Results 231 to 240 of about 388,487 (329)

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

A Devotion to the Law [PDF]

open access: yes, 1994
Carrera, David
core  

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo   +3 more
wiley   +1 more source

Bubbles Acting as Micro End‐Effectors for Dexterous Manipulation and Sensing in Aqueous Environment

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Inspired by bubbles, this article proposes a low‐cost method for multifunctional manipulation and sensing using microbubbles in aqueous environments. Bubbles are easily generated in situ, enabling the safe and adaptive handling of microobjects and sensing of microforces and surface textures.
Zichen Xu, Qingsong Xu
wiley   +1 more source

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