Results 61 to 70 of about 83,436 (246)

Understanding Decoherence of the Boron Vacancy Center in Hexagonal Boron Nitride

open access: yesAdvanced Functional Materials, EarlyView.
State‐of‐the‐art computations unravel the intricate decoherence dynamics of the boron vacancy center in hexagonal boron nitride across magnetic fields from 0 to 3 T. Five distinct regimes emerge, dominated by nuclear spin interactions, revealing optimal coherence times of 1–20 µs in the 180–350 mT range for isotopically pure samples.
András Tárkányi, Viktor Ivády
wiley   +1 more source

On domains of convergence of multiple random Dirichlet series [PDF]

open access: yesМатематичні Студії, 2011
We establish relations between domains of convergence and absolute convergence of the multiple random Dirichlet series.
O. B. Skaskiv, O. Yu. Zadorozhna
doaj  

Unveiling Phonon Contributions to Thermal Conductivity and the Applicability of the Wiedemann—Franz Law in Ruthenium and Tungsten Thin Films

open access: yesAdvanced Functional Materials, EarlyView.
Thermal transport in Ru and W thin films is studied using steady‐state thermoreflectance, ultrafast pump–probe spectroscopy, infrared‐visible spectroscopy, and computations. Significant Lorenz number deviations reveal strong phonon contributions, reaching 45% in Ru and 62% in W.
Md. Rafiqul Islam   +14 more
wiley   +1 more source

World health status 1950-2015: Converging or diverging.

open access: yesPLoS ONE, 2019
ObjectiveTo advance the goal of "Grand Convergence" in global health by 2035, this study tested the convergence hypothesis in the progress of the health status of individuals from 193 countries, using both standard and cutting-edge convergence metrics ...
Srinivas Goli   +3 more
doaj   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

open access: yesAdvanced Functional Materials, EarlyView.
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker   +5 more
wiley   +1 more source

Convergence of household expenditures of the EU-member and acceding countries in the years 1995-2002

open access: yesAgricultural Economics (AGRICECON), 2004
The convergence in household consumption expenditure contributes to the aims defined in the Treaty of the European Union. Consumption expenditure convergence also restricts the impacts of asymmetric shocks under the bounded inner market mobility of goods,
M. Ševela
doaj   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

open access: yesAdvanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva   +9 more
wiley   +1 more source

Non-polynomial spline method for singularly perturbed differential difference equations with delay and advance terms

open access: yesҚарағанды университетінің хабаршысы. Математика сериясы
In this study, we introduced a non-polynomial spline technique to address singularly perturbed differential difference equations involving both delay and advanced parameters.
A.M. Regal, S.D. Kumar
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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