Results 151 to 160 of about 13,204,286 (295)

Opportunities of Semiconducting Oxide Nanostructures as Advanced Luminescent Materials in Photonics

Advanced Materials, EarlyView.
The review discusses the challenges of wide and ultrawide bandgap semiconducting oxides as a suitable material platform for photonics. They offer great versatility in terms of tuning microstructure, native defects, doping, anisotropy, and micro‐ and nano‐structuring. The review focuses on their light emission, light‐confinement in optical cavities, and
Ana Cremades, Pedro Hidalgo, David Maestre, Ruth Martínez‐Casado, Emilio Nogales, Beatriz Rodríguez, G. Cristian Vásquez, Bianchi Méndez   +7 more
wiley   +1 more source

Algorithmic Mass: A Theory of Stability and Change in Machine Learning

This paper introduces the concept of "Algorithmic Mass," a theoretical framework for understanding the inherent stability and resistance to change within machine learning models. Algorithmic Mass is defined as a measure of the accumulated complexity and learned parameters within a model, directly proportional to its difficulty to modify.
openaire   +1 more source

Coordinative structures as scale-free networks: Cascade and percolation dynamics in motor learning with empirical validation. [PDF]

PLoS Comput Biol
Park C.
europepmc   +1 more source

Flexoelectrically Induced Polar Topology in Twisted SrTiO3 Membranes

Advanced Materials, EarlyView.
Twisted SrTiO3 bilayers host polar vortices of flexoelectric origin, revealed through combined experiment and theory. By reconstructing polarization from the toroidal moment of strain gradients, the work establishes a 3D chiral state with broken inversion and mirror symmetries.
Isabel Tenreiro, Hugo Aramberri, Víctor Rouco, Gabriel Sánchez‐Santolino, Mariona Cabero, Fernando Gallego, David Sánchez‐Manzano, José M. González‐Calbet, Federico Mompeán, Mar García‐Hernández, Alberto Rivera‐Calzada, Jorge Íñiguez‐González, Carlos León, Jacobo Santamaría   +13 more
wiley   +1 more source

Predicting Density and Elucidating the Thermodynamic Drivers of Viscosity in Carboxy-Functionalized Imidazolium Ionic Liquids. [PDF]

Molecules
Cakó Bagány N, Armaković S, Armaković S, Šarac B, Belić S, Cerc-Korošec R, Bešter-Rogač M, Gadžurić S.   +7 more
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

Algorithmic Stability Theory for Distributed Learning with Partial Observability

Distributed learning offers significant advantages for large-scale machine learning, particularly in scenarios where data is inherently distributed and communication is constrained. However, the convergence of these algorithms is often fragile, especially when faced with partial observability – where agents only have access to incomplete information ...
openaire   +1 more source

Conflict, trust, and power in international joint ventures: a governance perspective. [PDF]

Front Psychol
Almahmoud M, Zhao X, Ullah F, Hlaing NM.
europepmc   +1 more source

Single‐Chromophore Homojunction Organic Solar Cells: A Path to Simplicity and Efficiency

Advanced Materials, EarlyView.
This perspective discusses how the intrinsic optoelectronic properties of organic semiconductors, their molecular packing in the solid‐state, and internal energetic gradients within a device can enable free‐charge carrier generation in homojunction organic solar cells.
Shaun McAnally, Paul L. Burn, Paul E. Shaw   +2 more
wiley   +1 more source

Data field theory: a geometric framework for learning on Riemannian manifolds with synthetic validation and limitation analysis. [PDF]

Front Big Data
Nehzati M.
europepmc   +1 more source