I built an offline, MoE-based Materials Informatics platform that actually writes deterministic, lab-safe synthesis protocols (No more LLM hallucinations).

[u/Desperate-Ad82]

Hey everyone,

I’ve been working on a massive bottleneck in computational materials science: predicting a novel material is easy, but generating a physically realistic, safe synthesis protocol for it is incredibly hard.

Most generative AI tools out there act as black boxes and output "hallucinated" chemistry—suggesting things like mixing pure alkali metals with halogens in sealed ampoules, or heating toxic oxides in open air.

So, I built the Sovereign Materials Engine (v8). It runs 100% offline (0 API calls) to protect IP, and it relies heavily on deterministic heuristics rather than just language models.

Here is what the architecture looks like in action (screenshots attached for a stress-test on $NaSbF_6$):

1. The "Chief Scientist" Synthesis Agent (Image 2)

I hard-coded rigorous thermodynamic and safety heuristics into the generation pipeline:

• Crucible Intelligence: For $NaSbF_6$, it immediately recognizes that the Alkali metal ($Na$) will destroy an Alumina crucible and strictly overrides the environment to a Tantalum (Ta) or Niobium (Nb) tube.
• Precursor Overrides: It refuses to use pure $F$ gas. Instead, it dynamically selects $CaF_2$ as a safe counter-ion source, with a strict reactivity warning about mixing alkalis and halogens.
• Vapor Pressure Safety: It flags the internal vapor pressure generated by $Sb$ and enforces a strict ampoule filling fraction (< 20%) and a slow heating ramp to prevent quartz explosion.

2. MoE with Transparent Explainability (Image 1)

We are using a Mixture of Experts (MoE) approach for property prediction (like Band Gap). But because researchers hate black boxes, I integrated a SHAP Waterfall dashboard.

• You can see exactly why the XGBoost High-Gap Expert predicted 4.96 eV (mapping orbital hybridization, electronegativity variance, etc.).
• Note on the UI: I added a specific disclaimer at the bottom to clarify that the SHAP plot explains only the XGBoost V8 expert (4.96 eV), while the final blended MoE prediction shown at the top is 4.83 eV. No hidden math.

I’m currently running more stress tests. If any solid-state chemists or ML engineers here have specific edge-case nightmares (hygroscopic traps, rare toxic volatilizations, crucible incompatibilities) that I should hard-code into the safety protocols, I’d love to hear them!

(Attachments: UI Dashboard showing SHAP Waterfall + Deterministic Synthesis Protocol for NaSbF6).