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Designing an Institutional Research Management System Framework for Higher Education 3

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Designing an Institutional Research Management System Framew...

3rd International Conference on information Management and technology, ICIMTech 2018

作者： Noerlina Elda Hiererra, Siti Saleh Abbas, Bahtiar Andro Makalew, Brilly Maya Kristin, Desi Nugraha Mursitama, Tirta David Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Mobile Application Technology Program Jakarta11480 Indonesia Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Although research activity plays a big role in institutional ranking and provides a great benefit for university lecturer, the process of managing all research activity is tedious and exhausting. In most university, management must be able to collect all hundreds of proposals and reports;not to mention they must be able to accommodate the process of reviewing every single proposal. They also need to monitor all research output in final report and make sure that all of the outputs are correctly achieved from proposed target. In addition to the problems stated, previous activities are done manually, leaving a lot of opportunity to improve and automate the process. All of the addressable opportunity for improvement are explained and explored, thus a model of the web application is created. This paper presents the design of web application used to solve persistent problem in research management, specifically in Binus University. The design methodology is divided into two phases: requirement engineering phase, and system design. Upon finishing the requirement engineering phase, system model is depicted using Unified Modeling Language, specifically: Activity Diagram, Use Case Diagram, and Conceptual Class Diagram. © 2018 IEEE.

关键词： Unified Modeling Language

Roadmap on Nonlocality in Photonic Materials and Metamaterials

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arXiv 2025年

作者： Monticone, Francesco Mortensen, N. Asger Fernández-Domínguez, Antonio I. Luo, Yu Tserkezis, Christos Khurgin, Jacob B. Shahbazyan, Tigran V. Chaves, André J. Peres, Nuno M.R. Wegner, Gino Busch, Kurt Hu, Huatian della Sala, Fabio Zhang, Pu Ciracì, Cristian Aizpurua, Javier Babaze, Antton Borisov, Andrei G. Chen, Xue-Wen Christensen, Thomas Yan, Wei Yang, Yi Hohenester, Ulrich Huber, Lorenz Wubs, Martijn de Liberato, Simone Gonçalves, P.A.D. de Abajo, F. Javier García Hess, Ortwin Tarasenko, Illya Cox, Joel D. Jelver, Line Dias, Eduardo J.C. Sánchez, Miguel Sánchez Margetis, Dionisios Gómez-Santos, Guillermo Stauber, Tobias Tretyakov, Sergei Simovski, Constantin Pakniyat, Samaneh Gómez-Díaz, J. Sebastián Bondarev, Igor V. Biehs, Svend-Age Boltasseva, Alexandra Shalaev, Vladimir M. Krasavin, Alexey V. Zayats, Anatoly V. Alù, Andrea Song, Jung-Hwan Brongersma, Mark L. Levy, Uriel Long, Olivia Y. Guo, Cheng Fan, Shanhui Bozhevolnyi, Sergey I. Overvig, Adam Prudêncio, Filipa R. Silveirinha, Mário G. Gangaraj, S. Ali Hassani Argyropoulos, Christos Huidobro, Paloma A. Galiffi, Emanuele Yang, Fan Pendry, John B. Miller, David A.B. School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States POLIMA Center for Polariton-driven Light–Matter Interactions University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark D-IAS—Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 Odense MDK-5230 Denmark Departamento de Física Teórica de la Materia Condensada Universidad Autónoma de Madrid MadridE-28049 Spain Universidad Autónoma de Madrid MadridE-28049 Spain School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of Education College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States Department of Physics Jackson State University JacksonMS39217 United States Department of Physics Aeronautics Institute of Technology SP So Jos dos Campos12228-900 Brazil Departamento de Física Universidade do Minho BragaP-4710-057 Portugal Av Mestre José Veiga Braga4715-330 Portugal Max-Born-Institut Berlin12489 Germany Humboldt-Universität zu Berlin Institut für Physik AG Theoretische Optik and Photonik Berlin12489 Germany Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Via Barsanti 14 Arnesano73010 Italy Via Monteroni Campus Unisalento Lecce73100 Italy School of physics Huazhong University of Science and Technology Luoyu Road 1037 Wuhan430074 China Donostia International Physics Center DIPC Donostia-San Sebastián20018 Spain Ikerbasque Basque Foundation for Science Bilbao48009 Spain Department of Electricity and Electronics University of the Basque Country Leioa48940 Spain Department of Applied Physics University of the Basque Country Donostia20018 Spain Université Paris-Saclay CNRS Institut des Scienc

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally made in optical material modeling. On one end, the growing interest in plasmonic, polaritonic and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces–can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In the case of metasurfaces, in particular, nonlocality engineering has become a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward–toward new scientific discoveries and technological advancements. Copyright © 2025, The Authors. All rights reserved.

关键词： Nanocrystals

The Future of Work in the Age of Automation: Proceedings of a Workshop on Norbert Wiener's 21st Century Legacy

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IEEE Transactions on Technology and Society

IEEE Transactions on technology and Society 2024年

作者： Love, Heather A. Adamson, Greg James, Mallory Lajoie, Jason Mareels, Iven Pearl, Zach Schiff, Daniel S. Schmitt, Ketra Arohi, Thirumala Buchanan, John Camarena, Stephanie Kaevats, Marten Reynolds, Jeremy Albuquerque, Pedro H. Havens, John C. Chacon-Hurtado, Davis Lahiri, Sucheta Ocal, Ayse Orchard, Alexi Rigby, Michael Sherlock, Rebecca Sundararaj, Victor Zhu, Qin University of Waterloo Department of English Language and Literature WaterlooONN2L 3G1 Canada University of Melbourne School of Population and Global Health MelbourneVIC3010 Australia Technical University of Munich Department of Science Technology and Society Munich80333 Germany Cambridge MA02140 United States Federation University Australia BallaratVIC3353 Australia York University Department of Art Media Performance and Design TorontoONM3J 1P3 Canada Purdue University Department of Political Science West LafayetteIN47907 United States Concordia University Centre for Engineering in Society Department for Schmitt MontrealQCH3G 1M8 Canada Infosys Limited Bengaluru560100 India University of Sydney Business School SydneyNSW2006 Australia Source Transitions MelbourneVIC3124 Australia IEEE City Sherpa Estonia Purdue University Department of Sociology West LafayetteIN47907 United States Aix-Marseille Univ CNRS AMSE Marseille13284 France IEEE Planet Positive2030 New YorkNY10016 United States University of Connecticut School of Civil and Environmental Engineering StorrsCT06269 United States Syracuse University School of Information Studies SyracuseNY13244 United States Yildiz Technical University Computer Engineering Department Istanbul34349 Turkey University of Notre Dame Technology and Digital Studies Program Notre DameIN46556 United States Melbourne VIC3000 Australia Virginia Tech Department of Engineering Education BlacksburgVA24061 United States

This article synthesizes the insights gained through presentations and discussions at the 2023 IEEE Workshop on Norbert Wiener in the 21st Century (21CW2023), which focused on "The Future of Work in the Age of Automation."Hosted at Purdue University, this interdisciplinary convening of technologists, social scientists, and humanists explored the impacts of automation on labor, drawing on Wiener's legacy of insights as a backdrop to examine the technologically mediated future we face in coming decades. The workshop presented a rare opportunity to reflect critically on these issues at a pivotal moment in human and technological history, and to elicit underappreciated dimensions. Areas of focus include: the qualitative and quantitative losses associated with automation and AI, the impacts automation has for questions about the meaningfulness of work, the challenges we face related to uncertainty and lack of predictability in technological advancement, and the opportunities that exist for centering human values and agency in these conversations. While acknowledging many items for concern in the context of automation in the future of work, such as the domination of economic narratives, a potential loss of qualitative texture, and the neglect of certain issues key to human identity, the authors conclude by offering optimistic visions - or calls - for redefining value and labor, preserving human agency, and embracing creative problem-solving. © 2024 IEEE.

关键词： Ethical technology

Student Sensemaking of Learning Analytics Dashboard Interventions in Higher Education

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Journal of Educational technology Systems 2019年第1期48卷 130 - 154页

作者： Carrie Klein Jaime Lester Thien Nguyen Abigail Justen Huzefa Rangwala Aditya Johri Higher Education Program George Mason University Fairfax VA USA College of Engineering George Mason University Fairfax VA USA Department of Computer Science George Mason University Fairfax VA USA Department of Information Sciences and Technology George Mason University Fairfax VA USA

DeePMD-kit v2: A software package for Deep Potential models

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

Covid-19 Series: A rule-based decision support system for analysis behavior of people while working from home

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IOP Conference Series: Materials science and Engineering 2020年第1期1007卷

作者： Henderi Rani Putri Merliasari Harco L.H. S. Warnars Sugiyatno Department of Informatics Engineering University of Raharja Indonesia Master of Information Technology University of Raharja Computer Science Department Graduate Program – Doctor of Computer Science Bina Nusantara University Indonesia Department of Informatics Bhayangkara Jakarta Raya University Indonesia

COVID-19 makes the community must carry out activities such as school, work, and worship at home. However, the long-running activities from home make people experience boredom which can lead to stress. On the other side, the entertainment obtained by the public through smartphones by reading articles by their interests can reduce boredom. This paper proposed a rules-based decision support system to help the people to make choices of their activities from home while COVID-19 e rules-based approach for make an application decision support system. Ruled base used in application to selected process through characteristics following the interests of the community. This decision support system is implemented in mobile web applications. The system can display articles based on interests by questions or statements through the front end system. The results showed that most users of the application in a happy condition while working from home.

关键词：

Warding off the plagiarism with the applications (Case study at Bina Nusantara University student and faculty member) 1

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Warding off the plagiarism with the applications (Case study...

1st International Conference on information and Communications technology, ICOIACT 2018

作者： Surjandy Suparta, Wayan Trisetyarso, Agung Kang, Chul Ho Abbas, Bahtiar Saleh Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Audit Program Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronics and Communication Engineering Kwangwoon University Korea Republic of Department of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538609545

Plagiarism in the education sector is as serious issues. In 2015 Indonesia ministry of research, technology and higher education stated to eradicate the plagiarism, and after 2 years the similar statement by Indonesia ministry of research, technology, and higher education. The plagiarism becomes the serious program by the ministry. The plagiarism in higher education happened, the faculty member or even a professor found did the plagiarism. Therefore, this paper research conducted using descriptive analysis methodology to elaborate on deep the correlation plagiarism variables. Hence, warding off the plagiarism might possible to perform using the applications. The aim of this research to find the correlation variables that might use to ward off the plagiarism in the future. The very interesting result from 15 questioners and the report shows there are several significant correlation variables of the plagiarism. © 2018 IEEE.

关键词： Intellectual property

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

Electron Acceleration in Carbon Nanotubes

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arXiv 2025年

作者： Bonţoiu, Cristian Bonatto, Alexandre Apsimon, Öznur Bandiera, Laura Cavoto, Gianluca Drebot, Illya Gatti, Giancarlo Giner-Navarro, Jorge Lei, Bifeng Martín-Luna, Pablo Rago, Ilaria Pérez, Juan Rodríguez Nunes, Bruno Silveira Sytov, Alexei Valagiannopoulos, Costas Welsch, Carsten P. Xia, Guoxing Resta-López, Javier Department of Physics University of Liverpool Oxford Street LiverpoolL69 7ZE United Kingdom Graduate Program in Information Technology and Healthcare Management the Beam Physics Group Federal University of Health Sciences of Porto Alegre RS Porto Alegre90050-170 Brazil Department of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Cockroft Institute Keckwick Lane Daresbury WarringtonWA4 4AD United Kingdom INFN Sezione di Ferrara Via Saragat 1 Ferrara44122 Italy Dipartimento di Fisica Sapienza Università di Roma Piazzale Aldo Moro 2 Roma00185 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Rome00185 Italy INFN Sezione di Milano Via G. Celoria 16 Milano20133 Italy Centro de Láseres Pulsados Building M5 Science Park Calle Adaja 8 Salamanca Villamayor37185 Spain Universidad de Valencia Paterna46071 Spain Universidad de Valencia CSIC Paterna46980 Spain Nuclear and Energy Research Institute IPEN–CNEN SP São Paulo Brazil National Technical University of Athens School of Electrical and Computer Engineering Zografou157 73 Greece Departamento de Física Aplicada y Electromagnetismo Universidad de Valencia Burjassot46100 Spain

Laser wakefield acceleration (LWFA) may achieve TeV/m gradients using high-density solid-state plasmas as accelerating media. However, the application of bulk solid materials requires attosecond laser pulses, such as X-ray lasers, to drive wakefields at these high densities. Additionally, the short wakefield wavelengths associated with solid-state plasmas greatly limit the accelerating length. An alternative approach employs 2D carbon-based nanomaterials, like graphene or carbon nanotubes (CNTs), configured into structured targets. These nanostructures are designed with voids or low-density regions to effectively reduce the overall plasma density. This reduction enables the use of longer-wavelength lasers and also extends the plasma wavelength and the acceleration length. In this study, we present, to our knowledge, the first numerical demonstration of electron acceleration via self-injection into a wakefield bubble driven by an infrared laser pulse in structured CNT targets, similar to the behavior observed in gaseous plasmas for LWFA in the nonlinear (or bubble) regime. Using the PIConGPU code, bundles of CNTs are modeled in a 3D geometry as 25 nm-thick carbon tubes with an initial density of 1022 cm−3. The carbon plasma is ionized by a three-cycle, 800 nm wavelength laser pulse with a peak intensity of 1021 W cm−2, achieving an effective plasma density of 1020 cm−3. The same laser also drives the wakefield bubble, responsible for the electron self-injection and acceleration. Simulation results indicate that fs-long electron bunches with hundreds of pC charge can be self-injected and accelerated at gradients exceeding 1 TeV/m. Both charge and accelerating gradient figures are unprecedented when compared with LWFA in gaseous plasma. © 2025, CC BY-NC-ND.

关键词： X ray lasers