Results 101 to 110 of about 2,151,737 (304)
Minimum H-decompositions of graphs
Given graphs \(G\) and \(H\), an \(H\)-decomposition of \(G\) is a partition of the edge set of \(G\) such that each part is either a single edge or forms a graph isomorphic to \(H\). Let \(\varphi_H(n)\) be the smallest number \(\varphi\) such that any graph \(G\) of order \(n\) admits an \(H\)-decomposition with at most \(\varphi\) parts.
Oleg Pikhurko, Teresa Sousa
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This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
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On double-star decomposition of graphs
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Saieed Akbari +3 more
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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
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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
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Triangle decompositions of planar graphs
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Christina M. Mynhardt +1 more
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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
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Spectral Complexity of Directed Graphs and Application to Structural Decomposition
We introduce a new measure of complexity (called spectral complexity) for directed graphs. We start with splitting of the directed graph into its recurrent and nonrecurrent parts.
Igor Mezić +3 more
doaj +1 more source
Resolving Heterogeneity of Targeted Lipid Nanoparticles Through Solution‐Based Biophysical Analyses
AF4‐UV‐DLS‐MALS‐SAXS resolves previously inaccessible targeted lipid nanoparticle (tLNP) subpopulations that differ in size, shape, and composition. Correlation of subpopulation‐resolved biophysical properties with in vivo RNA delivery reveals that targeted placental transfection is associated with distinct tLNP subpopulations rather than ensemble ...
Hannah C. Geisler +14 more
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Decomposition of graph functions
AbstractThe V-functions of Tutte [1] are generalized to U-functions on graphs with a distinguished subset of vertices. The class of U-functions of two variables generalize dichromatic polynomials as well as the W-functions defined by Tutte [2]. The values of U-functions on a graph G are characterized in terms of spanning subgraphs of G and also in ...
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