Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Photons with spin angular momentum possess intrinsic chirality, which underpins many phenomena including nonlinear optics, quantum optics, topological photonics and chiroptics. Intrinsic chirality is weak in natural materials, and recent theoretical proposals aimed to enlarge circular dichroism by resonant metasurfaces supporting bound states in the continuum that enhance substantially chiral light-matter interactions. Those insightful works resort to three-dimensional sophisticated geometries, which are too challenging to be realized for optical frequencies. Therefore, most of the experimental attempts showing strong circular dichroism rely on false/extrinsic chirality by using either oblique incidence or structural anisotropy. Here we report on the experimental realization of true/intrinsic chiral response with resonant metasurfaces in which the engineered slant geometry breaks both in-plane and out-of-plane symmetries. Our result marks, to our knowledge, the first observation of intrinsic chiral bound states in the continuum with near-unity circular dichroism of 0.93 and a high quality factor exceeding 2,663 for visible frequencies. Our chiral metasurfaces may lead to a plethora of applications in chiral light sources and detectors, chiral sensing, valleytronics and asymmetric photocatalysis.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1038/s41586-022-05467-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Gene mutation estimations via mutual information and Ewens sampling based CNN & machine learning algorithms.
J Appl Stat
February 2025
Department of Mathematics and State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, People's Republic of China.
We conduct gene mutation rate estimations via developing mutual information and Ewens sampling based convolutional neural network (CNN) and machine learning algorithms. More precisely, we develop a systematic methodology through constructing a CNN. Meanwhile, we develop two machine learning algorithms to study protein production with target gene sequences and protein structures.
View Article and Find Full Text PDFUnravelling phosphorylation-induced impacts on inhibitor-CDK2 through multiple independent molecular dynamics simulations and deep learning.
SAR QSAR Environ Res
August 2025
Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China.
Phosphorylation plays an important role in the activity of CDK2 and inhibitor binding, but the corresponding molecular mechanism is still insufficiently known. To address this gap, the current study innovatively integrates molecular dynamics (MD) simulations, deep learning (DL) techniques, and free energy landscape (FEL) analysis to systematically explore the action mechanisms of two inhibitors (SCH and CYC) when CDK2 is in a phosphorylated state and bound state of CyclinE. With the help of MD trajectory-based DL, key functional domains such as the loops L3 loop and L7 are successfully identified.
View Article and Find Full Text PDFOptimizing dose rate to minimize delivery time in proton pencil beam dose-driven continuous scanning.
Med Phys
September 2025
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Background: Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.
Purpose: This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT).
Visible Light-Driven Membrane-Bound Compartment for Precise Regulation of Enzyme Activity.
Angew Chem Int Ed Engl
September 2025
State Key Laboratory of Advanced Drug Delivery and Release Systems, Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
Photo-responsive systems provide a powerful tool to reversibly regulate enzyme activity. However, inhibitor-based strategies, though widely used, are often restricted to specific enzymes. Noninhibitor strategies, such as enzyme surface modification or genetic mutation, often compromise structural integrity or residual activity.
View Article and Find Full Text PDFTwo-Step Semi-Automated Classification of Choroidal Metastases on MRI: Orbit Localization via Bounding Boxes Followed by Binary Classification via Evolutionary Strategies.
AJNR Am J Neuroradiol
September 2025
From the Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America (J.S.S., B.M., S.H., A.H., J.S.), and Department of Aerospace Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (H.S.).
Background And Purpose: The choroid of the eye is a rare site for metastatic tumor spread, and as small lesions on the periphery of brain MRI studies, these choroidal metastases are often missed. To improve their detection, we aimed to use artificial intelligence to distinguish between brain MRI scans containing normal orbits and choroidal metastases.
Materials And Methods: We present a novel hierarchical deep learning framework for sequential cropping and classification on brain MRI images to detect choroidal metastases.