Results 141 to 150 of about 7,124 (268)
Electric Field‐Induced Hole‐ and Electron‐Type Flat Bands in Twisted Double Bilayer Graphene
The electronic structure of twisted double bilayer graphene is visualized using angle‐resolved photoemission spectroscopy with micrometer spatial resolution at twists of 3.1∘$^\circ$ and 6.0∘$^\circ$ as a function of gate voltage. Tunable hybridization effects and flat band formation occurs between valence and conduction band states due to a finite ...
Zhihao Jiang +13 more
wiley +1 more source
Tunable narrow-and-sharp defect modes and transmission peak degeneracy in periodic superconducting photonic crystals. [PDF]
Liu A, Gao H, Xiao Y, Zheng J, Zhang Q.
europepmc +1 more source
Advancing Energy Materials by In Situ Atomic Scale Methods
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
Fast computation model for superconducting pinning Maglev mechanical system. [PDF]
Wang L +5 more
europepmc +1 more source
A donor–acceptor covalent organic framework is designed as an ambipolar cathode for aluminum‐ion energy storage. The crystalline, microporous architecture enables intrinsic charge transport without conductive additives. Multi‐electron redox activity at donor and acceptor sites supports high capacity, excellent stability, and efficient reversible ...
Cataldo Valentini +11 more
wiley +1 more source
Machine Learning for Superconductor Discovery: From Data-Driven Insights to Accelerated Design. [PDF]
Zhang J +12 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
Geometry-controlled engineering of the low-temperature proximity effect in normal metal-superconductor junctions. [PDF]
Tomayeva MA +4 more
europepmc +1 more source
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
Spin-polarized edge modes between different magnet-superconductor-hybrids. [PDF]
Zahner F +6 more
europepmc +1 more source

