Results 241 to 250 of about 240,834 (310)

On the Elusive Ninth Vibrational State of the Argon Dimer

open access: yesNatural Sciences, Volume 6, Issue 1, January 2026.
ABSTRACT An unresolved discrepancy between high‐accuracy potential energy curves for the argon dimer (Ar2${\rm Ar}_2$), which support different numbers of bound vibrational states and profoundly different scattering lengths for Ar2${\rm Ar}_2$, is probed by morphing these curves to available spectral data within the reduced potential energy curve ...
Vladimír Špirko
wiley   +1 more source

Observation of a bilayer superfluid with interlayer coherence. [PDF]

open access: yesNat Commun
Rydow E   +6 more
europepmc   +1 more source

Extensile Active Hydrogels Driven by Living FtsZ Polymers

open access: yesSmall, Volume 22, Issue 3, 13 January 2026.
Upon post‐gelation activation with Mg2⁺/GTP, living FtsZ polymers treadmill inside a polyacrylamide network, generating extensile internal stresses that drive isotropic swelling and softening. Interpreting mechanics against a Flory–Rehner swelling baseline separates passive dilution from genuine activity, revealing an FR‐normalized permittivity that ...
Mikheil Kharbedia   +8 more
wiley   +1 more source

A New Platform for Twistronics: Perovskite Moiré Superlattices Beyond van der Waals

open access: yesSmall Structures, Volume 7, Issue 1, January 2026.
This Perspective highlights perovskite moiré superlattices as a non–van der Waals platform for twistronics. Owing to ionic–covalent bonding and soft octahedral lattices, perovskites support deep moiré potentials and room‐temperature excitons. Recent progress in two‐dimensional Ruddlesden–Popper perovskites and three‐dimensional perovskite lamellae is ...
Shule Huang   +3 more
wiley   +1 more source

Integrating Physical Parameterization and Attention Mechanisms in Recurrent Neural Networks for Hydrological Modeling: Quantification of Storage Layers Dynamics and Meteorological Responses Within the PRNN Model Framework

open access: yesWater Resources Research, Volume 62, Issue 1, January 2026.
Abstract With the advancement of deep neural networks and physics‐data‐driven coupling methods, significant new opportunities have emerged for improving watershed hydrological simulations. Attention mechanisms (AM) and physical process‐wrapped recurrent neural networks (PRNN) enhance model performance by dynamically highlighting key hydrological ...
Peiyuan Sun   +4 more
wiley   +1 more source

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