Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
11,771
result(s) for
"Jiang, C."
Sort by:
Diverse polarization angle swings from a repeating fast radio burst source
Fast radio bursts (FRBs) are millisecond-duration radio transients
1
,
2
of unknown origin. Two possible mechanisms that could generate extremely coherent emission from FRBs invoke neutron star magnetospheres
3
–
5
or relativistic shocks far from the central energy source
6
–
8
. Detailed polarization observations may help us to understand the emission mechanism. However, the available FRB polarization data have been perplexing, because they show a host of polarimetric properties, including either a constant polarization angle during each burst for some repeaters
9
,
10
or variable polarization angles in some other apparently one-off events
11
,
12
. Here we report observations of 15 bursts from FRB 180301 and find various polarization angle swings in seven of them. The diversity of the polarization angle features of these bursts is consistent with a magnetospheric origin of the radio emission, and disfavours the radiation models invoking relativistic shocks.
Polarization observations of the fast radio burst FRB 180301 with the FAST radio telescope show diverse polarization angle swings, consistent with a magnetospheric origin of the emission.
Journal Article
Enhanced charge density wave with mobile superconducting vortices in La1.885Sr0.115CuO4
Superconductivity in the cuprates is found to be intertwined with charge and spin density waves. Determining the interactions between the different types of order is crucial for understanding these important materials. Here, we elucidate the role of the charge density wave (CDW) in the prototypical cuprate La
1.885
Sr
0.115
CuO
4
, by studying the effects of large magnetic fields (
H
) up to 24 Tesla. At low temperatures (
T
), the observed CDW peaks reveal two distinct regions in the material: a majority phase with short-range CDW coexisting with superconductivity, and a minority phase with longer-range CDW coexisting with static spin density wave (SDW). With increasing magnetic field, the CDW first grows smoothly in a manner similar to the SDW. However, at high fields we discover a sudden increase in the CDW amplitude upon entering the vortex-liquid state. Our results signify strong coupling of the CDW to mobile superconducting vortices and link enhanced CDW amplitude with local superconducting pairing across the
H
−
T
phase diagram.
Superconductivity in the cuprates is known to be intertwined with charge and spin density waves. Here, the authors study the prototypical cuprate La
1.885
Sr
0.115
CuO
4
via x-ray scattering and discover a sudden increase in the charge-density-wave amplitude upon entering the superconducting-vortex-liquid state at high magnetic field.
Journal Article
Cavity optomechanical spring sensing of single molecules
Label-free bio-sensing is a critical functionality underlying a variety of health- and security-related applications. Micro-/nano-photonic devices are well suited for this purpose and have emerged as promising platforms in recent years. Here we propose and demonstrate an approach that utilizes the optical spring effect in a high-
Q
coherent optomechanical oscillator to dramatically enhance the sensing resolution by orders of magnitude compared with conventional approaches, allowing us to detect single bovine serum albumin proteins with a molecular weight of 66 kDa at a signal-to-noise ratio of 16.8. The unique optical spring sensing approach opens up a distinctive avenue that not only enables biomolecule sensing and recognition at individual level, but is also of great promise for broad physical sensing applications that rely on sensitive detection of optical cavity resonance shift to probe external physical parameters.
Detection of a single nanoparticle or molecule is essential for many applications. Here, Yu
et al.
demonstrate the use of an optical cavity with optomechanical oscillation to detect single bovine serum albumin proteins, with potential for studying mechanical properties and interactions of individual molecules.
Journal Article
Dynamic anticrack propagation in snow
Continuum numerical modeling of dynamic crack propagation has been a great challenge over the past decade. This is particularly the case for anticracks in porous materials, as reported in sedimentary rocks, deep earthquakes, landslides, and snow avalanches, as material inter-penetration further complicates the problem. Here, on the basis of a new elastoplasticity model for porous cohesive materials and a large strain hybrid Eulerian–Lagrangian numerical method, we accurately reproduced the onset and propagation dynamics of anticracks observed in snow fracture experiments. The key ingredient consists of a modified strain-softening plastic flow rule that captures the complexity of porous materials under mixed-mode loading accounting for the interplay between cohesion loss and volumetric collapse. Our unified model represents a significant step forward as it simulates solid-fluid phase transitions in geomaterials which is of paramount importance to mitigate and forecast gravitational hazards.
Anticrack propagation in snow results from the mixed-mode failure and collapse of a buried weak layer and can lead to slab avalanches. Here, authors reproduce the complex dynamics of anticrack propagation observed in field experiments using a Material Point Method with large strain elastoplasticity.
Journal Article
Arabidopsis Transcription Factors: Genome-Wide Comparative Analysis among Eukaryotes
The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.
Journal Article
Exceeding 20% efficiency with in situ group V doping in polycrystalline CdTe solar cells
CdTe-based solar technology has achieved one of the lowest levelized costs of electricity among all energy sources as well as state-of-the-art field stability. Yet, there is still ample headroom to improve. For decades, mainstream technology has combined fast CdTe deposition with a CdCl
2
anneal and Cu doping. The resulting defect chemistry is strongly compensated and limits the useful hole density to ~10
14
cm
−3
, creating a ceiling for fill factor, photovoltage and efficiency. In addition, Cu easily changes energy states and diffuses spatially, creating a risk of instabilities that must be managed with care. Here, we demonstrate a significant shift by doping polycrystalline CdSe
x
Te
1 −
x
and CdTe films with As while removing Cu entirely from the solar cell. The absorber majority-carrier density is increased by orders of magnitude to 10
16
–10
17
cm
−3
without compromising the lifetime, and is coupled with a high photocurrent greater than 30 mA cm
−2
. We demonstrate pathways for fast dopant incorporation in polycrystalline thin films, improved stability and 20.8% solar cell efficiency.
CdTe solar cells have relied for decades on copper, which creates limited hole density, stability issues and a ceiling for voltage and efficiency. Now, Metzger et al. demonstrate As-doped Cu-free polycrystalline CdTe cells with enhanced hole density and dopant stability, achieving 20.8% efficiency.
Journal Article
Probability-interval hybrid uncertainty analysis for structures with both aleatory and epistemic uncertainties: a review
Traditional structural uncertainty analysis is mainly based on probability models and requires the establishment of accurate parametric probability distribution functions using large numbers of experimental samples. In many actual engineering problems, the probability distributions of some parameters can be established due to sufficient samples available, whereas for some parameters, due to the lack or poor quality of samples, only their variation intervals can be obtained, or their probability distribution types can be determined based on the existing data while some of the distribution parameters such as mean and standard deviation can only be given interval estimations. This thus will constitute an important type of probability-interval hybrid uncertain problem, in which the aleatory and epistemic uncertainties both exist. The probability-interval hybrid uncertainty analysis provides an important mean for reliability analysis and design of many complex structures, and has become one of the research focuses in the field of structural uncertainty analysis over the past decades. This paper reviews the four main research directions in this area, i.e., uncertainty modeling, uncertainty propagation analysis, structural reliability analysis, and reliability-based design optimization. It summarizes the main scientific problems, technical difficulties, and current research status of each direction. Based on the review, this paper also provides an outlook for future research in probability-interval hybrid uncertainty analysis.
Journal Article
Evidence-theory-based structural reliability analysis with epistemic uncertainty: a review
Epistemic uncertainty widely exists in the early design stage of complex engineering structures or throughout the full-life cycle of innovative structure design, which should be appropriately quantified, managed, and controlled to ensure the reliability and safety of the product. Evidence theory is usually regarded as a promising model to deal with epistemic uncertainty, as it employs a general and flexible framework, the basic probability assignment function, which enables the quantification and propagation of epistemic uncertainty more effective. Due to its strong ability, evidence theory has been applied in the field of structural reliability during the past few decades, and a series of important progresses have been achieved. Evidence-theory-based reliability analysis thus provides an important means for engineering structure design, especially under epistemic uncertainty, and it has become one of the research hotspots in the field of structural reliability. This paper reviews the four main research directions of evidence-theory-based reliability analysis, and each one is focused on solving one critical issue in this field, namely, computational efficiency, parameter correlation, hybrid uncertainties, and reliability-based design optimization. It summarizes the main scientific problems, technical difficulties, and current research status of each direction. Based on the review, this paper also provides an outlook for future research in evidence-theory-based structural reliability analysis.
Journal Article
The Investigation of Consumers’ Behavior Intention in Using Green Skincare Products: A Pro-Environmental Behavior Model Approach
Increasing environmental awareness among societies is motivating consumers to use green cosmetic products. Green skincare products are the fastest growing sector in the worldwide market compared with other green cosmetic products. However, compared with general cosmetic products, the market share of green cosmetic products in Indonesia is relatively low. The present research investigated consumers’ purchasing intentions toward green skincare products in Indonesia using the pro-environmental reasoned action (PERA) model. A total of 251 female consumers participated in this study. Structural equation modeling was conducted to reveal the relationships between the five factors in the PERA model. The results indicated that perceived authority support (PAS) has a positive effect on perceived environmental concern (PEC). PAS and PEC have positive effects on attitude (AT) and subjective norms (SN), and AT and SN have positive effects on behavioral intention (BI) to purchase green skincare products, with the key factor being attitude. The PERA model was able to describe 62.6% of the BI to purchase green skincare products. Green skincare companies are recommended to produce more green skincare products and market the products by involving public figures and emphasizing the green attributes. Furthermore, we recommend that green skincare companies produce quality and sustainable products using quality processes, and be involved in pro-environmental activity to increase consumer attention to the green skincare products.
Journal Article