Austin Sendek
CEO
Aionics
Aionics utilizes artificial intelligence and physics-based simulation to design customized electrolytes for high-performance electrochemical systems, including batteries for electric vehicles and long-duration energy storage. By screening billions of formulations, Aionics accelerates materials discovery, significantly enhancing the efficiency and performance of energy storage solutions.
- Artificial Intelligence
- Data & Analytics
- Battery Technology
- Chemical Technology
- Clean Technology
- New Materials
Updated 7 months ago
Funding
Raised to date
$8MRaised 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
Electrolyte design for electrochemical systems, such as batteries, is a slow and complex process, hindering the development of high-performance energy storage solutions. Traditional methods struggle to efficiently explore the vast chemical space of potential electrolyte formulations. This bottleneck limits advancements in electric vehicle batteries, long-duration energy storage, and other applications.
Solution
Aionics leverages artificial intelligence and physics-based simulation to accelerate the discovery and design of customized electrolytes for advanced electrochemical systems. The company's platform screens billions of electrolyte formulations, identifying optimal candidates tailored to specific performance requirements. Aionics also facilitates supply chain logistics by connecting customers with trusted chemical partners. Furthermore, they offer mechanistic modeling and machine learning assessments to provide deeper insights into electrochemical systems and guide materials development.
Target Audience
Aionics serves companies in the electric vehicle, aerospace, and energy storage industries, as well as research institutions focused on electrochemical systems and materials science.
Features
- AI-driven screening of billions of electrolyte formulations
- Physics-based simulation for accurate property prediction
- Custom electrolyte design tailored to specific performance profiles
- Mechanistic modeling for understanding system behavior
- Machine learning assessments for data-driven insights
- Identification of novel molecules for enhanced performance
- Collaboration with chemical partners to secure supply chains