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Static and dynamic Raman excitation mapping of chirality-pure carbon nanotube films
Raman spectroscopy is a powerful method for probing electronic and vibrational properties of materials, particularly nanomaterials such as single-wall carbon nanotubes. Typically, Raman spectroscopy is conducted at a single, or few, excitation wavelengths, but that provides limited information about excitation resonance structure, and their dynamical evolution. Here, we extend a sensitive full-spectrum technique to rapidly obtain two-dimensional Raman excitation maps both statically and dynamically for chirality-pure single-wall carbon nanotube films. We demonstrate sensitive evaluation of structured resonance profiles even from weak vibrational modes, and sub-second time resolution of the dynamics of photo-driven defect production. Findings include the direct observation of bands and their profiles – including bands which could be missed in conventional Raman spectroscopy – and demonstration of differences for odd vs. even defect band combinations. This opens up possibilities to investigate the coupling of electronic states with vibrational modes in nanomaterials and track their dynamical evolution subject to intentional modulation.
Elastic trapping by acoustoelastically induced transparency
Elastic bound states in the continuum (BICs) have recently attracted significant interests due to their exceptionally high-Q-factor, which enables the confined mode to be completely decoupled from spectrally coexisting radiative channels. We report on the emergence of a state that induces a slow vibration phenomenon, which exhibits a multiphysics analogy to the notion of slow light observed in electromagnetically induced transparency (EIT). Such a state can be achieved through the interaction of acoustoelastic coupling. Our proposed design involves a composite with two acoustic cavities encased in an elastic bar, making quasi-BICs feasible with high spatial efficiency in a localized area while allowing for the tunability of the Purcell factor by around six orders of magnitude. The observation of quasi-BICs with acoustoelastically induced transparency (AEIT) lineshapes, which are manifested by the coupling of two disparate physics domains, will expand the BIC family and enable applications in areas such as lasing, sensing, screening, and energy storage platforms where ultrahigh-Q-factor modes and radiative channels coexist.
Fabrication and modulation of flexible electromagnetic metamaterials
Flexible electromagnetic metamaterials are a potential candidate for the ideal material for electromagnetic control due to their unique physical properties and structure. Flexible electromagnetic metamaterials can be designed to exhibit specific responses to electromagnetic waves within a particular frequency range. Research shows that flexible electromagnetic metamaterials exhibit significant electromagnetic control characteristics in microwave, terahertz, infrared and other frequency bands. It has a wide range of applications in the fields of electromagnetic wave absorption and stealth, antennas and microwave devices, communication information and other fields. In this review, the currently popular fabrication methods of flexible electromagnetic metamaterials are first summarized, highlighting the electromagnetic modulation capability in different frequency bands. Then, the applications of flexible electromagnetic metamaterials in four aspects, namely electromagnetic stealth, temperature modulation, electromagnetic shielding, and wearable sensors, are elaborated and summarized in detail. In addition, this review also discusses the shortcomings and limitations of flexible electromagnetic metamaterials for electromagnetic control. Finally, the conclusion and perspective of the electromagnetic properties of flexible electromagnetic metamaterials are presented.
An artificial market model for the forex market
As financial markets have transitioned toward electronic trading, there has been a corresponding increase in the number of algorithmic strategies and degree of transaction frequency. This move to high-frequency trading at the millisecond level, propelled by algorithmic strategies, has brought to the forefront short-term market reactions, like market impact, which were previously negligible in low-frequency trading scenarios. Such evolution necessitates a new framework for analyzing and developing algorithmic strategies in these rapidly evolving markets. Employing artificial markets stands out as a solution to this problem. This study aims to construct an artificial foreign exchange market referencing market microstructure theory, without relying on the assumption of information or technical traders. Furthermore, it endeavors to validate the model by replicating stylized facts, such as fat tails, which exhibit a higher degree of kurtosis in the return distribution than that predicted by normal distribution models. The validated artificial market model will be used to simulate market dynamics and algorithm strategies; its generated rates could also be applied to pricing and risk management for currency options and other foreign exchange derivatives. Moreover, this work explores the importance of order flow and the underlying factors of stylized facts within the artificial market model.
Semantic embeddings reveal and address taxonomic incommensurability in psychological measurement
Taxonomic incommensurability denotes the difficulty in comparing scientific theories due to different uses of concepts and operationalizations. To tackle this problem in psychology, here we use language models to obtain semantic embeddings representing psychometric items, scales and construct labels in a vector space. This approach allows us to analyse different datasets (for example, the International Personality Item Pool) spanning thousands of items and hundreds of scales and constructs and show that embeddings can be used to predict empirical relations between measures, automatically detect taxonomic fallacies and suggest more parsimonious taxonomies. These findings suggest that semantic embeddings constitute a powerful tool for tackling taxonomic incommensurability in the psychological sciences.
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