Stable and Highly Efficient Near‐Infrared Emission Achieved in Spinel Blocks
Synopsis: Utilizing a 2D framework matrix, a strategy is presented to balance Cr3⁺-pair emissions at high doping concentrations while effectively suppressing undesirable quenching, thereby ensuring sustained luminescent efficiency.
Abstract
Developing efficient and stable near-infrared emitters related to Cr3+-pairs for advanced optoelectronic devices remains a challenge due to concentration quenching effects and unclear luminescence mechanisms. In this study, Cr3+ ions are incorporated into a matrix structure consisting of ZnAl₂O₄ spinel units separated by 11.312 Å, effectively restricting energy transfer between luminescent centers and alleviating quenching effects. Computational analysis identifies the lattice positions of isolated Cr3+ ions and Cr3+-pairs at different doping levels, providing insights into their spatial distribution and local structural environments. Photoluminescence measurements reveals a Cr3+-concentration-dependent emission broadening, with a Cr3+-pair emission band peak at 750 nm, while detailed spectral analysis further clarified the energy level structure of Cr3+-pairs for the first time. Enhanced material performance is achieved through flux-assisted synthesis, reaching a high external quantum efficiency of 58.3%. Consequently, the assembled pc-LEDs exhibit minimal efficiency roll-off and achieve a high output of 183 mW at 650 mA, demonstrating their potential in near-infrared light sources and night vision technology application.
Angstrom Confinement‐Triggered Adaptive Spin State Transition of CoMn Dual Single Atoms for Efficient Singlet Oxygen Generation
Angstrom-confined cobalt (Co) manganese (Mn) CoMn dual single atoms within the carbon nitride interlayer are constructed to efficiently activate peroxymonosulfate for water purification. The angstrom-confined strategy leads to the adaptive change of atomic spin state, and reduces the energy barrier for *SO5 formation and *O2 desorption during singlet oxygen generation, enabling a 38.6-fold increase in singlet oxygen production compared to the surface unconfined one.
Abstract
To achieve high selectivity in the transformation from peroxymonosulfate to singlet oxygen, adaptive tuning of atomic spin state as the peroxymonosulfate structure varied is crucial. The angstrom confinement can effectively tune spin state, but developing an adaptive angstrom-confined atomic system is challenging. Angstrom-confined cobalt (Co) manganese (Mn) dual single atoms within flexible 2D carbon nitride interlayer are constructed to drive adaptive tuning of spin state by changing atomic coordination under angstrom confinement. The in situ characterizations and density functional theory calculations showed that medium-spin Co in Co─N4 absorbed electrons after the adsorption of peroxymonosulfate on CoMn dual single-atom sites and then cleaved O─H of peroxymonosulfate to facilitate *SO5 generation, while the introduction of *SO5 increased interlayer distance and then cleaved Co─N and Mn─N, resulting in the spin state transition from medium to high. Subsequently, the high-spin Co and Mn in Co─N2 and Mn─N2 desorbed the *O2 from *SO5, restoring the initial medium spin state. The adaptive spin state transition enhanced 38.6-fold singlet oxygen yield compared to the unconfined control. The proposed angstrom-confined diatomic strategy is applicable to serial diatomic catalysts, providing an efficient and universal design scheme for singlet oxygen-mediated selective wastewater treatment technology at the atomic level.
Tue 11 Feb 16:00: Towards Scalable Foundation Models for Wearable Sensing Zoom: https://cam-ac-uk.zoom.us/j/82858548158?pwd=GxehopMD68LvYlArGHNjDmiLTgYAC0.1
Abstract: Consumer wearable devices have seen remarkable progress in recent years, becoming more accurate, pervasive, and affordable. Despite these advancements, large-scale foundation models trained on wearable data are a relatively new phenomenon, unlike in many other domains. This talk will explore the technical landscape currently limiting progress in this area, and present our new work, “Scaling Wearable Foundation Models,” recently accepted to ICLR .
Bio: Shyam Tailor is a senior research scientist at Google, specializing in the development of practical, scalable techniques for harnessing large foundational models in health. With a strong track record of both research and real-world impact, Shyam has contributed to several flagship features on Google Fitbit devices, including the first widely available GenAI-powered feature, as well as advanced sensing algorithms for heart rate and activity monitoring which have been widely applauded by the press. Shyam completed his PhD at the University of Cambridge in under three years, where his research, under the guidance of Professor Nic Lane, focused on creating resource-efficient machine learning algorithms. His work has earned recognition across major conferences and workshops, with publications at prestigious venues including ICLR , ICML, MLSys, ECCV , and Ubicomp/IMWUT, and he has won multiple best paper awards for his contributions.
Zoom: https://cam-ac-uk.zoom.us/j/82858548158?pwd=GxehopMD68LvYlArGHNjDmiLTgYAC0.1
- Speaker: Shyam Tailor, Google
- Tuesday 11 February 2025, 16:00-17:00
- Venue: Online.
- Series: Mobile and Wearable Health Seminar Series; organiser: Cecilia Mascolo.
Fri 07 Feb 13:00: Unimodular JT gravity and de Sitter quantum cosmology
In this talk, I will show how a gauge-theoretic approach to Jackiw–Teitelboim (JT) gravity naturally yields a two-dimensional Henneaux–Teitelboim (HT) unimodular theory, applicable to both flat and curved spacetimes. Under a mini-superspace reduction, the Wheeler–DeWitt equation becomes a Schrödinger-like equation admitting a consistent, unitary quantum description. The resulting wavefunction describes a quantum distribution for the scale factor, illuminating cosmic expansion and contraction, and allowing topology change at a=0.
- Speaker: Farbod Rassouli, University of Nottingham
- Friday 07 February 2025, 13:00-14:00
- Venue: Potter room / https://cam-ac-uk.zoom.us/j/87235967698.
- Series: DAMTP Friday GR Seminar; organiser: Xi Tong.
Thu 15 May 14:00: Walter Kohn: the theoretical physicist who created DFT and won the Nobel Prize for Chemistry
Abstract not available
- Speaker: Prof. Sir David Clary, FRS (University of Oxford)
- Thursday 15 May 2025, 14:00-15:30
- Venue: TCM Seminar Room.
- Series: Theory of Condensed Matter; organiser: Bo Peng.
Fri 07 Feb 16:00: Flavour Physics Beyond the Standard Model with the SMEFT Likelihood
New physics beyond the Standard Model (SM) is needed to address open questions within the SM and to explain experimental observations that the SM cannot account for. While direct searches at the Large Hadron Collider have reached their energy limit without finding particles beyond the SM (BSM), precision measurements, in particular those in flavour physics, probe energy scales far beyond the reach of direct searches. In this talk I will discuss how measurements of flavour and other precision observables, combined with Effective Field Theory (EFT) methods, can be used to indirectly search for heavy BSM particles. I will present a likelihood function in the Standard Model EFT (SMEFT) that includes a large number of flavour observables, and show how it can be applied to the flavour phenomenology of BSM models.
- Speaker: Peter Stangl (CERN)
- Friday 07 February 2025, 16:00-17:00
- Venue: MR19 (Potter Room, Pavilion B), CMS.
- Series: HEP phenomenology joint Cavendish-DAMTP seminar; organiser: Nico Gubernari.
An integrated design for high-energy, durable zinc–iodine batteries with ultra-high recycling efficiency
DOI: 10.1039/D4EE05873A, PaperLeiqian Zhang, Han Ding, Haiqi Gao, Jiaming Gong, Hele Guo, Shuoqing Zhang, Yi Yu, Guanjie He, Tao Deng, Ivan P. Parkin, Johan Hofkens, Xiulin Fan, Feili Lai, Tianxi Liu
This work presents a zinc–iodine battery featuring a liquid–liquid biphasic electrolyte and an integrated cell structure, which facilitates an iodine loading of 69.8 mg cm−2, a self-discharge rate of 3.4% per month, and ∼100% recycling efficiency.
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Fri 07 Feb 13:00: Barlow Twins Earth Foundation Model
Abstract
Satellite imagery provides a critical lens for monitoring Earth’s dynamic systems, yet integrating multi-source, multi-temporal data into globally consistent, high-resolution representations remains a challenge. Traditional remote sensing vision models, which process patches or images as inputs, often struggle to capture fine-grained spatiotemporal-spectral relationships critical for downstream tasks like land classification, climate modeling, and change detection. We present a self-supervised framework leveraging Barlow Twins to train an Earth Foundation Model that outputs pixel-level representations from diverse satellite data sources. Unlike conventional ML approaches, our model treats pixels as primary units of learning, explicitly optimizing for temporal-spectral coherence across billions of global 10m-resolution pixels. Preliminary results demonstrate that the resulting representation map encodes high-quality spatiotemporal patterns, outperforming traditional ML methods in land classification. By bridging multi-modal satellite data into a harmonized latent space, our approach unlocks new opportunities for monitoring planetary-scale processes with higher precision.
Bio
Frank Feng is a first-year PhD student in the Department of Computer Science and Technology at the University of Cambridge. His research interests lie at the intersection of machine learning and earth sciences, with a particular focus on the application of self-supervised learning in remote sensing.
- Speaker: Frank Feng, University of Cambridge
- Friday 07 February 2025, 13:00-13:55
- Venue: FW11, 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.
Strategies to Improve the Photovoltaic Performance of M-Series Acceptor-Based Polymer Solar Cells: Chemical Hybridization Versus Physical Blending of Acceptors
DOI: 10.1039/D5EE00294J, PaperHaiting Shi, Hui Guo, Dongdong Cai, Jin-Yun Wang, Yunlong Ma, Qingdong Zheng
A novel asymmetric acceptor, M36-FCl, has been developed by chemically hybridizing two symmetric M-series acceptors: one with fluorinated terminal groups (M36F) and the other with chlorinated terminal groups (M36Cl). This...
The content of this RSS Feed (c) The Royal Society of Chemistry
Mon 15 Sep 11:00: LMB Seminar - Title TBC
Abstract not available
- Speaker: Alan Brown, Harvard Medical School
- Monday 15 September 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.
Mon 10 Feb 11:00: LMB Seminar - Alpha-Synuclein and its aggregation: Past, Present and Future
Most neurodegenerative diseases are characterised by the presence of abnormal intracellular protein inclusions. These inclusions were described at the beginning of last century as the defining neuropathological features of diseases, such as Alzheimer’s, Pick’s and Parkinson’s. In Alzheimer’s, Pick’s and several other diseases, the inclusions are made of the microtubule-associated protein tau. The filamentous inclusions of Parkinson’s disease, in the form of Lewy bodies and Lewy neurites, are made of the protein alpha-synuclein; the same is true of the Lewy pathology of dementia with Lewy bodies and the glial cytoplasmic inclusions of multiple system atrophy. Alpha-synuclein aggregates can be also found in about 60% of Alzheimer’s cases. The importance of the assembly of alpha-synuclein in these diseases is supported by the finding that mutations in its gene (SNCA) cause disease and these disorders are now also known as alpha-synucleinopathies. Studies on the distribution of Lewy pathology have suggested that in Parkinson’s disease alpha-synuclein aggregation begins in the periphery and spreads to the brain, resulting in pre-motor and then motor symptoms. Besides the Lewy bodies in the substantia nigra and other brain areas, smaller alpha-synuclein aggregates are present at synapses in the striatum, where they impair neurotransmitter release and contribute to the early stages of neurodegeneration. We have generated transgenic mouse models with alpha-synuclein aggregates that reproduce the characteristic features of disease and that can be used for testing new therapeutic approaches. Alpha-synuclein aggregation is a promising target for therapy.
- Speaker: Maria Grazia Spillantini, University of Cambridge, Dept of Clinical Neurosciences
- Monday 10 February 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/98728840077?pwd=Z0MZ2xWLsyUC6fI31cIklaUbSYALwy.1.
- Series: MRC LMB Seminar Series; organiser: Scientific Meetings Co-ordinator.
Tue 11 Mar 14:00: Title to be confirmed
Abstract not available
- Speaker: Daniel Kious (Bath)
- Tuesday 11 March 2025, 14:00-15:00
- Venue: MR12.
- Series: Probability; organiser: ww295.
Tue 18 Mar 14:00: Title to be confirmed
Abstract not available
- Speaker: Louis-Pierre Arguin (Oxford)
- Tuesday 18 March 2025, 14:00-15:00
- Venue: MR12.
- Series: Probability; organiser: ww295.
Tue 04 Mar 14:00: TBA
Abstract not available
- Speaker: Armand Riera (Paris)
- Tuesday 04 March 2025, 14:00-15:00
- Venue: MR12.
- Series: Probability; organiser: ww295.
Tue 18 Feb 14:00: TBA
Abstract not available
- Speaker: Titus Lupu (Paris)
- Tuesday 18 February 2025, 14:00-15:00
- Venue: MR12.
- Series: Probability; organiser: ww295.
Fri 14 Mar 14:00: Evaluating a black-box algorithm: stability, risk, and model comparisons
When we run a complex algorithm on real data, it is standard to use a holdout set, or a cross-validation strategy, to evaluate its behavior and performance. When we do so, are we learning information about the algorithm itself, or only about the particular fitted model(s) that this particular data set produced? In this talk, we will establish fundamental hardness results on the problem of empirically evaluating properties of a black-box algorithm, such as its stability and its average risk, in the distribution-free setting. This work is joint with Yuetian Luo and Byol Kim.
- Speaker: Rina Foygel Barber (University of Chicago)
- Friday 14 March 2025, 14:00-15:00
- Venue: Centre for Mathematical Sciences MR12, CMS.
- Series: Statistics; organiser: Qingyuan Zhao.
Thu 13 Mar 16:00: Algorithmic stability for regression and classification
In a supervised learning setting, a model fitting algorithm is unstable if small perturbations to the input (the training data) can often lead to large perturbations in the output (say, predictions returned by the fitted model). Algorithmic stability is a desirable property with many important implications such as generalization and robustness, but testing the stability property empirically is known to be impossible in the setting of complex black-box models. In this work, we establish that bagging any black-box regression algorithm automatically ensures that stability holds, with no assumptions on the algorithm or the data. Furthermore, we construct a new framework for defining stability in the context of classification, and show that using bagging to estimate our uncertainty about the output label will again allow stability guarantees for any black-box model. This work is joint with Jake Soloff and Rebecca Willett.
Evaluating a black-box algorithm: stability, risk, and model comparisons
When we run a complex algorithm on real data, it is standard to use a holdout set, or a cross-validation strategy, to evaluate its behavior and performance. When we do so, are we learning information about the algorithm itself, or only about the particular fitted model(s) that this particular data set produced? In this talk, we will establish fundamental hardness results on the problem of empirically evaluating properties of a black-box algorithm, such as its stability and its average risk, in the distribution-free setting. This work is joint with Yuetian Luo and Byol Kim.
A wine reception in the Central Core will follow this lecture
- Speaker: Rina Foygel Barber (Chicago)
- Thursday 13 March 2025, 16:00-17:00
- Venue: Centre for Mathematical Sciences MR2.
- Series: Peter Whittle Lecture; organiser: HoD Secretary, DPMMS.
Thu 06 Feb 14:00: Low-power embedded event-based vision processing for low-latency robotics
Brain inspired information processing in hardware and in software – or “neuromorphic computing” – opens a possible path to real-time, low-energy computation. Today, various neuromorphic computing systems are available as customizable hardware for small or large applications, from single chips to computer server rooms. For efficient use of such novel hardware, we need to rethink computation in terms of event-based or spiking neuromorphic algorithms, instead of traditional sequential (CPU) or parallel (GPU) computing. In this presentation, I will first briefly introduce the concepts of neuromorphic computing, including a quick overview of present and upcoming neuromorphic hardware for sensing and computation. Following, I will show and discuss multiple application examples of event-based sensing and perception, leading a path towards closed-loop actuated robotic systems.
The seminar will be held in the JDB Seminar Room , Department of Engineering, and online (zoom): https://newnham.zoom.us/j/92544958528?pwd=YS9PcGRnbXBOcStBdStNb3E0SHN1UT09
- Speaker: Jörg Conradt, KTH Stockholm, Sweden
- Thursday 06 February 2025, 14:00-15:00
- Venue: JDB Seminar Room, Department of Engineering and online (Zoom).
- Series: CUED Control Group Seminars; organiser: Fulvio Forni.
Fri 07 Feb 16:00: A CUED-developed flexible multi-sensor device enabling handheld sensing of heart sounds by untrained users
Heart valve disease has a large and growing burden, with a prognosis worse than many cancers. Screening with a traditional stethoscope is underutilised, often inaccurate even in skilled hands, and requires time-consuming, intimate examinations.
In this talk I will present a handheld device designed to enable untrained users to record high-quality heart sounds without requiring patients to undress. The device, developed at the CUED Acoustics Lab, incorporates multiple high-sensitivity sensors embedded in a flexible substrate that conforms to the contours of the human body.
The use of multiple sensors allows us to address challenges from localised heart sound vibrations and noise interference. I will introduce a time-frequency signal quality algorithm which we have developed to allow automated selection of the best sensor in the device and rejection of recordings with insufficient diagnostic quality.
A validation study conducted at CUED demonstrates the device’s effectiveness across a diverse range of body types, with multiple sensors significantly increasing the likelihood of a successful recording. The device has the potential to enable accurate, accessible and low-cost heart disease screening.
- Speaker: Dr Max Nussbaumer, CUED
- Friday 07 February 2025, 16:00-17:00
- Venue: JDB Seminar Room, CUED.
- Series: Engineering - Dynamics and Vibration Tea Time Talks; organiser: div-c.
Mon 10 Feb 14:00: Extreme pushed and pulled fronts
I shall describe the propagation properties of a class of quasilinear reaction-diffusion equations, motivated by applications to biological tissue growth.
- Speaker: John R. King (University of Nottingham)
- Monday 10 February 2025, 14:00-15:00
- Venue: MR13.
- Series: Partial Differential Equations seminar; organiser: Giacomo Ageno.