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Accelerating SUStainable TECHnological trajectories with computational chemistry and machine learning

CORDIS · observation · Publication date unknown

Accelerating SUStainable TECHnological trajectories with computational chemistry and machine learning SUSTECH addresses a critical paradox at the heart of modern society: synthetic chemicals have been instrumental in societal advancement in their manifold uses ranging from materials to fertilizers and pharmaceuticals. Yet, they pose escalating risks to human health and environmental sustainability. There is an urgent need to reorient technological development toward safer and more sustainable alternatives. This project aims to generate a comprehensive understanding of the technological pathways that lead to the commercialization of hazardous compounds to inform policy-makers how to redirect innovation in ways that align with societal and environmental well-being. SUSTECH investigates the decision-making processes and incentive structures that drive the development and the market approval of hazardous compounds to identify potentially misguided incentives. The interdiscip

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recordType

award

status

SIGNED

region

EU

value

9761394

unit

EUR