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Microporous polyimine membranes for efficient separation of liquid hydrocarbon mixtures

science (New York, N.Y.) 2025年第6749期388卷 839-844页

作者： Tae Hoon Lee Marcel Balcik Zain Ali Taigyu Joo Matthew P Rivera Ingo Pinnau Zachary P Smith Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA. Department of Future Energy Engineering Sungkyunkwan University Suwon Republic of Korea. Advanced Membranes and Porous Materials Center Chemical Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia. Osmoflo Water Management Pty Ltd. Burton SA Australia.

Interfacial polymerization has been an industrial standard for preparing desalination membranes. Extending the same concept to molecular separation of organic solvents would be a key enabler for the decarbonization of the chemical and petrochemical industries through energy-efficient crude or biocrude oil fractionation. Here, we report a molecular engineering approach based on acid-catalyzed interfacial polymerization for efficient hydrocarbon separation. The design strategies include (i) changing the linkage from amide to imine and (ii) subsequent introduction of shape-persistent units such as triptycene and spirobifluorene. The prepared polyimine membranes exhibit ultrahigh microporosity and enhanced swelling and plasticization resistance compared with conventional polyamide counterparts. These membranes, which feature fast and selective transport of hydrocarbons, including multicomponent and industrially relevant mixtures, outperform commercial and state-of-the-art benchmark membranes.

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EEG-based Assessment of Human Endurance: Association between Endurance and Brain-wave Activity 5

EEG-based Assessment of Human Endurance: Association between...

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5th IEEE International Conference on Artificial Intelligence and Big Data, ICAIBD 2022

作者： Zhang, Haipeng Zhang, Changshui Wang, Yulu Zhang, Keying Liu, Ruidong Fang, Lei Wu, Fangfang Cao, Chunmei Tsinghua University Institute for Artificial Intelligence Departmetn of Automation Beijing China Tsinghua University Division of Sports Science and Physical Education Beijing China Tsinghua University Department of Mechanical Engineering Beijing China

ISBN: (纸本)9781665499132

Endurance is a fundamental human potential that researchers have focused on widely. Studies on athletes have shown that human endurance is linked to brain signals. To improve modern assessment and intervention systems for human endurance, it is necessary to identify certain cortical brain-signal activity reflecting endurance potential. This study proposes a deep learning-based model that automatically extracts features from electroencephalograms (EEGs) to predict human endurance performance and identify the frequency ranges and brain regions reflecting key endurance characteristics in running athletes during task and resting states. The EEGs of 50 individuals (27 running athletes and 23 non-athletes) were acquired during resting and bicycle-riding states. The signals were preprocessed, transformed into spectrograms, and fed into a convolutional neural network (CNN) for feature extraction and inter-individual classification. The results showed that when applying this model to the data of three different states, one riding and two resting, the average accuracies were 82.0%, 82.0%, and 74.7% respectively, outperforming the baseline methods in all cases. Furthermore, the features were visualized by class activation mapping (CAM) to identify the frequencies and brain regions associated with key endurance characteristics. Accuracies were improved by selecting the featured regions, but were significantly compromised if masked, thereby confirming the reliability of the extracted features. It is indicated that high beta (20-30 Hz) and gamma (31-40 Hz) activities in the parietal and occipital regions were most related to endurance characteristics during tasks, while gamma activities in the premotor and primary motor cortex differed between athletes and non-athletes at rest. The results were further confirmed using Wilcoxon signed-rank tests. © 2022 IEEE.

关键词： Deep learning

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Selectivity of CO_(2)reduction reaction to CO on the graphitic edge active sites of Fe-single-atom and dual-atom catalysts:A combined DFT and microkinetic modeling

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Carbon Resources Conversion 2024年第1期7卷 21-31页

作者： Ahmad Nuruddin Adhitya Gandaryus Saputro Arifin Luthfi Maulana Febdian Rusydi Fiki Taufik Akbar Hadi Teguh Yudistira Hermawan Kresno Dipojono Advanced Functional Materials Research Group Faculty of Industrial TechnologyInstitut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Research Center for Nanosciences and Nanotechnology Institut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Research Center for Quantum Engineering Design Department of PhysicsFaculty of Science and TechnologyUniversitas AirlanggaSurabaya 60115Indonesia Theoretical High Energy Physics Research Division Faculty of Mathematics and Natural SciencesInstitut Teknologi BandungJl.Ganesha No.10Bandung 40132Indonesia Mechanical Engineering Study Program Institut Teknologi Sumatera(ITERA)South LampungLampungIndonesia Department of Materials Science and Engineering University of CaliforniaBerkeleyBerkeleyCA 94720United States

We study the carbon dioxide reduction reaction(CO_(2)RR)activity and selectivity of Fe single-atom catalyst(Fe-SAC)and Fe dual-atom catalyst(Fe-DAC)active sites at the interior of graphene and the edges of graphitic nanopore by using a combination of DFT calculations and microkinetic *** trend of limiting potentials for CO_(2)RR to produce CO can be described by using either the adsorption energy of COOH,CO,or their ***_(2)RR process with reasonable reaction rates can be achieved only on the active site configurations with weak tendencies toward CO *** efficiency of CO_(2)RR on a catalyst depends on its ability to suppress the parasitic hydrogen evolution reaction(HER),which is directly related to the behavior of H adsorption on the catalyst’s active *** find that the edges of the graphitic nanopore can act as potential adsorption sites for an H atom,and in some cases,the edge site can bind the H atom much stronger than the main Fe *** linear scaling between CO and H adsorptions is broken if this condition is *** condition also allows some edge active site configurations to have their CO_(2)RR limiting potential lower than the HER process favoring CO production over H2 production.

关键词： CO_(2)RR FexNy active site Fe-SAC Fe-DAC Graphitic edges DFT Microkinetic

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Biomass-based biomimetic-oriented Janus nanoarchitecture for efficient heavy-metal enrichment and interfacial solar water sanitation

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Interdisciplinary Materials 2022年第4期1卷 537-547页

作者： Hao-Yu Zhao Wei-Xu Dong Yu Deng Li-Feng Chen Chen-Fan Zhao Chuan-Ling Zhang Jie Zhou Yi-Fan Qu Yan-Song Li Dong-Jun Li Shu-Hong Yu Department of Chemistry Anhui Engineering Laboratory of Biomimetic MaterialsHefei National Research Center for Physical Sciences at the MicroscaleHefei Comprehensive National Science CenterDivision of Nanomaterials and ChemistryInstitute of EnergyInstitute of Biomimetic Materials and ChemistryUniversity of Science and Technology of ChinaHefeiAnhuiPR China CAS Key Laboratory of Mechanical Behavior and Design of Materials(LMBD) Department of Thermal Science and Energy EngineeringUniversity of Science and Technology of ChinaHefeiAnhuiPR China School of Chemistry and Chemical Engineering Hefei University of TechnologyHefeiAnhuiPR China

Interfacial solar steam generation(ISSG),involving the use of solar energy to evaporate water at the water-to-vapor interface,has presented prospects for the desalination and purification of water due to high energy conversion efficiency and low-cost freshwater ***,inspired by the aligned nanostructure of plants for efficiently transporting nutrient ions,we optimally design and construct a biomass-based Janus architecture evaporator with an oriented nanostructure for ISSG,using the ice template method,followed by biomimetic mineralization with the resource-abundant and low-cost biomass of the carboxymethyl cellulose and sodium alginate as the raw *** advantage of the oriented nanostructure allowing efficient transportation of water and coordination capacity of sodium alginate for effective enrichment of heavy-metal ions,the biomass-based Janus architecture shows much lower thermal conductivity and an ultrahigh steam regeneration rate of 2.3 kg m−2 h−1,considerably surpassing those of previously reported oriented biomass-based ***,the biomass precursor materials are used for this Janus evaporator,guaranteeing minimum impact on the water ecology and environment during the regeneration process of clean drinking *** study presents an efficient,green,and sustainable pathway for ISSG to effectively achieve heavy-metal-free drinking water.

关键词： biomass-based nanomaterials biomimetic-oriented nanostructure heavy-metal enrichment interfacial solar water sanitation Janus nanoarchitecture

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Detection of magnetohydrodynamic waves by using machine learning

arXiv

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arXiv 2022年

作者： Chen, Fang Samtaney, Ravi Mechanical Engineering Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

Nonlinear wave interactions, such as shock refraction at an inclined density interface, in magnetohydrodynamic (MHD) lead to a plethora of wave patterns with myriad wave types. Identification of different types of MHD waves is an important and challenging task in such complex wave patterns. Moreover, flowing to the multiplicity of solutions and their admissibility for different systems, especially for intermediate-type MHD shock waves, the identification of MHD wave types is complicated if one solely relies on the Rankine-Hugoniot jump conditions. MHD wave detection is further exacerbated by unphysical smearing of discontinuous shock waves in numerical simulations. We present two MHD wave detection methods based on a convolutional neural network (CNN) which enables the classification of waves and identification of their locations. The first method separates the output into a regression (location prediction) and a classification problem assuming the number of waves for each training data is fixed. In the second method, the number of waves is not specified a priori and the algorithm, using only regression, predicts the waves' locations and classifies its types. We use one-dimensional (1D) input data (density, velocity and magnetic fields) to train the two models that successfully reproduce a complex two-dimensional (2D) MHD shock refraction structure. The first fixed output model efficiently provides high precision and recall, the accuracy of total neural network achieved is up to 0.99, and the classification accuracy of some waves approaches unity. The second detection model has a relatively lower performance, with more sensitivity to the setting of parameters, such as the number of grid cells Ngridand the thresholds of confidence score and class probability, etc. The accuracy of the detection model attains more than 0.9 and a high F1score of more than 0:95. The proposed two methods demonstrate very strong potential to be applied for MHD wave detection in some comple

关键词： Magnetohydrodynamics

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Characterising Bicyclist Posture in Various Bicycle Types for Safety Evaluation

Characterising Bicyclist Posture in Various Bicycle Types fo...

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2024 International Research Council on the Biomechanics of Injury, IRCOBI 2024

作者： Oikonomou, Maria Iraeus, Johan Lioras, Athanasios Mylonas, Vasileios Rorris, Lambros Mihailidis, Athanassios School of Mechanical Engineering Aristotle University of Thessaloniki Greece Division of Vehicle Safety Chalmers University of Technology Gothenburg Sweden Software Research and DevelopmentDepartment BETA CAE Systems SA Thessaloniki Greece School of Physical Education and Sport Science Aristotle University of Thessaloniki Greece Software Research and Development Department BETA CAESystems International Luzern Switzerland

The growing use of bicycles and the increasing frequency of accidents underscore the need for an in-depth investigation into bicyclists' kinematics and injuries. This study aims to collect and analyse bicyclists' posture data across three bicycle types to facilitate the positioning of Human Body Model (HBM) for implementation in crash simulations. Ten male volunteers, with characteristics similar to the 50th percentile male, were measured while riding in the city, racing, and mountain bikes. Characteristic angles of the volunteers' postures were calculated for each bicycle and for pedal angles ranging from 0 degrees to 360 degrees, with a 30-degree increment. This approach allowed for the examination of posture variations throughout the pedaling cycle and across different bicycle types. The findings indicate that, apart from the characteristic angles of the lower extremities, the pelvis and spine were most influenced through the pedaling for each bike. Notably, the differences in characteristic angles across the three bikes were greater in the pelvis, spine region, and upper extremities compared to those occurring in the lower extremities. The posture information obtained from this study can guide the future positioning of HBMs, thereby enhancing the accuracy of crash simulations. © 2024 International Research Council on the Biomechanics of Injury. All rights reserved.

关键词： Bicycles

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Investigations into the linear coupling between symmetric and anti-symmetric modes of v-shaped mems resonators under electrostatic perturbation

Investigations into the linear coupling between symmetric an...

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ASME 2021 International mechanical engineering Congress and Exposition, IMECE 2021

作者： Alcheikh, Nouha Ouakad, Hassen M. Mbarek, Sofiane Ben Younis, Mohammad I. Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Mechanical & Industrial Engineering Department Sultan Qaboos University AlKhoudh Muscat123 Oman

ISBN: (纸本)9780791885611

In this paper, we investigate experimentally and theoretically the linear coupling between the first two symmetric and anti-symmetric modes of an electrothermally and electrostatically actuated in-plane V-shaped micro-beam. The micro-beam is fabricated from highly doped silicon and is sandwiched between four electrodes to electrostatically activate both modes of vibrations. When tuning the electrothermal voltage, the natural frequencies of the two modes approach each other until they cross. Under electrostatic actuation, it is shown experimentally that the system undergoes a transition between modes crossing to veering. In addition, an analytical study is presented based on a Galerkin-based reduced-order model of a nonlinear Euler–Bernoulli shallow arch beam equation. The analytical results are compared to experimental data showing excellent agreement. Copyright © 2021 by ASME

关键词： Electrostatic actuators

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Implementation of contact line motion based on the phase-field lattice Boltzmann method

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physical Review E 2024年第4期109卷 045307-045307页

作者： Long Ju Zhaoli Guo Bicheng Yan Shuyu Sun Computational Transport Phenomena Laboratory (CTPL) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Kingdom of Saudi Arabia Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan 430074 China Energy Resource and Petroleum Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Kingdom of Saudi Arabia

This paper proposes a strategy to implement the free-energy-based wetting boundary condition within the phase-field lattice Boltzmann method. The greatest advantage of the proposed method is that the implementation of contact line motion can be significantly simplified while still maintaining good accuracy. For this purpose, the liquid-solid free energy is treated as a part of the chemical potential instead of the boundary condition, thus avoiding complicated interpolations with irregular geometries. Several numerical testing cases, including droplet spreading processes on the idea flat, inclined, and curved boundaries, are conducted, and the results demonstrate that the proposed method has good ability and satisfactory accuracy to simulate contact line motions.

关键词： Contact line dynamics Wetting Lattice-Boltzmann methods

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Localization of a Crack in Moving Cylindrical Ferromagnetic Rods by Measuring the Fourier Coefficients of the Leakage Magnetic Flux

Localization of a Crack in Moving Cylindrical Ferromagnetic ...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Kanta Shiku Masafumi Kuromizu Yuji Gotoh Takaaki Nara Graduate School of Information Science and Technology The University of Tokyo bunkyo-ku Japan Division of Materials Science and Production Engineering Graduate School of Engineering Oita University Oita Japan Intelligent Mechanical Systems Program Faculty of Science and Technology Oita University Oita Japan

ISBN: (数字)9798350362213

ISBN: (纸本)9798350362220

Electromagnetic nondestructive inspection for high-speed moving ferromagnetic materials is necessary for manufacturing efficiency. In this paper, we present a novel leakage magnetic flux (LMF) method to estimate the crack position in a moving cylindrical ferromagnetic rod. The method directly measures the first-order Fourier coefficients of the LMF moving with the crack by using only two coils with DC excitation. The location of a crack is estimated by the proposed method, as demonstrated for an S45C cylindrical rod.

关键词： Location awareness Coils Magnetic flux Inspection Ferromagnetic materials Manufacturing Electromagnetics

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MeshDMP: Motion Planning on Discrete Manifolds using Dynamic Movement Primitives

arXiv

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arXiv 2024年

作者： Vedove, Matteo Dalle Abu-Dakka, Fares J. Palopoli, Luigi Fontanelli, Daniele Saveriano, Matteo Department of Industrial Engineering Università di Trento Trento Italy DRIM Italy Mechanical Engineering Program Division of Engineering New York University Abu Dhabi Abu Dhabi United Arab Emirates Department of Information Engineering and Computer Science Università di Trento Trento Italy

An open problem in industrial automation is to reliably perform tasks requiring in-contact movements with complex workpieces, as current solutions lack the ability to seamlessly adapt to the workpiece geometry. In this paper, we propose a Learning from Demonstration approach that allows a robot manipulator to learn and generalise motions across complex surfaces by leveraging differential mathematical operators on discrete manifolds to embed information on the geometry of the workpiece extracted from triangular meshes, and extend the Dynamic Movement Primitives (DMPs) framework to generate motions on the mesh surfaces. We also propose an effective strategy to adapt the motion to different surfaces, by introducing an isometric transformation of the learned forcing term. The resulting approach, namely MeshDMP, is evaluated both in simulation and real experiments, showing promising results in typical industrial automation tasks like car surface polishing. © 2024, CC BY-SA.

关键词： Mesh generation

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