The performance of rechargeable batteries is governed by processes deep within their components. A fundamental understanding of electrochemistry, structure–property–performance relationships and the ...

An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new ...

Regulators are modernizing their expectations, and it's become clear that validation can no longer function as a point-in-time event.

The recent advent of AI is transforming daily life from streamlining routine tasks to augmenting productivity and ...

Unlike traditional testing, which requires hundreds or thousands of charge – discharge cycles, the model can estimate a new ...

A 'learner,' 'interpreter' and 'oracle' work together with minimal experiments to draw parallels between historical data and new battery designs A ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

Dynamic digital product passports – real-time, intelligent digital records that capture the true condition of perishable goods such as food and drink throughout their lifecycle – could dramatically ...

The melting and calving of icebergs can influence the climate. Therefore, researchers track them with AI to obtain data for ...

Evolving toxicity assessments for engineered nanoparticles underline the importance of predictive models and life-cycle risk ...

Asking an engineer to refactor a large, tightly coupled AI pipeline to test an idea is almost guaranteed to fail. Monoliths don’t optimize well either. You’ll spend more time (and money) iterating on ...