Nanoscience News (<front>)

Laser micropatterning is presented as a promising technology in the search for autonomous dew water harvesting materials. Laser-grooved metallic surfaces achieve simultaneously high infrared emissivity and superhydrophilicity, which gives them self-cooling properties under atmospheric radiative deficit and the ability to condense water in an efficient filmwise fashion. An autonomous dew water harvesting system based on those surfaces yields remarkable results.

Abstract

The present work explores a unique yet unexplored synergy between the properties of laser micropatterned metallic surfaces and the requirements for an autonomous dew water harvesting candidate material. Laser-patterned aluminum surfaces achieved simultaneously high infrared emissivity (up to 0.95 in the atmospheric window) and superhydrophilic wettability (water contact angle of 0°), key properties enabling passive radiative cooling and filmwise condensation dynamics respectively. The generation of micrometric-sized grooves during laser processing plays a fundamental role in both properties, as they provide a broadband enhancement of the emissivity based on multiscale topographies and oxide layers, while limiting the growth of the water film during condensation through strong capillary wicking forces. As a result, the patterned aluminum surfaces display self-cooling capacities under radiative deficit conditions as well as low water retention levels (three times lower than the untreated dropwise condensation counterparts). The promising results obtained lead to the construction and evaluation of a real size outdoors autonomous dew water harvesting system based on those surfaces, demonstrating the scalability of the technology. A 70% improvement in the collected dew water in comparison to a state-of-the-art reference material is consistently measured during 1-year outdoor study, proving the robustness of the surfaces and their performance.

Is There Hope for the Climate?

Abstract Stay tuned!

Bio

Srinivasan Keshav is the Robert Sansom Professor of Computer Science at the University of Cambridge, focusing on the intersection of computer science and sustainability. He earned his PhD from UC Berkeley and has held roles at Bell Labs, Cornell University, and the University of Waterloo. A Fellow of the Royal Society of Canada, ACM , and IEEE , Keshav is recognized for his contributions to networking and sustainability. His research includes innovations in energy systems, carbon footprint reduction, and forest conservation using remote sensing. Keshav emphasizes practical applications of computer science to global challenges, fostering collaborative solutions in smart grids and biodiversity conservation.

• Speaker: Srinivasan Keshav, University of Cambridge
• Thursday 01 May 2025, 13:00-14:00
• Venue: GS15, William Gates Building. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon .
• Series: Energy and Environment Group, Department of CST; organiser: lyr24.

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Chiral flower-like aluminum oxyhydroxide (AlOOH) supraparticles (SPs) are fabricated as an adjuvant, indicating that that L-SPs enters dendritic cells (DCs) via Toll-like receptor 2 (TLR2) to enhance NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome activation.

Abstract

Aluminum-based adjuvants dominate global vaccine formulations owing to their proven efficacy in humoral immunity induction. However, their inherent limitations in activating cellular immunity pose critical challenges for vaccine development. In this study, chiral flower-like aluminum oxyhydroxide (AlOOH) supraparticles (SPs) are synthesized via a one-pot hydrothermal method using cysteine (Cys) enantiomers as chiral ligands, achieving a g-factor of 0.004. L-AlOOH SPs (L-SPs) demonstrate significantly greater enhancement in dendritic cell (DC) maturation and antigen cross-presentation efficiency compared to D-AlOOH SPs (D-SPs), indicating its potential as an adjuvant. Mechanistic studies reveal that L-SPs enter DCs via Toll-like receptor 2 (TLR2), thereby enhancing NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome activation. In vivo experiments show that L-SPs generate 21.59-fold higher OVA-specific antibody titers than commercial aluminum adjuvants. Further studies show that L-SPs, after mixed with H9N2 virus proteins, enhance influenza virus antibody titers by 15.28-fold, with sustained protection, confirming its translational potential. This study demonstrates the performance of chiral AlOOH SPs to simultaneously amplify humoral and cellular immunological responses, entering it as a promising next-generation adjuvant for cancer immunotherapy and pandemic preparedness.

CuInS₂/ZnS quantum dots (nCIS QDs) are developed via template-assisted cation exchange, enabling photon upconversion (UC) with NIR-I emission, a large Stokes shift (≈650 meV), and high PLQY (≈0.95). The QDs are incorporated into a 3D-printed polymer matrix, forming a scaffold with strong optical contrast under UC imaging. This system enables high-contrast NIR imaging for surgical guidance, even under interference layers.

Abstract

A facile synthesis and application of photon upconversion (UC) probes, CuInS₂/ZnS quantum dots (nCIS QDs) is presented, which exhibits near-infrared (NIR) spectral emission. The nCIS QDs are synthesized via a template-assisted cation-exchange reaction during a heating process, resulting in NIR-I emission with a large Stokes shift (≈650 meV) and a high photoluminescence quantum yield (PLQY, ≈0.95). This behavior is attributed to a template-assisted cation-exchange mechanism that produces a wurtzite crystal structure and deep defect states, leading to a relatively long fluorescence lifetime (≈5 µs). The quantum confinement effect allows for the emission of light at different wavelengths by adjusting the size of the nanocrystals. Moreover, their deep defect states facilitate photon UC via a self-trapping triplet-triplet annihilation mechanism. The promising potential of the nCIS QDs is explored in UC imaging, demonstrating high-contrast NIR imaging under IR vision modules, even in the presence of interference layers. It suggests potential applications in surgical guidance and future biomedical imaging.

Spacetime Singularities and Black Holes

After a brief introduction to Einstein’s theory of general relativity and its most profound prediction of black holes, I will focus on spacetime singularities, i.e., regions where general relativity breaks down and must be replaced by a quantum theory of gravity.  I first discuss singularities inside black holes. This is the usual case and is an old story, but there have been some recent developments. I will next describe some new results which show that some black holes have singularities on their surface. Finally, I will discuss the possibility of singularities outside black holes.

• Speaker: Professor Gary Horowitz - University of California, Santa Barbara
• Wednesday 14 May 2025, 16:00-17:00
• Venue: MR3.
• Series: Theoretical Physics Colloquium; organiser: Amanda Stagg.

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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE01165E, PaperJunjie Zhang, Xiaopeng Duan, Xiaoming Li, Guangkuo Dai, Jiawei Deng, Xunchang Wang, Jiawei Qiao, Hanzhi Wu, Liming Liu, Haodong Huang, Sha Liu, Jun Yan, Huotian Zhang, Xiao-Tao Hao, Renqiang Yang, Feng Gao, Yanming Sun
Minimizing energy loss has been identified as an effective approach to achieve further efficiency breakthroughs in organic solar cells (OSCs), and the main loss channel can be attributed to non-radiative...
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Nature Nanotechnology, Published online: 16 April 2025; doi:10.1038/s41565-025-01905-4

Caesium cations promote the coagulation of 2D and 3D perovskite colloids, synchronizing their nucleation kinetics and enabling the formation of homogeneous 2D/3D heterostructured lead-free photovoltaics with a certified power conversion efficiency of 16.65%.

Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D4EE04699D, PaperJunjie Yang, Jianyu Li, Yuehao Gu, Rongfeng Tang, Lei Huang, Zhiyuan Cai, Bo Che, Qi Zhao, Shuwei Sheng, Hong Wang, Changfei Zhu, Tao Chen
Environmentally friendly Sb2(S,Se)3 with excellent optoelectronic properties is considered to be a promising light-harvesting material, which can be applied to highly efficient semitransparent solar cells when well coupled with a...
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Cambridge MedAI Seminar - April 2025

Sign up on Eventbrite: https://medai_april2025.eventbrite.co.uk

Join us for the Cambridge AI in Medicine Seminar Series, hosted by the Cancer Research UK Cambridge Centre and the Department of Radiology at Addenbrooke’s. This series brings together leading experts to explore cutting-edge AI applications in healthcare—from disease diagnosis to drug discovery. It’s a unique opportunity for researchers, practitioners, and students to stay at the forefront of AI innovations and engage in discussions shaping the future of AI in healthcare.

This month’s seminar will be held on Friday 25 April 2025, 12-1pm at the Jeffrey Cheah Biomedical Centre (Main Lecture Theatre), University of Cambridge and streamed online via Zoom. A light lunch from Aromi will be served from 11:45. The event will feature the following talks:

Unlocking Hidden Potential: Federated Machine Learning on Blood Count Data Enables Accurate Iron Deficiency Detection in Blood Donors – Daniel Kreuter, PhD Student, Department of Applied Mathematics and Theoretical Physics, University of Cambridge

Daniel is a PhD student in the BloodCounts! project, focusing on building algorithms for advanced full blood count analysis to extract additional clinical information from the world’s most common medical test. His research aims to improve healthcare decision-making through more efficient use of existing data. He is in his final year and is supervised by Prof Carola-Bibiane Schönlieb from the Applied Mathematics department and Prof Willem Ouwehand from the department of Haematology. Before coming to Cambridge, Daniel studied physics at the Technische Universität Darmstadt in Germany. His Master’s thesis project focused on replacing costly laser-plasma interaction simulations with a much faster neural network model, reducing computation time from 4 hours to a few milliseconds.

Abstract: The full blood count is the world’s most common medical laboratory test, with 3.6 billion tests performed annually worldwide. Despite this ubiquity, the rich single-cell flow cytometry data generated by haematology analysers to calculate standard parameters like haemoglobin and cell counts is routinely discarded. Our research demonstrates how AI models can extract this hidden value, transforming a routine test into a powerful screening tool for iron deficiency in blood donors—with no additional testing required. Iron deficiency remains a major challenge in blood donation programs, affecting donor health and donation efficiency. By applying advanced machine learning to previously unused data dimensions within standard blood counts, we achieve significantly improved detection accuracy compared to conventional parameters. Furthermore, we show that federated learning enables this approach to scale and generalise across multiple centres while preserving data privacy. This work exemplifies how AI can enhance existing medical infrastructure, extracting new clinical value from already-collected data to improve donor health.

Reconstructing extremely low dose CT images using machine learning – Dr Ander Biguri, Senior Research Associate, Department of Applied Mathematics and Theoretical Physics, University of Cambridge

Ander Biguri received his Ph.D. in Electrical Engineering from the University of Bath in 2018, for his work on 4D Computed Tomography for radiotherapy. Since, he has held research positions at University of Southampton, University College London and lastly University of Cambridge. His research lies in the intersection of inverse problems and their applications in real-case scenarios, such as Positron Emission Tomography or various computed tomography modalities. He is best known for the development of the TIGRE toolbox for applied tomography applications.

Abstract: ML models can be used to denoise medical images, however when doing this we don’t use information from the measurements. You can instead add machine learning to the image formation/reconstruction process, ensuring high quality images that still match the measured data from medical scanners. In this talk we will briefly see different ways of adding machine learning to these mathematical processes and discuss the challenges still needed to be tackled to make the application of such methods a clinical reality.

This is a hybrid event so you can also join via Zoom:

https://zoom.us/j/99050467573?pwd=UE5OdFdTSFdZeUtIcU1DbXpmdlNGZz09

Meeting ID: 990 5046 7573 and Passcode: 617729

We look forward to your participation! If you are interested in getting involved and presenting your work, please email Ines Machado at im549@cam.ac.uk

For more information about this seminar series, see: https://www.integratedcancermedicine.org/research/cambridge-medai-seminar-series/

• Speaker: Daniel Kreuter and Dr Ander Biguri
• Friday 25 April 2025, 11:45-13:00
• Venue: Jeffrey Cheah Biomedical Centre (Main Lecture Theatre), University of Cambridge.
• Series: Cambridge MedAI Seminar Series; organiser: Hannah Clayton.

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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE00101C, PaperJunwei Dong, Yinfeng Li, Chentong Liao, Xiaopeng Xu, Liyang Yu, Ruipeng Li, Qiang Peng
Organic solar cells (OSCs) have shown promise with power conversion efficiencies (PCEs) exceeding 20%, but their performance still lags behind silicon-based and hybrid perovskite solar cells. A critical limitation is...
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Energy Environ. Sci., 2025, Advance Article
DOI: 10.1039/D5EE00048C, Communication Open Access &nbsp This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Ramchandra Gawas, Douglas I. Kushner, Xiong Peng, Rangachary Mukundan
This work employs online gas chromatography and hydrogen oxidation current measurements for accurate quantification of the hydrogen crossover rates in proton exchange membrane water electrolyzers operating at high differential pressure.
To cite this article before page numbers are assigned, use the DOI form of citation above.
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This review explores the integration of responsive materials and soft robotic actuators with implantable electronics to address key challenges in bioelectronic medicine. By enabling shape actuation, these technologies improve deployment, adaptability, and accuracy in minimally invasive procedures. The review discusses actuation mechanisms, device designs, and future opportunities for intelligent, responsive implants with enhanced therapeutic and diagnostic capabilities.

Abstract

Bioelectronic medicine uses implantable electronic devices to interface with electrically active tissues and transform the way disease is diagnosed and treated. One of the biggest challenges is the development of minimally invasive devices that can be deployed to patients at scale. Responsive materials and soft robotic actuators offer unique opportunities to make bioelectronic devices with shape actuation, promising to address the limitations of existing rigid and passive systems, including difficult deployment, mechanical mismatch with soft tissues, and limited adaptability in minimally invasive settings. In this review, an overview is provided of smart materials and soft robotic technologies that show promises for implantable use, discussing advantages and limitations of underlying actuation mechanisms. Examples are then presented where soft actuating mechanisms are combined with microelectrodes to create shape actuating bioelectronic devices. Opportunities and challenges for next-generation intelligent bioelectronic devices assisted by responsive materials and soft robotic actuators are then discussed. These innovations may allow electronic implants to safely navigate to target areas inside the body and establish large area and spatiotemporally controlled interfaces for diagnostic or therapeutic procedures that are minimally invasive.

Inspired by glow-worms, a high-performance multifunctional fluorescent actuator is fabricated by combining ultra-stable perovskite quantum dots with self-healing materials. It integrates large deformation, high brightness, high color-purity, color-changing function and full-device self-healing function together. The full-device self-healing function enables reconfigurable on-demand fluorescent patterns. This actuator opens new paths to soft robots and reconfigurable information encryption.

Abstract

Fluorescent actuators with light-emitting and shape-deformation properties are promising in bionics and soft robotics. However, current fluorescent actuators barely balance actuation performances with fluorescence properties, as they exhibit insufficient brightness, poor color-purity, low-stability, and few functional-integrations, limiting their applications in complex scenarios. Herein, inspired by glow-worms, a multifunctional fluorescent actuator by combining ultra-stable perovskite quantum dots with polyurethane and graphene oxide composites is reported, which integrates large deformation, high brightness, high color-purity, color-changing function and full-device self-healing function together. The actuator shows a large bending curvature of 2.48 cm−1. It exhibits excellent fluorescence performances, such as quantum yields as high as 58.88% and full-widths at half-maximum as narrow as 21 nm. The actuation and fluorescence properties show long-term stability during more than 1100 cycles of near-infrared irradiation and 12 h of ultraviolet exposure. Moreover, the actuator is integrated with color-changing and full-device self-healing functions, enabling a synergetic color/shape change and reconfigurable on-demand fluorescent patterns. Then, a smart gripper and a crawling robot with crawling/rollover motions are demonstrated. Finally, a non-contact dynamic display of reconfigurable encrypted information driven by light is fabricated to mimic light communications of glow-worms. This actuator demonstrates unprecedented multifunctionality, opening new avenues for fluorescent soft robotics.

This work presents a neuromorphic transistor integrating sensing, memory, and computing in one device to address the challenges of commercial artificial vision system. By varying top gate voltages, it can operate as an ultrasensitive photo-sensor (≈6.515 kA W−1), a non-volatile multi-level optical memory (>4 bits), and a neuromorphic visual synapse with 95.26% image recognition accuracy by combing artificial neural network model.

Abstract

In commercial artificial vision system (AVS), the sensing, storage, and computing units are usually physically separated due to their architecture and performance gaps, which thus increases the volume, complexity, and energy loss. This work develops a neuromorphic transistor integrating these different modules within one single device. Leveraging the gate-tunable out-of-plane electric field, the device achieves the multi-mode integration of photo-sensor, optical memory, and visual synapse. When operating at negative top gate voltage (VTG), a strong photo-gating effect enables highly sensitive photo-response with responsivity of ≈6.515 kA W−1 and detectivity up to ≈3.92 × 1014 Jones. Due to the charge storage effect, it can also act as a non-volatile multi-level (>4 bits) optical memory with a long endurance of over 10 000 s and a high writing/erasing ratio of up to 106. At zero or positive VTG, the transistor switches to visual synapse mode with neuromorphic computing capability, providing a pathway for complex biological learning and flexible synaptic plasticity. By further combining the synaptic plasticity with an artificial neural network (ANN), it achieves precise image recognition and classification with an accuracy of up to 95.26%. This work develops a multi-mode transistor that integrates key components of an AVS, addressing the existing challenges of all-in-one integration and manufacturing complexity.

LMB Seminar - Title TBC

Abstract not available

• Speaker: David Klenerman, University of Cambridge
• Monday 03 November 2025, 11:00-12:00
• Venue: In person in the Max Perutz Lecture Theatre (CB2 0QH) and via Zoom link .
• Series: MRC LMB Seminar Series; organiser: Scientific Meetings Co-ordinator.

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LMB Seminar - Blueprints of Life: Understanding the Sex Chromosomes

Sex chromosomes represent the only chromosome pair that differ between males and females, and as such are responsible for the myriad sexual dimorphisms observed in mammals. However, relative to the rest of the genome, their biology remains under explored. In this talk, I will describe how the sex chromosomes appeared during mammalian evolution, the mechanisms by which they regulate their most celebrated role in germline development, and their contribution to male-female differences in disease.

• Speaker: James Turner, The Francis Crick Institute
• Monday 19 May 2025, 11:00-12:00
• Venue: In person in the Max Perutz Lecture Theatre (CB2 0QH) and via Zoom link https://mrc-lmb-cam-ac-uk.zoom.us/j/94132066038?pwd=OF2EjwrvRQxl0XgpGK0N5L4bDNaayi.1.
• Series: MRC LMB Seminar Series; organiser: Scientific Meetings Co-ordinator.

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A novel bifacial-iridescent solar cell is developed using an inverse opal perovskite photonic crystal. It exhibited unique iridescent structural colors on both sides and achieved an impressive bifacial equivalent efficiency of 18.00% for small cells and 12.77% for mini-modules.

Abstract

Colorful perovskite solar cells exhibit excellent potential for building-integrated photovoltaics (BIPVs), which increase the utilization of clean power. However, their efficiencies are lower than those of uncolored devices. Moreover, traditional mono-facial colored devices cannot satisfy diverse BIPV scenarios. Here a bifacial iridescent solar cell (BFI-SC) is developed, constructed by inverse opal (IO) perovskite photonic crystals and transparent front and rear electrodes. The developed BFI-SC exhibited bright vivid colors on both sides, which originate from the reflection at the photonic stop band of the IO perovskite photonic crystal. Moreover, this unique IO photonic crystal decreased the interfacial Fresnel reflection and generated a slow-photon effect, which increases the material light absorption and utilization to obtain high efficiency. Furthermore, the BFI-SC can harvest light from both sides, considerably enhancing the device efficiency. Thus, the BFI-SC achieved an impressive bifacial equivalent efficiency (η eq) of 18.00%, which is the highest value achieved for the reported multicolored (or iridescent) solar cell. A larger-scale BFI-SC module is successfully assembled, achieving a champion η eq of 12.77%. In addition, another perovskite material with an IO structure and wide-bandgap components exhibited vivid colors on both sides, indicating the universality of this coloring strategy and its independence of the perovskite components.

This work uncovers an anomalous density-scaling toughening law in discrete lattices, where ultrahigh specific fracture toughness can be achieved at ultralow relative density, thereby filling gaps in material property space. This anomalous toughening law stems from crack-tip blunting triggered by delocalized strut-buckling transformation at ultralow densities, which is universal across various lattice metamaterials with varying sizes, topologies, and component properties.

Abstract

Lightweight lattice metamaterials attract considerable attention due to their exceptional and tunable mechanical properties. However, their practical application is ultimately limited by their tolerance to inevitable manufacturing defects. Traditional fracture mechanics of lattice metamaterials are confined to localized tensile failure of a crack-tip strut, overlooking the toughening effect of buckling instability in discrete struts around the crack front. Here, via a combination of additive manufacturing, numerical simulation, and theoretical analysis, this work identifies an anomalous power scaling law of specific fracture energy with relative density, where the scaling exponent shifts to negative values below a critical relative density. This anomalous toughening law stems from crack-tip blunting triggered by delocalized strut-buckling transformation at ultralow densities, which is universal across various lattice metamaterials with varying length scales, crack orientations, node connectivity, and component properties. By strategically harnessing strut buckling mechanisms, exceptionally high specific fracture toughness can be achieved at extremely low relative density, thereby addressing gaps in the material property design space. These findings not only provide physical insights into discrete lattice fracture but also offer design motifs for ultralight, ultra-tough lattice metamaterials.

This study developed a bio-active, inhalable nanozyme-backpacked M13 phage (CZM) which specifically delivers to the ischemic core via the olfactory bulb pathway. Leveraging M1-microglia hitchhiking, CZM accumulates specifically at the lesion site, scavenging reactive oxygen species (ROS) to mitigate neuroinflammation and neuronal apoptosis, providing a safe and effective strategy for the precise treatment of neuroinflammatory disorders.

Abstract

There is a desperate need for precise nanomedications to treat ischemic cerebral injury. Yet, the drawbacks of poor delivery efficiency and off-target toxicity in pathologic parenchyma for traditional antioxidants against ischemic stroke result in inadequate brain accumulation. M13 bacteriophages are highly phagocytosed by M1-polarized microglia and can be carried toward the neuroinflammatory sites. Here, a bio-active, inhalable, Ce0.9Zr0.1O2-backpacked-M13 phage (abbreviated as CZM) is developed and demonstrates how M13 bacteriophages are taken up by different phenotypes’ microglia. With the M1 microglia's proliferating and migrating, CZM can be extensively and specifically delivered to the site of the ischemic core and penumbra, where the surviving nerve cells need to be shielded from secondary oxidative stress and inflammatory cascade initiated by reactive oxygen species (ROS). With non-invasive administration, CZM effectively alleviates oxidative damage and apoptosis of neurons by eliminating ROS generated by hyperactive M1-polarized microglia. Here, a secure and effective strategy for the targeted therapy of neuroinflammatory maladies is offered by this research.

A ZVO/RuO2 cathode is designed by coupling Zn0.85V10O24·7.4H2O (ZVO) and RuO2 through interfacial V─O─Ru bonds in which a dynamic reversible breakage and reconstruction of V─O─Ru, which provide a reversible electron transfer channel between RuO2 and ZVO, making RuO2 as an additional electron acceptor and donor, accelerating the migration kinetics of H+/Zn2+ in ZVO.

Abstract

Intercalation-type layered vanadium oxides have been widely explored as cathode materials for aqueous zinc–ion batteries (AZIBs). However, attaining both high power density and superior stability remains a formidable challenge. Herein, layered vanadium oxides are pre-intercalated with Zn2+ to form Zn0.85V10O24·7.4H2O (ZVO), which is then combined with RuO2 nanoparticles to construct a ZVO/RuO2 heterostructure featuring interphase V─O─Ru bonds. ZVO/RuO2 heterostructure exhibits a dynamic stable coupling at the interphase via V─O─Ru chemical bonds reconstruction during discharging/charging processes. The dynamically reversible reconstruction of interphase V─O─Ru bonds provides a fast electron transfer channel between RuO2 and ZVO cathode, as demonstrated by ex situ X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) calculations, making RuO2 an additional electron acceptor and donor, and accelerating the migration of H+/Zn2+ in layered ZVO cathode. Therefore, an ultra-high capacity (411 mAh g−1 at 0.5 A g−1, 225 mAh g−1 at 20 A g−1) and long cycling stability (a retention of 92.2% at 20 A g−1 over 20000 cycles) performances are achieved. This interphase reversible reconstruction route provides a promising approach to achieving excellent cycling stability in cathode materials.