IBM has unveiled a new family of open-source foundational Artificial Intelligence (AI) models for chemistry, aimed at accelerating the discovery of new, more sustainable materials with applications in chip fabrication, clean energy, and consumer packaging. According to the company, AI has the potential to transform the discovery of safer and more sustainable materials, providing a powerful solution to phase out toxic substances tracked by the US Environmental Protection Agency.
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Material Discovery with AI
IBM Research designed these new AI models to accelerate this process by screening millions of molecules for desirable properties and generating new, safer alternatives. Available on platforms like GitHub and Hugging Face, the models have been downloaded over 100,000 times, reflecting strong interest in their potential, according to IBM.
"Foundation models pre-trained on vast molecular databases can be used to screen millions of molecules at a time for desirable properties while weeding out the ones with dangerous side effects. These models can also be used to generate molecules entirely new to nature, circumventing the traditional drawn-out, trial-and-error-based discovery process," IBM said on December 20.
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Overcoming Challenges
The primary challenge in applying AI to chemistry lies in representing molecular structures effectively. IBM's researchers addressed this by integrating various data formats—SMILES, SELFIES, and molecular graphs—into a unified "multi-view" mixture of experts (MoE) model. This adaptable model improves task-specific performance and has outperformed existing models in predicting properties such as toxicity and solubility, key benchmarks in drug and materials discovery, according to IBM.
IBM also announced plans to release new fusion techniques and models in the coming year, built on additional data modalities, including the positioning of atoms in 3D space. Through the AI Alliance, the company is also collaborating with other academic and industry researchers to accelerate the discovery of safer, more sustainable materials.
Collaborations for Global Sustainability
Earlier this year, IBM and the Japanese materials company JSR established a working group for materials (WG4M), which has attracted approximately 20 corporate and academic partners. The group focuses on developing foundation models, datasets, and benchmarks to address challenges ranging from creating reusable plastics to advancing materials for renewable energy.
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Power of AI
Through ongoing collaborations with industry and academia, IBM aims to drive the development of new foundation models and datasets to tackle global challenges, including the creation of reusable plastics and materials supporting clean energy. IBM emphasises that AI has the power to multiply creativity and expedite the search for safer, greener alternatives across industries.
"New, more sustainable materials are needed in virtually every industry, from semi manufacturing to clean energy. AI now gives us the power to multiply our creativity," said Dave Braines, the CTO of emerging technology at IBM Research UK.
