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Decision support systems like computer-aided energy system analysis (ESA) are considered one of the main pillars for developing sustainable and reliable energy transformation strategies. Although today's diverse tools can already support…

Harnessing the demand-side flexibility in building and mobility sectors can help to better integrate renewable energy into power systems and reduce global CO2 emissions. Enabling this sector coupling can be achieved with advances in energy…

Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique in particular. In this study, we introduce a novel method that enhances the efficiency…

Materials Science · Physics 2024-01-26 Shuo Tao , Xuecheng Shao , Li Zhu

The complexity and unpredictability of postbuckling responses in even simple thin shells have raised great challenges to emerging technologies exploiting buckling transitions. Here we comprehensively survey the buckling landscapes to show…

Materials Science · Physics 2019-10-22 Jack Panter , Junbo Chen , Teng Zhang , Halim Kusumaatmaja

Foundation models have enormous potential in advancing Earth and climate sciences, however, current approaches may not be optimal as they focus on a few basic features of a desirable Earth and climate foundation model. Crafting the ideal…

Artificial Intelligence · Computer Science 2024-05-08 Xiao Xiang Zhu , Zhitong Xiong , Yi Wang , Adam J. Stewart , Konrad Heidler , Yuanyuan Wang , Zhenghang Yuan , Thomas Dujardin , Qingsong Xu , Yilei Shi

Technologies based on the use of hydrogen are promising for future energy requirements in a more sustainable world. Consequently, modelling fuel cells is crucial, for instance, to optimize their control to achieve excellent performance, to…

Systems and Control · Electrical Eng. & Systems 2024-10-18 Raphaël Gass , Zhongliang Li , Rachid Outbib , Samir Jemei , Daniel Hissel

In the past two decades, artificial structures known as metamaterials have been found to exhibit extraordinary material properties that enable the unprecedented manipulation of electromagnetic waves, elastic waves, molecules, and particles.…

Applied Physics · Physics 2022-11-08 Jade E. Holliman , H. Todd Schaef , B. Peter McGrail , Quin R. S. Miller

The rise of foundation models -- large, pretrained machine learning models that can be finetuned to a variety of tasks -- has revolutionized the fields of natural language processing and computer vision. In high-energy physics, the question…

High Energy Physics - Phenomenology · Physics 2026-01-12 Anna Hallin

Hydrogen's growing role in the transition towards climate-neutral energy systems necessitates structured modeling frameworks. Existing gas network models, largely developed for natural gas, fail to capture hydrogen systems distinct…

Optimization and Control · Mathematics 2025-12-03 Abdullah Shahin , Hannes Gernandt , Anton Plietzsch , Johannes Schiffer

Smart energy systems comprise multiple domains like power, thermal, control, information, and communication technology, which increases the complexity of research and development studies. This expansion also requires larger and ever so…

We present the advantages of a multiscale modelling strategy for the understanding of systems with charged interfaces. On the one hand, one can simulate a complex system at different levels, depending on the relevant length and time scales…

Chemical Physics · Physics 2018-11-26 Benjamin Rotenberg

The process of design and discovery of new materials can be significantly expedited and simplified if we can learn effectively from available data. Deep learning (DL) approaches have recently received a lot of interest for their ability to…

This paper presents a scaling study on the planning phase of a multi-energy system (MES), which is becoming increasingly prominent in the energy sector. The research aims to investigate the interactions and challenges associated with…

Computational Engineering, Finance, and Science · Computer Science 2024-10-24 Jan Soeren Schwarz , Minh Cong Pham , Quoc Tuan Tran , Kai Heussen

The high emission and low energy efficiency caused by internal combustion engines (ICE) have become unacceptable under environmental regulations and the energy crisis. As a promising alternative solution, multi-power source electric…

Machine Learning · Computer Science 2022-11-09 Jincheng Hu , Yang Lin , Liang Chu , Zhuoran Hou , Jihan Li , Jingjing Jiang , Yuanjian Zhang

The rapid advancement of machine learning and artificial intelligence (AI)-driven techniques is revolutionizing materials discovery, property prediction, and material design by minimizing human intervention and accelerating scientific…

Materials Science · Physics 2026-01-06 Dilshod Nematov , Mirabbos Hojamberdiev

The social context in relation to energy policies, energy supply, and sustainability concerns as well as advances in more energy-efficient technologies is driving a need for a change in the manufacturing sector. The main purpose of this…

Optimization and Control · Mathematics 2023-08-31 Ahmed Missaoui , Cemalettin Ozturk , Barry O'Sullivan , Michele Garraffa

Traditional design cycles for new materials and assemblies have two fundamental drawbacks. The underlying physical relationships are often too complex to be precisely calculated and described. Aside from that, many unknown uncertainties,…

Thanks to the unique advantages such as long life cycles, high power density, minimal environmental impact, and high power quality such as fast response and voltage stability, the flywheel/kinetic energy storage system (FESS) is gaining…

Systems and Control · Electrical Eng. & Systems 2022-01-10 Xiaojun Li , Alan Palazzolo

Modeling microstructure evolution in electrochemical systems is vital for understanding the mechanism of various electrochemical processes. In this work, we propose a general phase field framework that is fully variational and thus…

Materials Science · Physics 2023-12-12 Jin Zhang , Alexander F. Chadwick , Peter W. Voorhees