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Showing papers by "Tongji University published in 2021"


Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations



Journal ArticleDOI
Richard J. Abbott1, T. D. Abbott2, Sheelu Abraham3, Fausto Acernese4  +1335 moreInstitutions (144)
TL;DR: The data recorded by these instruments during their first and second observing runs are described, including the gravitational-wave strain arrays, released as time series sampled at 16384 Hz.

320 citations


Journal ArticleDOI
TL;DR: Tumor Immune Single Cell Hub is presented, a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types and provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the Tme.
Abstract: Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors but posed computational challenges on integrating and utilizing the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, clustering, cell-type annotation, malignant cell classification, differential expression analysis and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

318 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigate how external stimuli such as Limited Quantity Scarcity (LQS) and Limited Time Scarcity(LTS) affect the emotional arousal among people, which in turn influences consumers' impulsive and obsessive buying behaviors.

283 citations


Proceedings ArticleDOI
01 Jun 2021
TL;DR: Sun et al. as mentioned in this paper proposed sparse R-CNN, a purely sparse method for object detection in images, which completely avoids all efforts related to object candidates design and many-to-one label assignment.
Abstract: We present Sparse R-CNN, a purely sparse method for object detection in images. Existing works on object detection heavily rely on dense object candidates, such as k anchor boxes pre-defined on all grids of image feature map of size H × W. In our method, however, a fixed sparse set of learned object proposals, total length of N, are provided to object recognition head to perform classification and location. By eliminating HWk (up to hundreds of thousands) hand-designed object candidates to N (e.g. 100) learnable proposals, Sparse R-CNN completely avoids all efforts related to object candidates design and many-to-one label assignment. More importantly, final predictions are directly output without non-maximum suppression post-procedure. Sparse R-CNN demonstrates accuracy, run-time and training convergence performance on par with the well-established detector baselines on the challenging COCO dataset, e.g., achieving 45.0 AP in standard 3× training schedule and running at 22 fps using ResNet-50 FPN model. We hope our work could inspire re-thinking the convention of dense prior in object detectors. The code is available at: https://github.com/PeizeSun/SparseR-CNN.

256 citations



Journal ArticleDOI
TL;DR: The primary endpoint was met at the interim analysis, showing a statistically significant and clinically meaningful improvement in progression-free survival with camrelizumab plus carboplatin and pemetrexed versus chemotherapy alone in all patients, supporting camrelIZumabplus carboplasin and pemberrexed as a first-line treatment option for Chinese patients with advanced non-squamous NSCLC.

204 citations


Journal ArticleDOI
TL;DR: A new method is put forward that fuses multi-modal sensor signals, i.e. the data collected by an accelerometer and a microphone, to realize more accurate and robust bearing-fault diagnosis.

199 citations


Journal ArticleDOI
TL;DR: In this paper, the authors developed the underlying mechanism through which corporate social responsibility influences the customer loyalty by simultaneously including corporate reputation, customer satisfaction, and customer trust as mediators, and corporate abilities as a moderator.

190 citations


Journal ArticleDOI
TL;DR: A novel JADE variant is presented by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem and has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.
Abstract: JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in comparison with other evolutionary optimization algorithms. However, it suffers from the premature convergence problem and is easily trapped into local optima. This article presents a novel JADE variant by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem. Taking advantages of the ergodicity and nonrepetitious nature of chaos, it can diversify the population and thus has a chance to explore a huge search space. Because of the inherent local exploitation ability, its embedded CLS can exploit a small region to refine solutions obtained by JADE. Hence, it can well balance the exploration and exploitation in a search process and further improve its performance. Four kinds of its CLS incorporation schemes are studied. Multiple chaotic maps are individually, randomly, parallelly, and memory-selectively incorporated into CLS. Experimental and statistical analyses are performed on a set of 53 benchmark functions and four real-world optimization problems. Results show that it has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.

Journal ArticleDOI
TL;DR: In this article, the stability, mechanical properties, lattice thermal conductivity, piezoelectric response, and photocatalytic and electronic features of MA2Z4 (M = Cr, Mo, W, A = Si, Ge, Z = N, P) monolayers are explored.

Proceedings ArticleDOI
01 Jun 2021
TL;DR: DenseCL as discussed by the authors proposes a pairwise contrastive (dis)similarity loss at the pixel level between two views of input images to improve the performance of self-supervised learning.
Abstract: To date, most existing self-supervised learning methods are designed and optimized for image classification. These pre-trained models can be sub-optimal for dense prediction tasks due to the discrepancy between image-level prediction and pixel-level prediction. To fill this gap, we aim to design an effective, dense self-supervised learning method that directly works at the level of pixels (or local features) by taking into account the correspondence between local features. We present dense contrastive learning (DenseCL), which implements self-supervised learning by optimizing a pairwise contrastive (dis)similarity loss at the pixel level between two views of input images.Compared to the baseline method MoCo-v2, our method introduces negligible computation overhead (only <1% slower), but demonstrates consistently superior performance when transferring to downstream dense prediction tasks including object detection, semantic segmentation and instance segmentation; and outperforms the state-of-the-art methods by a large margin. Specifically, over the strong MoCo-v2 baseline, our method achieves significant improvements of 2.0% AP on PASCAL VOC object detection, 1.1% AP on COCO object detection, 0.9% AP on COCO instance segmentation, 3.0% mIoU on PASCAL VOC semantic segmentation and 1.8% mIoU on Cityscapes semantic segmentation.Code and models are available at: https://git.io/DenseCL

Journal ArticleDOI
01 Feb 2021-Carbon
TL;DR: In this paper, a multilayer-sandwiched Ti3C2Tx MXene heterostructure decorated with one-dimensional Co nanochains has been synthesized successfully through a facile in situ process.

Journal ArticleDOI
TL;DR: In this article, the authors used Google Street View imagery and a fully convolutional neural network to evaluate human-scale, eye-level streetscape greenery, and adopted a machine learning technique, namely random forest modeling, to scrutinize the non-linear effects of streetscape greenery on the walking propensity of older adults.

Journal ArticleDOI
TL;DR: Enable technologies and systems suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals are reviewed.
Abstract: Coronavirus disease 2019 (COVID-19) has emerged as a pandemic with serious clinical manifestations including death. A pandemic at the large-scale like COVID-19 places extraordinary demands on the world's health systems, dramatically devastates vulnerable populations, and critically threatens the global communities in an unprecedented way. While tremendous efforts at the frontline are placed on detecting the virus, providing treatments and developing vaccines, it is also critically important to examine the technologies and systems for tackling disease emergence, arresting its spread and especially the strategy for diseases prevention. The objective of this article is to review enabling technologies and systems with various application scenarios for handling the COVID-19 crisis. The article will focus specifically on 1) wearable devices suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals; 2) unobtrusive sensing systems for detecting the disease and for monitoring patients with relatively mild symptoms whose clinical situation could suddenly worsen in improvised hospitals; and 3) telehealth technologies for the remote monitoring and diagnosis of COVID-19 and related diseases. Finally, further challenges and opportunities for future directions of development are highlighted.

Journal ArticleDOI
TL;DR: In this paper, the authors constructed FeN4 structures on a carbon nanotube to obtain single-atom catalysts (FeSA-N-CNT) to generate reactive iron species (RFeS) in the presence of peroxymonosulfate (PMS).
Abstract: Recently, reactive iron species (RFeS) have shown great potential for the selective degradation of emerging organic contaminants (EOCs). However, the rapid generation of RFeS for the selective and efficient degradation of EOCs over a wide pH range is still challenging. Herein, we constructed FeN4 structures on a carbon nanotube (CNT) to obtain single-atom catalysts (FeSA-N-CNT) to generate RFeS in the presence of peroxymonosulfate (PMS). The obtained FeSA-N-CNT/PMS system exhibited outstanding and selective reactivity for oxidizing EOCs over a wide pH range (3.0-9.0). Several lines of evidences suggested that RFeS existing as an FeN4═O intermediate was the predominant oxidant, while SO4·- and HO· were the secondary oxidants. Density functional theory calculation results revealed that a CNT played a key role in optimizing the distribution of bonding and antibonding states in the Fe 3d orbital, resulting in the outstanding ability of FeSA-N-CNT for PMS chemical adsorption and activation. Moreover, CNT could significantly enhance the reactivity of the FeN4═O intermediate by increasing the overlap of electrons of the Fe 3d orbital, O 2p orbital, and bisphenol A near the Fermi level. The results of this study can advance the understanding of RFeS generation in a heterogeneous system over a wide pH range and the application of RFeS in real practice.

Journal ArticleDOI
01 Feb 2021
TL;DR: This paper reviews more than 170 papers and organizes the related research according to three themes of impedance modeling, acquisition, and application under the premise of electric vehicle implementation; the strength and weaknesses of the research in each theme are discussed.
Abstract: Impedance is closely related to the internal physical and chemical processes of lithium-ion batteries. And the properties of the processes can be characterized and thus more detailed information be provided based on it. In the past decades, the impedance is frequently reported as a powerful tool used in the field of lithium-ion battery state estimation and diagnosis. This paper reviews more than 170 papers and organizes the related research according to three themes of impedance modeling, acquisition, and application under the premise of electric vehicle implementation. The strength and weaknesses of the research in each theme are discussed. Based on the research, the possibility and the value of impedance in onboard battery management are revealed. However, challenges are still faced due to the cost limitations, the complex vehicular conditions, and the time-varying battery states. The unsolved issues are summarized in the conclusion. To realize a more smart battery management system with the impedance, more significant work is still needed.

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and presented the large scale, single cell resolution profiles of advanced NSCLCs.
Abstract: Lung cancer is a highly heterogeneous disease. Cancer cells and cells within the tumor microenvironment together determine disease progression, as well as response to or escape from treatment. To map the cell type-specific transcriptome landscape of cancer cells and their tumor microenvironment in advanced non-small cell lung cancer (NSCLC), we analyze 42 tissue biopsy samples from stage III/IV NSCLC patients by single cell RNA sequencing and present the large scale, single cell resolution profiles of advanced NSCLCs. In addition to cell types described in previous single cell studies of early stage lung cancer, we are able to identify rare cell types in tumors such as follicular dendritic cells and T helper 17 cells. Tumors from different patients display large heterogeneity in cellular composition, chromosomal structure, developmental trajectory, intercellular signaling network and phenotype dominance. Our study also reveals a correlation of tumor heterogeneity with tumor associated neutrophils, which might help to shed light on their function in NSCLC. Comprehensive profiles of tumour and microenvironment are critical to understand heterogeneity in non-small cell lung cancer (NSCLC). Here, the authors profile 42 late-stage NSCLC patients with single-cell RNA-seq, revealing immune landscapes that are associated with cancer subtype or heterogeneity.

Journal ArticleDOI
TL;DR: A single treatment of SPNIIR‐mediated NIR‐II photothermal immunotherapy effectively inhibits growth of both primary and distant tumors and eliminates lung metastasis in a murine mouse model, providing a remote‐controlled smart delivery system to synergize photomedicine with immunotherapy for enhanced cancer treatment.
Abstract: Immunotherapy has offered new treatment options for cancer; however, the therapeutic benefits are often modest and desired to be improved. A semiconducting polymer nanoadjuvant (SPNII R) with a photothermally triggered cargo release for second near-infrared (NIR-II) photothermal immunotherapy is reported here. SPNII R consists of a semiconducting polymer nanoparticle core as an NIR-II photothermal converter, which is doped with a toll-like receptor (TLR) agonist as an immunotherapy adjuvant and coated with a thermally responsive lipid shell. Upon NIR-II photoirradiation, SPNII R effectively generates heat not only to ablate tumors and induce immunogenic cell death (ICD), but also to melt the lipid layers for on-demand release of the TLR agonist. The combination of ICD and activation of TLR7/TLR8 enhances the maturation of dendritic cells, which amplifies anti-tumor immune responses. Thus, a single treatment of SPNII R-mediated NIR-II photothermal immunotherapy effectively inhibits growth of both primary and distant tumors and eliminates lung metastasis in a murine mouse model. This study thus provides a remote-controlled smart delivery system to synergize photomedicine with immunotherapy for enhanced cancer treatment.

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the recent progress on diverse heterogeneous ferrites (Ni/Cu/Zn/Co/Mn-ferrites) and ferrite composites catalysts for peroxymonosulfate (PMS) activation.

Journal ArticleDOI
Baiwen Deng1, Zhicheng Liu1, Fei Pan1, Zhen Xiang1, Xiang Zhang1, Wei Lu1 
TL;DR: In this article, the authors synthesized two-dimensional magnetized MXene hybrids by electrostatic assembly of negatively charged few-layered Ti3C2Tx (MXene) with positively charged hollow Fe3O4 nanoparticles (HFO).
Abstract: Electromagnetic pollution often interferes with the normal use of sophisticated electric devices leading to the necessity of developing electromagnetic wave absorbers with light weight and strong absorption ability. Herein, we synthesized two-dimensional magnetized MXene hybrids by electrostatic assembly of negatively charged few-layered Ti3C2Tx (MXene) with positively charged hollow Fe3O4 nanoparticles (HFO). The few-layered MXene was obtained by etching Ti3AlC2via a modified LiF–HCl method followed by a sonication process, while HFO was fabricated by a facile hydrothermal process. The MXene/HFO hybrids were light weight and achieved a high EM wave absorption performance (RLmin of −63.7 dB at a thin thickness of 1.56 mm). Moreover, the strong EM wave attenuation resulted from the synergistic effect arising from dielectric loss, magnetic loss, interface polarization and improved impedance matching. Therefore, the as-prepared magnetized MXene hybrids are expected to be candidates for high performance electromagnetic microwave absorbers.


Journal ArticleDOI
Zhen Xiang1, Yuyang Shi1, Xiaojie Zhu1, Lei Cai1, Wei Lu1 
TL;DR: In this article, an electrostatic assembly approach for fabricating 2D/1D/0D construction of Ti3C2Tx/carbon nanotubes/Co nanoparticles was proposed, which achieved a strong reflection loss of -85.8 dB and an ultrathin thickness of 1.4 mm.
Abstract: High-performance electromagnetic wave absorption and electromagnetic interference (EMI) shielding materials with multifunctional characters have attracted extensive scientific and technological interest, but they remain a huge challenge. Here, we reported an electrostatic assembly approach for fabricating 2D/1D/0D construction of Ti3C2Tx/carbon nanotubes/Co nanoparticles (Ti3C2Tx/CNTs/Co) nanocomposites with an excellent electromagnetic wave absorption, EMI shielding efficiency, flexibility, hydrophobicity, and photothermal conversion performance. As expected, a strong reflection loss of -85.8 dB and an ultrathin thickness of 1.4 mm were achieved. Meanwhile, the high EMI shielding efficiency reached 110.1 dB. The excellent electromagnetic wave absorption and shielding performances were originated from the charge carriers, electric/magnetic dipole polarization, interfacial polarization, natural resonance, and multiple internal reflections. Moreover, a thin layer of polydimethylsiloxane rendered the hydrophilic hierarchical Ti3C2Tx/CNTs/Co hydrophobic, which can prevent the degradation/oxidation of the MXene in high humidity condition. Interestingly, the Ti3C2Tx/CNTs/Co film exhibited a remarkable photothermal conversion performance with high thermal cycle stability and tenability. Thus, the multifunctional Ti3C2Tx/CNTs/Co nanocomposites possessing a unique blend of outstanding electromagnetic wave absorption and EMI shielding, light-driven heating performance, and flexible water-resistant features were highly promising for the next-generation intelligent electromagnetic attenuation system.

Journal ArticleDOI
TL;DR: In this paper, a deep autoencoder based energy method (DAEM) is proposed for bending, vibration and buckling analysis of Kirchhoff plates, where the objective function is to minimize the total potential energy.
Abstract: In this paper, we present a deep autoencoder based energy method (DAEM) for the bending, vibration and buckling analysis of Kirchhoff plates. The DAEM exploits the higher order continuity of the DAEM and integrates a deep autoencoder and the minimum total potential principle in one framework yielding an unsupervised feature learning method. The DAEM is a specific type of feedforward deep neural network (DNN) and can also serve as function approximator. With robust feature extraction capacity, the DAEM can more efficiently identify patterns behind the whole energy system, such as the field variables, natural frequency and critical buckling load factor studied in this paper. The objective function is to minimize the total potential energy. The DAEM performs unsupervised learning based on generated collocation points inside the physical domain so that the total potential energy is minimized at all points. For the vibration and buckling analysis, the loss function is constructed based on Rayleigh’s principle and the fundamental frequency and the critical buckling load is extracted. A scaled hyperbolic tangent activation function for the underlying mechanical model is presented which meets the continuity requirement and alleviates the gradient vanishing/explosive problems under bending. The DAEM is implemented using Pytorch and the LBFGS optimizer. To further improve the computational efficiency and enhance the generality of this machine learning method, we employ transfer learning. A comprehensive study of the DAEM configuration is performed for several numerical examples with various geometries, load conditions, and boundary conditions.

Journal ArticleDOI
TL;DR: In this paper, the authors have profiled the transcriptomes of 36,424 single cells from 13 prostate tumours and identified the epithelial cells underlying disease aggressiveness. But the transcriptomic heterogeneity of prostate cancer is poorly understood.
Abstract: Prostate cancer shows remarkable clinical heterogeneity, which manifests in spatial and clonal genomic diversity. By contrast, the transcriptomic heterogeneity of prostate tumours is poorly understood. Here we have profiled the transcriptomes of 36,424 single cells from 13 prostate tumours and identified the epithelial cells underlying disease aggressiveness. The tumour microenvironment (TME) showed activation of multiple progression-associated transcriptomic programs. Notably, we observed promiscuous KLK3 expression and validated the ability of cancer cells in altering T-cell transcriptomes. Profiling of a primary tumour and two matched lymph nodes provided evidence that KLK3 ectopic expression is associated with micrometastases. Close cell-cell communication exists among cells. We identified an endothelial subset harbouring active communication (activated endothelial cells, aECs) with tumour cells. Together with sequencing of an additional 11 samples, we showed that aECs are enriched in castration-resistant prostate cancer and promote cancer cell invasion. Finally, we created a user-friendly web interface for users to explore the sequenced data.

Journal ArticleDOI
TL;DR: A multilayer design architecture for advanced battery management, which consists of three progressive layers, which aims at providing a comprehensive understanding of battery, and the application layer ensures a safe and efficient battery system through sufficient management.
Abstract: Lithium-ion batteries are promising energy storage devices for electric vehicles and renewable energy systems. However, due to complex electrochemical processes, potential safety issues, and inherent poor durability of lithium-ion batteries, it is essential to monitor and manage batteries safely and efficiently. This study reviews the development of battery management systems during the past periods and introduces a multilayer design architecture for advanced battery management, which consists of three progressive layers. The foundation layer focuses on the system physical basis and theoretical principle, the algorithm layer aims at providing a comprehensive understanding of battery, and the application layer ensures a safe and efficient battery system through sufficient management. A comprehensive overview of each layer is presented from both academic and engineering perspectives. Future trends in research and development of next-generation battery management are discussed. Based on data and intelligence, the next-generation battery management will achieve better safety, performance, and interconnectivity.

Journal ArticleDOI
TL;DR: LiMn2O4 and its derivatives with cubic lattice symmetry on average are discussed in this paper, where the authors show reversible hybrid anionand cation-redox 0.5O4 degradation.
Abstract: DOI: 10.1002/aenm.202000997 prospects in grid level energy storage. Such development dramatically accelerates the progress of modern civilization and is acknowledged by the 2019 Nobel Prize in Chemistry awarded to John B. Goodenough, M. Stanley Whittingham, and Akira Yoshino.[1] Among many other milestones that contributed to the huge success of LIBs is the development of three families of cathode materials (layered structure LiCoO2, spinel structure LiMn2O4, and olivine structure LiFePO4) pioneered by Goodenough and co-workers. This review article shall focus on manganese spinel cathode LiMn2O4 and its derivatives, with cubic lattice symmetry on average. The discovery of LiMn2O4 for battery applications came from the quest to find an inexpensive oxide as the cathode material.[5] In 1981, Hunter[6] first reported the conversion of spinel LiMn2O4 into a new form of manganese dioxide called λ-MnO2 by chemical delithiation in aqueous acidic solutions. The λ-MnO2 preserves the [B2]O4 framework of A[B2]O4 spinel and turns out to be the end product of LiMn2O4 after electrochemical delithiation. After early investigations of electrochemical lithiation of Fe3O4 spinel,[7] Thackeray et al. reported electrochemical lithiation[3a] and delithiation[3b] of LiMn2O4 spinel in 1983 and 1984, respectively, which boosted research interest in this family of cathodes with good thermal stability.[8] Further investigations of complex phase diagrams and versatile structure/chemistry of Mn-based materials[9] as well as efforts to optimize the electrochemical properties (especially on cycling)[10] led to the discovery and development of high-voltage spinel cathodes (e.g., LiNi0.5Mn1.5O4), high-capacity layered Li-/Mn-rich cathodes (e.g., Li2MnO3 and xLiNi1/3Co1/3Mn1/3O2·(1−x)Li2MnO3), and other advanced cathode materials/composites.[13] The major milestones of the development of LiMn2O4 and its derivatives are briefly summarized in the flow chart in Figure 1. To date, even though LiMn2O4 has smaller capacity and energy density compared to the later developed layered LiNi1−x−yCoxMnyO2 (NCM), LiNi1−x−yCoxAlyO2 (NCA), Li-/Mn-rich cathodes, and LiCoO2 (see comparison of different cathode materials in Table 1), it is cost-effective, nontoxic, and environmentally friendly (cobalt-free, with abundant nontoxic manganese) and has a more robust crystal structure with fast diffusion kinetics, so it is commonly blended with layered cathodes to reduce cost, increase structural and thermal stability, and improve rate performance.[14] High-voltage spinel LiNi0.5Mn1.5O4 has Spinel LiMn2O4, whose electrochemical activity was first reported by Prof. John B. Goodenough’s group at Oxford in 1983, is an important cathode material for lithium-ion batteries that has attracted continuous academic and industrial interest. It is cheap and environmentally friendly, and has excellent rate performance with 3D Li+ diffusion channels. However, it suffers from severe degradation, especially under extreme voltages and during high-temperature operation. Here, the current understanding and future trends of the spinel cathode and its derivatives with cubic lattice symmetry (LiNi0.5Mn1.5O4 that shows high-voltage stability, and Li-rich spinels that show reversible hybrid anionand cation-redox activities) are discussed. Special attention is given to the degradation mechanisms and further development of spinel cathodes, as well as concepts of utilizing the cubic spinel structure to stabilize high-capacity layered cathodes and as robust framework for high-rate electrodes. “Good spinel” surface phases like LiNi0.5Mn1.5O4 are distinguished from “bad spinel” surface phases like Mn3O4.

Journal ArticleDOI
Yuchuan Du1, Ning Pan1, Zihao Xu1, Fuwen Deng1, Yu Shen1, Hua Kang1 
TL;DR: The proposed YOLO-based approach is able to detect PD with high accuracy, which requires no manual feature extraction and calculation during detecting, and significantly outperforms with appropriate illumination.
Abstract: The detection and classification of pavement distress (PD) play a critical role in pavement maintenance and rehabilitation. Research on PD automation detection and measurement has been actively con...

Journal ArticleDOI
TL;DR: In this article, the authors proposed an efficient and environmental friendly process for the rapid removal of emerging contaminants and enriched the understandings on the evolution mechanism of ·OH in Fe(IV)-mediated processes.
Abstract: Potassium periodate (PI, KIO4) was readily activated by Fe(II) under acidic conditions, resulting in the enhanced abatement of organic contaminants in 2 min, with the decay ratios of the selected pollutants even outnumbered those in the Fe(II)/peroxymonosulfate and Fe(II)/peroxydisulfate processes under identical conditions. Both 18O isotope labeling techniques using methyl phenyl sulfoxide (PMSO) as the substrate and X-ray absorption near-edge structure spectroscopy provided conclusive evidences for the generation of high-valent iron-oxo species (Fe(IV)) in the Fe(II)/PI process. Density functional theory calculations determined that the reaction of Fe(II) with PI followed the formation of a hydrogen bonding complex between Fe(H2O)62+ and IO4(H2O)-, ligand exchange, and oxygen atom transfer, consequently generating Fe(IV) species. More interestingly, the unexpected detection of 18O-labeled hydroxylated PMSO not only favored the simultaneous generation of ·OH but also demonstrated that ·OH was indirectly produced through the self-decay of Fe(IV) to form H2O2 and the subsequent Fenton reaction. In addition, IO4- was not transformed into the undesired iodine species (i.e., HOI, I2, and I3-) but was converted to nontoxic iodate (IO3-). This study proposed an efficient and environmental friendly process for the rapid removal of emerging contaminants and enriched the understandings on the evolution mechanism of ·OH in Fe(IV)-mediated processes.