It is the first commercial end-to-end generative AI materials partnership.
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
Users express pride in the Cusp AI team and excitement about the future potential of its generative AI for designing materials that remove PFAS from water.
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Awesome.
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
There’s been a lot of talk about AI revolutionizing science and human health, but I feel like often there’s a gap between the narrative (often by consumer AI companies) and the actual results.
Now it’s actually starting to happen: Max’s company CuspAI is making serious progress towards AI-discovered materials for PFAS removal.
https://www.kemira.com/news-and-stories/newsroom/releases/new-ai-designed-materials-show-promising-potential-to-remove-forever-chemicals-from-drinking-water-in-industry-first-breakthrough/
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
https://www.kemira.com/news-and-stories/newsroom/releases/new-ai-designed-materials-show-promising-potential-to-remove-forever-chemicals-from-drinking-water-in-industry-first-breakthrough/
The candidates are now advancing to further development and testing.
I am proud of the @cusp_ai team and excited by what this says about the future of materials discovery!
This is the way
AI to solve environmental challenges and ensure a safe and prosperous future for our children. Congratulations and thanks @cusp_ai team 👏🙏
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
The candidates are now advancing to further development and testing.
I am proud of the @cusp_ai team and excited by what this says about the future of materials discovery!
This is a shift from AI as a screening tool to AI as a generative design system: creating new structures from scratch, then evaluating them against real requirements.
The project reached this stage in six months, not years.
PFAS are a hard and important class of problems: persistent synthetic chemicals, present in water systems worldwide, and subject to tightening regulation.
The brief from Kemira was understandably demanding.
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
@KemiraGroup defined requirements: target specific PFAS molecules, operate at sub-parts-per-billion concentrations, and use chemistry that is stable, sustainable, synthesizable and cost-effective.
That matters. AI discovery has to meet physical and industrial constraints.
PFAS are a hard and important class of problems: persistent synthetic chemicals, present in water systems worldwide, and subject to tightening regulation.
The brief from Kemira was understandably demanding.
This is a shift from AI as a screening tool to AI as a generative design system: creating new structures from scratch, then evaluating them against real requirements.
The project reached this stage in six months, not years.
Our platform explored a design space of ~300 trillion possible MOF structures and generated more than 5,000 novel material designs with property data for GenX, PFBS and PFOS.
These were narrowed to around 20 priority candidates.
@wellingmax @ac_edwards_1 @cusp_ai @KemiraGroup Exceptional achievement 👏
Today @cusp_ai and @KemiraGroup announce a milestone in AI-driven materials discovery.
We have used generative AI to design new materials targeting PFAS removal from drinking and process water at trace concentrations.
Our platform explored a design space of ~300 trillion possible MOF structures and generated more than 5,000 novel material designs with property data for GenX, PFBS and PFOS.
These were narrowed to around 20 priority candidates.
@KemiraGroup defined requirements: target specific PFAS molecules, operate at sub-parts-per-billion concentrations, and use chemistry that is stable, sustainable, synthesizable and cost-effective.
That matters. AI discovery has to meet physical and industrial constraints.
@TacoCohen @ac_edwards_1 💯
There’s been a lot of talk about AI revolutionizing science and human health, but I feel like often there’s a gap between the narrative (often by consumer AI companies) and the actual results.
Now it’s actually starting to happen: Max’s company CuspAI is making serious progress towards AI-discovered materials for PFAS removal.