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Symmetry-adapted graph neural networks for constructing molecular dynamics force fields

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Science China(Physics,Mechanics & Astronomy) 2021年第11期64卷 118-126页

作者： Zun Wang Chong Wang SiBo Zhao ShiQiao Du Yong Xu bing-lin gu WenHui Duan State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua UniversityBeijing 100084China Department of Physics Carnegie Mellon UniversityPittsburgh 15213USA Institute for Advanced Study Tsinghua UniversityBeijing 100084China Frontier Science Center for Quantum Information Beijing 100084China RIKEN Center for Emergent Matter Science(CEMS) WakoSaitama 351-0198Japan

Molecular dynamics is a powerful simulation tool to explore material properties.Most realistic material systems are too large to be simulated using first-principles molecular dynamics.Classical molecular dynamics has a lower computational cost but requires accurate force fields to achieve chemical accuracy.In this work,we develop a symmetry-adapted graph neural network framework called the molecular dynamics graph neural network(MDGNN)to construct force fields automatically for molecular dynamics simulations for both molecules and crystals.This architecture consistently preserves translation,rotation,and permutation invariance in the simulations.We also propose a new feature engineering method that includes high-order terms of interatomic distances and demonstrate that the MDGNN accurately reproduces the results of both classical and first-principles molecular dynamics.In addition,we demonstrate that force fields constructed by the proposed model have good transferability.The MDGNN is thus an efficient and promising option for performing molecular dynamics simulations of large-scale systems with high accuracy.

关键词： graph neural networks molecular dynamics force fields

Heterogeneous relational message passing networks for molecular dynamics simulations

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npj Computational Materials 2022年第1期8卷 509-517页

作者： Zun Wang Chong Wang Sibo Zhao Yong Xu Shaogang Hao Chang Yu Hsieh bing-lin gu Wenhui Duan State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua UniversityBeijingChina Tencent Quantum Lab TencentShenzhenGuangdong518057China Department of Physics Carnegie Mellon UniversityPittsburghPAUSA Frontier Science Center for Quantum Information Beijing100084China RIKEN Center for Emergent Matter Science(CEMS) WakoSaitama351-0198Japan Institute for Advanced Study Tsinghua UniversityBeijing100084China

With many frameworks based on message passing neural networks proposed to predict molecular and bulk properties,machine learning methods have tremendously shifted the paradigms of computational sciences underpinning physics,material science,chemistry,and biology.While existing machine learning models have yielded superior performances in many occasions,most of them model and process molecular systems in terms of homogeneous graph,which severely limits the expressive power for representing diverse interactions.In practice,graph data with multiple node and edge types is ubiquitous and more appropriate for molecular systems.Thus,we propose the heterogeneous relational message passing network(HermNet),an end-to-end heterogeneous graph neural networks,to efficiently express multiple interactions in a single model with ab initio *** performs impressively against many top-performing models on both molecular and extended systems.Specifically,HermNet outperforms other tested models in nearly 75%,83%and 69%of tasks on revised Molecular Dynamics 17(rMD17),Quantum Machines 9(QM9)and extended systems datasets,respectively.In addition,molecular dynamics simulations and material property calculations are performed with HermNet to demonstrate its performance.Finally,we elucidate how the design of HermNet is compatible with quantum mechanics from the perspective of the density functional theory.Besides,HermNet is a universal framework,whose sub-networks could be replaced by other advanced models.

关键词： theory passing dynamics

Low-energy-consumption temperature swing system for CO_(2) capture by combining passive radiative cooling and solar heating

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Green Energy & Environment 2024年第3期9卷 507-515页

作者： Ying-Xi Dang Peng Tan Bin Hu Chen gu Xiao-Qin Liu lin-bing Sun State Key Laboratory of Materials-Oriented Chemical Engineering Jiangsu National Synergetic Innovation Center for Advanced Materials(SICAM)College of Chemical EngineeringNanjing Tech UniversityNanjing211816China

Temperature-swing adsorption(TSA)is an effective technique for CO_(2) capture,but the temperature swing procedure is energy-intensive.Herein,we report a low-energy-consumption system by combining passive radiative cooling and solar heating for the uptake of CO_(2) on commercial activated carbons(CACs).During adsorption,the adsorbents are coated with a layer of hierarchically porous poly(vinylidene fluoride-co-hexafluoropropene)[P(VdF-HFP)HP],which cools the adsorbents to a low temperature under sunlight through radiative cooling.For desorption,CACs with broad absorption of the solar spectrum are exposed to light irradiation for heating.The heating and cooling processes are completely driven by solar energy.Adsorption tests under mimicked sunlight using the CACs show that the performance of this system is comparable to that of the traditional ones.Furthermore,under real sunlight irradiation,the adsorption capacity of the CACs can be well maintained after multiple cycles.The present work may inspire the development of new temperature swing procedures with little energy consumption.

关键词： CO_(2)capture Solar heating Passive radiative cooling Temperature swing adsorption

Efficient degradation of aqueous dichloromethane by an enhanced microbial electrolysis cell:Degradation kinetics,microbial community and metabolic mechanisms

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Journal of Environmental Sciences 2024年第5期139卷 150-159页

作者： Meng Wu Di Zhao bing gu ZiruWang Jun Hu Zhiliang Yu Jianming Yu College of Environment College of Biotechnology and BioengineeringCollaborative Innovation Center of Yangtze River Delta Region Green PharmaceuticalsZhejiang University of TechnologyHangzhou 310014China Shentuo Environment(Hangzhou)Co.Ltd. Hangzhou 311121China Zhejiang Tianyi Environmental Co.Ltd. Hangzhou 310000China

Dichloromethane(DCM)has been listed as a toxic and harmful water pollutant,and its re moval needs attention.Microbial electrolysis cells(MECs)are viewed as a promising alterna tive for pollutant removal,which can be strengthened from two aspects:microbial inocula tion and acclimation.In this study,the MEC for DCM degradation was inoculated with the ac tive sludge enhanced by Methylobacterium rhodesianum H13(strain H13)and then acclimated in the form of a microbial fuel cell(MFC).Both the introduction of strain H13 and the initi ation in MFC form significantly promoted DCM degradation.The degradation kinetics were fitted by the Haldane model,with V_(max),K_(h),K_(i)and v_(max)values of 103.2 mg/L/hr,97.8 mg/L268.3 mg/L and 44.7 mg/L/hr/cm^(2),respectively.The cyclic voltammogram implies that DCM redox reactions became easier with the setup of MEC,and the electrochemical impedance spectrogram shows that the acclimated and enriched microbes reduced the charge transfe resistance from the electrode to the electrolyte.In the biofilm,the dominant genera shifted from Geobacter to Hyphomicrobium in acclimation stages.Moreover,Methylobacterium played an increasingly important role.DCM metabolism mainly occurred through the hydrolytic glutathione S-transferase pathway,given that the gene dcmA was identified rather than the dhlA and P450/MO.The exogenous electrons facilitated the reduction of GSSG,directly o indirectly accelerating the GSH-catalyzed dehalogenation.This study provides support fo the construction of an efficient and stable MEC for DCM removal in water environment.

关键词： Dichloromethane Microbial electrolysis cells Metabolic pathways Electron transfer Degradation kinetics

Flexible and Robust Functionalized Boron Nitride/Poly(p‑Phenylene Benzobisoxazole)Nanocomposite Paper with High Thermal Conductivity and Outstanding Electrical Insulation

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Nano-Micro Letters 2024年第2期16卷 423-437页

作者： lin Tang Kunpeng Ruan Xi Liu Yusheng Tang Yali Zhang Junwei gu Chongqing Key Laboratory of Green Synthesis and Applications College of ChemistryChongqing Normal UniversityChongqing 401331People’s Republic of China Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710072People’s Republic of China

With the rapid development of 5G information technology,thermal conductivity/dissipation problems of highly integrated electronic devices and electrical equipment are becoming prominent.In this work,“high-temperature solid-phase&diazonium salt decomposition”method is carried out to prepare benzidine-functionalized boron nitride(m-BN).Subsequently,m-BN/poly(pphenylene benzobisoxazole)nanofiber(PNF)nanocomposite paper with nacremimetic layered structures is prepared via sol–gel film transformation approach.The obtained m-BN/PNF nanocomposite paper with 50 wt%m-BN presents excellent thermal conductivity,incredible electrical insulation,outstanding mechanical properties and thermal stability,due to the construction of extensive hydrogen bonds andπ–πinteractions between m-BN and PNF,and stable nacre-mimetic layered structures.Itsλ∥andλ_(⊥)are 9.68 and 0.84 W m^(-1)K^(-1),and the volume resistivity and breakdown strength are as high as 2.3×10^(15)Ωcm and 324.2 kV mm^(-1),respectively.Besides,it also presents extremely high tensile strength of 193.6 MPa and thermal decomposition temperature of 640°C,showing a broad application prospect in high-end thermal management fields such as electronic devices and electrical equipment.

关键词： Poly(p-phenylene-2,6-benzobisoxazole)nanofiber Boron nitride Thermal conductivity Electrical insulation

An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 577-591页

作者： Qing Zhu linlin gu Huijie lin Electricity Technology Branch Nari Technology Co.Ltd.Nanjing211106China NARI-TECH Nanjing Control Systems Co. Ltd.Nanjing211106China

With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.

关键词： Load estimation deep learning attention mechanism image fingerprint construction

Ultra reliability and massive connectivity provision in integrated internet of military things(IoMT)based on tactical datalink

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Defence Technology（防务技术） 2024年第3期33卷 386-398页

作者： Li bing Yating gu Lanke Hu Li Bowen Yang Lihua Jue Wang Yue Yin Northwestern Polytechnical University Xi'an 710072China China Academy of Information and Communications Technology Beijing 100191China China Intelligent and Connected Vehicles(Beijing)Research Institute Co. LtdBeijing 100176China The 20th Research Institute of China Electronic Technology Group Corporation Xi’an 710068China Xidian University Xi'an 710071China

One of the major challenges arising in internet of military things(IoMT)is accommodating massive connectivity while providing guaranteed quality of service(QoS)in terms of ultra-high reliability.In this regard,this paper presents a class of code-domain nonorthogonal multiple accesses(NOMAs)for uplink ultra reliable networking of massive IoMT based on tactical datalink such as link-16 and joint tactical information distribution system(JTIDS).In the considered scenario,a satellite equipped with Nr antennas servers K devices including vehicles,drones,ships,sensors,handset radios,etc.Nonorthogonal coded modulation,a special form of multiple input multiple output(MIMO)-NOMA is proposed.The discussion starts with evaluating the output signal to interference-plus-noise(SINR)of receiver filter,leading to the unveiling of a closed-form expression for overloading systems as the number of users is significantly larger than the number of devices admitted such that massive connectivity is rendered.The expression allows for the development of simple yet successful interference suppression based on power allocation and phase shaping techniques that maximizes the sum rate since it is equivalent to fixed-point programming as can be proved.The proposed design is exemplified by nonlinear modulation schemes such as minimum shift keying(MSK)and Gaussian MSK(GMSK),two pivotal modulation formats in IoMT standards such as link-16 and JITDS.Numerical results show that near capacity performance is offered.Fortunately,the performance is obtained using simple forward error corrections(FECs)of higher coding rate than existing schemes do,while the transmit power is reduced by 6 dB.The proposed design finds wide applications not only in IoMT but also in deep space communications,where ultra reliability and massive connectivity is a keen concern.

关键词： Satellite network Deep space communications Internet of military things Non-orthogonal multiple access MIMO link-16 JITDS

Compressed Data Separation via ?q-Split Analysis with ?∞-Constraint

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1655-1673页

作者： Ming Yang gu Song LI Jun Hong lin School of Mathematical Science Zhejiang University Center for Data Science Zhejiang University

In this paper, we study compressed data separation（CDS） problem, i.e., sparse data separation from a few linear random measurements. We propose the nonconvex ?q-split analysis with ?∞-constraint and 0 < q ≤ 1. We call the algorithm ?q-split-analysis Dantzig selector（?q-split-analysis DS）. We show that the two distinct subcomponents that are approximately sparse in terms of two different dictionaries could be stably approximated via the ?q-split-analysis DS, provided that the measurement matrix satisfies either a classical D-RIP（Restricted Isometry Property with respect to Dictionaries and ?2norm） or a relatively new（D, q）-RIP（RIP with respect to Dictionaries and ?q-quasi norm） condition and the two different dictionaries satisfy a mutual coherence condition between them.For the Gaussian random measurements, the measurement number needed for the（D, q）-RIP condition is far less than those needed for the D-RIP condition and the（D, 1）-RIP condition when q is small enough.

关键词： Data separation ℓ q -split analysis Dantzig selector frames restricted isometry property compressed sensing 94A12 41A29 65T99 94A20

Green synthesis of ZSM-5 using silica fume and catalytic co-cracking of lignin and plastics for production of monocyclic aromatics

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Chinese Journal of Chemical Engineering 2024年第1期65卷 92-105页

作者： Hongbing Fu Yufei gu Tianhua Gao Fuwei Li Hengshuo gu Hucheng Ge Yuke Liu Zhixia Li Hongfei lin Jiangfei Cao School of Chemistry and Chemical Engineering Guangxi UniversityNanning 530004China guangxi Bossco Environmental Protection Technology Co. Ltd.Nanning 530007China School of Environmental and Chemical Engineering Zhaoqing UniversityZhaoqing 526000China

ZSM-5 with hierarchical pore structure was synthesized by a simple two-step hydrothermal crystallization from silica fume without using any organic ammonium templates.The synthesized ZSM-5 were oval shaped particles with a particle size about 2.0 μm and weak acid-dominated with proper Brønsted(B)and Lewis(L)acid sites.The ZSM-5 was used for catalytic co-cracking of n-octane and guaiacol,lowdensity polyethylene(LDPE)and alkali lignin(AL)to enhance the production of benzene,toluene,ethylbenzene and xylene(BTEX).The most significant synergistic effect occurred at n-octane/guaiacol at 1:1 and LDPE/AL at 1:3,under the condition,the achieved BTEX selectivity were 24%and 33%(mass)higher than the calculated values(weighted average).The highest BTEX selectivity reached 88.5%,which was 3.7%and 54.2%higher than those from individual cracking LDPE and AL.The synthesized ZSM-5 exhibited superior catalytic performance compared to the commercial ZSM-5,indicating potential application prospect.

关键词： Silica fume ZSM-5 Catalytic co-cracking Plastics Lignin