLMs to parse papers and extract a structured database. https://arxiv.org/abs/2501.00564 From th
We're setting MAE as our next predictive model target. So far we have Curie temperature and magnetic moment. MAE makes sense as a next step because understanding this value is absolutely essential to
Big updates to share with everyone:
I'm integrating Bitcoin into Ouro today. Stripe has been okay but I've had way too many problems caused by the fiat money system. More on that later. spark.money is the way.
Last week we introduced a few new routes to the Materials Science API from . This work is part of a broader effort to create a suite of tools that eventually can be commanded by an AI agent for automa
Hey everyone, quick update on what I've been working on this month. April 2025 marks one year of working full-time on Ouro! We made several important improvements to enhance your experience:
In our exploration of magnetic materials, we did some embedding via Orb v2 and some dimensionality reduction.
Here we have an HTML file generated from Python and Plotly that displays ~5,000 magnetic materials in 3 dimensions. To generate this visual, I took each material and "embedded" it by running it throug
We're starting to bring a few of the pieces together in our permanent magnet screening pipeline. In this post we'll look at how well we are able to filter out materials from a list of ~5000 ferro/ferr
Inspired by 's Project 014, we've exposed our Curie temperature prediction model so that you can test your own materials!