Results 161 to 170 of about 13,686,872 (271)

POTENTIAL, VALUE AND PROBABILITY [PDF]

This paper focuses on the probabilistic point of view and proposes a extremely simple probabilistic model that provides a single and simple story to account for several extensions of the Shapley value, as weighted Shapley values, semivalues, and weak ...
Annick Laruelle, Federico Valenciano
core  

Non-commutative structures of brain and cognition: quantum and contextual probability as a translational framework. [PDF]

Front Hum Neurosci
Emori H, Khrennikov A, Iriki A.
europepmc   +1 more source

Photoinduced Charge Separation in Single‐Component Squaraine Films: The Key Role of Electrostatic Disorder

Advanced Functional Materials, EarlyView.
ABSTRACT Neat films of organic dyes are an interesting technological platform for solar cells and photodetectors. Recently, the conventional biphasic bulk‐heterojunction paradigm for photoinduced charge separation was challenged by the observation that charge carriers can be photogenerated in single‐component materials. A comprehensive experimental and
Davide Giavazzi, João Pedro Ferreira Assunção, Michael Bauer, Matthias Diethelm, Wei‐Hsu Hu, Mohammad Jafarpour, Roland Widmer, Antonia Neels, Dimitrios Sapalidis, Bruno F. B. Silva, Roland Hany, Frank Nüesch, Anna Painelli   +12 more
wiley   +1 more source

A language network in the individualized functional connectomes of 1199 human brains doing arbitrary tasks. [PDF]

Nat Commun
Shain C, Fedorenko E.
europepmc   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Probabilistic Aseismic Performance Assessment of Rubber-Sand-Concrete Tunnel Linings Considering Spatial Variability of Rock Mass. [PDF]

Materials (Basel)
Li K, Mei X, Li B, Sheng H, Cui Z, Wang Y, Wu H, Wang T.   +7 more
europepmc   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
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
wiley   +1 more source

When Poor Exciton Dissociation Limits Photocurrents in Organic Solar Cells: Why Low Offset Non‐Fullerene Acceptor Blends Can't Be Efficient

Advanced Materials, EarlyView.
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

Predictions From Evolutionary Theory for Urban Environments. [PDF]

Evol Appl
MacPherson A, Caizergues AE, Savary P, Xu K, Messer PW, Akbar MN, Fortin MJ, Holt RD, Hoi AG, Mideo N, Ness R, Peres-Neto PR, Santangelo JS, Johnson MTJ.   +13 more
europepmc   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
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, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source