Results 71 to 80 of about 567 (213)
Hermite type moving-least-squares approximations
The moving-least-squares approach, first presented by McLain [1], is a method for approximating multivariate functions using scattered data information.
Komargodski, Z., Levin, D.
core +1 more source
Conventional doping of P3HT with F4TCNQ results in poor charge transport. However, when F4TCNQ is exchanged with LiTFSI, the transport characteristics are greatly enhanced. We find the increase in charge transport is directly related to an increase in the mesoscale ordering of P3HT, resulting in longer and better‐connected transport pathways.
Quynh M. Duong +9 more
wiley +1 more source
Error bound for radial basis interpolation in terms of a growth function
We suggest an improvement of Wu-Schaback local error bound for radial basis interpolation by using a polynomial growth function. The new bound is valid without any assumptions about the density of the interpolation centers.
Davydov, Oleg
core
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Significant nanoscale oxygen diffusion coefficient variations are measured in ferroelectric hafnium zirconium oxide films with grain boundaries and electrode interfaces exhibiting values 104 times larger than the grain cores. Overall coefficients are 10X larger for films prepared with metal nitride electrodes compared to refractory metals. New insights
Liron Shvilberg +6 more
wiley +1 more source
Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction [PDF]
[Objectives] To enhance water quality prediction accuracy, this study aims to address the following challenges: (1) traditional prediction methods often rely on simple, elementary decomposition techniques, limiting their ability to extract meaningful ...
GUO Li-jin, WU Hao-tian
doaj +1 more source
Orthogonal-least-squares forward selection for parsimonious modelling from data
The objective of modelling from data is not that the model simply fits the training data well. Rather, the goodness of a model is characterized by its generalization capability, interpretability and ease for knowledge extraction.
Sheng Chen, Chen, Sheng
core
Near‐Infrared Light‐Driven Zn/Au Janus Micromotors for Multiplex SERS Detection of Anticancer Drugs
Zn/Au Janus micromotors, propelled by thermophoretic effects under NIR light, function as active SERS platforms for single and multiplex detection of anticancer drugs. Their dynamic motion enhances analyte exchange at the Au interface, reducing saturation and competitive adsorption, thereby improving sensitivity and extending the linear detection range.
Tijana Maric +8 more
wiley +1 more source
Metasurfaces and other structured photonic environments can dramatically modify the absorption and/or light emission of semiconductors. However, the consequences of these changes on the temperature of the system are not well understood. The authors address this problem for colloidal nanocrystals and leverage their findings to convert light into ...
Hugo Kowalczyk +7 more
wiley +1 more source
Smoothing under Diffeomorphic Constraints with Homeomorphic Splines [PDF]
In this paper we introduce a new class of diffeomorphic smoothers based on general spline smoothing techniques and on the use of some tools that have been recently developed in the context of image warping to compute smooth diffeomorphisms.
Gadat, Sébastien, Bigot, Jérémie
core +1 more source

