While a large variety of conjugated polymers exist, polydiacetylenes (PDAs) remain a major research area among scientists due to their interesting optical, spectral, electronic, and structural properties. Heavily reviewed in regards to their stimuli responsive properties, much is known about the assortment of sensing and detection capabilities of PDAs. In this article, we look more upon the structural diversities of polydiacetylenes that have been achieved in recent years, particularly from a hierarchical perspective of 1, 2, and 3-dimensional configurations. In addition, we examine how these different dimensional arrangements of PDAs have heralded clear applications in several key areas. Successful integration of these stimuli-responsive "smart" materials into various geometries has required researchers to have a comprehensive understanding of both the fabrication and synthesis processes, as well as the signalling mechanism for the optical, fluorogenic or spectral transitions. The on-going discovery of new PDA formulations continues to provide interesting structural manifestations such as liposomes, tubes, fibres, organic/inorganic incorporated hybrids and composite structures. By highlighting some of the recent conceptual and technological developments, we hope to provide a measure of the current pace in new PDA derivative development as core components in efficient sensor, imaging and display systems.
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http://dx.doi.org/10.1039/c2cc17441c | DOI Listing |
J Imaging Inform Med
January 2025
Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3400 Spruce St., Philadelphia, PA, 19104, USA.
Integration of artificial intelligence (AI) into radiology practice can create opportunities to improve diagnostic accuracy, workflow efficiency, and patient outcomes. Integration demands the ability to seamlessly incorporate AI-derived measurements into radiology reports. Common data elements (CDEs) define standardized, interoperable units of information.
View Article and Find Full Text PDFSci Rep
January 2025
Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, People's Republic of China.
A dual-polarity, photovoltaic photodetector for red-green dual-wavelength detection is demonstrated, operating in the self-powered mode. It is based on a core-shell n-InGaN nanowire/p-CuO heterostructure with inner upward energy band bending and near surface downward energy band bending. This produces negative photocurrent for red light illumination and positive photocurrent for green light illumination.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
February 2025
Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616.
The L-type Ca channel (Ca1.2) is essential for cardiac excitation-contraction coupling. To contribute to the inward Ca flux that drives Ca-induced-Ca-release, Ca1.
View Article and Find Full Text PDFAdv Mater
January 2025
State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, 510275, China.
Terahertz (THz) signals are crucial for ultrawideband communication and high-resolution radar, demanding miniaturized detectors that can simultaneously measure multiple parameters such as intensity, frequency, polarization, and phase. Traditional detectors fail to meet these needs. To address this, we introduce a plasmon polariton atomic cavity (PPAC) detector based on monolayer graphene, offering a multifunctional, monolithic, and miniaturized solution.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Pathology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Background: Ras-GTPase-activating protein (GAP)-binding protein 1 (G3BP1) emerges as a pivotal oncogenic gene across various malignancies, notably including nasopharyngeal carcinoma (NPC). The use of automated image analysis tools for immunohistochemical (IHC) staining of particular proteins is highly beneficial, as it could reduce the burden on pathologists. Interestingly, there have been no prior studies that have examined G3BP1 IHC staining using digital pathology.
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