Results 51 to 60 of about 549,230 (245)

Near‐Infrared Emitting Lanthanide Catecholate Giant Single Crystals – Morphology Control and Photon Down‐Conversion

open access: yesAdvanced Functional Materials, EarlyView.
Controlled syntheses of lanthanide coordination polymers based on the dihydroxybenzoquinone (DHBQ) organic linker afforded large single crystals of Ln‐DHBQ CPs (Ln = Yb, Nd). A novel structural variant of Yb‐DHBQ is identified by means of single crystal diffraction analysis.
Marina I. Schönherr   +7 more
wiley   +1 more source

Exploring the PV Power Forecasting at Building Façades Using Gradient Boosting Methods

open access: yesEnergies, 2023
Solar power forecasting is of high interest in managing any power system based on solar energy. In the case of photovoltaic (PV) systems, and building integrated PV (BIPV) in particular, it may help to better operate the power grid and to manage the ...
Jesús Polo   +5 more
doaj   +1 more source

Stochastic oscillations of adaptive networks: application to epidemic modelling

open access: yes, 2012
Adaptive-network models are typically studied using deterministic differential equations which approximately describe their dynamics. In simulations, however, the discrete nature of the network gives rise to intrinsic noise which can radically alter the ...
Catherine Mills   +9 more
core   +1 more source

Atomic‐Scale Light Coupling Control in Ultrathin Photonic Membranes

open access: yesAdvanced Functional Materials, EarlyView.
Ultrathin photonic nanomembranes provide atomic‐scale control over the coupling between incident light and high‐Q photonic modes, enabling angstrom‐level resonance tuning and strong field confinement. When integrated with TMD monolayers, they further yield enhanced light–matter interactions, offering a versatile platform for advancing quantum photonics,
Chih‐Zong Deng   +8 more
wiley   +1 more source

Stochastic embedding DFT: Theory and application to p-nitroaniline in water. [PDF]

open access: yes, 2019
Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham density functional theory (DFT) method, the density is an average over multiple stochastic ...
Baer, Roi   +4 more
core  

Domain Wall Rebounds Driven by Competing Entropic and Spin‐Transfer Torques in Cylindrical Nanowires

open access: yesAdvanced Functional Materials, EarlyView.
Domain‐wall motion in cylindrical magnetic nanowires driven by nanosecond current pulses. Low current densities efficiently displace domain walls, whereas higher currents cause rebound at the wire ends. The effect results from the interplay between spin‐transfer torque and thermally induced processes, highlighting the role of thermal gradients in ...
Elias Saugar   +11 more
wiley   +1 more source

Statistical Interpolation of Tidal Datums and Computation of Its Associated Spatially Varying Uncertainty

open access: yesJournal of Marine Science and Engineering, 2016
Tidal datums are key components in NOAA’s Vertical Datum transformation project (VDatum). In this paper, we propose a statistical interpolation method, derived from the variational principle, to calculate tidal datums by blending the modeled and the ...
Lei Shi, Edward Myers
doaj   +1 more source

A stochastic sub-national population projection methodology with an application to the Waikato region of New Zealand [PDF]

open access: yes, 2010
In this paper we use a stochastic population projection methodology at the sub-national level as an alternative to the conventional deterministic cohort-component method.
Cameron, Michael Patrick, Poot, Jacques
core   +1 more source

2D Magnetic and Topological Quantum Materials and Devices for Ultralow Power Spintronics

open access: yesAdvanced Functional Materials, EarlyView.
2D magnets and topological quantum materials enable ultralow‐power spintronics by combining robust magnetic order with symmetry‐protected, Berry‐curvature‐driven transport. Fundamentals of 2D anisotropy and spin‐orbit‐coupling induced band inversion are linked to scalable growth and vdW stacking.
Brahmdutta Dixit   +5 more
wiley   +1 more source

Probabilistic short term wind power forecasts using deep neural networks with discrete target classes [PDF]

open access: yesAdvances in Geosciences, 2018
Usually, neural networks trained on historical feed-in time series of wind turbines deterministically predict power output over the next hours to days.
M. Felder   +5 more
doaj   +1 more source

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