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This review systematically summarizes the latest advancements in transition metal-based photocatalysts for hydrogen evolution-related applications. It provides a comprehensive classification of these materials, unveils effective strategies to enhance their catalytic performance, and delves into the fundamental principles underlying their modifications. Furthermore, the review outlines future perspectives in this field and offers guidance on developmental strategies to address existing challenges.

Abstract

Artificial photosynthesis offers a promising pathway to address environmental challenges and the global energy crisis by converting solar energy into storable chemical fuels such as hydrogen. Among various photocatalysts, transition metal-based materials have garnered significant attention due to their tunable crystal phase, morphology, surface active sites, and other key properties. This review provides a comprehensive overview of recent advances in transition metal-based photocatalysts for hydrogen production, with a particular focus on modification strategies and their underlying mechanisms. By systematically classifying these materials, this work highlights effective approaches for enhancing their catalytic performance, including structural engineering, electronic modulation, and interfacial optimization. Furthermore, this work discusses the fundamental principles governing these modifications, offering deeper insights into their roles in charge separation, surface reactions, and stability. Finally, this work outlines future research directions and key challenges in the rational design of highly efficient transition metal-based photocatalysts for sustainable hydrogen production.

We employ photocatalysis to decrease the iron migration barrier, enabling the repositioning of disordered iron atoms into their designated octahedral sites while simultaneously facilitating Li+ diffusion into the LFP lattice, thereby realizing the direct recovery of S-LFP. This method has substantial environmental and economic benefits, making it a promising solution for sustainable lithium-ion battery recycling.

Abstract

Fe-Li (FeLi) anti-site defects, commonly observed in degraded LiFePO4 cathodes, impede Li+ mobility and disrupt the electronic pathways, leading to significant performance degradation in LFP. However, addressing FeLi anti-site defects to achieve direct recycling of LFP remains challenging due to Fe high migration energy barriers and the lattice distortions they induce. Here, a feasible strategy is proposed for LFP regeneration by utilizing photocatalysis to reduce the Fe migration barrier. This approach facilitates repositioning disordered Fe atoms to their designated octahedral sites while simultaneously enabling Li+ diffusion into the LFP lattice, thus restoring capacity and ensuring cycling stability. The mechanism of the photocatalysis regeneration strategy is comprehensively analyzed through a combination of theoretical calculations, in-depth atomic characterization techniques, and electrochemical evaluations. Notably, this strategy is adaptable to varying levels of FeLi anti-site defects in spent LFP. Furthermore, life cycle analysis highlights the substantial environmental and economic benefits of this advanced strategy, making it a promising solution for sustainable lithium-ion battery recycling.

Flexible QZPCs formulated by the MES@CNT/CC air cathode and IL-PANa hydrogel electrolyte demonstrate a high cell-level energy density of 105 Wh kgcell −1, and an ultra-long cycle life of 4000 cycles at 5 mA cm−2 even at low temperature of −30 °C. The electronic synergy within the bifunctional MES@CNT/CC air cathode, initiates an intriguing adaptive active-site-switching catalytic mechanism during the reciprocating ORR and OER processes, thereby sustaining the high performance of the QZPCs.

Abstract

Quasi-solid-state Zn-air pouch cells (QZPCs) promise a high energy-to-cost ratio while ensuring inherent safety. However, addressing the challenges associated with exploring superior energy-wise cathode catalysts along with their activity origin, and the super-ionic electrolytes remains a fundamental task. Herein, the realistic high-performance QZPCs are contrived, underpinned by a robust NiVFeCo medium-entropy metal sulfides (MESs) bifunctional air cathode with a record-low potential polarization of 0.523 V, paired with a sodium polyacrylate-ionic liquid hydrogel exhibiting exceptional conductivity (234 mS cm−1) and water retention (93.8% at 7 days) at room temperature as the super-ionic conductor electrolyte. Through combined studies of in situ Raman, ex situ X-ray absorption fine structure analysis, and theoretic calculations, an intriguing adaptive active-sites-switching mechanism of the MESs cathode during discharging/charging processes is unveiled, revealing a dynamic role transition of Co and Ni active sites in the reversible oxygen electrocatalysis. Consequently, the persistent low cathode polarization and super ion-conductive electrolyte endorse QZPCs an excellent rate performance from 1 to 100 mA cm−2 at room temperature. Moreover, an impressively high cell-level energy density of 105 Wh kgcell −1 with an ultra-long cycle lifespan of 4000 cycles at 5 mA cm−2 and a low temperature of −30 °C is achieved.

Bioinspired Ru-doped metal hydroxide (Ru-Co(OH)x) is developed as an O2-evolution catalyst with proton-coupled electron transfer (PCET) pathway for efficient and low-energy O2 generation. The lattice H species in Ru-Co(OH)x optimizes Ru-oxygen intermediates interactions, thereby enhancing O2 production performance. This technique ensures an uninterrupted O2 supply during emergencies and in regions with limited O2 availability, providing significant societal benefits.

Abstract

Producing high-purity oxygen (O2) has a wide range of applications across diverse sectors, such as medicine, tunnel construction, the chemical industry, and fermentation. However, current O2 production methods are burdened by complexity, heavy equipment, high energy consumption, and limited adaptability to harsh environments. Here, to address this grand challenge, the de novo design of Ru-doped metal hydroxide is proposed to serve as bioinspired O2-evolution catalysts with proton-coupled electron transfer (PCET) pathway for low-energy, environmentally friendly, cost-effective, and portable O2 generation. The comprehensive studies confirm that the lattice H species in Ru-Co(OH)x-based O2-evolution catalyst can trigger a PCET pathway to optimize Ru-oxygen intermediates interactions, thus ultimately reducing reaction energy barriers and improving the activities and durabilities. Consequently, the prepared Ru-Co(OH)x-loaded membrane catalysts exhibit rapid and long-term stable O2 production capabilities. Furthermore, the proposed material design strategy of lattice H-species shows remarkable universality and adaptability to broad Ru-doped metal hydroxides. This efficient, portable, and cost-effective O2 generation technique is suggested to ensure an uninterrupted O2 supply during emergencies and in regions with limited O2 availability or air pollution, thus offering significant societal benefits in broad applications.

The authors show that the (011)C perovskite planes are prone to stacking faults formation in all leading formamidinium-rich perovskite compositions. Using ethylene thiourea as a precursor additive, Othman et al. suppress those vulnerable facets, significantly enhancing the absorber's intrinsic stability under various operational conditions.

Abstract

The poor intrinsic perovskite absorber stability is arguably a central limitation challenging the prospect of commercialization for photovoltaic (PV) applications. Understanding the nanoscopic structural features that trigger instabilities in perovskite materials is essential to mitigate device degradation. Using nanostructure characterization techniques, we observe the local degradation to be initiated by material loss at stacking faults, forming inherently in the (011)-faceted perovskite domains in different formamidinium lead triiodide perovskite compositions. We introduce Ethylene Thiourea (ETU) as an additive into the perovskite precursor, which manipulates the perovskite crystal growth and results in dominantly in-and out-of-plane (001) oriented perovskite domains. Combining in-depth experimental analysis and density functional theory calculations, we find that ETU lowered the perovskite formation energy, readily enabling crystallization of the perovskite phase at room temperature without the need for an antisolvent quenching step. This facilitated the fabrication of high-quality large area 5 cm by 5 cm blade-coated perovskite films and devices. Encapsulated and unmasked ETU-treated devices, with an active area of 0.2 cm2, retained > 93 % of their initial power conversion efficiency (PCE) for > 2100 hours at room temperature, and additionally, 1 cm2 ETU-treated devices maintained T80 (the duration for the PCE to decay to 80 % of the initial value) for > 600 hours at 65 °C, under continuous 1-sun illumination at the maximum power point in ambient conditions. Our demonstration of scalable and stable perovskite solar cells represents a promising step towards achieving a reliable perovskite PV technology.

Low-dimensional semiconductor materials are promising candidates for photosensitive components in next-generation image sensors. This review offers a thorough and timely examination of novel image sensors, covering their working principles, intriguing materials categorized into four main groups, and advanced imaging applications. Additionally, it delves into the roadmap for next-generation image sensors, exploring future opportunities and challenges in the field.

Abstract

With the rapid advancement of technology of big data and artificial intelligence (AI), the exponential increase in visual information leads to heightened demands for the quality and analysis of imaging results, rendering traditional silicon-based image sensors inadequate. This review serves as a comprehensive overview of next-generation image sensors based on low-dimensional semiconductor materials encompassing 0D, 1D, 2D materials, and their hybrids. It offers an in-depth introduction to the distinctive properties exhibited by these materials and delves into the device structures tailored specifically for image sensor applications. The classification of novel image sensors based on low-dimensional materials, in particular for transition metal dichalcogenides (TMDs), covering the preparation methods and corresponding imaging characteristics, is explored. Furthermore, this review highlights the diverse applications of low-dimensional materials in next-generation image sensors, encompassing advanced imaging sensors, biomimetic vision sensors, and non-von Neumann imaging systems. Lastly, the challenges and opportunities encountered in the development of next-generation image sensors utilizing low-dimensional semiconductor materials, paving the way for further advancements in this rapidly evolving field, are proposed.

Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE01092F, PaperSinan Zheng, Yang Wang, Bin Luo, Kun Zhang, Leilei Sun, Zhean Bao, Guosheng Duan, Dinghao Chen, Hanwei Hu, Jingyun Huang, Zhizhen Ye
The dynamic reconstruction of electric double layers (EDLs) holds the key to stabilizing aqueous Zn metal batteries. However, the charge compatibility within EDL is destroyed by the spatiotemporal discord between...
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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D4EE05757K, PaperQunhao Wang, Xueyong Deng, Xiaolin Xue, Jian Zhang, Jiangqi Zhao, Zengyan Sui, Yuefei Zou, Longbo Luo, Wei Zhang, Xiangyang Liu, Canhui Lu
Rechargeable aqueous zinc batteries (ZIBs) are a promising device for sustainable energy storage, yet their application is hindered by uncontrollable Zn dendrite growth and parasitic reactions. Herein, a flexible membrane...
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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE00737B, PaperKang Yan, Yongbo Fan, Xueya Yang, Xinyu Wang, Shengmei Chen, Weijia Wang, Mingchang Zhang, Huiqing Fan, Longtao Ma
Highly concentrated salts, like 30 m ZnCl₂, can reduce free water molecules in aqueous electrolytes but also increase acidity, causing severe acid-catalyzed corrosion of the Zn anode, current collector, and...
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DAC-AA into SnO2 colloids favors the crystalline phase and preferential orientation along high-oriented (101) and (200) crystal planes by reducing surface absorption energy and modulating crystal thermodynamics, promoting heating transfer rate in the flexible PEN substrate and favoring perovskite/SnO2 lattice matching. The f-PSCs fabricated in full-air conditions produce an efficiency of 23.87% and exceptional mechanical stability.

Abstract

Tin (IV) oxide (SnO2) electron transport layer (ETL) emerges as the most promising n-type semiconductor material for flexible perovskite solar cells (f-PSCs). The (110) facet-dominated SnO2 colloids are readily created, whereas other best-performing (101) and (200) facets-dominated ones with superior potential in interface modulation and lattice matching remain insufficiently explored. Here water-soluble acryloyloxyethyltrimethyl ammonium chloride-acrylamine (DAC-AA) doping into SnO2 colloids produces more (101)- and (200)-oriented crystal domains through lowering surface absorption energy and offering additional thermodynamic driving force. Theoretical and experimental analyses corroborate that the grain preference orientation induced by DAC-AA modification strengthens heating transfer rate on the flexible substrate and favors lattice matching of perovskite (100) plane on SnO2 (101) and (200) facets. Accordingly, the champion f-PSCs on high-oriented SnO2-DAC-AA ETLs fabricated fully in ambient air conditions achieve the efficiencies of 23.87% and 22.41% with aperture areas of 0.092 and 1 cm2. In parallel, the propitious interfacial lattice arrangement attenuates the formation of micro-strain inside perovskite films, maintaining 92.5% of their initial performance after 10 000 bending cycles with a curvature radius of 6 mm.

The combination of flexible matrices with embedded hard-magnetic nodes enables metastructures with reprogrammable mechanical properties, even in the absence of external magnetic fields. The evolving interaction between nodes during structural deformation allows mechanical tunability under quasi-static and dynamic loading, and bistable transitions. This approach enables engineered structural components with adaptable mechanical responses, reprogrammable via magnetic element redistribution or applied fields.

Abstract

This study experimentally demonstrates the reprogrammability of a rotating-squares-based mechanical metamaterial with an embedded array of permanent magnets. How the orientation, residual magnetization, and stiffness of the magnets influence both the static and dynamic responses of the metamaterial is systematically investigated. It is showed that by carefully tuning the magnet orientation within the metamaterial, notable tunability of the metamaterial response can be achieved across static and dynamic regimes. More complex magnetic node configurations can optimize specific structural responses by decoupling the tunability of quasi-static stress–strain behavior from energy absorption under impact loading. Additionally, reprogrammability can be further enhanced by an external magnetic field, which modulates magnetic interactions within the structure. This work paves the way for developing engineered structural components with adaptable mechanical responses, reprogrammable through either the redistribution of magnetic elements or the application of an external magnetic field.

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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