Composition & structure
The public example constructs 196 numerical features from chemical composition and crystal structure.
OUR FLAGSHIP / IN RESEARCH
Scientific screening.
Reproducible by design.
An early-stage platform connecting materials data, predictive models, and an inspectable evaluation workflow.
Which candidates deserve
the next stage
of validation?
PURPOSE
Prediction becomes useful when its inputs, methods, and evaluation can be understood.
VALTRIX explores scientific screening and candidate prioritization for materials and molecular research. Our public JARVIS example uses composition and crystal-structure features with a tabular neural model to predict exfoliation energy.
The platform is in research. Technical briefs are available for prospective collaborators working on materials-property prediction or molecular screening.
PUBLIC EVIDENCE / JARVIS
Evaluated on the official test split of 81 materials. The public package includes inference code, the model checkpoint, and instructions to reproduce the submitted predictions.
Submission PR #34 is open in the active JARVIS-Leaderboard repository. Acceptance and leaderboard integration are pending.
A TRACEABLE WORKFLOW
The public example constructs 196 numerical features from chemical composition and crystal structure.
The inference package applies the stored preprocessing and trained checkpoint to generate predictions.
Inspect the reported result alongside its code and the current benchmark submission status.
COLLABORATION
A material property. A dataset. An evaluation requirement.
We welcome discussions with scientific R&D teams and research partners who need to understand a model’s inputs, reproducibility, and suitability for a screening workflow.
Discuss a pilotLET’S WORK ON A REAL QUESTION
For scientific R&D teams, research collaborators, and technical partners exploring materials or molecular screening.