Results 31 to 40 of about 16,490 (305)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced 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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Synergistic Compatibilization of CsPbBr3 Perovskites and HfO2 Nanocrystals for Hybrid Sensitized Nanoscintillators

Advanced Functional Materials, EarlyView.
Lead halide perovskite nanocrystals are promising scintillators but suffer from reabsorption losses and limited compatibility with high‐Z additives. Hybridization of CsPbBr3 nanocrystals with PbBr2‐passivated HfO2 nanoparticle sensitizers, achieved during or after synthesis, produces stable composites with maintained optical quality, improved ...
Francesco Bruni, Saptarshi Chakraborty, Andrea Fratelli, Abdessamad El Adel, Jordi Llusar, Francesco Carulli, Matteo L. Zaffalon, Chenger Wang, Vojtech Zabloudil, Etiennette Auffray, Francesco Meinardi, Leonardo Poletti, Laura Lazzarini, Daniela Manno, Anna Galli, Francesca Rossi, Ivan Infante, Sergio Brovelli   +17 more
wiley   +1 more source

Single- and Multi-Frequency Direct Sampling Methods in a Limited-Aperture Inverse Scattering Problem

IEEE Access, 2020
Although the direct sampling method (DSM) has demonstrated its feasibility and robustness for imaging of small inhomogeneities, mathematical analyses of DSM have been conducted only on the full-aperture inverse scattering problem.
Sangwoo Kang, Marc Lambert, Chi Young Ahn, Taeyoung Ha, Won-Kwang Park   +4 more
doaj   +1 more source

Circular‐Polarization‐Sensitive Organic Photodetectors with a Chiral Nanopatterned Electrode Inverse‐Designed by Genetic Algorithm

Advanced Functional Materials, EarlyView.
A chiral photodetector capable of selectively distinguishing left‐ and right‐handed circularly polarized light is experimentally demonstrated. The device, which features a nanopatterned electrode inverse‐designed by a genetic algorithm within a metal–dielectric–metal nanocavity that incorporates a vacuum‐deposited small‐molecule multilayer, exhibits ...
Kyung Ryoul Park, Jewoong Lee, In‐Suk Choi, Changsoon Kim   +3 more
wiley   +1 more source

Two-Dimensional Scattering of Line Source Electromagnetic Waves by a Layered Obstacle

Mathematics, 2023
We consider the scattering problem of line source electromagnetic waves using a multi-layered obstacle with a core, which may be a perfect conductor, a dielectric, or has an impedance surface. We formulate this problem in two dimensions and we prove some
Christodoulos E. Athanasiadis, Paraskevi Roupa   +1 more
doaj   +1 more source

Block Copolymers: Emerging Building Blocks for Additive Manufacturing

Advanced Functional Materials, EarlyView.
This review addresses how block copolymer (BCP) physics and rheology have led to the widespread use of BCPs in advanced additive manufacturing techniques, with particular emphasis on the untapped potential of these nanostructured materials toward achieving multi‐scale architected materials with unique, programmable material properties.
Alice S. Fergerson, Hemish B. Thakkar, Jiaen Wu, Emily C. Davidson   +3 more
wiley   +1 more source

Characterizing Scalar Metasurfaces Using Time-Domain Reflectometry

IEEE Access, 2022
Two efficient methodologies for the determination of electromagnetic (EM) constitutive properties of scalar metasurfaces are introduced and discussed. In contrast to the available methods, and in line with the recent increasing interest in time-domain ...
Tomas Dolezal, Petr Kadlec, Martin Stumpf   +2 more
doaj   +1 more source

A Programmable Semiconductor Containing Active Molecular Photoswitches Located in the Crystal's Volume Phase

Advanced Functional Materials, EarlyView.
A novel approach for the design of functional semiconductors is presented, which utilizes the excellent optoelectronic properties of layered hybrid perovskites and the possibility to introduce a molecular photoswitch as the organic spacer. This concept is successfully demonstrated on a coumarin‐based system with the possibility to change the bandgap ...
Oliver Treske, Yaşar Krysiak, Hans Tornatzky, Markus R. Wagner, Sebastian Polarz   +4 more
wiley   +1 more source

A deep neural network for general scattering matrix

Nanophotonics, 2023
The scattering matrix is the mathematical representation of the scattering characteristics of any scatterer. Nevertheless, except for scatterers with high symmetry like spheres or cylinders, the scattering matrix does not have any analytical forms and ...
Jing Yongxin, Chu Hongchen, Huang Bo, Luo Jie, Wang Wei, Lai Yun   +5 more
doaj   +1 more source