Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
21,713
result(s) for
"Yang, Ren"
Sort by:
Intelligent Vehicle Violation Detection System Under Human–Computer Interaction and Computer Vision
In view of the current problems of low detection accuracy, poor stability and slow detection speed of intelligent vehicle violation detection systems, this article will use human–computer interaction and computer vision technology to solve the existing problems. First, the picture data required for the experiment is collected through the Bit Vehicle model dataset, and computer vision technology is used for preprocessing. Then, use Kalman filtering to track and study the vehicle to help better predict the trajectory of the vehicle in the area that needs to be detected; finally, use human–computer interaction technology to build the interactive interface of the system and improve the operability of the system. The violation detection system based on computer vision technology has an accuracy of more than 96.86% for the detection of the eight types of violations extracted, and the average detection is 98%. Through computer vision technology, the system can accurately detect and identify vehicle violations in real time, effectively improving the efficiency and safety of traffic management. In addition, the system also pays special attention to the design of human–computer interaction, provides an intuitive and easy-to-use user interface, and enables traffic managers to easily monitor and manage traffic conditions. This innovative intelligent vehicle violation detection system is expected to help the development of traffic management technology in the future.
Journal Article
Efficient blue light-emitting diodes based on quantum-confined bromide perovskite nanostructures
The emergence of inorganic–organic hybrid perovskites, a unique class of solution-processable crystalline semiconductors, provides new opportunities for large-area, low-cost and colour-saturated light-emitting diodes (LEDs) ideal for display and solid-state lighting applications1. However, the performance of blue perovskite LEDs (PeLEDs)2–11 is far inferior to that of their near-infrared, red and green counterparts12–19, strongly limiting the practicality of the PeLED technology. Here, we demonstrate blue PeLEDs emitting at 483 nm with colour coordinates of (0.094, 0.184) and operating with a peak external quantum efficiency of up to 9.5% at a luminance of 54 cd m–2. The devices have a T50 lifetime of 250 s for an initial brightness of 100 cd m–2. The efficient blue electroluminescence originates from a structure of quantum-confined perovskite nanoparticles embedded within quasi-two-dimensional phases with higher bandgaps, prepared by an antisolvent processing scheme. Our work paves the way towards high-performance PeLEDs in the blue region.
Journal Article
In situ observation of thermal-driven degradation and safety concerns of lithiated graphite anode
Graphite, a robust host for reversible lithium storage, enabled the first commercially viable lithium-ion batteries. However, the thermal degradation pathway and the safety hazards of lithiated graphite remain elusive. Here, solid-electrolyte interphase (SEI) decomposition, lithium leaching, and gas release of the lithiated graphite anode during heating were examined by in situ synchrotron X-ray techniques and in situ mass spectroscopy. The source of flammable gas such as H
2
was identified and quantitively analyzed. Also, the existence of highly reactive residual lithium on the graphite surface was identified at high temperatures. Our results emphasized the critical role of the SEI in anode thermal stability and uncovered the potential safety hazards of the flammable gases and leached lithium. The anode thermal degradation mechanism revealed in the present work will stimulate more efforts in the rational design of anodes to enable safe energy storage.
The role of the lithiated graphite anode in battery thermal runaway failure remains under intense investigation. In this work, with multiple in situ synchrotron X-ray characterizations, the phase evolution, gas release, and lithium leaching of lithiated graphite anode are illustrated in detail.
Journal Article
Entropy and crystal-facet modulation of P2-type layered cathodes for long-lasting sodium-based batteries
P2-type sodium manganese-rich layered oxides are promising cathode candidates for sodium-based batteries because of their appealing cost-effective and capacity features. However, the structural distortion and cationic rearrangement induced by irreversible phase transition and anionic redox reaction at high cell voltage (i.e., >4.0 V) cause sluggish Na-ion kinetics and severe capacity decay. To circumvent these issues, here, we report a strategy to develop P2-type layered cathodes via configurational entropy and ion-diffusion structural tuning. In situ synchrotron X-ray diffraction combined with electrochemical kinetic tests and microstructural characterizations reveal that the entropy-tuned Na
0.62
Mn
0.67
Ni
0.23
Cu
0.05
Mg
0.07
Ti
0.01
O
2
(CuMgTi-571) cathode possesses more {010} active facet, improved structural and thermal stability and faster anionic redox kinetics compared to Na
0.62
Mn
0.67
Ni
0.37
O
2
. When tested in combination with a Na metal anode and a non-aqueous NaClO
4
-based electrolyte solution in coin cell configuration, the CuMgTi-571-based positive electrode enables an 87% capacity retention after 500 cycles at 120 mA g
−1
and about 75% capacity retention after 2000 cycles at 1.2 A g
−1
.
The use of Mn-rich layered cathodes in Na-based batteries is hindered by inadequate cycling reversibility and sluggish anionic redox kinetics. Here, the authors report a strategy to stabilize the structure and promote anionic redox via configurational entropy and ion-diffusion structural tuning.
Journal Article
Space reconstruction process and internal driving mechanisms of Taobao villages in metropolitan fringe areas: A case study of Lirendong village in Guangzhou, China
This paper examines the process and internal mechanisms of rural ecommerce industry agglomeration and space reconstruction in metropolitan fringe areas, employing Lirendong village in Guangzhou, China, as a case study. Questionnaire surveys and in-depth interviews were utilized and interpreted through the perspective of the actor-network theory. The results show that, in Lirendong village, local government, processing enterprises, rural collectives, e-commerce entrepreneurial talent, and other key actors participate in the pursuit and realization of suburban land value according to their action logic. Actors jointly evolved and constructed the phased industrial processes and space value accumulation process of the e-commerce industry. The reconstruction process experienced three stages, including the government-led agricultural decentralization stage, the market-oriented industrialization stage, and the Internet+ stage dominated by the social network of fellow villagers. The development process has evolved from the dominance of exogenous forces to that of endogenous forces, and, as a result, the types and structures of rural land use are diversified. The spatial texture and rural environment of the traditional country gradually disappeared, forming a diversified mixed form of urban-rural land and mixed-use landscape of industrial, commercial, and residential land in vertical space. At the same time, the social network changed from a single and homogeneous social network of acquaintances to a multiple network of strangers.
Journal Article
High-throughput design of high-performance lightweight high-entropy alloys
Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further improves the accuracy of the thermodynamic database of the discovered alloy system. This study shows that integrating high-throughput screening, multiscale modeling, and experimental validation proves to be efficient and useful in accelerating the discovery of advanced precipitation-strengthened structural materials tuned by the high-entropy alloy concept.
Advanced screening strategies for the design of high-entropy alloys are highly desirable. Here the authors use the project-oriented design strategy and CALPHAD-based high-throughput calculation tool to rapidly screen promising Al-Cr-Fe-Mn-Ti structural HEAs for high-temperature applications.
Journal Article
High-content ductile coherent nanoprecipitates achieve ultrastrong high-entropy alloys
Precipitation-hardening high-entropy alloys (PH-HEAs) with good strength−ductility balances are a promising candidate for advanced structural applications. However, current HEAs emphasize near-equiatomic initial compositions, which limit the increase of intermetallic precipitates that are closely related to the alloy strength. Here we present a strategy to design ultrastrong HEAs with high-content nanoprecipitates by phase separation, which can generate a near-equiatomic matrix in situ while forming strengthening phases, producing a PH-HEA regardless of the initial atomic ratio. Accordingly, we develop a non-equiatomic alloy that utilizes spinodal decomposition to create a low-misfit coherent nanostructure combining a near-equiatomic disordered face-centered-cubic (FCC) matrix with high-content ductile Ni
3
Al-type ordered nanoprecipitates. We find that this spinodal order–disorder nanostructure contributes to a strength increase of ~1.5 GPa (>560%) relative to the HEA without precipitation, achieving one of the highest tensile strength (1.9 GPa) among all bulk HEAs reported previously while retaining good ductility (>9%).
High entropy alloys usually emphasize equiatomic compositions, which restrict the compositions available to induce strengthening via precipitation. Here the authors use spinodal decomposition in a five-element alloy to obtain high content nanophases and the highest tensile strength reported to date.
Journal Article
Correlation between manganese dissolution and dynamic phase stability in spinel-based lithium-ion battery
Historically long accepted to be the singular root cause of capacity fading, transition metal dissolution has been reported to severely degrade the anode. However, its impact on the cathode behavior remains poorly understood. Here we show the correlation between capacity fading and phase/surface stability of an LiMn
2
O
4
cathode. It is revealed that a combination of structural transformation and transition metal dissolution dominates the cathode capacity fading. LiMn
2
O
4
exhibits irreversible phase transitions driven by manganese(III) disproportionation and Jahn-Teller distortion, which in conjunction with particle cracks results in serious manganese dissolution. Meanwhile, fast manganese dissolution in turn triggers irreversible structural evolution, and as such, forms a detrimental cycle constantly consuming active cathode components. Furthermore, lithium-rich LiMn
2
O
4
with lithium/manganese disorder and surface reconstruction could effectively suppress the irreversible phase transition and manganese dissolution. These findings close the loop of understanding capacity fading mechanisms and allow for development of longer life batteries.
To unlock the potential of Mn-based cathode materials, the fast capacity fading process has to be first understood. Here the authors utilize advanced characterization techniques to look at a spinel LiMn
2
O
4
system, revealing that a combination of irreversible structural transformations and Mn dissolution takes responsibility.
Journal Article
Enhancing predictions of antimicrobial resistance of pathogens by expanding the potential resistance gene repertoire using a pan-genome-based feature selection approach
Background
Predicting which pathogens might exhibit antimicrobial resistance (AMR) based on genomics data is one of the promising ways to swiftly and precisely identify AMR pathogens. Currently, the most widely used genomics approach is through identifying known AMR genes from genomic information in order to predict whether a pathogen might be resistant to certain antibiotic drugs. The list of known AMR genes, however, is still far from comprehensive and may result in inaccurate AMR pathogen predictions. We thus felt the need to expand the AMR gene set and proposed a pan-genome-based feature selection method to identify potential gene sets for AMR prediction purposes.
Results
By building pan-genome datasets and extracting gene presence/absence patterns from four bacterial species, each with more than 2000 strains, we showed that machine learning models built from pan-genome data can be very promising for predicting AMR pathogens. The gene set selected by the eXtreme Gradient Boosting (XGBoost) feature selection approach further improved prediction outcomes, and an incremental approach selecting subsets of XGBoost-selected features brought the machine learning model performance to the next level. Investigating selected gene sets revealed that on average about 50% of genes had no known function and very few of them were known AMR genes, indicating the potential of the selected gene sets to expand resistance gene repertoires.
Conclusions
We demonstrated that a pan-genome-based feature selection approach is suitable for building machine learning models for predicting AMR pathogens. The extracted gene sets may provide future clues to expand our knowledge of known AMR genes and provide novel hypotheses for inferring bacterial AMR mechanisms.
Journal Article