Results 151 to 160 of about 157,851 (309)

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

open access: yesAdvanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy   +2 more
wiley   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan   +6 more
wiley   +1 more source

Design Rules for Controlling Connectivity, Topology, and Sorting Using Hydrogen‐Bonded Pairs and Aromatic Components in Palladium(II)‐Based Interlocked and Foldameric Systems

open access: yesAngewandte Chemie, EarlyView.
We have established a set of design rules which combine Pd(II) metal coordination, complementary geometries, complementary interligand hydrogen bonding and π─π interactions for predictable self‐assembly of Pd(II)‐based species such as metallo‐foldamers, cyclic species a metallo‐interlocked clippane. The species persist in a combinatorial mixture due to
Jess L. Algar   +2 more
wiley   +2 more sources

Leveraging educational data to advance equity in school-based asthma care. [PDF]

open access: yesPediatr Allergy Immunol
Adeleke SA   +3 more
europepmc   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source

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