Amit Luthra
CEO of PhaseTree
PhaseTree
PhaseTree provides an intuitive, online platform for multi-scale materials modeling that integrates first-principles physics with AI for accurate predictions. This synergy accelerates materials discovery cycles significantly, enabling researchers to screen thousands of candidates virtually. The platform supports faster, sustainable material innovation by making advanced simulation accessible for collaborative R&D teams.
- Artificial Intelligence
- Chemical Technology
- New Materials
Updated 5 months ago
Funding
Raised to date
$3.2MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Traditional materials discovery and development processes are slow, expensive, and rely heavily on trial-and-error lab testing, often taking up to 20 years to bring new materials to market. This lengthy process hinders innovation and the development of sustainable alternatives to scarce resources.
Solution
PhaseTree offers a cloud-based materials design platform that accelerates the discovery and development of new materials by combining physics-driven simulations with AI modeling. The platform enables researchers to simulate material behavior from the atomic level to real-world conditions, capturing complex behaviors across scales. By integrating multiscale simulations, lab automation, and AI, PhaseTree reduces the development cycle to approximately two years. The platform also facilitates the exploration of a large number of material candidates virtually, expanding the scope of discovery and enabling the design of greener, more efficient, and durable materials.
Target Audience
PhaseTree targets materials scientists, researchers, and engineers in industries such as energy, transportation, construction, electronics, and healthcare who are seeking to accelerate materials discovery and develop sustainable alternatives.
Features
- Multi-scale modeling to simulate material behavior from atomic to real-world conditions
- Physics-first approach combined with AI for accurate predictions
- AI-driven identification of new chemical combinations and synthesis methods
- Cloud-based platform accessible to both experts and newcomers
- Streamlined workflow from material parameter input to simulation and analysis
- Automated simulation and analysis of countless material variations
- Clear reporting of predicted material properties and recommendations