BiFeO3-based heterostructures have attracted much attention for potential applications due to their room-temperature multiferroic properties, proper band gaps and ultrahigh ferroelectric polarization ...of BiFeO3, such as data storage, optical utilization in visible light regions and synapse-like function. Here, this work aims to offer a systematic review on the progress of BiFeO3-based heterostructures. In the first part, the optical, electric, magnetic, and valley properties and their interactions in BiFeO3-based heterostructures are briefly reviewed. In the second part, the morphologies of BiFeO3 and medium materials in the heterostructures are discussed. Particularly, in the third part, the physical properties and underlying mechanism in BiFeO3-based heterostructures are discussed thoroughly, such as the photovoltaic effect, electric field control of magnetism, resistance switching, and two-dimensional electron gas and valley characteristics. The fourth part illustrates the applications of BiFeO3-based heterostructures based on the materials and physical properties discussed in the second and third parts. This review also includes a future prospect, which can provide guidance for exploring novel physical properties and designing multifunctional devices.
Recently, sensors that can imitate human skin have received extensive attention. Capacitive sensors have a simple structure, low loss, no temperature drift, and other excellent properties, and can be ...applied in the fields of robotics, human–machine interactions, medical care, and health monitoring. Polymer matrices are commonly employed in flexible capacitive sensors because of their high flexibility. However, their volume is almost unchanged when pressure is applied, and they are inherently viscoelastic. These shortcomings severely lead to high hysteresis and limit the improvement in sensitivity. Therefore, considerable efforts have been applied to improve the sensing performance by designing different microstructures of materials. Herein, two types of sensors based on the applied forces are discussed, including pressure sensors and strain sensors. Currently, five types of microstructures are commonly used in pressure sensors, while four are used in strain sensors. The advantages, disadvantages, and practical values of the different structures are systematically elaborated. Finally, future perspectives of microstructures for capacitive sensors are discussed, with the aim of providing a guide for designing advanced flexible and stretchable capacitive sensors via ingenious human‐made microstructures.
The advantages, disadvantages, and practical applications of several popular microstructures that are widely employed in capacitive sensors are summarized. A microstructured dielectric layer or electrode can improve sensor sensitivity, reduce hysteresis, and endow the rigid electronic device with excellent elastic stretchability, which is an essential part of next‐generation wearable devices and soft robots.
Abstract
Triple-negative breast cancer (TNBC), a specific subtype of breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor ...2 (HER-2), has clinical features that include high invasiveness, high metastatic potential, proneness to relapse, and poor prognosis. Because TNBC tumors lack ER, PR, and HER2 expression, they are not sensitive to endocrine therapy or HER2 treatment, and standardized TNBC treatment regimens are still lacking. Therefore, development of new TNBC treatment strategies has become an urgent clinical need. By summarizing existing treatment regimens, therapeutic drugs, and their efficacy for different TNBC subtypes and reviewing some new preclinical studies and targeted treatment regimens for TNBC, this paper aims to provide new ideas for TNBC treatment.
Amorphous carbon nitride (ACN) with a bandgap of 1.90 eV shows an order of magnitude higher photocatalytic activity in hydrogen evolution under visible light than partially crystalline graphitic ...carbon nitride with a bandgap of 2.82 eV. ACN is photocatalytically active under visible light at a wavelength beyond 600 nm.
Soil stabilization technology based on microbial-induced carbonate precipitation (MICP) has gained widespread interest in geotechnical engineering. MICP has been found to be able to improve soil ...strength, stiffness, liquefaction resistance, erosion resistance, while maintaining a good permeability simultaneously. MICP processes involves a series of biochemical reactions that are affected by many factors, both intrinsically and externally. This paper reviews various influential factors for MICP process, including bacterial species, concentration of bacteria, temperature, pH, composition and concentration of cementation solution, grouting strategies, and soil properties. Through this comprehensive review, we find that: (1) the species and strains of bacteria, concentration of bacteria solution, temperature, pH value, and the cementation solution properties all affect the characteristics of formed calcium carbonate, such as crystal type, appearance and size, which consequently affect the cementation degree and distribution in geomaterials; (2) the condition with temperature between 20 and 40 °C, pH between 7 and 9.5, the concentration of the cementation solution within 1 mol/L, and high bacteria concentration is optimal for applying MICP in soil. Under the optimal condition, relatively low temperature, high pH value, and low concentration of cementation solution could help retain permeability and vice versa; (3) the effective grain size ranging from 10 to 1000 µm. MICP treatment works most effectively for larger size, well-graded sand; (4) the multi-phase, multi-concentration or electroosmotic grouting method can improve the MICP treatment efficiency. The grouting velocity below 0.042 mol/L/h is beneficial for improving the utilization ratio of cementation solution. The recommended grouting pressure is generally between 0.1 and 0.3 bar for MICP applications in sand and should not exceed 1.1 bar for silty and clayey soils.
Image-language matching tasks have recently attracted a lot of attention in the computer vision field. These tasks include image-sentence matching, i.e., given an image query, retrieving relevant ...sentences and vice versa, and region-phrase matching or visual grounding, i.e., matching a phrase to relevant regions. This paper investigates two-branch neural networks for learning the similarity between these two data modalities. We propose two network structures that produce different output representations. The first one, referred to as an embedding network , learns an explicit shared latent embedding space with a maximum-margin ranking loss and novel neighborhood constraints. Compared to standard triplet sampling, we perform improved neighborhood sampling that takes neighborhood information into consideration while constructing mini-batches. The second network structure, referred to as a similarity network , fuses the two branches via element-wise product and is trained with regression loss to directly predict a similarity score. Extensive experiments show that our networks achieve high accuracies for phrase localization on the Flickr30K Entities dataset and for bi-directional image-sentence retrieval on Flickr30K and MSCOCO datasets.
Increasing visible light absorption of classic wide‐bandgap photocatalysts like TiO2 has long been pursued in order to promote solar energy conversion. Modulating the composition and/or stoichiometry ...of these photocatalysts is essential to narrow their bandgap for a strong visible‐light absorption band. However, the bands obtained so far normally suffer from a low absorbance and/or narrow range. Herein, in contrast to the common tail‐like absorption band in hydrogen‐free oxygen‐deficient TiO2, an unusual strong absorption band spanning the full spectrum of visible light is achieved in anatase TiO2 by intentionally introducing atomic hydrogen‐mediated oxygen vacancies. Combining experimental characterizations with theoretical calculations reveals the excitation of a new subvalence band associated with atomic hydrogen filled oxygen vacancies as the origin of such band, which subsequently leads to active photo‐electrochemical water oxidation under visible light. These findings could provide a powerful way of tailoring wide‐bandgap semiconductors to fully capture solar light.
In contrast to the common tail‐like absorption band in hydrogen‐free oxygen‐deficient TiO2, an unusual strong absorption band spanning the full spectrum of visible light is achieved in red anatase TiO2 by intentionally introducing atomic hydrogen‐mediated oxygen vacancies that subsequently lead to active photo‐electrochemical water oxidation under visible light.
A unique sandwich structure is designed with pure sulfur between two graphene membranes, which are continuously produced over a large area, as a very simple but effective approach for the fabrication ...of Li–S batteries with ultrafast charge/discharge rates and long lifetimes.
One major limitation currently with studying street level urban design qualities for walkability is the often inconsistent and unreliable measures of streetscape features across different field ...surveyors even with costly training due to lack of more objective processes, which also make large scale study difficult. The recent advances in sensor technologies and digitization have produced a wealth of data to help research activities by facilitating improved measurements and conducting large scale analysis. This paper explores the potential of big data and big data analytics in the light of current approaches to measuring streetscape features. By applying machine learning algorithms on Google Street View imagery, we generated objectively three measures on visual enclosure. The results showed that sky areas were identified fairly well for the calculation of proportion of sky. The three visual enclosure measures were found to be correlated with pedestrian volume and Walk Score. This method allows large scale and consistent objective measures of visual enclosure that can be done reproducibly and universally applicable with readily available Google Street View imagery in many countries around the world to help test their association with walking behaviors.
•We generated objective visual enclosure variables applying machine learning algorithms on Google Street View imagery.•The results showed that the proportion of sky ahead the street is strongly associated with the sky proportions across the street.•The visual enclosure variables are significantly associated with observed pedestrian counts and Walk Score negatively.•This method allows large scale and consistent objective measures of visual enclosure.
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