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Molecule functionalization to facilitate electrocatalytic oxygen reduction on graphdiyne

Journal of Energy Chemistry 2022年第2期31卷 141-148页

作者： Huiying Yao Yasong Zhao Nailiang Yang Wei Hao Hu Zhao Shuzhou Li Jia Zhu Lin Shen Weihai Fang College of Chemistry Key Laboratory of Theoretical&Computational Photochemistry of Ministry of EducationBeijing Normal UniversityBeijing 100875China State Key Laboratory of Biochemical Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Materials Science and Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore Department of Physics Beijing Normal UniversityBeijing 100875China Laboratory of Theoretical and Computational Nanoscience CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyChinese Academy of SciencesBeijing 100190China

Chemical doping is verified to be a promising strategy to regulate local electron distribution and further promote the poor intrinsic catalytic activity of ***,the current doping approach still faces problems such as precise doping for creating active sites and the destruction of graphdiyne skeleton calling for high ***,we achieved charge redistribution on graphdiyne surface through molecule functionalization.A p-type molecule–F4 TCNQ(2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodime thane)was introduced and the site-defined functionalization was *** calculations showed that the charge transfer ability is improved and graphdiyne becomes positively *** oxygen reduction electrocatalysis was conducted as a proof of principle,where the electronic states of sp hybridized C active site was tuned toward favorable reaction intermediates’*** work from both theoretical prediction and experimental validation,found that molecule functionalization is effective to promote the electrocatalytic oxygen reduction,which creates new possibilities for graphdiyne’s applications in different electrochemical reactions.

关键词： Graphdiyne F4TCNQ Density functional calculations Electronic structure Oxygen reduction reaction

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Investigating the Feasibility and Benefits of Integrating Renewable Energy systems into Sustainable Pavement Materials and Structures 8th

Investigating the Feasibility and Benefits of Integrating Re...

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8th International Conference on Material engineering and Nanotechnology, ICMEN 2024

作者： Khasawneh, Mohammad Ali Sawalha, Ansam Khasawneh, Ahmad Ali Rababah, Samer Department of Civil Engineering Prince Mohammad Bin Fahd University Al Khobar Saudi Arabia Department of Civil Engineering American University of Madaba Madaba Jordan Management Engineering and Process Improvement Department/Integrated Systems Engineering Department Ohio State University Wexner Medical Center & Ohio State University 660 Ackerman Road ColumbusOH43202 United States Department of Civil Engineering Joordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9789819636235

Sustainability and green environment concepts have evolved in various fields, including but not limited to industry, energy, transport, and construction. Several applications and technologies are integrated into pavement in order to enhance the sustainability of transport infrastructure. Thus, this paper aims to provide an in-depth review to examine the feasibility and benefits of embedding several renewable energy technologies, such as piezoelectric, photovoltaic, thermoelectric, and kinetic energy harvesting systems, into pavement materials. The paper also addresses the environmental impacts of integrating renewable energy into pavement materials and structures. The findings suggest that despite challenges such as high costs and efficiency optimization needs, the integration of renewable energy into transport infrastructure can significantly contribute to reducing greenhouse gas emissions and promoting sustainable development. Finally, future advancements in renewable energy-integrated pavement systems could transform sustainable infrastructure by enabling roads to generate power. Techniques such as piezoelectric materials, photovoltaic pavements, thermoelectric materials, and geothermal energy harvesting, alongside carbon-neutral materials with carbon capture, offer innovative ways to reduce the carbon footprint of roadways and provide alternative energy sources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Clean energy

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Stability improvement of nuclear magnetic resonance gyroscope with self-calibrating parametric magnetometer

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Physical Review Applied 2024年第1期21卷 014042-014042页

作者： Guoping Gao Jinbo Hu Feng Tang Wenhui Liu Xiangdong Zhang Baoxu Wang Dongge Deng Mingzhi Zhu Nan Zhao Beijing Computational Science Research Center Beijing 100193 People’s Republic of China Institute of Systems Engineering China Academy of Engineering Physics Mianyang Sichuan 621999 People’s Republic of China

In this paper, we study the stability of nuclear magnetic resonance gyroscope (NMRG), which employs Xe nuclear spins to measure inertial rotation rate. The Xe spin polarization is sensed by an in situ Rb magnetometer. The Rb magnetometer works in a parametric oscillation mode (henceforth referred to as the Rb parametric magnetometer, or Rb PM), in which the Larmor frequency of the Rb spins is modulated and the transverse components of Xe nuclear spin polarization are measured. As the measurement output of the Rb PM, the phase of the Xe nuclear spin precession is eventually converted to the Xe nuclear magnetic resonance (NMR) frequencies and the inertial rotation rate. Here we provide a comprehensive study of the NMR phase measured by the Rb PM, and analyze the influence of various control parameters, including the dc magnetic field, the frequency and phase of the modulation field, and the Rb resonance linewidth, on the stability of the NMR phase. Based on these analyses, we propose and implement a self-calibrating method to compensate the NMR phase drift during the Rb-PM measurement. With the self-calibrating Rb PM, we improve the bias instability of the NMRG from 1 to 0.2deg/hr for datasets of 8 h, or to 0.02deg/hr for the best approximately 5000s dataset.

关键词： Magnetometry Quantum sensing Rotation sensing Atomic gases Nuclear magnetic resonance Nuclear spin resonance Optically detected magnetic resonance

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A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

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Computers, Materials & Continua 2023年第4期75卷 697-714页

作者： Samra Rehman Muhammad Attique Khan Majed Alhaisoni Ammar Armghan Usman Tariq Fayadh Alenezi Ye Jin Kim Byoungchol Chang Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakahSaudi Arabia Department of Management Information Systems CoBAPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Identifying fruit disease manually is time-consuming, expertrequired,and expensive;thus, a computer-based automated system is widelyrequired. Fruit diseases affect not only the quality but also the *** a result, it is possible to detect the disease early on and cure the fruitsusing computer-based techniques. However, computer-based methods faceseveral challenges, including low contrast, a lack of dataset for training amodel, and inappropriate feature extraction for final classification. In thispaper, we proposed an automated framework for detecting apple fruit leafdiseases usingCNNand a hybrid optimization algorithm. Data augmentationis performed initially to balance the selected apple dataset. After that, twopre-trained deep models are fine-tuning and trained using transfer ***, a fusion technique is proposed named Parallel Correlation Threshold(PCT). The fused feature vector is optimized in the next step using a hybridoptimization algorithm. The selected features are finally classified usingmachine learning algorithms. Four different experiments have been carriedout on the augmented Plant Village dataset and yielded the best accuracy of99.8%. The accuracy of the proposed framework is also compared to that ofseveral neural nets, and it outperforms them all.

关键词： Convolutional neural networks deep learning features fusion features optimization classification

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Towards Resilient and Sustainable Water and Energy Sectors in Jordan 8th

Towards Resilient and Sustainable Water and Energy Sectors i...

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8th International Conference on Material engineering and Nanotechnology, ICMEN 2024

作者： Sawalha, Ansam Baqain, Sameeh Khasawneh, Mohammad Ali Sawalha, Amani Khasawneh, Ahmad Ali Department of Civil Engineering American University of Madaba Madaba Jordan Department of Mechanical Engineering American University of Madaba Madaba Jordan Department of Civil Engineering Prince Mohammad Bin Fahd University Al Khobar Saudi Arabia Department of Architecture Engineering Applied Science Private University Amman Jordan Management Engineering and Process Improvement Department/Integrated Systems Engineering Department Ohio State University Wexner Medical Center and Ohio State University 660 Ackerman Road ColumbusOH43202 United States

ISBN: (纸本)9789819636235

The concepts of resilience and sustainability have recently gained significant attention from industrial and academic institutions. The resilience concept in the water and energy sectors indicates the ability to recover from disruptions such as natural disasters, whereas the sustainable concept ensures that current needs are met without compromising future generations. In Jordan, the water and energy sectors face numerous challenges, including scarce natural resources combined with the growth in climate-related disasters, regional instability, conflicts, urbanization, continuing difficulties in water and energy resources, and consumer awareness of sources’ conservation and sustainability. To address these pressing issues, the authors conducted in-depth interviews with 33 experts from government, international organizations, private companies, and donor agencies. These discussions explored the current state of the water and energy sectors, highlighting key challenges, the critical need to integrate resilience and sustainability, and potential future directions. The study’s findings emphasize the importance of coordinated strategic planning, along with specific recommendations such as upgrading water pumps, installing smart meters, and implementing time-based tariffs to promote responsible consumption. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Energy Energy Sector Resilience Sustainable Water Water Sector

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Acetic acid-assisted mild dealloying of fine CuPd nanoalloys achieving compressive strain toward high-efficiency oxygen reduction and ethanol oxidation electrocatalysis

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Carbon Energy 2023年第7期5卷 112-120页

作者： Danye Liu Yu Zhang Hui Liu Peng Rao Lin Xu Dong Chen Xinlong Tian Jun Yang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijingChina State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine ChemistrySchool of Chemical Engineering and TechnologyHainan UniversityHaikouChina Jiangsu Key Laboratory of New Power Batteries School of Chemistry and Materials ScienceJiangsu Collaborative Innovation Centre of Biomedical Functional MaterialsNanjing Normal UniversityNanjingChina Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijingChina Nanjing IPE Institute of Green Manufacturing Industry NanjingJiangsuChina

Dealloying by which the transition metal is partially or completely leached from an alloy precursor is an effective way to optimize the fundamental effects for further enhancing the electrocatalysis of a ***,to address the deficiencies associated with the commonly used dealloying methods,for example,electrochemical and sulfuric acid/nitric acid treatment,we report an acetic acid-assisted mild strategy to dealloy Cu atoms from the outer surface layers of CuPd alloy nanoparticles to achieve high-efficiency electrocatalysis for oxygen reduction and ethanol oxidation in an alkaline *** leaching of Cu atoms by acetic acid exerts an additional compressive strain effect on the surface layers and exposes more active Pd atoms,which is beneficial for boosting the catalytic performance of a dealloyed catalyst for the oxygen reduction reaction(ORR)and the ethanol oxidation reaction(EOR).In particular,for ORR,the CuPd nanoparticles with a Pd/Cu molar ratio of 2:1 after acetic dealloying show a half-wave potential of 0.912 V(***)and a mass activity of 0.213 AmgPd^(-1) at 0.9 V,respectively,while for EOR,the same dealloyed sample has a mass activity and a specific activity of 8.4 Amg^(-1) and 8.23 mA cm^(-2),respectively,much better than their dealloyed counterparts at other temperatures and commercial Pd/C as well as a Pt/C catalyst.

关键词： compressive strain effect dealloying electrocatalysis ethanol oxidation reaction oxygen reduction reaction

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Environmental memory facilitates search with home returns

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Physical Review Research 2024年第2期6卷 023255-023255页

作者： Amy Altshuler Ofek Lauber Bonomo Nicole Gorohovsky Shany Marchini Eran Rosen Ofir Tal-Friedman Shlomi Reuveni Yael Roichman The Raymond and Beverley School of Chemistry Center for Physics and Chemistry of Living Systems Department of Materials Science and Engineering The Raymond and Beverley School of Physics & Astronomy Sackler Center for Computational Molecular & Materials Science

Search processes in the natural world are often punctuated by home returns that reset the position of foraging animals, birds, and insects. Many theoretical, numerical, and experimental studies have now demonstrated that this strategy can drastically facilitate search, which could explain its prevalence. To further facilitate search, foragers also work as a group: modifying their surroundings in highly sophisticated ways, e.g., by leaving chemical scent trails that imprint the memory of previous excursions. Here, we design a controlled experiment to show that the benefit coming from such environmental memory is significant even for a single, nonintelligent searcher that is limited to simple physical interactions with its surroundings. To this end, we employ a self-propelled bristle robot that moves randomly within an arena filled with obstacles that the robot can push around. To mimic home returns, we reset the bristle robot's position at constant time intervals. We show that trails created by the robot give rise to a form of environmental memory that facilitates search by increasing the effective diffusion coefficient. Numerical simulations and theoretical estimates designed to capture the essential physics of the experiment support our conclusions and indicate that these are not limited to the particular system studied herein.

关键词： Animal behavior, social interactions & emergent phenomena Diffusion Living matter & active matter Nonequilibrium statistical mechanics Random walks Search strategy Stochastic processes Stochastic resetting

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Transition pathways in Cylinder-Gyroid interface

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Communications in computational Physics 2022年第8期32卷 810-828页

作者： Xiaomei Yao Jie Xu Lei Zhang Beijing International Center for Mathematical Research Peking UniversityBeijing 100871China LSEC&NCMIS Institute of Computational Mathematics and Scientific/Engineering Computing(ICMSEC)Academy of Mathematics and Systems Science(AMSS)Chinese Academy of SciencesBeijingChina

When two distinct ordered phases contact,the interface may exhibit rich and fascinating *** on the Cylinder-Gyroid interface system,transition pathways connecting various interface morphologies are studied armed with the Landau–Brazovskii ***,minimum energy paths are obtained by computing transition states with the saddle *** present four primary transition pathways connecting different local minima,representing four different mechanisms of the formation of the Cylinder-Gyroid *** connection of Cylinder and Gyroid can be either direct or indirect via Fddd with three different *** different displacements,each of the four pathways may have the lowest energy.

关键词： Landau-Brazovskii model Cylinder-Gyroid interface saddle dynamics transition state transition pathway

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Arc plasma-deposited Co single-atom catalysts supported on an aligned carbon nanofiber for hydrogen peroxide electrosynthesis and an electro-Fenton process

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Carbon Energy 2024年第11期6卷 234-255页

作者： Chang‐Kyu Hwang Sooyeon Kim Ki Ro Yoon Thao Thi Le Chinh V.Hoang Jae Won Choi Wenjun Zhang Sae Yane Paek Chung Hyeon Lee Ji Hyun Lee Keun Hwa Chae Sohee Jeong Seung Yong Lee Byeong-Kwon Ju Sang Hoon Kim Sang Soo Han Jong Min Kim Materials Architecturing Research Center Korea Institute of Science and Technology (KIST))seculSecrngbuk-guRepublic of Korea Department of Micro/Nano Systems Korea UniversitySeoulSeongbuk-guRepublic of Korea Computational Science Research Center Korea Institute of Science and Technology (KIST)SeculSecrngbuk-guRepublic of Korea Advanced Textile R&D Department Korea Institute of Industrial Technology (KITECH)AmsanGyeonggi-doRepublic of Korea Extreme Materials Research Center Korea Institute of Science and Technology (KIST)SeoulSeongbuk:guRepubic of Korea Nanoscience and Technology KIST School University of Science and TechnologySeoulRepublic of Korea Advanced Analysis and Data Center Korea Institute of Science and TechnologySeoulSeongbuk-guRepublic of Korea Display and Nanosensor Laboratory School of Electrical Engineering Korea UniversitySeoulSeongbuk guRepublic of Korea KHU-KIST Department of Converging Science and Technology Kyung Hee UniversitySeoulSeongbuk-guRepubic of Korea

Atomically dispersed single-atom catalysts(SACs)on carbon supports show great promise for H_(2)O_(2) electrosynthesis,but conventional wet chemistry methods using particulate carbon blacks in powder form have limited their potential as two-electron(2^(e−))oxygen reduction reaction(ORR)***,we demonstrate high-performance Co SACs supported on a free-standing aligned carbon nanofiber(CNF)using electrospinning and arc plasma deposition(APD).Based on the surface oxidation treatment of aligned CNF and precise control of the deposition amount in a dry-based APD process,we successfully form densely populated Co SACs on aligned *** experimental analyses and density functional theory calculations,we reveal that Co SAC has a Co–N_(2)–O_(2) moiety with one epoxy group,leading to excellent 2^(e−)ORR ***,the aligned CNF significantly improves mass transfer in flow cells compared to randomly oriented CNF,showing an overpotential reduction of 30 mV and a 1.3-fold improvement(84.5%)in Faradaic efficiency,and finally achieves an outstanding production rate of 15.75 mol gcat^(−1) h^(−1) at 300 mA cm^(−2).The high-performance Co SAC supported on well-aligned CNF is also applied in an electro-Fenton process,demonstrating rapid removal of methylene blue and bisphenol F due to its exceptional 2e^(−)ORR activity.

关键词： arc plasma deposition electro-Fenton flow reactor hydrogen peroxide production oxygen reduction reaction single-atom catalysts

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Towards understanding structure–property relations in materials with interpretable deep learning

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npj computational Materials 2023年第1期9卷 157-168页

作者： Tien-Sinh Vu Minh-Quyet Ha Duong-Nguyen Nguyen Viet-Cuong Nguyen Yukihiro Abe Truyen Tran Huan Tran Hiori Kino Takashi Miyake Koji Tsuda Hieu-Chi Dam Japan Advanced Institute of Science and Technology NomiIshikawaJapan HPC SYSTEMS Inc. MinatoTokyoJapan Applied Artificial Intelligence Institute Deakin UniversityGeelongVICAustralia School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGAUSA Research and Services Division of Materials Data and Integrated System National Institute for Materials ScienceTsukubaIbarakiJapan Research Center for Computational Design of Advanced Functional Materials National Institute of Advanced Industrial Science and TechnologyTsukubaIbarakiJapan Department of Computational Biology and Medical Sciences Graduate School of Frontier SciencesUniversity of TokyoKashiwa-shiChiba-kenJapan International Center for Synchrotron Radiation Innovation Smart(SRIS) Tohoku UniversityAoba-kuSendaiJapan

Deep learning(DL)models currently employed in materials research exhibit certain limitations in delivering meaningful information for interpreting predictions and comprehending the relationships between structure and material *** address these limitations,we propose an interpretable DL architecture that incorporates the attention mechanism to predict material properties and gain insights into their structure–property *** proposed architecture is evaluated using two well-known datasets(the QM9 and the Materials Project datasets),and three in-house-developed computational materials ***–test–split validations confirm that the models derived using the proposed DL architecture exhibit strong predictive capabilities,which are comparable to those of current state-of-the-art ***,comparative validations,based on first-principles calculations,indicate that the degree of attention of the atoms’local structures to the representation of the material structure is critical when interpreting structure–property relationships with respect to physical *** properties encompass molecular orbital energies and the formation energies of *** proposed architecture shows great potential in accelerating material design by predicting material properties and explicitly identifying crucial features within the corresponding structures.

关键词： properties property structure

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