Nanoscience News (<front>)

Correlations of the Möbius function

I will survey recent progress on Chowla’s conjecture on the correlations of the Möbius function. I will discuss some of the methods that have been used to approach this conjecture, and how these methods have turned out to be useful also for some other problems in additive combinatorics and ergodic theory.

• Speaker: Joni Teräväinen (University of Cambridge)
• Wednesday 28 May 2025, 13:30-15:00
• Venue: MR4, CMS.
• Series: Discrete Analysis Seminar; organiser: Julia Wolf.

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Hope in Hard Places: Bridging the Cancer Care Gap in Resource Limited Settings: Lessons and Innovations from the Uganda Cancer Institute

Initial support by the British Empire Cancer Campaign in Uganda led to the description of Burkitt Lymphoma and subsequently to the establishment of the Uganda Cancer Institute (UCI). The Uganda Cancer Institute was established in 1967 as a result of a collaboration between Makerere University, the Ministry of Health and the US National Cancer Institute. It was established as a treatment centre for the then recently discovered Burkitt Lymphoma, and was expanded in 1969 to cater for all cancer. The Institute participated in the seminal initial studies on combination chemotherapy. However, years of political turmoil led to a steady decline in care, research and training. Over the past ten years, the UCI has been building capacity address the cancer care gap and here we describe some of the steps taken towards this effort. The Institute has expanded clinical care capacity, increase human resource capacity and is currently building a cancer research and innovation facility. The Institute is undertaking high quality research and here we describe Our model could also serve other developing countries in building capacity for cancer care and research to address the growing burden of cancer in LMI Cs.

• Speaker: Nixon Niyonzima, Uganda Cancer Institute
• Thursday 19 June 2025, 13:00-14:00
• Venue: CRUK CI Lecture Theatre.
• Series: Cancer Research UK Cambridge Institute (CRUK CI) Seminars in Cancer; organiser: .

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Advanced Materials, Volume 37, Issue 21, May 26, 2025.

Multidimensional-Encrypted Meta-Optics Storage

By introducing a single-cell order-decoupling method and enabling simultaneous four-dimensional optical parameter manipulation, the meta-optics storage system developed by Zhongyang Li and co-workers achieves multidimensional optical encryption. This platform supports 16-channel encrypted holographic images with low crosstalk and high fidelity, demonstrating significant potential for advanced optical information security and storage applications. More details can be found in article number 2419322.

Metal-Polyphenol Meat Freshness Intelligent Monitoring Platform

In article number 2503246, Yunfei Xie, Tiancong Zhao, and co-workers propose for the first time a multi-level competitive coordination chromogenic mechanism between metal, polyphenol, and amine. The metal-polyphenol network colorimetric sensor array (MPN-CSA) developed based on this has excellent stability, specificity, and economic environmental benefits. Combined with convolutional neural network technology, it can achieve sensitive, accurate, and real-time online intelligent monitoring of meat freshness.

Residue-Free Fabrication of 2D Materials

In article number 2418669, Minyoung Lee, Changho Kim, Jae Hun Seol, and co-workers report a residue-free fabrication technique for 2D materials using van der Waals interactions. This approach allows for the isolation and precise manipulation of residue-free 2D materials while preserving their intrinsic properties. The technique enhances the performance and versatility of 2D material-based electronic and optoelectronic devices.

Stretchable Electronics

The stretchable circuit can resist compression and autonomously repair circuit cracks by filling a micropillar-embedded channel with a biphasic liquid-solid metal. More details can be found in article number 2420469 by Jian Lv, Jinyou Shao, and co-workers.

Nature Energy, Published online: 27 May 2025; doi:10.1038/s41560-025-01788-8

Na and Ti share roles

Nature Energy, Published online: 27 May 2025; doi:10.1038/s41560-025-01789-7

Contamination control

Title to be confirmed

Abstract not available

• Speaker: Dr Zac Goodwin (Oxford)
• Wednesday 04 June 2025, 16:00-17:30
• Venue: Seminar Room 3, RDC.
• Series: Theory of Condensed Matter; organiser: Bo Peng.

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Modularity of certain trianguline Galois representations

An unpublished result of Emerton states that every trianguline representation of the absolute Galois group of Q, satisfying certain conditions, arises as a twist of the Galois representation attached to an overconvergent p-adic cuspidal eigenform of finite slope. I will outline a new approach to prove this result by patching trianguline varieties and eigenvarieties for modular forms on GL2 to establish an “R=T” theorem in the setting of rigid analytic spaces. There are several nice consequences to such a theorem, including a new approach to deduce the classicality of overconvergent eigenforms of small slope, as well as applications to the Fontaine-Mazur conjecture.

• Speaker: James Kiln (Queen Mary)
• Tuesday 27 May 2025, 14:30-15:30
• Venue: MR13.
• Series: Number Theory Seminar; organiser: Jef Laga.

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This work systematically summarizes the development of synaptic devices with negative photoconductivity (NPC) phenomena. Material systems, device structures, and mechanisms of NPC effect-based devices are summarized for designing high-performance neuromorphic electronics. The prospect and challenge are deeply discussed for advanced application scenarios, which provides valuable guidance for next-generation optoelectronic in-sensor neuromorphic computing devices.

Abstract

The emerging optoelectronic devices with positive photoconductivity (PPC) and negative photoconductivity (NPC) have promoted the development of high-performance photodetectors, non-volatile photoelectric memory, and neuromorphic computing. With advantages of high bandwidth, low power consumption, and parallel computing, NPC effect-based optoelectronic devices show great application potential in logic gates, in-sensor computing, and artificial visual systems. Material systems, device structures, and mechanisms of NPC effect-based devices are summarized for designing high-performance neuromorphic electronics. The evaluation parameters of the photoelectric properties, memory capabilities, and synaptic plasticity of optoelectronic devices are discussed for the realization of high-efficiency neuromorphic computing. Hardware and software operation of in-sensor computing for neuromorphic computing using NPC effect-based devices are systematically summarized to provide insights into future applications. The prospect and challenge are deeply discussed for advanced application scenarios, which provides valuable guidance for next-generation optoelectronic in-sensor neuromorphic computing devices.

A self-healing, recyclable polyurethane-based conductor (DACPU/100Li) is engineered via supramolecular and dynamic covalent networks, exhibiting ionic conductivity (1.23 × 10− 3 S cm−1), tensile strength (7.62 MPa), 1200% stretchability, and tear resistance (45.6 kJ m− 2). Its sensor enables machine-learning-assisted gesture recognition (sensitivity 5.89, strain 0.1–1000%), while its triboelectric nanogenerator harvests energy (3.87 W m− 2) and supports machine-learning-assisted object recognition.

Abstract

Flexible ionic conductors hold potential for wearable sensors and energy harvesting. However, most gel-based conductors suffer from solvent evaporation and liquid leakage, limiting practical applications. Although solid-state ionic conductors mitigate these issues, achieving strong mechanics, high conductivity, self-healing, and stability remains challenging. Here, by integrating supramolecular engineering and dynamic covalent adaptive networks, a self-healing polyurethane-based solid-state ion-conductive elastomer (DACPU/100Li) with outstanding overall properties is successfully synthesized. DACPU/100Li exhibits ultrahigh ionic conductivity (1.23 × 10− 3 S cm−1) and high tensile strength (7.62 MPa), along with an elongation at break of 1200%. Additionally, it exhibits excellent tear resistance and a fracture energy of 45.6 kJ m− 2, along with 96% self-healing efficiency (after self-healing at 120 °C for 24 h), good recyclability, and stability under extreme conditions. The DACPU/100Li-based sensor has high sensitivity (5.89) and a wide strain range (0.1–1000%). Integrated with machine learning, it enables precise gesture recognition and human–machine interaction. Furthermore, the triboelectric nanogenerator based on DACPU/100Li achieves a high power density of 3.87 W m− 2. It harvests energy from body motion to power small devices and aids object recognition via machine learning. It is believed that these solid-state ion-conductive elastomers provide new opportunities for wearable electronics, energy harvesting, and ionotronics.

Advanced Materials, EarlyView.

Solar-driven interfacial water evaporation is a sustainable water treatment technology for desalination. This review highlights the advantages of biomass materials in solar evaporators, discussing their unique structures, light absorption, and thermal conductivity. It covers design principles, performance enhancement strategies, and recent advancements in biomass-based evaporators. Challenges and future directions for biomass-based evaporators are also summarized.

Abstract

Solar-driven interfacial water evaporation is a green and energy-efficient water treatment technology with diverse applications in desalination, steam power generation, and agricultural irrigation. Biomass materials have gained significant attention in solar evaporator engineering due to their unique structure, low cost, and ease of adjustment. With enhanced light absorption and high thermal conductivity, biomass materials can improve evaporation efficiency substantially, thus providing opportunities in solar evaporation applications. Therefore, in this critical review, the operating principles and design concepts of solar evaporators are first briefly discussed in terms of the photothermal conversion mechanism. Subsequently, the superiority of biomass materials in solar evaporator design is described in detail from the types of biomass and their structural properties at micro/macro scales. The design principles and corresponding performance enhancement strategies for biomass-based evaporators are also highlighted, including material selection, structural design, and thermal management techniques. Meanwhile, recent advances in biomass-based evaporators for several cutting-edge applications are comprehensively discussed. This review can provide a comprehensive reference for the relevant researchers to advance the research and application of biomass-based solar evaporators and to promote their wide application in the field of green technology.

A heterogeneous liquid-crystal superstructure is proposed to activate higher optical dimensions in soft matter. Multilevel optical information is precisely encoded into the superstructure through a new strategy called multidimensional photopatterning. Consequently, near-field full-color printing and far-field full-color holography are achieved simultaneously with brightness controllability and spin selectivity. This facilitates the exquisite construction of LC superstructures and enlightens higher-dimensional optics.

Abstract

Soft matter, featuring superior flexibility and intriguing tunability, has shown enormous potential in sensors, soft robots, and light tailoring. However, limited by its inherent structural complexity, soft matter remains uncompetitive in multidimensional and high-density information optics. Herein, a heterogeneous liquid-crystal (LC) superstructure composed of interlocked nematic and chiral LCs is designed to achieve higher-dimensional light control. Optically multidimensional photopatterning with programmable UV polarization and dosage is proposed to precisely customize both transverse and longitudinal LC arrangements, bringing in a wide range of light-matter interactions within a single micrometer-thick film. The constructed heterogeneous LC superstructure not only enables simultaneous near-field full-color printing and far-field full-color holography but also boasts brightness controllability and polarization selectivity. This low-cost photonic structure enables a high information density of ≈1.6 million hybrid-dimensional optical data per square millimeter, unlocking new capabilities in optical storage, display, and encryption. This work creates an ingenious bond between advanced photopatterning technologies and higher-level optical informatics, and pioneers soft-matter-mediated full-dimensional optics.

Latent Concepts in Large Language Models

Large Language Models (LLMs) have achieved remarkable fluency and versatility—but understanding how they represent meaning internally remains a challenge. In this talk, we explore the emerging science of latent concepts in LLMs: the semantic abstractions implicitly encoded in their internal activations.

We examine how concepts—such as truthfulness, formality, or sentiment—can be represented as low-dimensional structures, discovered through training dynamics, and understood through the lens of linear algebra and associative memory. We discuss the implications for interpretability, robustness, and control, including how concepts can be steered at test time to adjust model behavior without retraining. Specifically, we explore empirical and theoretical evidence supporting the linear representation hypothesis, where such concepts correspond to vectors or affine subspaces, emerging naturally from training dynamics and next-token prediction objectives. We further show that LLMs behave as associative memory systems, retrieving outputs based on latent similarity rather than logical inference. This behavior underlies phenomena such as context hijacking, where semantically misleading prompts can bias the model’s response.

We introduce formal latent concept models that unify these ideas, describe conditions under which concepts are identifiable, and propose learning algorithms for extracting interpretable, controllable representations. We argue that such latent concept modeling offers a principled framework for bridging representation learning with interpretability and model alignment, and offers a promising path toward safer, more controllable, and more trustworthy AI.

• Speaker: Prof. Pradeep Ravikumar, Carnegie Mellon University
• Tuesday 10 June 2025, 14:00-15:00
• Venue: JDB Seminar Room, CUED.
• Series: Signal Processing and Communications Lab Seminars; organiser: Prof. Ramji Venkataramanan.

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Nature Nanotechnology, Published online: 26 May 2025; doi:10.1038/s41565-025-01927-y

Ferroelectric membranes of BaTiO3 can form centre-convergent polar topology domes that couple with light to generate circularly polarized beams.

Title to be confirmed

Abstract not available

• Speaker: Amila Jayasinghe, University of Cambridge
• Friday 13 June 2025, 15:00-16:00
• Venue: CivEng Seminar Room (1-33) (Civil Engineering Building).
• Series: Engineering Department Structures Research Seminars; organiser: Shehara Perera.

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Title to be confirmed

Abstract not available

• Speaker: Keith Seffen, University of Cambridge
• Friday 20 June 2025, 15:00-16:00
• Venue: CivEng Seminar Room (1-33) (Civil Engineering Building).
• Series: Engineering Department Structures Research Seminars; organiser: Shehara Perera.

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