Results 31 to 40 of about 1,157 (152)

Using the Photostationary State of Arylazopyrazoles to Control Phase Transitions of Liquid Crystals

open access: yesAdvanced Functional Materials, EarlyView.
A series of new arylazopyrazole photoswitches is designed as dopants for liquid crystalline materials. Unprecedented, the distribution of photoisomers at the photostationary state upon irradiation with light of specific wavelengths (365, 460, 520 nm) is used to control the liquid crystalline phase transitions under isothermal conditions, including ...
Tobias Thiele   +3 more
wiley   +1 more source

Complex contact Lie groups and generalized complex Heisenberg groups

open access: yesDifferential Geometry and its Applications, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

open access: yesAdvanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Stacking‐Engineered Magnonic Topology and Transport in Honeycomb Homobilayers

open access: yesAdvanced Functional Materials, EarlyView.
ABSTRACT Topological magnons have emerged as a promising platform for dissipationless bosonic transport. However, a straightforward and effective strategy to engineer such topological states in real materials has yet to be fully realized. Here, a general scheme for controlling magnonic topological states via stacking engineering in van der Waals ...
Xiaoran Feng   +6 more
wiley   +1 more source

Correlated spin liquids in the quantum kagome antiferromagnet at finite field: a renormalization group analysis

open access: yesNew Journal of Physics, 2019
We analyze the antiferromagnetic spin-1/2 XXZ model on the kagome lattice at finite external magnetic field with the help of a non-perturbative zero-temperature renormalization group (RG) technique.
Santanu Pal   +2 more
doaj   +1 more source

Jacobi-Lie symmetry in WZW model on the Heisenberg Lie group $H_{4}$

open access: yes, 2018
We show that the Wess-Zumino-Novikov-Witten (WZW) model on the Heisenberg Lie group $H_{4}$ has Jacobi-Lie symmetry with four dual Lie groups. We construct Jacobi-Lie T-dual sigma models with one of their Jacobi-Lie bialgebra and show that the original model is equivalent to the $H_{4}$ WZW model. The conformality of the dual sigma model up to one-loop
Rezaei-Aghdam, A., Sephid, M.
openaire   +2 more sources

Indirect Band Edge and Chain‐Locked Linear Dichroism in the Quasi‐1D Van der Waals Antiferromagnet AgCrP2S6

open access: yesAdvanced Functional Materials, EarlyView.
AgCrP2S6 reveals a momentum‐indirect band edge (≈1.35 eV) and chain‐locked linear dichroism: the first direct transitions emerge at 1.6–1.8 eV for E||a. Resonant Raman and photoemission corroborate this assignment. In ACPS/graphene heterostructures, photocurrent turns on above ≈1.5 eV and follows the same polarization selection rules (anisotropy ≈0.53),
Oleksandr Volochanskyi   +9 more
wiley   +1 more source

Spin and Charge Control of Topological End States in Chiral Graphene Nanoribbons on a 2D Ferromagnet

open access: yesAdvanced Materials, EarlyView.
Chiral graphene nanoribbons on a ferromagnetic gadolinium‐gold surface alloy display tunable spin and charge states at their termini. Atomic work function variations and exchange fields enabe transitions between singlet, doublet, and triplet configurations.
Leonard Edens   +8 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

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

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