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Asymmetrically coordinated single atom Cu catalyst with unsaturated C-Cu-N structure for CO_(2) reduction to CO

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Nano Research 2024年第5期17卷 3911-3918页

作者： Zheng liu Yuxuan liu Jingqiao Zhang Ting Cao Zhiyi Sun Juzhe liu Huishan Shang State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing 100012China SEPA Key Laboratory of Eco-Industry Chinese Research Academy of Environmental SciencesBeijing 100012China The Key Laboratory of Resources and Environmental System Optimization Ministry of EducationCollege of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China

Single atom catalysts(SACs)play a crucial role in energy catalysis due to their distinct coordination environment and high atomic utilization *** study focuses on the synthesis of a monatomic Cu catalyst with Cu-N1C1 coordination anchored to N-doped Ti_(3)C_(2)T_(x) MXene(Cu SA@N-Ti_(3)C_(2)T_(x))to achieve efficient reduction of CO_(2) to *** characterization,including morphology and multispectral analysis,confirmed the uniform distribution of asymmetrically coordinated Cu atoms in unsaturated C-Cu-N bridge fragments on Ti_(3)C_(2)T_(x).The Cu SA@N-Ti_(3)C_(2)T_(x) catalyst exhibited an excellent CO selectivity with Faraday efficiency of 97.4%at-0.58 V *** hydrogen electrode(RHE)and satisfactory *** in situ X-ray absorption fine structure(XAFS)results confirmed that the carbon dioxide reduction reaction(CO_(2)RR)product distribution is mainly affected by potential-dependent valence change of Cu *** findings highlight the extensive potential of tuning coordination structure of MXene-based single-atom catalysts for CO_(2) reduction reactions.

关键词： cooper single atom atomic regulation MXene Ti_(3)C_(2)T_(x) CO_(2)reduction

Deep learning to develop zero-equation based turbulence model for CFD simulations of the built environment

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Building Simulation 2024年第3期17卷 399-414页

作者： Giovanni Calzolari Wei liu Division of Sustainable Buildings Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyBrinnelvägen 23Stockholm11428Sweden

This study aims to improve the accuracy and speed of predictions for thermal comfort and air quality in built environments by creating a coupled framework between computational fluid dynamics(CFD)simulations and deep learning *** coupling approach is showcased by the development of a data-driven turbulence *** new turbulence model is built using a deep learning neural network,whose mapping structure is based on a zero-equation turbulence model for built environment simulations,and is coupled with the CFD software OpenFOAM to create a hybrid *** neural network is a standard shallow multi-layer *** number of hidden layers and nodes per layer was optimized using Bayesan optimization *** framework is trained on an indoor environment case study,as well as tested on an indoor office simulation and an outdoor building array *** show that the deep learning based turbulence model is more robust and faster than traditional two-equation Reynolds average Navier-Stokes(RANS)turbulence models,while maintaining a similar level of *** model also outperforms the standard algebraic zero-equation model due to its superior ability to generalize to various flow *** some challenges,namely the mapping constraint,the limited training dataset size and the source of generation of training data,the hybrid framework demonstrates the viability of the coupling technique and serves as a starting point for future development of more reliable and advanced models.

关键词： neural networks computational fluid dynamics(CFD) turbulence model OpenFOAM

Exponential Time Differencing Method for a Reaction-Diffusion System with Free Boundary

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Communications on Applied Mathematics and Computation 2024年第1期6卷 354-371页

作者： Shuang liu Xinfeng liu Department of Mathematics University of CaliforniaSan Diego9500 Gilman DriveLa JollaCalifornia92093-0112USA Department of Mathematics University of South CarolinaColumbiaSouth Carolina29208USA

For reaction-diffusion equations in irregular domains with moving boundaries,the numerical stability constraints from the reaction and diffusion terms often require very restricted time step sizes,while complex geometries may lead to difficulties in the accuracy when discretizing the high-order derivatives on grid points near the *** is very challenging to design numerical methods that can efficiently and accurately handle both *** an implicit scheme may be able to remove the stability constraints on the time step,however,it usually requires solving a large global system of nonlinear equations for each time step,and the computational cost could be *** factor(IF)or exponential time differencing(ETD)methods are one of the popular methods for temporal partial differential equations(PDEs)among many other *** our paper,we couple ETD methods with an embedded boundary method to solve a system of reaction-diffusion equations with complex *** particular,we rewrite all ETD schemes into a linear combination of specificФ-functions and apply one state-of-the-art algorithm to compute the matrix-vector multiplications,which offers significant computational advantages with adaptive Krylov *** addition,we extend this method by incorporating the level set method to solve the free boundary *** accuracy,stability,and efficiency of the developed method are demonstrated by numerical examples.

关键词： Reaction diffusion equations Free boundary Integrating factor method Level set method

UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 1031-1041页

作者： Meng liu Jianwei Niu Yu liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

NC1000气相色谱在气体中氧氩含量分析的应用

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低温与特气 2020年第1期38卷 47-51页

作者：刘正启李永义爱尔兰AGC仪器公司北京代表处

氧气和氩气由于相近的沸点,导致其最难分离;采用MXT-5A分子筛柱,搭载DID检测器,对高纯气体中微量氧氩含量,进行分离并检测。

关键词：氧氩分离 MXT-5A分子筛柱 DID

MRm-DLDet:a memory-resident malware detection framework based on memory forensics and deep neural network

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Cybersecurity 2024年第1期7卷 88-109页

作者： Jiaxi liu Yun Feng Xinyu liu Jianjun Zhao Qixu liu Institute of Information Engineering Chinese Academy of SciencesBeijing 100085China School of Cyber Security University of Chinese Academy of SciencesBeijing 100049China

Cyber attackers have constantly updated their attack techniques to evade antivirus software detection in recent *** popular evasion method is to execute malicious code and perform malicious actions only in ***-cious programs that use this attack method are called memory-resident malware,with excellent evasion capability,and have posed huge threats to cyber *** static and dynamic methods are not effective in detect-ing memory-resident *** addition,existing memory forensics detection solutions perform unsatisfactorily in detection rate and depend on massive expert knowledge in memory *** paper proposes MRm-DLDet,a state-of-the-art memory-resident malware detection framework,to overcome these ***-DLDet first builds a virtual machine environment and captures memory dumps,then creatively processes the memory dumps into RGB images using a pre-processing technique that combines deduplication and ultra-high resolution image cropping,followed by our neural network MRmNet in MRm-DLDet to fully extract high-dimensional features from memory dump files and detect *** receives the labeled sub-images of the cropped high-resolution RGB images as input of ResNet-18,which extracts the features of the *** trains a network of gated recurrent units with an attention ***,it determines whether a program is memory-resident malware based on the detection results of each sub-image through a specially designed voting *** created a high-quality dataset consisting of 2,060 benign and memory-resident *** other words,the dataset contains 1,287,500 labeled sub-images cut from the MRm-DLDet transformed ultra-high resolution RGB *** implement MRm-DLDet for Windows 10,and it performs better than the latest methods,with a detection accuracy of up to 98.34%.Moreover,we measured the effects of mimicry and adversarial attacks on MRm-DLDet,and the experimental results demonstrated the robustness

关键词： Memory-resident malware Memory forensics Malware detection Deep learning Ultra-high resolution image

A study on vector mediator top-philic dark matter

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Communications in Theoretical Physics 2024年第8期76卷 67-78页

作者： Yanyan Hu Yandong liu Yuanyuan liu College of Nuclear Science and Technology Beijing Normal UniversityJoint Laboratory of Jinping Ultra-low Radiation Background Measurement of Ministry of Ecology and EnvironmentJinping Deep Underground Frontier Science and Dark Matter Key Laboratory of Sichuan ProvinceKey Laboratory of Beam Technology of Ministry of EducationBeijing 100875China Beijing Radiation Center Beijing 100875China

We conducted a study on a simplified dark matter model that introduces a vector-like intermediate particle,facilitating exclusive interactions between dark matter and the top quark in the Standard *** analysis focused on the relic density of Dirac-type fermion dark matter and highlighted the complementary role of direct detection in constraining the dark matter ***,in instances when dark matter mass is small,the tree-level two-body annihilation process experiences *** such scenarios,the contributions of the threebody process(χχ→tbW-)and the one-loop process(χχ→gg)dominate the relic *** regard to direct detection,calculations were performed for the two-loop contribution to the dark-matter-gluon interaction,yielding the corresponding spin-independent scattering cross section.

关键词： dark matter new physics effective field theory

Hydrogen and nitrogen absorption properties of Ce-added Zr_(2)(Fe_(1-x)Ni_(x)) alloys

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Journal of Rare Earths 2024年第6期42卷 1136-1141,I0005页

作者： Kai Yin Xiaopeng liu State Key Laboratory of Advanced Materials for Smart Sensing GRINM Group Co.Ltd.Beijing10088China GRIMAT Engineering Institute Co. Ltd.Beijing101407China General Research Institute of Nonferrous Metals Beijing100088China

To improve the nitriding resistance of Zr_(2)Fe alloy,the Ce-added Zr_(2)(Fe_(1-x)Ni_(x))(x=0,0.15,0.3,0.5)alloys were prepared by magnetic levitation melting *** effects of Ni substitution for Fe on the phase structure,hydrogen and nitrogen absorption properties of the alloys were investigated by X-ray diffraction,scanning electron microscopy and p-c isotherm *** experimental results show that Ni substitution can effectively inhibit the formation of both α-Zr and ZrFe_(2) phases and promote the formation of C16 structure Zr_(2)(Fe,Ni)phase,causing Ni-substituted alloys to exhibit low nitrogen absorption rate and *** 623 K under 0.5 MPa nitrogen pressure,the nitrogen absorption capacity of Ce-added Zr_(2)(Fe_(0.5)Ni_(0.5))alloy reaches to 0.8 mL/g,much lower than that of Zr_(2)Fe alloy(1.5 mL/g).Ni substitution decreases the crystal cell volume of the C_(16)Zr_(2)(Fe,Ni)phase,resulting in an increase in the hydrogen absorption equilibrium *** 623 K under 0.05 MPa hydrogen pressure,the hydrogen absorption capacity decreases from 1.46 wt%of Zr_(2)Fe alloy to 1.41 wt%of Ce-added Zr_(2)(Fe_(0.5)Ni_(0.5))alloy.

关键词： Zr_(2)Fe alloy Ce Pressure-composition isotherm Hydrogen absorption Nitrogen absorption Rare earths

Modeling urban scale human mobility through big data analysis and machinelearning

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Building Simulation 2024年第1期17卷 3-21页

作者： Yapan liu Bing Dong Department of Mechanical&Aerospace Engineering Syracuse University263 Link HallSyracuseNY 13244USA

In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas *** behavior has drawn increasing research interests due to its impacts on the building energy ***,occupant behavior study at urban scale remains a challenge,and very limited studies have been *** an effort to couple big data analysis with human mobility modeling,this study has explored urban scale human mobility utilizing three months Global Positioning System(GPS)data of 93,o00 users at Phoenix Metropolitan *** research extracted stay points from raw data,and identified users'home,work,and other locations by Density-Based Spatial Clustering ***,daily mobility patterns were constructed using different types of *** propose a novel approach to predict urban scale daily human mobility patterns with 12-hour prediction horizon,using Long Short-Term Memory(LSTM)neural network *** shows the developed models achieved around 85%average accuracy and about 86%mean *** developed models can be further applied to analyze urban scale occupant behavior,building energy demand and flexibility,and contributed to urban planning.

关键词： urban human mobility big data analysis urban scale occupant behavior recurrent neural networks