AI-driven

Engineering of Materials

AI-driven Engineering
of Materials

at the Atomic Scale

Entalpic designs molecules and materials for surface-driven industrial processes using AI, atomistic simulations and experimental feedback loops.

Our high-throughput discovery engine rapidly screens large chemical spaces to identify viable materials candidates under real industrial constraints.

As pioneers in AI for Science, our mission is to master fundamental chemistry towards a more efficient and sustainable future.

Value Proposition

An innovative approach built on 3 pillars

AI & Quantum Modeling

We are a team of machine learning experts with a proven track record in developing state-of-the-art predictive and generative models for the discovery of new materials and chemistry.

Multimodal Datasets

Our AI models leverage multiple data sources, including quantum simulations, scientific literature, patents and experimental data generated by our customers.

Experimental Integration

We view experiments as essential data sources for AI-driven R&D. Our platform is designed to interface seamlessly with experimental labs, enhancing discovery potential through data feedback loops

We are a team of machine learning experts with a proven track record in developing state-of-the-art predictive and generative models for the discovery of new materials and chemistry.

AI &
Quantum Modeling

Our AI models leverage multiple data sources, including quantum simulations, scientific literature, patents and experimental data generated by our customers.

Multimodal
datasets

We view experiments as essential data sources for AI-driven R&D. Our platform is designed to interface seamlessly with experimental labs, enhancing discovery potential through data feedback loops.

Experimental
integration

Technology

Click on the blocks to discover our technology

Process Modeling
(Digital Twins)

Screening and
Discovery Engine

Quantum  
Simulations

Patents &
Publications

Experimental
data

High-quality multi-modal datasets

By combining ML with computational fluid dynamics, we model ALP reactors and experimental systems to simulate candidate material behavior under real manufacturing conditions.

Experimental and characterization data feed back into our discovery engine, ensuring AI-designed materials are reliably manufactured.

Our Atomistic Discovery Engine explores chemical space and ranks candidate materials, enabling R&D teams to rapidly identify the most promising options for experimental validation.

It combines generative models with predictive workflows based on physics-based simulations and machine-learning models.

To power our R&D, we curate and generate high-quality multimodal datasets:

Patents & academic publications: structured analysis of scientific literature to map emerging opportunities and guide discovery
Atomistic simulation: data collected from open repositories and generated through our proprietary high-throughput pipelines
Experimental data: produced in collaboration with partner laboratories and, soon, within our own integrated lab

We apply AI and atomistic modeling to solve

industrial challenges in surface chemistry.

We apply AI and atomic-scale modeling to
solve industrial challenges in surface chemistry.

Our expertise lies in solid-fluid interactions and interface engineering, where atomic-scale decisions ultimately determine real-world performance.

Semiconductors

Designing thin-films and coatings where atomic-scale precision determines process yield and device reliability.

Batteries

Optimizing cathode active materials, surface coatings, and interfacial chemistries for higher-performance batteries.

Catalysis

Designing catalytical surfaces and active sites to maximize activity, selectivity and industrial stability.

Advanced Materials

Designing new precursors and specialty chemicals for deposition processes.

Your Application Field

We are open to exploring new scientific and business opportunities. Contact us to discuss how we can collaborate on your challenge.

Semiconductors

Designing thin-films and coatings where atomic-scale precision determines process yield and device reliability.

Batteries

Optimizing cathode active materials, surface coatings, and interfacial chemistries for higher-performance batteries.

Catalysis

Designing catalytical surfaces and active sites to maximize activity, selectivity and industrial stability.

Advanced materials

Designing new precursors and specialty chemicals for deposition processes.

Your Application Field

We are open to exploring new scientific and business opportunities. Contact us to discuss how we can collaborate on your challenge.

About us

Machine Learning, Chemistry
and Materials experts.

More than 50% PhDs

Alumni of Intel, Air Liquide, Applied Materials, Meta, Google, Amazon

We are forward-thinking scientific explorers, deeply rooted in AI expertise and bound by integrity. Our core purpose is to help achieve Net Zero and drive the energy transition. We embrace working with energy-intensive industries to drive sustainable processes.

Machine Learning, Chemistry and Materials experts.

More than 50% PhDs

Alumni of Intel, Air Liquide, Applied Materials, Meta, Google, Amazon