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Non-Markovian quantum dynamics in physical systems: description and control
This collection aims to gather the latest approaches to characterize and quantify quantum non-Markovianity and to exploit it in practical applications
Image: © [M] your_photo / Getty Images / iStockOpen for submissions -
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Micro- and Nano-optomechanical sensors: principles and applications
In this cross-journal collection between Communications Physics, Nature Communications and Scientific Reports, we invite submissions focused on the design principles and applications of micro- and nano-optomechanical sensors.
Image: © [M] xiaoliangge / Stock.adobe.comOpen for submissions -
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The superconducting diode effect
This collection aims to showcase the fundamental physics & current theoretical understanding of the superconducting diode effect and other nonreciprocal phenomena in superconductors.
Image: © tcareob72 / Getty Images / iStockOpen for submissions -
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Swarm intelligence - Collective motions from biology to robotic
This cross-journal Collection between Nature Communications, Communications Engineering, Communications Physics, and Scientific Reports brings together the advances in swarm intelligence.
Image: © [M] Duncan Shaw / Science Photo LibraryOpen for submissions -
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Superconductivity in nickelates
This cross-journal Collection between Nature Communications, Communications Physics and Scientific Reports welcomes submissions focusing on superconductivity in nickelate compounds.
Image: © [M] jcrosemann / Getty Images / iStockOpen for submissions -
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Neuromorphic Hardware and Computing 2024
An interdisciplinary approach is being taken to address the challenge of creating more efficient and intelligent computing systems that can perform diverse tasks, to design hardware with increasing complexity from single device to system architecture level, and to develop new theories and brain-inspired algorithms for future computing. In this cross-journal collection, we aim to bring together cutting-edge research of neuromorphic architecture and hardware, computing algorithms and theories, and the related innovative applications.
Image: Featured image of Jiang et al., Nat Commun 14, 1344 (2023)Open for submissions -
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Non-equilibrium dynamics of biological droplets: from Phase Separation to Self-Assembly
This cross-journal Collection between Communications Physics, Nature Communications, and Scientific Reports welcomes contributions where the description of the dynamics of biological droplets advances our understanding of specific biological processes, as well as more general contributions identifying common mechanisms and generating novel biophysical insight across the realm of biological droplets.
Image: © [M] Justlight / Generated with AI / Stock.adobe.comOpen for submissions -
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Topological physics of moiré matter
This cross-journal Collection between Nature Communications, Communications Physics and Scientific Reports combines the latest research on the topological physics of moiré heterostructures.
Image: © [M] Sashkin / stock.adobe.comOpen for submissions -
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Complexity and dynamics in ecological systems
This cross-journal Collection between Communications Physics, Communications Earth & Environment, and Scientific Reports aims at showcasing the methodological advances in treating the complexity of ecological systems, as well as the application of already established methods to generate new insight in the dynamics and response of ecological networks.
Image: © [M] Kanisorn / Generated with AI / Stock.adobe.comOpen for submissions -
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Tandem Perovskite Photovoltaics
This cross-journal Collection between Nature Communications, Communications Materials, Communications Physics and Scientific Reports brings together the latest research and development in perovskite-based tandem solar cells.
Image: © [M] JONGHO SHIN / Getty Images / iStockOpen for submissions -
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AI and machine learning in the design and synthesis of crystalline functional materials
This collection hosted by Communications Physics, Nature Communications and Scientific Reports aims to highlight recent advances and applications of AI and machine learning methods in solid-state materials science with a focus on crystalline systems.
Image: © [M] ismagilov / Getty Images / iStockOpen for submissions