AI in chemical engineering: From promise to practice
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
Correction to "Battlefield Neck Injuries: Contemporary Insights From the Israeli National Trauma Registry". [PDF]
europepmc +1 more source
Beyond Opioid Comparison: Interpreting Oliceridine in Contemporary Thoracic Recovery Pathways [Letter]. [PDF]
Lu CW, Chang KC.
europepmc +1 more source
Challenges and enablers in fluidization technology
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley +1 more source
Global patterns of disease progression in inflammatory bowel disease: a comprehensive synthesis of contemporary population-based cohorts. [PDF]
Gros B +5 more
europepmc +1 more source
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
Antimicrobial use and documented infection among hospitalized adults in South American acute care facilities during the coronavirus disease 2019 (COVID-19) pandemic. [PDF]
Dempsey LF +10 more
europepmc +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Prognostic utility of Killip classification in acute myocardial infarction: a retrospective cohort analysis in contemporary clinical practice. [PDF]
Speckauskiene V +4 more
europepmc +1 more source

