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Error correlations in photonic qudit-mediated entanglement generation

Liu, X. (author), Bharos, N.P. (author), Markovich, L. (author), Borregaard, J. (author)

Generating entanglement between distributed network nodes is a prerequisite for the quantum internet. Entanglement distribution protocols based on high-dimensional photonic qudits enable the simultaneous generation of multiple entangled pairs, which can significantly reduce the required coherence time of the qubit registers. However, current...

journal article 2024

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Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records

Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), Su, Jianbin (author)

Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land...

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Effects of Grain Boundaries and Surfaces on Electronic and Mechanical Properties of Solid Electrolytes

Xie, Weihang (author), Deng, Zeyu (author), Liu, Zhengyu (author), Famprikis, T. (author), Butler, Keith T. (author), Canepa, Pieremanuele (author)

Extended defects, including exposed surfaces and grain boundaries (GBs), are critical to the properties of polycrystalline solid electrolytes in all-solid-state batteries (ASSBs). These defects can alter the mechanical and electronic properties of solid electrolytes, with direct manifestations in the performance of ASSBs. Here, by building a...

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A Data-Driven Model for Power Loss Estimation of Magnetic Materials Based on Multi-Objective Optimization and Transfer Learning

Li, Z. (author), Wang, L. (author), Liu, R. (author), Mirzadarani, R. (author), Luo, T. (author), Lyu, D. (author), Ghaffarian Niasar, M. (author), Qin, Z. (author)

Traditional methods such as Steinmetz's equation (SE) and its improved variant (iGSE) have demonstrated limited precision in estimating power loss for magnetic materials. The introduction of Neural Network technology for assessing magnetic component power loss has significantly enhanced accuracy. Yet, an efficient method to incorporate detailed...

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Insights into micro-structure and separation mechanism of benzimidazole-linked polymer membrane for H₂/CO₂ separation

Shan, Meixia (author), Zhang, Jingjing (author), Cong, Shenzhen (author), Zhang, Yatao (author), He, Xuezhong (author), Kapteijn, F. (author), Liu, X. (author)

Separation of hydrogen from carbon dioxide for sustainable H₂ production and CO₂ capture still faces great challenges due to the smaller size of H₂ and higher condensability of CO₂. Herein, a high-performance benzimidazole-linked polymer (BILP) membrane for hydrogen separation was directly prepared...

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Critical turbidity thresholds for maintenance of estuarine tidal flats worldwide

Grandjean, Tim J. (author), Weenink, Roland (author), van der Wal, Daphne (author), Addink, Elisabeth A. (author), Hu, Zhan (author), Liu, Shuai (author), Wang, Zhengbing (author), Lin, Yuan (author), Bouma, Tjeerd J. (author)

Tidal flats are shrinking in extent globally. The dynamics of the response of estuarine tidal flats to global environmental changes remain unclear. Tidal-flat morphology is shaped by the interplay among wave and tidal forces, river discharge and sediment supply, and preservation of tidal flats requires a balance between erosional and...

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Advancing the local climate zones framework: A critical review of methodological progress, persisting challenges, and future research prospects

Han, Jie (author), Mo, Nan (author), Cai, Jingyi (author), Ouyang, Leixin (author), Liu, Zhengxuan (author)

The local climate zones (LCZs) classification system has emerged as a more refined method for assessing the urban heat island (UHI) effect. However, few researchers have conducted systematic critical reviews and summaries of the research on LCZs, particularly regarding significant advancements of this field in recent years. This paper aims to...

review 2024

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Nanostructure and damage characterisation of bitumen under a low cycle strain-controlled fatigue load based on molecular simulations and rheological measurements

Gao, Y. (author), Liu, X. (author), Ren, S. (author), Assaf Martinez-Streignard, E.I. (author), Liu, Pengfei (author), Zhang, Yuqing (author)

Bitumen fatigue resistance is critical to determine the overall fatigue performance and service life of asphalt pavements. However, the mechanisms responsible for fatigue damage of bitumen have previously not been well understood. Molecular dynamics (MD) simulation has recently emerged as a powerful computer-aided numerical technique to model...

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Introducing a force-matched united atom force field to explore larger spatiotemporal domains in molecular dynamics simulations of bitumen

Assaf Martinez-Streignard, E.I. (author), Liu, X. (author), Lin, P. (author), Erkens, S. (author)

This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages...

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Advancements and insights in thermal and water management of proton exchange membrane fuel cells: Challenges and prospects

Zhang, Zhenya (author), Mao, Jia (author), Liu, Zhengxuan (author)

In response to the growing global demand for clean and sustainable energy solutions, proton exchange membrane fuel cells (PEMFCs) have emerged as vital components in diverse decarbonization strategies. Despite their increasing importance, a comprehensive synthesis of recent advancements, challenges, and future prospects in thermal and water...

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Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories

Chen, K. (author), Li, Zhibin (author), Liu, Pan (author), Knoop, V.L. (author), Han, Yu (author), Jiao, Y. (author)

A lane-changing (LC) maneuver may cause the follower in the target lane (new follower) to decelerate and give up space, potentially affecting crash risk and traffic flow efficiency. In congested flow, a more aggressive LC maneuver occurs where the lane changer is partially next to the new follower and creates negative gaps, namely negative...

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FedViT: Federated continual learning of vision transformer at edge

Zuo, Xiaojiang (author), Luopan, Yaxin (author), Han, Rui (author), Zhang, Qinglong (author), Liu, Chi Harold (author), Wang, Guoren (author), Chen, Lydia Y. (author)

Deep Neural Networks (DNNs) have been ubiquitously adopted in internet of things and are becoming an integral part of our daily life. When tackling the evolving learning tasks in real world, such as classifying different types of objects, DNNs face the challenge to continually retrain themselves according to the tasks on different edge...

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Plastic particles affect N₂O release via altering core microbial metabolisms in constructed wetlands

Yang, X. (author), Chen, Yi (author), Liu, Tao (author), Zhang, Lu (author), Wang, Hui (author), Chen, Mengli (author), He, Qiang (author), Liu, G. (author), Ju, Feng (author)

Constructed wetlands (CWs) have been proven to effectively immobilize plastic particles. However, little is known about the differences in the impact of varying sized plastic particles on nitrous oxide (N₂O) release, as well as the intervention mechanisms in CWs. Here, we built a lab-scale wetland model and introduced plastic...

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Investigating the Role of Executive Intrafirm Alumni Networks in Top Management Fraud: Multilevel Study in China's Construction Industry

Wang, Ran (author), Wang, Tongbing (author), Lee, Chia-Jung (author), Liu, Zhengxuan (author), Zhang, G. (author)

To explore factors that influence the likelihood of committing fraud in the construction industry, this study concentrated on senior executives and tested whether some characteristics at the individual and firm levels have impacts on the likelihood of fraud committed by top management. Based on social network theory, this study first proposes...

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Research on shutdown purge characteristics of proton exchange membrane fuel cells: Purge parameters conspicuity and residual water

Zhang, Zhenya (author), Wei, Houyu (author), Xiao, Yanqiu (author), Cheng, Chuanxiao (author), Tian, Jiean (author), Li, Xinxin (author), Liu, Junrui (author), Liu, Zhengxuan (author)

This paper comprehensively investigates the purge mechanism of proton exchange membrane fuel cells during the shutdown process, which qualitatively examines the effect of purge parameters (including current density, stoichiometric ratio, and relative humidity) on water content variation, and further quantitatively investigates the remaining...

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PDB2DAT: Automating LAMMPS data file generation from PDB molecular systems using Python, Rdkit, and Pysimm

Assaf Martinez-Streignard, E.I. (author), Liu, X. (author), Lin, Peng (author), Erkens, S. (author)

Pdb2dat, developed in Python, is an open-source, self-contained utility that facilitates the conversion of PDB files into LAMMPS data files, catering to the need of initializing atomistic simulation from initial atomic configurations. It extracts molecular details from PDB files, uses Rdkit and Xyz2mol for bonding analysis and 3D conformer...

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General Optimal Trajectory Planning: Enabling Autonomous Vehicles with the Principle of Least Action

Huang, H. (author), Liu, Yicong (author), Liu, Jinxin (author), Yang, Q. (author), Wang, Jianqiang (author), Abbink, David (author), Zgonnikov, A. (author)

This study presents a general optimal trajectory planning (GOTP) framework for autonomous vehicles (AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently. Firstly, we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline. Cartesian coordinates...

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Physics-Informed Neural Networks to Model and Control Robots: A Theoretical and Experimental Investigation

Liu, J. (author), Borja, Pablo (author), Della Santina, C. (author)

This work concerns the application of physics-informed neural networks to the modeling and control of complex robotic systems. Achieving this goal requires extending physics-informed neural networks to handle nonconservative effects. These learned models are proposed to combine with model-based controllers originally developed with first...

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Maximizing eco-environmental gains: Exploring underground wastewater treatment plants in Beijing for sustainable urban water management

Zhang, Lujing (author), Hu, Yuchen (author), Li, Peng (author), Wei, Renke (author), Pang, Hongtao (author), de Kreuk, M.K. (author), Qu, Shen (author), Lam, K.L. (author), van der Meer, Walter (author), Liu, G. (author)

This study assessed the evolution of wastewater systems during the rapid urbanization of Beijing, with special focuses on the carbon footprints and growing underground WWTPs (u-WWTPs). Specifically, the Bishui plant (in situ constructed u-WWTP) was assessed in detail regarding eco-environmental benefits. Our results showed that, the direct...

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SMI2PDB: A self-contained Python tool to generate atomistic systems of organic molecules using their SMILES notations

Assaf Martinez-Streignard, E.I. (author), Liu, X. (author), Lin, P. (author), Erkens, S. (author)

The advent of computational techniques, particularly atomistic simulations, has lessened the dependency on physical experiments in various scientific fields. Yet, the preparation complexity for simulations using platforms like LAMMPS and GROMACS persists. We introduce SMI2PDB, a Python tool that automates molecular systems assembly from SMILES...

journal article 2024