Deep Principle

Introducing Hydrogen-1.0, Deep Principle’s first general-purpose large AI model, built to support scientific discovery.

Hydrogen-1.0 helps researchers reason through complex scientific questions, carry out calculations and simulations, turn research ideas into experimental plans, and use feedback to guide further exploration.

Today, we’re releasing its model weights for researchers and developers to adapt and evaluate on their own scientific tasks. Hydrogen-1.0 is also available in our AI Scientist product, MIRA.

Explore the benchmarks, research examples, and ways to get started in the posts below.

Building intelligence for scientific discovery.

We just dropped Materials Property Axiom (MPA).
The problem: most materials foundation models crush it on computed properties, but choke on real experimental data (boiling points, solubility, flammability, etc.).
MPA fixes this with physics-aligned transfer learning:
• 64M structures → 3D pre-training
• Thermochemistry + electronics + solvation → mid-training alignment
• Hybrid attention/additive readout → experimental fine-tuning
Results: ~10% better across 40 benchmarks, up to 51% on hard OOD tasks.
The rule: match the physics, not just the data.
Live at sciclaw.ai 🔗 blog.deepprinciple.com/introducing-ma…

Recently, Science published a feature article titled "How will we know if AI is smart enough to do science?".

The article focuses on the latest breakthroughs in evaluation systems for artificial intelligence's scientific capabilities, providing an in-depth analysis of the cutting-edge explorations by institutions such as Deep Principle, OpenAI, and FutureHouse in developing benchmarks for scientific intelligence.

Thrilled to be on the cover of JACS! @ACSPublications
LLM‑EO (LLMs + evolutionary optimization) designs transition‑metal complexes, surfacing top candidates and novel ligands from a 1.37M space. pubs.acs.org/doi/10.1021/ja…
From cover to frontier—Deep Principle keeps driving GenAI deeper into materials. More breakthroughs ahead.

#AI4Science #MyACSCover

#AI is already revolutionizing #material_science .

Haojun Jia, founder and CEO of Deep Principle, explains how leveraging both domain expertise and data-driven insights will be key to AI-enabled platforms transforming materials

#science #AMNC25
weforum.org/stories/2025/0…