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Title to be confirmed

Abstract not available

• Speaker: Speaker to be confirmed
• Thursday 03 July 2025, 15:50-17:20
• Venue: Lecture Theatre 2, Computer Laboratory, William Gates Building.
• Series: Foundation AI; organiser: Pietro Lio.

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Artificial Intelligence in Agrifood and Environment

Artificial Intelligence (AI) is expected to have a transformative impact on the natural sciences by enhancing modeling capabilities and improving the prediction of natural phenomena across multiple spatial and temporal scales. This talk will highlight the urgency of coordinated scientific and regulatory initiatives to ensure the sustainable development of our planet. It will also provide an overview of recent advances in AI-driven approaches within the environmental domain, with a particular focus on solutions for coastal and marine ecosystem monitoring. Finally, the presentation will offer ideas on potential future developments from a modeling perspective, underscoring emerging directions and opportunities for interdisciplinary research.

• Speaker: Prof. Antonino Staiano
• Tuesday 08 July 2025, 15:50-17:20
• Venue: Lecture Theatre 2, Computer Laboratory, William Gates Building.
• Series: Foundation AI; organiser: Pietro Lio.

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title

Abstract not available

• Speaker: Speaker to be confirmed
• Monday 07 July 2025, 17:00-17:45
• Venue: Lecture Theatre 2, Computer Laboratory, William Gates Building.
• Series: Foundation AI; organiser: Pietro Lio.

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title

Abstract not available

• Speaker: Speaker to be confirmed
• Tuesday 08 July 2025, 17:00-17:45
• Venue: Lecture Theatre 2, Computer Laboratory, William Gates Building.
• Series: Foundation AI; organiser: Pietro Lio.

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Predicting Global Patterns of Mycorrhizal Fungal Biodiversity with Self-Supervised Satellite Features

Abstract

Soil fungal communities are critical drivers of terrestrial ecosystem function, yet their global distribution remains largely unknown due to the challenges of widespread physical sampling. We developed a machine learning pipeline to predict fungal biodiversity across Europe and Asia using high-resolution, temporal satellite imagery. We introduce a novel feature set derived from a self-supervised learning (SSL) model applied to Sentinel time series. We trained a model on roughly 12,000 mycorrhizal fungal richness samples, comparing the predictive power of our SSL features against standard environmental datasets. Our combined model achieves a robust R2 of 0.53-0.55 across 50 cross-validation runs. We show that the SSL features are the single most important predictor group, outperforming traditional datasets and implicitly capturing land cover information. Furthermore, we demonstrate that prediction errors are geographically clustered in sparsely sampled regions, providing a data-driven method for identifying “biodiversity data deserts” and guiding future sampling efforts. This work presents a scalable framework for monitoring an overlooked component of global biodiversity and demonstrates the viability of temporally-rich, self-supervised representations for ecological modeling.

Bio

Robin Young is a first-year PhD student in Computer Science at the University of Cambridge.

• Speaker: Robin Young, University of Cambridge
• Thursday 10 July 2025, 13:00-14:00
• Venue: Room GS15 at the William Gates Building and on Zoom: 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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Dr John James, Immunology, Warwick Medical School. Warwick Medical School

This Cambridge Immunology Network Seminar will take place on Thursday 17 July 2025, starting at 4:00pm, in the Ground Floor Lecture Theatre, Jeffrey Cheah Biomedical Centre (JCBC)

Speaker: Dr John James, Associate Professor, Immunology, Warwick Medical School, University of Warwick

Title: Title: Elucidating T Cell Signalling Dynamics Using Reconstitution and Optogenetics

Abstract: T cells are an essential part of our immune system; they detect infected cells and either directly kill or orchestrate their removal to keep us healthy despite constant exposure to potential pathogens. Great progress has been made in identifying the parts of the signalling networks that T cells use to execute these decision-making processes, and we now have near-complete lists of these pathways. However, to fully describe T cell function we must also understand how signals traverse these network connections, but this knowledge remains far more limited in T cells.

To address this limitation, we use cellular reconstitution and light-mediated control over these signalling pathways to directly and quantitively investigate T cell signalling in the cellular context. In the talk, I will show how we have used these discovery-based tools to better understand the mechanisms of action for new therapeutics (bispecifics/CAR-T), as well as preliminary data on quantifying inhibitory receptor function. I will also present our reconstitution work on how the pre-T cell receptor can drive commitment to the αβ-T cell lineage in the absence of ligand.

Host: Mathilde Colombe and Tim Halim, CRUK Cambridge

Refreshments will be available following the seminar.

• Speaker: Dr John James, Immunology, Warwick Medical School. Warwick Medical School
• Thursday 17 July 2025, 16:00-17:00
• Venue: Lecture Theatre, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus.
• Series: Cambridge Immunology Network Seminar Series; organiser: Ruth Paton.

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Seminar cancelled - Spatial mapping of breast cancer tumour microenvironment in Black British and White British women

Women of Afro-Caribbean descent confront more aggressive breast cancer subtypes at a younger age than their Caucasian counterparts. Yet, breast cancer research and treatment development have predominantly focused on Caucasian populations, neglecting potential biological drivers of these disparities. Our study addresses this gap by in-depth characterising the breast tumour microenvironment (TME) in an ethnically diverse cohort. We analysed treatment-naïve breast cancer samples from 45 Black British and 45 White British women, matched by age, tumour subtype, and stage by employing spatial transcriptomics (NanoString GeoMx) and hyper-plex protein profiling (Leica Microsytems Cell DIVE ). We captured whole-transcriptome data from cancer (PanCK+), immune (CD45+), and stromal (aSMA+) compartments from both tumour centre and tumour edge. The most striking differences emerged within the immune and stromal compartments, not in the cancer cells, underscoring metabolic, adhesion, and extracellular matrix rewiring in Black British tumours. Complementary spatial protein profiling further revealed changes in tissue architecture with distinct recurrent patterns of cellular organisation and cell-cell interactions, involving endothelial and B-cells. Our findings suggest that the TME plays a pivotal role in driving ethnic disparities in breast cancer, highlighting the urgent need for ethnically tailored therapies and more inclusive clinical trials to advance precision cancer care. This breakthrough offers new avenues for improving overall outcomes in breast cancer.

**Seminar cancelled**

• Speaker: Professor Kairbaan Hodivala-Dilke, Centre for Tumour Microenvironment, 2 Barts Cancer Institute, a Cancer Research UK of Excellence, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
• Thursday 10 July 2025, 13:00-14:00
• Venue: CRUK CI Lecture Theatre.
• Series: Cancer Research UK Cambridge Institute (CRUK CI) Seminars in Cancer; organiser: Kate Davenport.

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‘Unpicking the biology of healthy human nasal microbiome’

This Cambridge Immunology Network Seminar will take place on Thursday 3 July 2025, starting at 4:00pm, in the Ground Floor Lecture Theatre, Jeffrey Cheah Biomedical Centre (JCBC)

Speaker: Dr Ewan Harrison, Head of Respiratory Virus and Microbiome Initiative, Wellcome Trust Sanger Institute

Title: ‘Unpicking the biology of healthy human nasal microbiome’

Host: Menna Clatworthy, CITIID , Cambridge

Refreshments will be available following the seminar.

• Speaker: Dr Ewan Harrison, Wellcome Sanger Institute
• Thursday 03 July 2025, 16:00-17:00
• Venue: Lecture Theatre, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus.
• Series: Cambridge Immunology Network Seminar Series; organiser: Ruth Paton.

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Optimizing Data Delivery and Scalable HI Profile Classification for the SKA Era: Infrastructure and Science Challenges at the Spanish SRC

This talk presents ongoing work at the Spanish SKA Regional Centre (esSRC) in the context of the SRC Net 0.1. The first part focuses on the development of efficient data delivery techniques from the distributed Rucio-based storage system to the SRC infrastructure and, ultimately, to user workspaces. Several approaches have been evaluated to support science-ready access, yet current solutions often involve unnecessary data duplication in user areas, resulting in increased usage of storage and computational resources. To address this, we have prototyped mechanisms based on file linking, caching, and data reuse, enabling more efficient access paths for users. While these methods show promising improvements in terms of performance and resource usage, challenges remain, particularly in terms of orchestration, scalability, and compatibility with existing workload managers. The second part presents advances in the automated classification of neutral hydrogen (HI) profiles using machine learning methods, building on previous work [Parra et al., 2024, arXiv:2501.11657]. We outline a roadmap for extending these techniques to handle the data volumes expected from the SKA Observatory. This includes developing scalable pipelines capable of ingesting and processing large spectral datasets in a reproducible and efficient manner, and adapting the classification models to cope with the diversity and complexity of the SKA data products.

• Speaker: Dr. Manu Parra-Royón (Astrophysics Institute of Andalucia - Spanish National Research Council)
• Tuesday 08 July 2025, 11:15-12:00
• Venue: Coffee area, Battcock Centre.
• Series: Hills Coffee Talks; organiser: Charles Walker.

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The engineered lipid nanoparticles (NanoCa) demonstrate potent anti-tumor effects by activating type I interferons, promoting the maturation of dendritic cells, and enhancing antigen presentation.

Abstract

Immune checkpoint inhibitors have revolutionized cancer therapy; however, many patients exhibit suboptimal responses, which is due to inadequate T cell priming by the innate immune response. Metal ions play a critical role in modulating the innate immune response. However, the mechanisms by which metal ions facilitate dendritic cell maturation through the activation of interferon remain poorly understood. This research identifies a nanomaterial Calcium phosphate-containing liposome (NanoCa), characterized by an atypical crystal structure and pH-responsive profile. NanoCa promotes bone marrow-derived dendritic cell maturation and exhibits antiviral effects and anti-tumor properties in different tumor models. Also, NanoCa acts as an immunostimulant by fostering antibody production. Furthermore, when combined with programmed cell death 1 receptor (PD-1)  blocking antibodies, NanoCa synergistically enhances anti-tumor efficacy in CT26 models. Mechanistically, NanoCa rapidly releases Ca2+ via the lysosome pathway post-endocytosis, subsequently triggering interferon through the Ca2+-calcineurin (CaN) - nuclear factor of activated T cells 2 (NFATc2) - protein kinase C beta (PKCβ) - interferon regulatory factor 3 (IRF3) signal pathway. Single-cell RNA sequencing (scRNA-seq) shows NanoCa increases the population of tumoral infiltrating dendritic cell (DC), C1qc+ TAM, and CD8T_eff cells and decreases the CD8T_ex and immunosuppressive SPP1+ TAM population in tumor-draining lymph nodes. Overall, NanoCa shows translational potential for anti-tumor immune therapeutics.

1D PbI2 superlattice are synthesized utilizing an antisolvent diffusion method, in which demonstrates in-plane anisotropic phonon vibrations and optical transport characteristics. Leveraging on the anisotropic optical transport nature and effective coupling with vdWMs, filter-free polarization-sensitive photodetector comprising vdWMs and PbI2 superlattice waveguide are realized in a broad spectra range with linear dichroism ratio values of 1.43–1.73.

Abstract

The ability to detect polarimetric information of light over a broad spectra range is central to practical optoelectronic applications and has been successfully demonstrated with photodetectors of low-symmetry 2D van der Waals materials (vdWMs). However, polarization sensitivity within such a photodetectors remains elusive due to the limited diversity. To address this challenge, an approach is proposed by transforms 2D Lead iodine (PbI2) into 1D superlattice microwires (SLMs) through a solution-phase antisolvent diffusion method. This structural shifting enables the creation of low-symmetry crystal characteristics, a well-defined geometric microcavity structure, and an increased bandgap, which collectively confer anisotropic waveguide properties across visible and near-infrared wavelengths. By integrating PbI2 SLMs with isotropic 2D vdWMs, that waveguide-integrated photodetectors are demonstrated capable of polarization detection, achieving linear dichroism ratio (LDR) values of 1.66 at 405 nm for PbI2 photodetectors and 1.73 at 785 nm for WSe2 photodetectors. This paradigm-shifting strategy enables polarimetric information detection using isotropic vdWMs and advances the development of next-generation polarization-resolved optoelectronic devices.

The accumulation of stress leads to electrochemical-mechanical degradation, resulting in rapid capacity loss of solid-state batteries. A stress-adaptive graphene@selenium cathode is developed in this work to enhance ion transport and relieve mechanical stress in all-solid-state lithium-selenium batteries, enabling superior electrochemical performance.

Abstract

All-solid-state lithium-selenium batteries (ASSLSeBs) offer high energy density and improved safety for next-generation energy storage. Still, selenium cathodes suffer from large volume changes during cycling, leading to mechanical stress and rapid capacity fade. To address this, a stress-adaptive 2D graphene@Se composite cathode is developed, where small Se nanoparticles are anchored onto acid-treated expanded graphite (AcEG) to enhance charge transport and alleviate stress. Mechanical characterization confirms that the composite effectively mitigates Li-ion-induced strain. As a result, ASSLSeBs with this cathode achieve exceptional cycling stability with ultrahigh capacity retention after 4000 cycles at 2 C and stable performance for over 400 cycles even under high active-material loading. Furthermore, an all-solid-state Li-Se pouch cell with a record energy density of 376.8 Wh kg⁻¹ is demonstrated, the highest reported for ASSLSeBs. This work presents a strategy for designing stress-adaptive cathodes, enabling ultra-stable ASSLSeBs for practical applications.

Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE00262A, PaperJie Zhang, Dawei Yang, Canhuang Li, Qianhong Gong, Wei Bi, WEIHONG LAI, Shengjun Li, Yaojie Lei, Guangmin Zhou, Andreu Cabot, Guoxiu Wang
Single-atom catalysts (SACs) have become the key to overcoming the inherent limitations of lithium-sulfur (Li-S) batteries for their exceptional catalytic activity, high selectivity, and strong affinity towards lithium polysulfides (LiPSs)....
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A self-evolving discovery integrating automation and AI is developed to address the high-dimensional-parameter-space challenge in carrier biomaterials. The discovered biomaterials showed ultra-low nonspecific protein adsorption, achieving a 10 000-fold reduction in experiment workload; and they are further fabricated into microfluidic-used carriers for protein-analysis applications, showing a 9-fold enhancement in detection sensitivity. This study has potential for applications in single-cell analysis.

Abstract

Carrier biomaterials used in single-cell analysis face a bottleneck in protein detection sensitivity, primarily attributed to elevated false positives caused by nonspecific protein adsorption. Toward carrier biomaterials with ultra-low nonspecific protein adsorption, a self-evolving discovery is developed to address the challenge of high-dimensional parameter spaces. Automation across nine self-developed or modified workstations is integrated to achieve a “can-do” capability, and develop a synergy-enhanced Bayesian optimization algorithm as the artificial intelligence brain to enable a “can-think” capability for small-data problems inherent to time-consuming biological experiments, thereby establishing a self-evolving discovery for carrier biomaterials. Through this approach, carrier biomaterials with an ultra-low nonspecific protein adsorption index of 0.2537 are successfully discovered, representing an over 80% decrease, while achieving a 10 000-fold reduction in experiment workload. Furthermore, the discovered biomaterials are fabricated into microfluidic-used carriers for protein-analysis applications, showing a 9-fold enhancement in detection sensitivity compared to conventional carriers. This is the very demonstration of a self-evolving discovery for carrier biomaterials, paving the way for advancements in single-cell protein analysis and further its integration with genomics and transcriptomics.

This study presents a novel stochastic orientational encoding approach utilizing a nanoscopic film of a novel rod-shaped π-architecture, achieved through facile ambient-atmosphere solution processing. Energetically favorable molecular assembly, driven by directional multiple hydrogen-bonding motifs and uniaxial microcrystal growth, results in a woven-textured pattern with random 1D features. The rich variations in microcrystal domain properties and crystal orientations coupled with artificial coloration enable high encoding capacity in a single-material, solution-processed system.

Abstract

The prevention of counterfeiting and the assurance of object authenticity require stochastic encoding schemes based on physically unclonable functions (PUFs). There is an urgent need for exceptionally large encoding capacities and multi-level responses within a molecularly defined, single-material system. Herein, a novel stochastic orientational encoding approach is demonstrated using a facile ambient-atmosphere solution processing of a molecular thin film based on the rod-shaped oligo(p-phenyleneethynylene) (OPE) π-architecture. The nanoscopic film, derived from the small molecule 2EHO-CF3PyPE with donor, acceptor, and π-spacer building units, is designed for energetically favorable uniaxial molecular assembly and crystal growth via directional multiple hydrogen-bonding motifs at the molecular termini and short C─H···π contacts at the center. A facile solvent vapor annealing induces concurrent dewetting and microscopic 1D random crystallization, yielding a woven-textured random features. Using convolutional neural networks, the rich variations in microcrystal domain properties and stochastic encoding of 1D crystal orientations generate artificial coloration, achieving an encoding capacity reaching (6.5 × 10⁴)(2752 × 2208). The results demonstrate an effective strategy for achieving ultrahigh encoding capacities in a thin film composed of a single-material. This approach enables low-cost, solution-processed fabrication for mass production and broad adoption, while opening new opportunities to explore molecular-PUFs through structural design and engineering noncovalent interactions.

A symmetry-protected Z₂ non-Hermitian skin effect (NHSE) is experimentally demonstrated in acoustic metamaterials. By implementing projective mirror symmetry—which enables pseudospins in spinless systems—both uniform and bidirectional Z₂ NHSEs characterized by different accumulation directions are observed. Active feedback circuits provide the requisite non-Hermitian gain/loss, establishing a platform for topological wave manipulation.

Abstract

Non-Hermitian skin effect (NHSE), where eigenstates localize at the boundary of non-Hermitian lattices, has gained significant attention in various fields. This phenomenon, driven by the point-gap topology of complex energy bands, occurs even without special symmetries. Nevertheless, additional symmetry may significantly enrich the NHSE. Notably, time-reversal symmetry protects a Z2 NHSE, featuring oppositely accumulated skin modes. Here, a 1D bilayer Z2 NHSE model based on projective mirror symmetry is proposed, making Z2 NHSE possible in spinless systems. Experimentally, both uniform and bidirectional Z2 NHSEs are observed in acoustic metamaterials, where the necessary non-Hermitian elements—gain and loss—are achieved through active feedback circuits. These findings open new avenues for exploring symmetry-enriched non-Hermitian topological phenomena and pave the way for potential applications in wave manipulation, sensing, and beyond.

A nanocrystal-nucleus template strategy addresses nanoscale phase separation and energy-level mismatch in wide-bandgap perovskite solar cells. By tailoring nanocrystals to match the target perovskite's composition and structure, this approach enables uniform halide distribution, enhanced crystallization, and improved electron extraction. The strategy achieves 23.4%-efficient PSCs (1.68 eV) with a record V OC of 1.30 V and certified 31.7%-efficient perovskite/silicon tandem solar cells.

Abstract

Wide-bandgap (WBG) perovskite solar cells (PSCs) are critical for advancing tandem solar cell efficiencies, yet suffer from severe photovoltage deficits and halide segregation, substantially degrading their performance and stability. Here, a nanocrystal-nucleus template (NCNT) strategy is developed to directly addresses heterogeneous nucleation—the root cause of phase separation—by precisely matching the I/Br ratio of nanocrystal to that of the target perovskite film. This approach guides homogeneous assembly of Pb-I/Br octahedra, achieving exceptional halide uniformity and precise crystallization control for WBG films. The NCNT simultaneously induces p-type doping and reduces the perovskite/C60 interfacial energy barrier, significantly enhancing charge extraction. Remarkably, 1.68-eV WBG PSCs fabricated via this approach achieve a record open-circuit voltage (VOC) of 1.30 V, alongside a champion efficiency of 23.4%. The broad applicability of this strategy is demonstrated across a wide bandgap range of 1.63–1.76 eV, all exhibiting (001)-preferred orientation and exceptional photostability. When integrated into a 0.945 cm2 monolithic perovskite/silicon tandem solar cell, the NCNT-based device delivers a high efficiency of 32.0% (certified 31.7%). This work highlights the pivotal role of nanocrystals in regulating perovskite crystallization, resolves long-standing VOC limitations in WBG perovskites, and establishes a scalable platform for next-generation optoelectronic devices and tandem photovoltaics.

Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE01118C, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Patricia Mayer, Florian Joseph Baader, David Yang Shu, Ludger Leenders, Christian Zibunas, Stefano Moret, André Bardow
The chemical industry's transition to net-zero greenhouse gas (GHG) emissions is particularly challenging due to the carbon inherently contained in chemical products, eventually released to the environment. Fossil feedstock-based production...
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Nature Materials, Published online: 03 July 2025; doi:10.1038/s41563-025-02272-0

Materials design and informatics have become increasingly prominent over the past several decades. Using the Materials Project as an example, this Perspective discusses how properties are calculated and curated, how this knowledge can be used for materials discovery, and the challenges in modelling complex material systems or managing software architecture.

Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D5EE02462E, Paper Open Access &nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.Junke Wang, Shuaifeng Hu, Zehua Chen, Zhongcheng Yuan, Pei Zhao, Akash Dasgupta, Fengning Yang, Jin Yao, MInh Anh Truong, Gunnar Kusch, Esther Hung, Nick R. M. Schipper, Laura Bellini, Guus J. W. Aalbers, Zonghao Liu, Rachel Oliver, Atsushi Wakamiya, Rene A J Janssen, Henry Snaith
Improved understanding of heterojunction interfaces has enabled multijunction photovoltaic devices to achieve power conversion efficiencies that exceed the detailed-balance limit for single-junctions. For wide-bandgap perovskites, however, the pronounced energy loss...
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