The periodic table, expanded into a scientific data universe
The Himia Project is a next-generation scientific reference for chemistry β built for students, educators, researchers, and developers who need more than a simple element card.
The Himia Project by the numbers
A living chemistry database, continuously expanding as science moves forward.
More than a periodic table. A structured universe of chemical knowledge.
Most periodic tables show basic facts: symbol, atomic number, mass, and a few properties. Himia goes deeper.
Each element profile connects scientific explanations with structured data: physical and chemical properties, isotopes, spectra, compounds, safety, environment, economics, abundance, crystal structures, electron configuration, nuclear data, identifiers, references, and advanced research values.
The goal is simple: make chemistry easier to learn, easier to explore, and easier to use in data-driven science.
Built as a seed dataset for AI-driven chemistry.
Modern scientific AI needs high-quality structured data. The Himia Project is designed to become a foundation for machine learning workflows in chemistry and materials science.
By organizing element properties, spectra, isotopes, compounds, references, and advanced descriptors into connected datasets, Himia can support future AI tools for prediction, classification, recommendation, and discovery.
Our long-term direction is materials informatics: using data science and ML models to predict what is missing, discover hidden patterns, and help generate new ideas for materials and compounds.
Prediction is the strongest frontier.
The most powerful use of chemical data is not only lookup β it is prediction.
Himia is being prepared for AI/ML tools that may help predict:
- Missing element properties
- Atomic and ionic radii
- Electronegativity values
- Compound stability
- Electrical conductivity
- Toxicity risks
- Reactivity patterns
- Phase behavior
- Potential material performance
This can help students understand trends, researchers explore hypotheses, and developers build scientific tools on top of structured chemistry data.
From element data to materials discovery.
The future of chemistry is not only about storing known facts. It is about using data to search for new possibilities.
Himia will move toward tools that help explore:
- New alloys
- New compounds
- Lightweight conductive materials
- Stronger and more efficient materials
- Safer chemical alternatives
- Materials optimized for specific properties
A user should be able to ask: "Find a lightweight conductor" β and receive suggested elements or compounds with scientific reasoning behind the answer.
The real power is in scientific features.
In machine learning, the model is only as strong as the data behind it. Himia is built to support rich feature engineering from chemical properties.
Future models can use relationships such as:
- Electronegativity differences for bond prediction
- Radius-to-mass ratios
- Ionization energy combined with atomic radius
- Oxidation states and reactivity indicators
- Spectral patterns
- Isotope distributions
- Crystal and electronic structure descriptors
These features can help AI systems discover patterns that are difficult to see in traditional tables.
Finding hidden families of elements.
The periodic table already shows powerful patterns. But data science can reveal more.
With clustering and explainable AI, Himia can help explore:
- Elements with similar behavior beyond traditional groups
- Hidden chemical families
- Properties that influence reactivity
- Why certain elements behave alike
- Which features matter most in a prediction
The goal is not to replace chemistry intuition β but to make it more visible, explainable, and discoverable.
A platform for future chemistry tools.
The Himia Project is evolving from a reference website into a scientific tool ecosystem.
- Element profiles
- Spectra
- Isotopes
- Compounds
- References
- Calculators
- Comparison tools
- Open API
- ML prediction
- Materials generation
- AI research assistants
For students, chemistry becomes visual.
Himia helps students move beyond memorization.
Instead of learning isolated facts, users can explore how electron configuration affects behavior, why isotopes matter, how spectra identify elements, how phase transitions work, and where elements appear in everyday life, industry, nature, and the universe.
Atomic models, orbital diagrams, spectra, phase timelines, crystal structures, and visual data tools make complex chemistry easier to understand.
For researchers, Himia connects deep data in one place.
The Himia Project brings together advanced reference data that is often scattered across many sources.
Element profiles may include thermodynamic values, nuclear properties, spectral lines, energy levels, isotope decay modes, X-ray scattering factors, screening constants, crystal radii, electronegativity scales, polarizability, dispersion data, Miedema parameters, abundance data, and extended radii values.
The result is a cleaner, more connected way to explore chemical and atomic data.
Open API coming soon.
The Himia Project is being prepared not only as a website, but also as an open data platform.
A free public API is planned to give developers, educators, researchers, and creators direct access to structured chemistry data for apps, visualizations, learning tools, scientific workflows, and AI experiments.
We believe chemical data should be open, connected, and useful for everyone.
A non-profit infrastructure project for scientific knowledge.
The Himia Project is built with a public mission: to make high-quality chemical knowledge accessible, structured, and useful for society.
Students need better learning tools. Teachers need modern references. Researchers need connected data. Developers need open datasets. The future of AI needs reliable scientific foundations.
Himia exists to support all of them.
Our goal is not to lock chemical knowledge behind closed systems, but to build an open foundation for education, research, and data-driven discovery.
Open chemical knowledge for the next generation.
Why this matters now.
Chemistry is entering a new era. AI and data science are changing how we search for materials, understand substances, predict properties, and teach complex scientific concepts.
But AI cannot work without structured, reliable, and well-connected data. The Himia Project aims to become one of those foundations β a bridge between classical chemical knowledge and the next generation of intelligent scientific tools.
The periodic table was only the beginning.
The Himia Project expands it into a living scientific data platform β visual, structured, open, and ready for the age of AI.
We are building a non-profit foundation for chemistry education, materials informatics, scientific discovery, and open data tools.
Explore the elements. Support the mission. Help build the future of chemical knowledge.