Results 151 to 160 of about 8,495 (264)

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

Clinical utility of pharyngeal high‐resolution manometry with impedance for upper esophageal sphincter dysfunction in gastroenterology

open access: yesAdvances in Digestive Medicine, EarlyView.
Abstract Pharyngeal high‐resolution manometry with impedance (P‐HRM‐I) is an established assessment method used to evaluate pharyngeal swallowing. It provides precise quantification of swallowing biomechanics that enable the detection of alterations in swallowing physiology.
Mistyka Schar   +5 more
wiley   +1 more source

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

open access: yesAdvanced Intelligent Discovery, EarlyView.
A multimodal fusion pipeline predicts high‐resolution ion distributions in imaging mass spectrometry by integrating Fourier transform ion cyclotron resonance, time‐of‐flight matrix‐assisted laser desorption/ionization, and time‐of‐flight secondary ion mass spectrometry data.
Md Inzamam Ul Haque   +7 more
wiley   +1 more source

Proceedings of the Inter Disciplinary Conclave (IDC)-2021

open access: yesJournal of Stem Cells and Regenerative Medicine, 2021
openaire   +1 more source

Information Dense and Industry Scalable Accelerated Formation

open access: yesAdvanced Intelligent Discovery, EarlyView.
Pulsed formation can reduce lithium‐ion battery formation time by over 50% while maintaining or enhancing performance. Validated on 25 Ah prismatic cells, this industry‐scalable method yields thinner, more homogeneous solid electrolyte interphases (SEIs).
Leon Merker   +3 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Home - About - Disclaimer - Privacy