Nanoscience News (<front>)

As use of artificial intelligence (AI) becomes more widespread, machine systems are increasingly required not only to display artificial intelligence but artificial morality too. AI is already used to aid decisions about life support, criminal sentencing, and the allocation of scarce medical resource, and so-called “moral machines” are even being thought to be able to act as “artificial moral advisors” by giving moral advice and helping to improve human moral decision making. In this talk, I will explore what it means to trust AI in the moral domain. Drawing on insights from social psychology and moral cognition, I will discuss how people conceptualise trust in AI, how judgments of effectiveness and ethicality intertwine, and how perceptions of intelligence shape attributions of morality. I will consider how people trust “artificial moral advisors,” and how people trust other humans who rely on AI for socio-relational tasks. Drawing on these findings, I will ask whether – and in what sense – we should place trust in ‘moral’ machines, and what kind of future we are willing to accept as AI takes on roles that shape not only our decisions, but our relationships, values, and humanity itself.

Host: Prof Simone Schnall (ss877@cam.ac.uk)

This talk will be recorded and uploaded to the Zangwill Club Youtube channel in due course.

• Speaker: Prof Jim A.C. Everett, University of Kent
• Friday 31 October 2025, 16:30-18:00
• Venue: Ground Floor Lecture Theatre, Department of Psychology.
• Series: Zangwill Club; organiser: Psychology Reception.

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In this talk I will present two strands of studies where we investigated two prominent mechanisms suggested to underlie human episodic memory. First, Hebbian learning (i.e “fire-together, wire together”) or Spike-Timing-Dependent-Plasticity (STDP), which posits that the firing of neurons in close temporal proximity is crucial for laying down a memory trace. Recording the co-firing of single-neuron in epilepsy patients in the medial-temporal-lobe during a memory task we found results that are consistent with STDP . I will also show results from rhythmic stimulation studies demonstrating that the manipulation of temporal patterns in the range of milliseconds modulates episodic memory formation. A second idea that has influenced memory research is the “Indexing Theory” which posits that the human hippocampus stores episodic memories via an Index – an agnostic conjunctive type of code that points to the different elements that belong to the episode. I will present recent evidence from human single neuron recordings where we found neurons that are consistent with such an indexing function. I will also present unpublished results from an ultra-highfield fMRI at 7T which support these human single unit findings and suggest that the Index is predominantly located in the hippocampal subfield CA3 . I will close the talk by presenting a recent theoretical framework where we integrate these findings with Concept Cells (so-called Jennifer Anniston cells) and the Engram Allocation Theory. At the end I will speculate how results from both streams could lead to the development of novel treatment for patients with memory problems.

Host: Denes Szucs (ds377@cam.ac.uk)

This talk will be recorded and uploaded to the Zangwill Club Youtube channel in due course.

• Speaker: Prof Simon Hanslmayr, University of Glasgow
• Friday 24 October 2025, 16:30-18:00
• Venue: Ground Floor Lecture Theatre, Department of Psychology.
• Series: Zangwill Club; organiser: Psychology Reception.

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In parallel with other species, humans possess a remarkable ability to encode detailed spatial information about our environments, forming cognitive maps that enable inference and generalisation for goal-directed behaviour. Long linked to the hippocampal-entorhinal system, growing evidence now suggests that the neural mechanisms supporting spatial navigation also extend to abstract domains, involving a broader network of cortical regions. In this talk, I will propose that the default mode network (DMN), traditionally associated with mind-wandering and self-referential processing, plays a domain-general role in constructing and traversing cognitive maps: structured representations of relational knowledge that span both spatial and non-spatial domains. I will present recent findings from our lab using ultra-high-field 7T fMRI, showing how spatial learning and memory are encoded across the DMN during navigation in virtual environments, and how these same regions organize conceptual knowledge along interpretable representational axes to support abstract mental navigation. Together, these results suggest that the DMN implements a unified computational architecture for mapping space, memory, meaning, and value. This framework bridges classical theories of cognitive maps with contemporary systems neuroscience and offers translational insights into disorders such as Alzheimer’s disease, where both spatial navigation and DMN function are compromised.

Host: Prof Trevor Robbins (twr2@cam.ac.uk)

This talk will be recorded and uploaded to the Zangwill Club Youtube channel in due course.

• Speaker: Dr Deniz Vatansever, Fudan University
• Friday 17 October 2025, 16:30-18:00
• Venue: Ground Floor Lecture Theatre, Department of Psychology.
• Series: Zangwill Club; organiser: Psychology Reception.

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In this Zangwill seminar, I explore how the brain regulates emotion—what goes wrong in disorders like depression and ADHD , and how we can measure affective states across species with increasing precision. From mouse genetic models of attention deficits focused on the developing hippocampus to neural signatures of pain-induced depression, we uncover how emotional dysregulation takes shape at the molecular, cellular, and systems level. For example, we consider the affective consequences of chronic pain, where both human imaging and rodent studies reveal early hippocampal changes, including enhanced neurogenesis and microglial modulation, as potential contributors to depression. We also harness deep learning to decode facial expressions in animals, revealing moments of pleasure, fear, and altered states—and extend this work to humans by tracking how young children express emotion and curiosity in natural social settings. Combining genetics, neuroimaging, behavior, and AI, this talk offers a multi-layered perspective on “hot” cognition and its neural underpinnings, opening new doors for early detection and intervention in affective and developmental disorders.

Host: Prof Trevor Robbins (twr2@cam.ac.uk)

This talk will be recorded and uploaded to the Zangwill Club Youtube channel in due course.

• Speaker: Dr Xiao Xiao, Fudan University
• Friday 17 October 2025, 13:00-14:30
• Venue: Ground Floor Lecture Theatre, Department of Psychology.
• Series: Zangwill Club; organiser: Psychology Reception.

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Abstract not available

• Speaker: Parth Shimpi, University of Glasgow
• Wednesday 05 November 2025, 14:15-15:15
• Venue: CMS MR13.
• Series: Algebraic Geometry Seminar; organiser: Dhruv Ranganathan.

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Turing-Patterned Substrates

The untapped potential of Turing patterns in surface-enhanced Raman spectroscopy (SERS) offers a transformative frontier. This illustration shows that Turing-nanoarchitected Ag needle enables dual-scale enhancement via mesoscopic light manipulation and microscopic molecular enrichment. Moreover, the injector-integrated design further unveils remarkable promise for field-deployable SERS diagnostics in solid matrices. More details can be found in article number 2506426 by Wei Ji, Yukihiro Ozaki, Yunfei Xie, and co-workers.

Exploring Neurotransmitter Dynamics

Optical investigation of molecular dynamics occurring within the biomimetic human biosensor system, especially under water environment, has been regarded as a challenging area of study. Based on the great advantage of spectral capabilities of terahertz spectroscopic tools, a unique biosensing platform has been proposed assisted by nanodisc-hybridized nanoscale metasurfaces. The sensing capability was determined to enable the receptor-ligand interactions occurring at optical hotspots, where the terahertz field was strongly localized and greatly enhanced, and controlled by targeting specific frequency of the metasurface. More details can be found in article number 2504858 by Hyun Seok Song, Minah Seo, and co-workers.

Triboelectric Nanogenerators

This illustration highlights polyelectrolyte-based triboelectric nanogenerators that achieve tunable tribopolarity and enhanced environmental stability through covalently fixed ionic groups. Systematic variation of polycation and polyanion compositions with different cations and anions enables consistent ion redistribution and predictable polarity shifts along the triboelectric series. This strategy provides a versatile and modular platform for stable energy-harvesting devices under heat and humidity. More details can be found in article number 2505547 by Ju-Hyuck Lee, Wonho Lee, and co-workers.

Morphing Matter Soft Robot

This cover illustrates a morphing matter soft robot controlled by remote electric fields. The robot is made of an elastomeric composite with nano paracrystalline carbon. When exposed to a nonuniform electric field, dielectrophoretic forces causes the robot to locomote, bend, stretch, and twist. Simultaneously, charge concentrations at the ends of the robot result in like-charge repulsion and finger-like protrusions. Soft morphing matter exhibits attractive remote-control morphogenetic actuation for next-generation soft robots. More details can be found in article number 2419077 by Ciqun Xu, Charl Faul, Majid Taghavi, and Jonathan Rossiter.

In Materia Reservoir Computing

Light-induced molecular dynamics in azopolymers can be exploited for data storage and neuromorphic-type of data processing, emulating a wide range of synaptic functionalities including long-term, short-term and visual memory. The adaptiveness of this light-responsive material can be exploited for spatiotemporal event detection and visual motion perception tasks, as well as for in-materia implementation of reservoir computing. More details can be found in the Research Article by Gianluca Milano, Angelo Angelini, and co-workers (DOI: 10.1002/adma.202501813).

Detachable Electronics

In article number 2506729, Eun Kwang Lee, Hocheon Yoo, and co-workers present an OECT device that mimics synaptic behavior using a P3HT-based π-ion film reinforced with a mesh support layer. The device is applied to reservoir computing and biosensing tasks. Its detachable and reusable nature offers a new paradigm for eco-friendly, modular device architectures.

Heterojunction-Driven Stochasticity

In article number 2505150, Hocheon Yoo and co-workers present a bi-heterojunction noise-enhanced negative transconductance transistor, which amplifies intrinsic noise and entropy throughput. This enables the generation of multi-bit true random numbers from amplified intrinsic noise, which are then used as latent vectors to drive high-fidelity image synthesis.

The fascinating properties of LCEs demonstrate outstanding potential in biomimetic soft robots. From the novel perspective of integrated material–structure–function interrelationship, this paper systematically reviewed the latest research progress of biomimetic LCE soft actuators, including plant-inspired biomimetic shape-morphing of LCEs, animal-inspired biomimetic locomotion of LCEs, and bionic intelligent color-changing of LCEs. The potential application prospects and challenges of bio-inspired LCE soft actuators are discussed.

After 30 years of development, liquid crystal elastomer (LCE) biomimetic soft robots have been engineered to possess the capability to mimic and surpass the locomotion of soft organisms. However, most of the current reviews on LCEs are focused on their material/alignment design, fabrication technologies, actuation mechanisms, and applications. The latest research progress of biomimetic LCE soft actuators is systematically reviewed here from a novel perspective of material–structure–function interrelationship, which includes plant-inspired biomimetic shape-morphing of LCEs, animal-inspired biomimetic locomotion of LCEs, and bionic intelligent color-changing of LCEs. In addition, the potential application prospects and challenges of bio-inspired LCE soft actuators are discussed, where further in-depth research is required. Directions and valuable insights are provided for subsequent research efforts. This paper offers an inspiring and critical overview of the significant progress in the field of smart biomimetic LCE soft robotics and provides an available guide for researchers who are considering entering the exciting domain of LCE soft actuators.

Metal-free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two-electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation-based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports, multivariate statistics, and explainable machine learning integrated with operando spectroscopy to identify accurate catalytic descriptors for rational catalyst development.

Electrochemical synthesis of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction (2e− ORR) has emerged as an environmentally friendly alternative to the traditional anthraquinone process. Metal-free carbon catalysts, featuring tunable structures, readily available precursors, and excellent stability, have garnered significant attention for sustainable H2O2 production. However, despite extensive investigations, the precise mechanisms underlying catalytic selectivity on these carbon materials remain unclear and highly debated. Previous mechanistic interpretations frequently attribute catalytic activity to specific oxygen functional groups or heteroatom dopants through correlation-driven hypotheses and simplified theoretical models. Such approaches often overlook the intrinsic complexity of carbon surfaces, where multiple variables, including dopant types, defect structures, surface groups, and hybridization states, coexist and interact simultaneously, leading to contradictory conclusions. This review critically examines the limitations of these traditional approaches and emphasize the need of systematic experimental designs that independently vary structural parameters, along with advanced analytical methods capable of resolving active-site ambiguity, are critically reviewed. Recent developments employing orthogonal material libraries, rigorous experimental controls, catalyst passport metadata, and advanced multivariate and meta-analytical tools have emerged as robust frameworks for bias-resistant catalyst design. Integrating explainable and generative machine learning models with operando spectroscopy provides a robust, end-to-end approach for identifying and validating accurate catalytic descriptors.

This review focuses on the recent development of thermally actuated soft robotics, highlighting the four major heating mechanisms, as well as structural designs, thermal management, material innovations, and emerging applications. A summary and outlook section present the current challenges of thermally actuated soft robots and the future directions to address these challenges.

Soft robots with exceptional adaptability and versatility have opened new possibilities for applications in complex and dynamic environments. Thermal actuation has emerged as a promising method among various actuation strategieis, offering distinct advantages such as programmability, light weight, low actuation voltage, and untethered operation. This review provides a comprehensive overview of soft thermal actuators, focusing on their heating mechanisms, material innovations, structural designs, and emerging applications. Heat generation mechanisms including Joule heating, electromagnetic induction, and electromagnetic radiation and heat transfer mechanisms such as fluid convection are discussed. Advances in materials are grouped into two areas: heating materials, primarily based on nanomaterials, and thermally responsive materials including hydrogels, liquid crystal elastomers, and shape-memory polymers. Structural designs, such as extension, bending, twisting, and 3D deformable configurations, are explored for enabling complex and precise movements. Applications of soft thermal actuators span environmental exploration, gripping and manipulation, biomedical devices for rehabilitation and surgery, and interactive systems for virtual/augmented reality and therapy. The review concludes with an outlook on challenges and future directions, emphasizing the need for further improvement in speed, energy efficiency, and intelligent soft robotic systems. By bridging fundamental principles with cutting-edge applications, this review aims to inspire further advancements in the field of thermally actuated soft robotics.

This review presents a comprehensive overview of 3D-printed electrochemical energy storage devices, including batteries, supercapacitors, and fuel cells. It covers recent progress in ink formulation, printing techniques, and device integration, with a focus on microscale precision and structural complexity. Future directions highlight AI-guided hybrid 3D printing for customizable, multifunctional, and shape-adaptable energy storage systems.

3D printing (3DP) has emerged as a transformative technology for the fabrication of electrochemical energy storage devices (EESDs), offering unprecedented advantages in design freedom, shape conformality, and material versatility. Unlike previous reviews that narrowly focus on specific materials or device types, this review offers a comprehensive and integrative perspective on the role of 3DP across the full architecture of EESDs, including batteries, supercapacitors, and fuel cells. Recent advances are highlighted in ink formulation strategies tailored for electrochemical functionality, advanced printing techniques enabling microscale precision and structural complexity, and the integration of printed components into functional devices. In discussing future directions, particular emphasis is placed on artificial intelligence (AI)-guided hybrid 3DP approaches that enable the simultaneous use of multiple materials and printing methods within a single process, facilitating the creation of customizable, multifunctional, and shape-adaptable EESDs. By outlining key opportunities and ongoing challenges, this review aims to provide a comprehensive roadmap for the future development of 3D-printed electrochemical energy storage technologies.

This review explores the emerging field of non-crystalline MOFs - amorphous, liquid, and glassy forms - highlighting how they differ from traditional crystalline MOFs. It discusses their unique synthesis strategies, fundamental principles, and diverse applications. The paper also addresses current challenges andindustrial potential, offering insights into future directions and the transformative role of computational tools in their development.

The concept of non-Crystalline Metal–Organic Frameworks (MOFs) is both theoretically exciting and rich in potential applications. Since their conceptual introduction, research in this field has experienced significant growth. This review provides a comprehensive overview of the design, synthesis, and applications of non-crystalline MOFs, highlighting the current state of the art. It examines the fundamental principles of non-crystalline MOFs, the various synthetic approaches, and the nature of non-crystalline MOFs. Additionally, the review outlines their pathway from the laboratory to industrial applications, emphasizing challenges and opportunities for further development.