Results 161 to 170 of about 8,458 (265)

Donor–Acceptor Covalent Organic Framework Enables Ambipolar Charge Storage in Aluminum‐Ion Energy Storage

Advanced Energy Materials, EarlyView.
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, Verónica Montes‐García, Wojciech Kukułka, Saira Sarwar, Michał Bielejewski, Mateusz Wlazło, Rossella Greco, Viktorija Pankratova, Ignacio Pérez‐Juste, Dawid Pakulski, Paolo Samorì, Artur Ciesielski   +11 more
wiley   +1 more source

Energy Transfer‐Mediated Magnetoluminescence of an Octahedral MnII Complex Ligated With Bis(Diphenylphosphino)Methane Dioxide

Angewandte Chemie, EarlyView.
Energy‐transfer‐mediated magnetoluminescence of paramagnetic transition metal complexes: dope solids of an octahedral MnII complex into the corresponding ZnII complex exhibited a pronounced magnetic field response of emission spectra under the application of magnetic fields.
Asato Mizuno, Takuto Mibu, Ryota Matsuoka, Takema Hikawa, Shojiro Kimura, Tetsuro Kusamoto   +5 more
wiley   +2 more sources

Microscopic study of the intermediate mixed state in intertype superconductors. [PDF]

Beilstein J Nanotechnol
Neverov VD, Kalashnikov AV, Krasavin AV, Vagov A.   +3 more
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
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

BCS-BEC crossover driven by small Fermi pockets of a high-T_c cuprate superconductor. [PDF]

Nat Commun
Jeong J, Enomoto Y, Kohama Y, Nakayama T, Ando K, Kurokawa K, Huh S, Yang Z, Nomura T, Watson MD, Kim TK, Cacho C, Lin C, Hashimoto M, Lu D, Sakai S, Tohyama T, Tokiwa K, Kondo T.   +18 more
europepmc   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
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, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Weakly Anisotropic Superconductivity of Pr₄Ni₃O₁₀ Single Crystals. [PDF]

J Am Chem Soc
Pei C, Shen Y, Peng D, Zhang M, Zhao Y, Xing X, Wang Q, Wu J, Wang J, Zhao L, Xing Z, Chen Y, Zhao J, Yang W, Liu X, Shi Z, Guo H, Zeng Q, Zhang GM, Qi Y.   +19 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Novel dynamics and Cooper-pair momentum measurement in Fulde-Ferrell-Larkin-Ovchinnikov superfluids on optical lattices. [PDF]

iScience
Tan S, Shi J, Zou P, Ma T, Zhao H.
europepmc   +1 more source