Results 221 to 230 of about 82,713 (298)

Consumer Acceptance of New Sustainable Food Technologies: Upcycling Technology, Biostimulants, and Artificial Intelligence

open access: yesAgribusiness, EarlyView.
ABSTRACT Food systems have a significant impact on environmental sustainability, underscoring the need for innovative technologies to support more sustainable agricultural methods. However, the adoption of these technologies hinges on consumer acceptance, making the analysis of consumer perceptions essential.
Greta Castellini, Guendalina Graffigna
wiley   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Learn from the blame game when AI causes harm. [PDF]

open access: yesProc Natl Acad Sci U S A
Killoran J, Park A.
europepmc   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

open access: yesAdvanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz   +2 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

open access: yesAdvanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia   +3 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

open access: yesAdvanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian   +12 more
wiley   +1 more source

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

open access: yesAdvanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen   +6 more
wiley   +1 more source

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