Results 111 to 120 of about 159 (158)

Challenges and Opportunities in Machine Learning for Light‐Emitting Polymers

Macromolecular Rapid Communications, EarlyView.
The performance of light‐emitting polymers emerges from coupled effects of chemical diversity, morphology, and exciton dynamics across multiple length scales. This Perspective reviews recent design strategies and experimental challenges, and discusses how machine learning can unify descriptors, data, and modeling approaches to efficiently navigate ...
Tian Tian, Yinyin Bao
wiley   +1 more source

On the analyzing of bifurcation properties of the one‐dimensional Mackey–Glass model by using a generalized approach

Mathematical Methods in the Applied Sciences, EarlyView.
The goal of this work is to look at how a nonlinear model describes hematopoiesis and its complexities utilizing commonly used techniques with historical and material links. Based on time delay, the Mackey–Glass model is explored in two instances. To offer a range, the relevance of the parameter impacting stability (bifurcation) is recorded.
Shuai Zhang, Yaya Wang, Hongyin Geng, Wei Gao, Esin Ilhan, Haci Mehmet Baskonus   +5 more
wiley   +1 more source

Unveiling New Perspectives on the Hirota–Maccari System With Multiplicative White Noise

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In this study, we delve into the stochastic Hirota–Maccari system, which is subjected to multiplicative noise according to the Itô sense. The stochastic Hirota–Maccari system is significant for its ability to accurately model how stochastic affects nonlinear wave propagation, providing valuable insights into complex systems like fluid dynamics
Mohamed E. M. Alngar, Khaled A. Gepreel, Reham M. A. Shohib, Yakup Yildirim   +3 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Localising the Sustainable Development Goals. A Place‐Based Analysis of Sustainable Development in Rural and Urban Areas

Sustainable Development, EarlyView.
ABSTRACT There are increasing calls for a place‐based approach towards the Sustainable Development Goals that show their territorial diversity at subnational level. Based on 33 indicators, covering 13 SDGs and aggregated in three sub‐indexes (economy, social and environment), this paper develops a Sustainable Development Index for Rural and Urban Areas
Lucas Olmedo, Paul Holloway, John Barimo, Mary O'Shaughnessy   +3 more
wiley   +1 more source

Do We Really Know Why Carbon Nanotubes Grow?

Small, EarlyView.
The CNT growth mechanism is still debated. We propose a heterogeneous (2D) classical nucleation framework comparing pathways for graphenic patches, caps, and full CNTs. Despite its simplicity, it rationalizes key trends, including the correlation between catalyst particle size and CNT diameter.
Nicola Verziaggi, Matteo Bragagnolo, Niloufar Atashi, Paula Dias, Adelio Mendes, Gonzalo Prieto, Simone Meloni   +6 more
wiley   +1 more source

Quantifying Population Reversibility of Sensor Performance in Multi‐Cycle Single‐Sensor Recovery Assay

Small, EarlyView.
Single‐walled carbon nanotubes (SWCNTs) are versatile optical nanosensors that can be imaged at the single‐sensor level to map biological processes. To translate such imaging into calibrated measurements, sensor recovery under repeated analyte exposures must be analyzed.
Geffen Rosenberg, Gili Bisker
wiley   +1 more source

mcstas_gisans: combining ray tracing with the distorted‐wave Born approximation using McStas and BornAgain for virtual GISANS experiments

Journal of Applied Crystallography, EarlyView.
mcstas_gisans is a Python‐based framework that enables simulation of grazing‐incidence small‐angle neutron scattering experiments by integrating McStas and BornAgain into a single workflow.The mcstas_gisans framework is a collection of Python scripts and modules to facilitate the simulation of grazing‐incidence small‐angle neutron scattering (GISANS ...
Milán Klausz, Artur Glavic, Sebastian Köhler, Thomas Arnold, Nicolò Paracini, Philipp Gutfreund, Marité Cárdenas, Max Wolff, Tommy Nylander   +8 more
wiley   +1 more source

Establishing Shape Correspondences: A Survey

Computer Graphics Forum, EarlyView.
Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
wiley   +1 more source

On optimisation of Paganin's method for propagation‐based X‐ray phase‐contrast imaging and tomography

Journal of Microscopy, EarlyView.
Abstract Paganin's method for image reconstruction in propagation‐based phase‐contrast X‐ray imaging and tomography has enjoyed broad acceptance in recent years, with over one thousand publications citing its use. The present paper discusses approaches to optimisation of the method with respect to simple image quality metrics, such as signal‐to‐noise ...
Timur E. Gureyev, David M. Paganin, Ashkan Pakzad, Harry M. Quiney   +3 more
wiley   +1 more source