A method for determining the modes that can be guided along infinite chains of metallic nanowires when they are embedded, as in most realistic set-ups, in layered media is presented. The method is based on a rigorous full-wave frequency-domain Source-Model Technique (SMT). The method allows efficient determination of the complex propagation constants and the surface-plasmon type modal fields. Sample results are presented for silver nanowires with circular and triangle-like cross-sections lying in an air-Si-glass layered structure.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1364/OE.19.025397 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
In unsupervised transfer learning for medical image segmentation, where existing algorithms face the challenge of error propagation due to inaccessible source domain data. In response to this scenario, source-free domain transfer algorithm with reduced style sensitivity (SFDT-RSS) is designed. SFDT-RSS initially pre-trains the source domain model by using the generalization strategy and subsequently adapts the pre-trained model to target domain without accessing source data.
View Article and Find Full Text PDFBioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.
J Chem Theory Comput
January 2025
School of Chemistry and Chemical Engineering, Queen's University Belfast, BT9 5AG Belfast, Northern Ireland, U.K.
Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy.
View Article and Find Full Text PDFIntegration of Multiple Climate Change Mitigation Actions and Health Co-Benefits: A Framework Using the Global Calculator.
Environ Health Perspect
December 2024
Centre for Environmental Policy, Imperial College, London, UK.
Background: The Global Calculator is an open-source model of the world's energy, land, and food systems. It is a pioneering online calculator to project the impact of interventions to mitigate climate change on global temperature. A few studies have been conducted to evaluate the health co-benefits of climate change mitigation, though they are still fragmentary.
View Article and Find Full Text PDFDeep generative models that produce novel molecular structures have the potential to facilitate chemical discovery. Flow matching is a recently proposed generative modeling framework that has achieved impressive performance on a variety of tasks including those on biomolecular structures. The seminal flow matching framework was developed only for continuous data.
View Article and Find Full Text PDFAccurate light source calibration is critical in numerous applications including physics-based computer vision and graphics. We propose an image-based method for calibrating non-isotropic point light sources, addressing challenges posed by their non-radially symmetric radiant intensity distribution and the non-Lambertian properties of the calibration target. We deduce an image formation model, and capture the intensity of the calibration target at multiple poses, coupled with accurate 3D geometry acquisition using the digital fringe projection technique.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!