arXiv subjects

Zhigang Wang

Publications and source records attributed to Zhigang Wang.

At least 109 records · Page 6Linked to original sources

arXiv2022

Autonomous Electric Vehicle Battery Disassembly Based on NeuroSymbolic Computing

The booming of electric vehicles demands efficient battery disassembly for recycling to be environment-friendly. Due to the unstructured environment and high uncertainties, battery disassembly is still primarily done by humans, probably assisted by robots. It is highly desirable to design autonomous solutions to improve work efficiency and lower human risks in high voltage and toxic environments. This paper proposes a novel framework of the NeuroSymbolic task and motion planning method to disassemble batteries in an unstructured environment using robots automatically. It enables robots to independently locate and disassemble battery bolts, with or without obstacles. This study not only provides a solution for intelligently disassembling electric vehicle batteries but also verifies its feasibility through a set of test results with the robot accomplishing the disassembly tasks in a complex and dynamic environment.

cs.RO↗

arXiv2022

The generality of uncooperative and cooperative effects in elementary hydrogen-bonded systems

The cooperative effect plays a significant role in understanding the intermolecular donor-acceptor interactions of hydrogen bonds (H-bonds, D-H...A). Herein, using the benchmark method of high-precision ab initio, the well-known cooperative effect is reproduced in elementary H-bonded systems with different D and A atoms. That is, with the decreasing of intermolecular distance, the D-H bond length first increases and then decreases, while the H...A bond length decreases. On the contrary, when D and A are the same, as the intermolecular distance decreases, the D-H bond length decreases without increasing, which is referred to as the uncooperative effect. Further analyses conclude that compared to cooperative H-bonded systems, uncooperative systems at their respective equilibrium position have a larger core-valence bifurcation (CVB) index (>0.022) and lower binding energies (<0.25 eV), showing a clear linear inverse relationship related to H-bond strength. Therefore, the intermolecular non-H-bonding interactions are predicted to reflect the uncooperative characteristics, which is confirmed by high-precision ab initio calculations. These findings provide a direction for the comprehensive understanding of H-bonds.

physics.chem-ph↗

arXiv2022

Implicit Sample Extension for Unsupervised Person Re-Identification

Most existing unsupervised person re-identification (Re-ID) methods use clustering to generate pseudo labels for model training. Unfortunately, clustering sometimes mixes different true identities together or splits the same identity into two or more sub clusters. Training on these noisy clusters substantially hampers the Re-ID accuracy. Due to the limited samples in each identity, we suppose there may lack some underlying information to well reveal the accurate clusters. To discover these information, we propose an Implicit Sample Extension (\OurWholeMethod) method to generate what we call support samples around the cluster boundaries. Specifically, we generate support samples from actual samples and their neighbouring clusters in the embedding space through a progressive linear interpolation (PLI) strategy. PLI controls the generation with two critical factors, i.e., 1) the direction from the actual sample towards its K-nearest clusters and 2) the degree for mixing up the context information from the K-nearest clusters. Meanwhile, given the support samples, ISE further uses a label-preserving loss to pull them towards their corresponding actual samples, so as to compact each cluster. Consequently, ISE reduces the "sub and mixed" clustering errors, thus improving the Re-ID performance. Extensive experiments demonstrate that the proposed method is effective and achieves state-of-the-art performance for unsupervised person Re-ID. Code is available at: \url{https://github.com/PaddlePaddle/PaddleClas}.

cs.CV↗

arXiv2021

Quantum tunnelling in hydrogen atom transfer brings uncertainty to polymer degradation

The low degradability of common polymers composed of light elements, results in a serious impact on the environment, which has become an urgent problem to be solved. As the reverse process of monomer polymerization, what deviates degradation from the idealized sequential depolymerization process, thereby bringing strange degradation products or even hindering further degradation? This is a key issue at the atomic level that must be addressed. Herein, we reveal that hydrogen atom transfer (HAT) during degradation, which is usually attributed to the thermal effect, unexpectedly exhibits a strong high-temperature tunnelling effect. This gives a possible answer to the above question. High-precision first-principles calculations show that, in various possible HAT pathways, lower energy barrier and stronger tunnelling effect make the HAT reaction related to the active end of the polymer occur more easily. In particular, although the energy barrier of the HAT reaction is only of 0.01 magnitude different from depolymerization, the tunnelling probability of the former can be 14~32 orders of magnitude greater than that of the latter. Furthermore, chain scission following HAT will lead to a variety of products other than monomers. Our work highlights that quantum tunnelling may be an important source of uncertainty in degradation and will provide a direction for regulating the polymer degradation process.

physics.app-ph↗

arXiv2021

Quantum resonant tunnelling enhances hydrogen bond rotation of confined water

Many studies have revealed that confined water chain flipping is closely related to the spatial size and even quantum effects of the confinement environment. Here, we show that these are not the only factors that affect the flipping process of a confined water chain. First-principles calculations and analyses confirm that quantum tunnelling effects from the water chain itself, especially resonant tunnelling, enhance the hydrogen bond rotation process. Importantly, resonant tunnelling can result in tunnelling rotation of hydrogen bonds with a probability close to 1 with only 0.597 eV provided energy. Compared to sequential tunnelling, resonant tunnelling dominants water chain flipping at temperatures up to 20 K higher. Additionally, the ratio of the resonant tunnelling probability to the thermal disturbance probability at 200 K is at least ten times larger than that of sequential tunnelling, which further illustrates the enhancement of hydrogen bond rotation brought about by resonant tunnelling.

physics.bio-ph↗

arXiv2021

Unsupervised Multi-Source Domain Adaptation for Person Re-Identification

Unsupervised domain adaptation (UDA) methods for person re-identification (re-ID) aim at transferring re-ID knowledge from labeled source data to unlabeled target data. Although achieving great success, most of them only use limited data from a single-source domain for model pre-training, making the rich labeled data insufficiently exploited. To make full use of the valuable labeled data, we introduce the multi-source concept into UDA person re-ID field, where multiple source datasets are used during training. However, because of domain gaps, simply combining different datasets only brings limited improvement. In this paper, we try to address this problem from two perspectives, \ie{} domain-specific view and domain-fusion view. Two constructive modules are proposed, and they are compatible with each other. First, a rectification domain-specific batch normalization (RDSBN) module is explored to simultaneously reduce domain-specific characteristics and increase the distinctiveness of person features. Second, a graph convolutional network (GCN) based multi-domain information fusion (MDIF) module is developed, which minimizes domain distances by fusing features of different domains. The proposed method outperforms state-of-the-art UDA person re-ID methods by a large margin, and even achieves comparable performance to the supervised approaches without any post-processing techniques.

cs.CV↗

arXiv2020

A short-range metastable defect in the double layer ice

Although the phase of water has extensively investigated whether there exists a defect distorting only locally the structure still under debate. Here we report a localized 5775 defect phase presented in the double layer ice on the Au (111) surface, which is a metastable structure with 5- and 7-membered rings compared with a perfect hexagonal one. Without altering the total number of the hydrogen bonds of the ice, the defect only introduces 0.08 Å molecular displacement and 3.27% interaction energy change outside the defected area. Such defect also exists without Au support but causes a larger lattice relaxation or smaller interaction energy change. The excessively high barrier as well as the low quantum tunneling and thermodynamic probabilities hinder the formation of the defect by post-grown isomerization from the perfect to the defected structure. This finding indicates that the defected ice is stable, and the defect can be formed during the ice growth stage.

cond-mat.mtrl-sci↗

arXiv2020

Unidirectional Oriented Water Wire in Short Nanotube

The orientation of water molecules is the key factor for the fast transport of water in small nanotubes. It has been accepted that the bidirectional water burst in short nanotubes can be transformed into unidirectional transport when the orientation of water molecules is maintained in long nanotubes under the external field. In this work, based on molecular dynamics simulations and first-principles calculations, we showed without external field, it only needs 21 water molecules to maintain the unidirectional single file water intrinsically in carbon nanotube at seconds. Detailed analysis indicates that the surprising result comes from the step by step process for the flip of water chain, which is different with the perceived concerted mechanism. Considering the thickness of cell membrane (normally 5-10 nm) is larger than the length threshold of the unidirectional water wire, this study suggests it may not need the external field to maintain the unidirectional flow in the water channel at the macroscopic timescale.

physics.comp-ph↗

arXiv2020

Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM

Service robots should be able to operate autonomously in dynamic and daily changing environments over an extended period of time. While Simultaneous Localization And Mapping (SLAM) is one of the most fundamental problems for robotic autonomy, most existing SLAM works are evaluated with data sequences that are recorded in a short period of time. In real-world deployment, there can be out-of-sight scene changes caused by both natural factors and human activities. For example, in home scenarios, most objects may be movable, replaceable or deformable, and the visual features of the same place may be significantly different in some successive days. Such out-of-sight dynamics pose great challenges to the robustness of pose estimation, and hence a robot's long-term deployment and operation. To differentiate the forementioned problem from the conventional works which are usually evaluated in a static setting in a single run, the term \textit{lifelong SLAM} is used here to address SLAM problems in an ever-changing environment over a long period of time. To accelerate lifelong SLAM research, we release the OpenLORIS-Scene datasets. The data are collected in real-world indoor scenes, for multiple times in each place to include scene changes in real life. We also design benchmarking metrics for lifelong SLAM, with which the robustness and accuracy of pose estimation are evaluated separately. The datasets and benchmark are available online at https://lifelong-robotic-vision.github.io/dataset/scene.

cs.RO↗

arXiv2019

A CNN-RNN Architecture for Multi-Label Weather Recognition

Weather Recognition plays an important role in our daily lives and many computer vision applications. However, recognizing the weather conditions from a single image remains challenging and has not been studied thoroughly. Generally, most previous works treat weather recognition as a single-label classification task, namely, determining whether an image belongs to a specific weather class or not. This treatment is not always appropriate, since more than one weather conditions may appear simultaneously in a single image. To address this problem, we make the first attempt to view weather recognition as a multi-label classification task, i.e., assigning an image more than one labels according to the displayed weather conditions. Specifically, a CNN-RNN based multi-label classification approach is proposed in this paper. The convolutional neural network (CNN) is extended with a channel-wise attention model to extract the most correlated visual features. The Recurrent Neural Network (RNN) further processes the features and excavates the dependencies among weather classes. Finally, the weather labels are predicted step by step. Besides, we construct two datasets for the weather recognition task and explore the relationships among different weather conditions. Experimental results demonstrate the superiority and effectiveness of the proposed approach. The new constructed datasets will be available at https://github.com/wzgwzg/Multi-Label-Weather-Recognition.

cs.CV↗

arXiv2018

Electronic quantum effect on hydrogen bond geometry in water dimer

During compression of a water dimer calculated with high-precision first-principles methods, the trends of H-bond and O-H bond lengths show quantum effect of the electronic structure. We found that the H-bond length keeps decreasing, while the O-H bond length increases up to the stable point and decreases beyond it when the water dimer is further compressed. The remarkable properties are different from those observed in most previous researches which can be understood and extrapolated through classical simulation. The observations can be explained by the decrease in orbital overlap and change in the exchange repulsion interaction between water monomers. The dominant interaction between water monomers changes from electrostatic interaction to exchange repulsion at the turning point of the O-H bond length when the O...O distance is decreased. These findings highlight the quantum effect on the hydrogen bond in extreme conditions and play an important role in the recognition of the hydrogen bond structure and mechanism.

physics.chem-ph↗

arXiv2018

Reconstruction of physics objects at the Circular Electron Positron Collider with Arbor

After the Higgs discovery, precise measurements of the Higgs properties and the electroweak observables become vital for the experimental particle physics. A powerful Higgs/Z factory, the Circular Electron Positron Collider(CEPC) is proposed. The Particle Flow oriented detector design is proposed to the CEPC and a Particle Flow algorithm, Arbor is optimized accordingly. We summarize the physics object reconstruction performance of the Particle Flow oriented detector design with Arbor algorithm and conclude that this combination fulfills the physics requirement of CEPC.

hep-ex↗

arXiv2018

Emerging disciplines based on superatoms: a perspective point of view

In this work, our statements are based on the progress of current research on superatomic clusters. Combining the new trend of materials and device manufacture at the atomic level, we analyzed the opportunities for the development based on the use of superatomic clusters as units of functional materials, and presented a foresight of this new branch of science with relevant studies on superatoms.

physics.atm-clus↗

arXiv2017

Spin Polarization and Dispersion Effects in Emergence of Roaming Transition State for Nitrobenzene Isomerization

Since roaming was found as a new but common reaction path of isomerization, many of its properties, especially those of roaming transition state (TSR), have been studied recently on many systems. However, the mechanism of roaming is still not clear at the atomic level. In this work, we used first-principles calculations to illustrate the detailed structure of TSR in an internal isomerization process of nitrobenzene. The calculations distinctively show its nature of antiferromagnetic coupling between two roaming fragments. Moreover, the effect of dispersion is also revealed as an important issue for the stability of the TSR. Our work provides a new insight from the view of electronic structure towards the TSR and contributes to the basic understanding of the roaming systems.

physics.atm-clus↗

arXiv2017

The Synthesis and Electrical Transport of Ligand-Protected Au13 Clusters

The ligand-protected Au13 clusters have been synthesized by using meso-2,3-imercaptosuccinic acid as the reducing and stabilizing agent. Transmission electron microscopic analysis shows a size distribution of 0.6nm. Optical spectrum shows an absorbance peak at 390 nm. The electrical transport measurement devices are fabricated using the electro-migration method. Coulomb blockade is observed at the temperature of 1.6 K,revealing the formation of the tunneling junction. The Coulomb oscillation on-off ratio is nearly 5. Three peaks are extracted in the dI-dV data and attributed to the energy levels of Au13 clusters, gapped by about 60 meV. First principle calculations are carried out to interpret the energy diagram.

cond-mat.mes-hall↗

arXiv2016

Electronic structure contribution to hydrogen bonding interaction of a water dimer

Hydrogen bond (H-bond) covalency has recently been observed in ice and liquid water, while the penetrating molecular orbitals (MOs) in the H-bond region of most typical water dimer system, (H2O)2, have also been discovered. However, obtaining the quantitative contribution of these MOs to the H-bond interaction is still problematic. In this work, we introduced the orbital-resolved electron density projected integral (EDPI) along the H-bond to approach this problem. The calculations show that, surprisingly, the electronic occupied orbital (HOMO-4) of (H2O)2 accounts for about 40% of the electron density at the bond critical point. Moreover, the charge transfer analysis visualizes the electron accumulating effect of the orbital interaction within the H-bond between water molecules, supporting its covalent-like character. Our work expands the classical understanding of H-bond with specific contributions from certain MOs, and will also advance further research into such covalency and offer quantitative electronic structure insights into intermolecular systems.

physics.atm-clus↗

arXiv2016

The self-consistent charge density functional tight-binding (DFTB) theory study of carbon adatoms using tuned Hubbard U parameters

The self-consistent charge density functional tight-binding (DFTB) theory is a useful tool for realizing the electronic structures of large molecular complex systems. In this study, we analyze the electronic structure of C61, formed by fullerene C60 with a carbon adatom, using the fully localized limit and pseudo self-interaction correction methods of DFTB to adjust the Hubbard U parameter (DFTB+U). The results show that both the methods used to adjust U can significantly reduce the molecular orbital energy of occupied states localized on the defect carbon atom and improve the gap between highest occupied molecular orbital(HOMO) and lowest unoccupied molecular orbital(LUMO) of C61. This work will provide a methodological reference point for future DFTB calculations of the electronic structures of carbon materials.

cond-mat.mtrl-sci↗

arXiv2015

Covalent features in the hydrogen bond of a water dimer: molecular orbital analysis

The covalent-like characteristics of hydrogen bonds offer a new perspective on intermolecular interactions. Here, using density functional theory and post-Hartree-Fock methods, we reveal that there are two bonding molecular orbitals (MOs) crossing the O and H atoms of the hydrogen-bond in water dimer. Energy decomposition analysis also shows a non-negligible contribution of the induction term. These results illustrate the covalent-like character of the hydrogen bond between water molecules, which contributes to the essential understanding of ice, liquid water, related materials, and life sciences.

physics.atm-clus↗