LAB NOTICE
- [VSI: E&B] Progress in Smart Technologies for Built Environment
- energy & buildings, JCR TOP10%[VSI: E&B] Progress in Smart Technologies for Built Environment https://www.sciencedirect.com/journal/energy-and-buildings/about/aims-and-scope Progress in Smart Technologies for Built EnvironmentSubmission deadline: 31 January 2026This virtual special issue (VSI) will cover wide spectra of contributions that will be mainly focused on strategies as well as solutions that will help to support the acceleration of the smart technologies in built environment. Considered VSI key topic is especially important from the energy transition aspect and certainly contributes to the more dynamic adaptation of buildings when considering rising demand for high performance buildings. Digitalization has entered various fields of engineering and buildings are one of the key implementation areas, where still there are specific technological challenges that should be bridged. Therefore, this VSI will highlight and present novel solutions and technological advancements in smart technologies in the built environment. Digitalization, data-driven approaches, innovative and cost-effective retrofitting policies, strategies, and measures for existing urban environments will be investigated, to enhance thermal and energy performance, even focusing on optimizing energy management, adaptive reuse of aging infrastructure, and energy transition for resilient societies. Finally, the outcomes of this VSI will be useful both for the research community as well as policymakers.The aim of this Virtual Special Issue is to collect and present innovative contributions on strategies, solutions, and technological advancements that accelerate the adoption of smart technologies in the built environment. Particular emphasis is placed on digitalization, energy performance enhancement, and the energy transition. The VSI seeks to promote data-driven approaches, effective and cost-efficient retrofitting policies, and the dynamic adaptation of buildings, ultimately supporting the development of more resilient buildings, districts, cities and societies. The outcomes are intended to provide valuable insights for the research community, professionals, and urban planners.Guest editors: Prof. Fabrizio AscioneUniversità degli Studi di Napoli Federico II, Naples, Italy Prof. Marcos Eduardo Gonzalez-TrevizoUniversidad Autónoma de Baja California, Mexicali, BCN, Mexico Prof. Tamara BajcUniversity of Belgrade, Belgrade, SerbiaManuscript submission information: Guest Editor Invitation OnlyOpen for Submission: from 27-Aug-2025 to 31-Jan-2026Submission Site: Editorial Manager®Article Type Name: "VSI: ENB_Smart Built Environment" - please select this item when you submit manuscripts onlineAll manuscripts will be peer-reviewed. Submissions will be evaluated based on originality, significance, technical quality, and clarity. Once accepted, articles will be posted online immediately and published in a journal regular issue within weeks. Articles will also be simultaneously collected in the online special issue.For any inquiries about the appropriateness of contribution topics, welcome to contact Managing Guest Editor (Prof. Fabrizio Ascione).Guide for Authors will be helpful for your future contributions. Read more: Guide for AuthorsFor more information, please visit our ScienceDirect Page: Energy and BuildingsKeywords: Smart Technologies; Decarbonization; Energy Transition; Plus Energy Buildings; Net Zero Energy Buildings; Mitigation Technologies; Climate Neutral Buildings; Digitalization; Passive Cooling; Building Retrofitting; Energy Performance; Renewables
2025-10-28
- [Desalination, Call for paper] Desalination Membranes and AI
- https://www.sciencedirect.com/special-issue/313168/desalination-membranes-and-aiDesalination Membranes and AISubmission deadline: 30 October 2025 In the quest for sustainable water treatment, the intersection of desalination membranes and artificial intelligence (AI) presents a transformative opportunity for addressing some of the most pressing water scarcity challenges facing the world today. The latest advancements in desalination membranes have been pivotal in enhancing the desalination efficiency and sustainability, especially via innovative structures, materials, and processes. AI can effectively and efficiently enhance membrane design, optimize operational efficiency, and predict maintenance needs for desalination systems.This special issue of “Desalination Membranes and AI” aims to compile a comprehensive collection of research that not only advances the field of desalination membranes but also leverages the transformative potential of AI. It seeks contributions that delve into AI-driven design and optimization of desalination membranes, AI algorithms for process control and optimization, and the use of machine learning for predictive maintenance and performance monitoring. It provides a comprehensive platform for the dissemination of breakthroughs in desalination membrane research, underscored by AI-driven methodologies.The related topics include but are not limited to:Membrane materials design (polymeric and inorganic membranes)Membrane processes (MD, ultrafiltarion, nanofiltration, reverse osmosis, forward osmosis etc.)AI applications in design, process and operation of membranesMachine learning models for predicting performance, fouling and lifespanAI approaches for smart monitoring and managementAI application in environmental footprint and energy optimizationEnergy and electronics wastewater treatment such as ion separation and recoveryNew membrane process (electrified membranes and process)Technological economics, life cycle analysis and life cycle cost analysis.Management, policy and laws for desalination and water treatmentEcological remediation and environmental sustainabilityGuest editors:Prof. Bin LinUniversity of Electronic Science and Technology of China, Chengdu, China, Email: bin@uestc.edu.cnProf. Zhanlin JiTelecommunications Research Centre, University of Limerick, Ireland, Email: zhanlin.ji@gmail.comProf. Ivan GanchevInstitute of Mathematics and Informatics—Bulgarian Academy of Sciences, Bulgaria, Email: ivan.ganchev@ul.ieProf. Yingchao DongThe Chinese University of Hong Kong, China, Email: ycdong@cuhk.edu.cnManuscript submission information:Manuscript submission deadline: 30/10/2025You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Bin Lin via bin@uestc.edu.cn.
2025-10-23
PUBLICATIONS
- Sustainable energies and machine learning: an organized review of recent applications and challenges
- Pouya Ifaei, Morteza Nazari-Heris, Amir Saman Tayerani Charmchi, Somayeh Asadi, ChangKyoo Yoo*, Sustainable energies and machine learning: an organized review of recent applications and challenges, Energy (ISSN: 0360-5442, SCI, Top 5% journal – THERMODYNAMICS), 266(1), pp.126432 (2023.3) (Ack 3개: Brain Pool Program2019H1D3A1A02071051 & NRF중견2021R1A2C2007838 & Collabo R&D of SMEs and Startups in 2022.(Project No. S3301144)
- Deep-AI soft sensor for sustainable health risk monitoring and control of fine particulate matter at sensor devoid underground spaces: A zero-shot transfer learning approach
- Shahzeb Tariq+, Jorge Loy-Benitez+, KiJeon Nam, SangYoun Kim, MinJeong Kim*, ChangKyoo Yoo*, Deep-AI soft sensor for sustainable health risk monitoring and control of fine particulate matter at sensor devoid underground spaces: A zero-shot transfer learning approach, Tunnelling and underground space (ISSN: 0886-7798, SCIE, JCR Top 10%-ENGINEERING, CIVIL, DOI), Elsevier, 131(1), pp.104843 (Ack: 2021R1A2C2007838 & Fine Dust Reduction Technology(21QPPW-B152306-03)
- Explainable multisensor fusion-based automatic reconciliation and imputation of faulty and missing data in membrane bioreactor plants for fouling alleviation and energy saving
- Abdulrahman H. Ba-Alawi, KiJeon Nam, SungKu Heo, TaeYong Woo, Hanaa Aamer, and Chang Kyoo Yoo*, Explainable multisensor fusion-based automatic reconciliation and imputation of faulty and missing data in membrane bioreactor plants for fouling alleviation and energy saving, Chemical Engineering Journal (IF>16.4, JCR TOP 3% journal/Top 1 journal-Chemical Engineering), 452(1), pp.139220 (2023.1) (Ack 3개:NRF2021R1A2C2007838, “Prospective green technology innovation project (2020003160009), SMEs and Startups in 2022 (Project No. S3301144)
