Results 71 to 80 of about 173,504,166 (216)
Atom‐Efficient Cerium‐Based Molecular Cages as Biocompatible Reactive Oxygen Scavengers
Discrete mixed‐valent cerium molecular cages organize accessible redox centers within confined coordination environments and scavenge superoxide, hydrogen peroxide, and hydroxyl radicals. Encapsulation of the lead cage in an ROS‐responsive DTP nanoplatform enables lesion‐associated delivery, attenuates macrophage oxidative stress and inflammation, and ...
Chao Li +9 more
wiley +1 more source
The energetic offset between the donor and the acceptor components in organic photoactive layers is central to the tradeoff between photovoltage and photocurrent losses. This Perspective covers the most important issues surrounding this topic in non‐fullerene acceptor blends, from the difficulty of accurately determining state energies and driving ...
Dieter Neher, Manasi Pranav
wiley +1 more source
Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger +14 more
wiley +1 more source
Spectral Characterization of the Hamming Graphs [PDF]
We show that the Hamming graph H(3; q) with diameter three is uniquely determined by its spectrum for q ¸ 36. Moreover, we show that for given integer D ¸ 2, any graph cospectral with the Hamming graph H(D; q) is locally the disjoint union of D copies of
Koolen, J.H., Bang, S., Dam, E.R. van
core
On classes of minimal circular-imperfect graphs
International audienceCircular-perfect graphs form a natural superclass of perfect graphs: on the one hand due to their definition by means of a more general coloring concept, on the other hand as an important class of \chi-bound graphs with the smallest
Annegret K. Wagler +3 more
core +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Constructing Structural VAR Models with Conditional Independence Graphs [PDF]
In this paper graphical modelling is used to select a sparse structure for a multivariate time series model of New Zealand interest rates. In particular, we consider a recursive structural vector autoregressions that can subsequently be described ...
Granville Tunnicliffe Wilson +2 more
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Phase‐Engineered MoS2 Quantum Monolayer Catalysts
A new type of catalyst model—phase‐engineered MoS2 quantum‐monolayer catalyst (∼0.8 nm thick, < 6 nm in the lateral size; switchable freely among metallic 1T, semiconducting 2H, and a hybrid phase of metallic‐semiconducting 1T‐2H)—is reported. It can efficiently and stably drive photochemical H2, syngas and ammonia synthesis as a catalyst or co ...
Ruijie Yang +12 more
wiley +1 more source
Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng +24 more
wiley +1 more source
We investigate here the intersection graphs of horizontal and vertical line segments in the plane, the so called B 0-VPG graphs. A forbidden induced subgraph characterization of B 0-VPG split graphs is given, and we present a linear time algorithm to ...
Golumbic, Martin Charles, Ries, Bernard
core +1 more source

