Octopus Tentacle‐Inspired In‐Sensor Adaptive Integral for Edge‐Intelligent Touch Intention Recognition
Inspired by the octopus cerebellum on its tentacles, a reconfigurable and adaptive intelligent touch sensor is proposed. It epitomizes touch strategic innovation by integrating a geometric progression structure that not only enhances deformability but also embeds an integral in-sensing mechanism. The work provides ground-breaking insight into the in-sensor computing and adaptive structure design strategies for advancing deformable multitouch electronics.
Abstract
Electronics continue to drive technological innovation and diversified applications. To ensure efficiency and effectiveness across various interactive contexts, the ability to adjust operating functions or parameters according to environmental shifts or user requirements is highly desirable. However, due to the inherent limitations of nonadaptive device structures and materials, the current development of touch electronics faces challenges, e.g., limited hardware resources, poor adaptability, weak deformation stability, and bottlenecks in sensing data processing. Here, a reconfigurable and adaptive intelligent (RAI) touch sensor is proposed, inspired by octopus's tentacle cognitive behavior. It realizes remarkable deformability and highly efficient multitouch interactions. The geometric progression structure of the sensing element equips the RAI touch sensor with a unique integrated-in-sensing mechanism and programmable logic. This greatly compresses sensing data dimensionality at the edge, yielding concise and undistorted interactive signals. By leveraging the advantages of hard-soft bonding and interface modulation of functional materials, the adaptability is achieved with a 200% strain range a 180° twist tolerance, and exceptional deformation stability of >10 000 cycles. The diverse application-specific configurations of the RAI touch sensor, enable a dynamic intention recognition accuracy of over 99%, advancing next-generation Internet of Things and edge computing research and innovation.
Fri 02 May 14:00: Frontiers in Embodied AI for Autonomous Driving
Over the last decade, we’ve seen unprecedented progress in AI across many disciplines and applications. However, autonomous vehicles are still far from mainstream even after billions of dollars of investment. In this talk we’ll explore what’s been holding progress back, and how by adopting a modern embodied AI approach to the problem, Wayve is finally unlocking the potential of scalable autonomous driving across the globe.
We’ll also explore some of our latest research in multimodal learning to combine the power of large language models with the driving problem, and in controllable generative world models as learned simulators.
Bio: Jamie leads Wayve’s Science department, where he guides our research teams to unlock new research breakthroughs, to enable those breakthroughs to have meaningful impact for the business, and to disrupt both our technical and business strategy to ensure Wayve stays at the forefront of innovation. Jamie has been at the forefront of applied AI research for the past 20 years. Before joining Wayve, Jamie was Partner Director of Science at Microsoft and Head of the Mixed Reality & AI Labs. While at Microsoft, Jamie shipped foundational features for Microsoft’s Kinect (Microsoft’s line of motion sensing input devices) and the hand- and eye-tracking that enable HoloLens 2’s interaction model (smart glasses). Jamie has a PhD in computer vision from the University of Cambridge and has received multiple Best Paper and Best Demo Awards at top-tier academic conferences. He was elected a Fellow of the Royal Academy of Engineering in 2021.
- Speaker: Jamie Shotton, Wayve
- Friday 02 May 2025, 14:00-15:00
- Venue: Computer Lab, LT1.
- Series: Cambridge ML Systems Seminar Series; organiser: Sally Matthews.
Signal Converter‐Based Therapy Platform Promoting Aging Bone Healing by Improving Permeability of the Mitochondrial Membrane
GelMA microspheres integrated with polydopamine-coated gold nanorods (GMPG) respond to ultrasound stimulation, converting it into biochemical signals that stimulate senescent bone marrow mesenchymal stem cells to highly express HSP70, thereby improving mitochondrial membrane permeability by inhibiting BAX activation, reducing inflammation and oxidative stress, and ultimately promoting aging bone regeneration.
Abstract
The aging microenvironment promotes persistent inflammation and loss of intrinsic regenerative capacity. These are major obstacles to effective bone tissue repair in older adults. This study aims to explore how physical thermal stimulation can effectively delay the bone marrow mesenchymal stem cells (BMSCs) aging process. Based on this, an implantable physical signal-converter platform is designed as a therapeutic system that enables stable heat signals at the bone injury site under ultrasound stimulation (US). It is found that the therapeutic platform controllably reduces the mitochondrial outer membrane permeabilization of aging BMSCs, bidirectionally inhibiting mitochondrial reactive oxygen species and mitochondrial DNA (mtDNA) leakage. The leakage ratio of mtDNA decreases by 22.7%. This effectively mitigates the activation of the cGAS-STING pathway and its downstream NF-κB signaling induced by oxidative stress in aging BMSCs, thereby attenuating the pathological advancement of chronic inflammation. Thus, it effectively restores the metabolism and osteogenic differentiation of aging BMSCs in vitro, which is further confirmed in a rat model. In the GMPG/US group, the bone mineral density increases 2–3 times at 4 weeks in the rats femoral defect model. Therefore, this ultrasound-based signal-conversion platform provides a promising strategy for aging bone defect repair.
Phagocytosis‐Activating Nanocomplex Orchestrates Macrophage‐Mediated Cancer Immunotherapy
A pro-phagocytic polymer-based nanocomplex, MNCCD47i-CALRt, is designed to enhance macrophage-mediated tumor cell engulfment by modulating both the pro- and anti-phagocytic signals. Comprising a PAMAM derivative to induce calreticulin exposure and an RNAi to inhibit CD47 expression, MNCCD47i-CALRt effectively delays tumor growth and prolongs survival in mice, offering a potent strategy to potentiate macrophage-mediated cancer immunotherapy.
Abstract
The phagocytosis of macrophages to tumor cells represents an alluring strategy for cancer immunotherapy; however, its effectiveness is largely hindered by the detrimental upregulation of anti-phagocytic signals and insufficient expression of pro-phagocytic signals of tumor cells. Here, a pro-phagocytic polymer-based nanocomplex is designed to promote the macrophage engulfment of tumor cells through concurrent modulation of both the “eat me” and “don't eat me” signals. The nanocomplex MNCCD47i-CALRt is formed by complexing a synthetic PAMAM derivative (G4P–C7A) that is capable of intrinsically inducing the exposure of calreticulin (CALR, a crucial pro-phagocytic protein) and a small inference RNA that can inhibit the expression of CD47 (a primary anti-phagocytic protein). MNCCD47i-CALRt can significantly delay tumor growth and prolong the survival of tumor-bearing mice with negligible hematopoietic toxicity in multiple murine colorectal cancer models. Furthermore, the pro-phagocytic capacity of MNCCD47i-CALRt is validated in the patient-derived tumor organoid model. Collectively, the phagocytosis-promoting nanocomplex provides a simple and potent strategy for boosting macrophage-mediated cancer immunotherapy.
Dual‐Scale Hydration‐Induced Electrical and Mechanical Torsional Energy Harvesting in Heterophilically Designed CNT Yarns
Despite the abundance and vast energy potential of water, its efficient utilization is hindered by single-mode energy conversion. Herein, heterophilic CNT yarns that allow for simultaneous energy harvesting by means of dual-scale hydration—electrical energy harvesting through proton gradients and mechanical torsional harvesting through microchannel absorption are presented.
Abstract
Water holds vast potential for a useful energy source, yet traditional approaches capture only a fraction of it. This study introduces a heterophilically designed carbon nanotube (CNT) yarn with an asymmetric configuration. This yarn is capable of both electrical and mechanical torsional energy harvesting through dual-scale hydration. Fabricated via half-electrochemical oxidation, the yarn contains a hydrophilic region enriched with oxygen-containing functional groups and a hydrophobic pristine CNT region. Molecular-scale hydration triggers proton release in the hydrophilic region. Consequently, a concentration gradient is established that generates a peak open-circuit voltage of 106.0 mV and a short-circuit current of 20.6 mA cm−2. Simultaneously, microscale hydration induces water absorption into inter-bundle microchannels, resulting in considerable yarn volume expansion. This process leads to hydro-driven actuation with a torsional stroke of 78.8° mm−1 and a maximum rotational speed of 1012 RPM. The presented simultaneous harvesting results in electrical and mechanical power densities of 3.5 mW m−2 and 34.3 W kg−1, respectively, during a hydration cycle. By integrating molecular and microscale hydrations, the proposed heterophilic CNT yarns establish an unprecedented platform for simultaneous electrical and mechanical energy harvesting from water, representing a groundbreaking development for sustainable applications.
Fri 30 May 16:30: Animal Consciousness: Evidence Models and Clues
The Hosts for this talk are Nicky Clayton and Max Knowles
- Speaker: Peter Godfrey Smith
- Friday 30 May 2025, 16:30-18:00
- Venue: Ground Floor Lecture Theatre, Department of Psychology.
- Series: Zangwill Club; organiser: Sara Seddon.
eg Electron Occupancy as a Descriptor for Designing Iron Single‐Atom Electrocatalysts
An e g electron occupancy descriptor for Fe-N-C is proposed to link the reaction rate of the electrocatalytic reduction reaction. This descriptor provides guidelines for the rational design of single-atom catalysts for the ORR as well as various other processes, showing great promise for advancing metal-air batteries to practical applications.
Abstract
A quantitative electronic structure-performance relationship is highly desired for the design of single-atom catalysts (SACs). The Fe single-atom catalysts supported by ordered mesoporous carbon with the e g electron occupancy from 1.7 to 0.7 are synthesized. A linear relationship has been established between the e g electron occupancy of the Fe site and the catalytic activity/activation entropy of oxygen-related intermediates. Fe SAC with an e g electron occupancy of 0.7 alters the rate determining step from *OH desorption to *OOH formation. The value of the turn-over frequency is ≈28 times that of the Fe SAC site with an e g electron occupancy of 1.7 e, and the mass activity is ≈6.3 times that of commercial Pt/C. When used in a zinc–air battery, the Fe SAC gives a remarkable power density of 196.3 mW cm−2 and a long-term stability exceeding 1500 h. The discovery of e g electron occupancy descriptor provides valuable insights for designing single-atom electrocatalysts.
Efficient Low‐temperature Ammonia Cracking Enabled by Strained Heterostructure Interfaces on Ru‐free Catalyst
Leveraging the strong metal-support interaction effect, heterostructured interfaces in a Co-based catalyst are designed to enable low-temperature ammonia (NH3) decomposition. The induced tensile lattice strain within the core-shell structure modulates d-band center of Co, enhancing NH3 adsorption and facilitating N─H bond dissociation. Furthermore, the dynamic lattice strain release and restoration mechanism promotes NH3 dehydrogenation and by-product desorption, effectively optimizing the reaction pathway and ensuring sustained catalytic activity.
Abstract
Ammonia (NH3) has emerged as a promising liquid carrier for hydrogen (H2) storage. However, its widespread adoption in H2 technology is impeded by the reliance on costly Ru catalysts for low-temperature NH3 cracking reaction. Here, a strained heterostructure Co@BaAl2O4−x core@shell catalyst is reported that demonstrates catalytic performance at low reaction temperatures comparable to most Ru-based catalysts. This catalyst exhibits exceptional activity across a range of space velocity conditions, maintaining high conversion rates at 475 to 575 °C and achieving an impressive H2 production rate of 64.6 mmol H2 gcat −1 min−1. Synchrotron X-ray absorption spectroscopy, synchrotron X-ray diffraction, and kinetic studies are carried out to elucidate the dynamic changes of the strained heterostructure interface of Co-core and BaAl2O4−x-overlayer under catalytic working conditions. The performance enhancement mechanisms are attributed to the tensile strained Co surface encapsulated in the defective BaAl2O4−x, which enhances NH3 adsorption and facilitates the rate-determining N─H dissociation. Furthermore, the strain release and restoration during NH3 dehydrogenation enable efficient nitrogen desorption, preventing active site poisoning. This work highlights the effectiveness of lattice strain engineering and the development of synergistic strong metal-support interfaces between active metal nanoparticles and oxide support to boost low-temperature NH3 cracking.
Fri 23 May 16:30: To be confirmed The host for this talk is Sarah-Jayne Blakemore
The Host for this talk is Sarah-Jayne Blakemore
The host for this talk is Sarah-Jayne Blakemore
- Speaker: Professor Ron Mangun,Center for Mind and Brain 267 Cousteau Place Davis, CA
- Friday 23 May 2025, 16:30-18:00
- Venue: Ground Floor Lecture Theatre, Department of Psychology.
- Series: Zangwill Club; organiser: Sara Seddon.
Fri 02 May 16:30: How the Built Environment Affects Spatial Behavior, Brain Activity and Aesthetics
The host for this talk is Nicky Clayton
Abstract: The talk will present research from our research team where we have explored how the structure of the environment affects wayfinding behaviour. It will cover our research with Sea Hero Quest in which we found growing up in griddy cities has a negative impact on navigation behaviour, as well as well as research with London taxi drivers how the environment affects how they plan. In the second part I will cover our recent research in neuroarchitecture exploring brain responses (fMRI) during watching movies of pleasant or unpleasant built environment and crowd dynamics in a study of 100 people navigating and exploring a fabricated large-scale art gallery (The 100 Minds in Motion Project).
Bio: Hugo Spiers is Professor of Cognitive Neuroscience, and a Vice Dean for Enterprise, at University College London (UCL). He has over 25 years of research experience in neuroscience and psychology studying how our brain recalls the past, navigates the present and imagines the future. He has published over 100 academic articles and received numerous awards including the Charles Darwin Award from the British Science Association and a James McDonnell Foundation Scholar Award. He is co-director of the International Centre for NeuroArchitecture and NeuroDesign, a Fellow of the Royal Institute of Navigation, a Lighthouse Fellow of the Centre for Conscious Design and the Vice Chair of the Academy of Neuroscience for Architecture in the UK. His research project Sea Hero Quest has tested over 4 million people in 195 nations on their navigation ability, providing a powerful benchmark for assessment in Alzheimer’s disease and global insight into cognition.
- Speaker: Professor Hugo Spiers
- Friday 02 May 2025, 16:30-18:00
- Venue: Ground Floor Lecture Theatre, Department of Psychology.
- Series: Zangwill Club; organiser: Sara Seddon.
Thu 01 May 14:00: Some topics at the intersection of control, dynamics, and learning.
Data-driven modeling typically involves simplifications of systems through dimensionality reduction (less variables) or through dimensionality enlargement (more variables, but simpler, perhaps linear, dynamics). Autoencoders with narrow bottleneck layers are a typical approach to the former (allowing the discovery of dynamics taking place in a lower-dimensional manifold), while autoencoders with wide layers provide an approach to the later, with “neurons” in these layers thought of as “observables” in Koopman representations. In the first part of this talk, I’ll briefly discuss some theoretical results about each of these topics. (Joint work with M.D. Kvalheim on dimension reduction and with Z. Liu and N. Ozay on Koopman representations.)
The training of autoencoders, and more generally the solution of other optimization problems, including policy optimization in reinforcement learning, typically relies upon some variant of gradient descent. There has been much recent work in the machine learning, control, and optimization communities in the application of the Polyak-Łojasiewicz Inequality (PŁI) to such problems in order to establish exponential (a.k.a. “linear” in the local-iteration language of numerical analysis) convergence of loss functions to their minima under the gradient flow. A somewhat surprising fact is that the exponential rate, at least in the continuous-time LQR problem, vanishes for large initial conditions, resulting in a mixed globally linear / locally exponential behavior. This is in sharp contrast with the discrete-time LQR problem, where there is global exponential convergence. The gap between CT and DT behaviors motivated our work on generalizations of the PŁI condition, and the second part of the talk will address that topic. In fact, these generalizations are key to understanding the effect of errors in the estimation of the gradient. Such errors might arise from adversarial attacks, wrong evaluation by an oracle, early stopping of a simulation, inaccurate and very approximate digital twins, stochastic computations (algorithm “reproducibility”), or learning by sampling from limited data. We will suggest an input to state stability (ISS) analysis of this issue. Time permitting, we will also mention some initial results on the performance of linear feedforward networks in feedback control. (Joint work with A.C.B. de Oliveira, L. Cui, Z.P. Jiang, and M. Siami).
The seminar will be held in JDB Seminar Room , Department of Engineering, and online (zoom): https://newnham.zoom.us/j/92544958528?pwd=YS9PcGRnbXBOcStBdStNb3E0SHN1UT09
- Speaker: Eduardo Sontag, Northeastern University
- Thursday 01 May 2025, 14:00-15:00
- Venue: JDB Seminar Room, Department of Engineering and online (Zoom).
- Series: CUED Control Group Seminars; organiser: Fulvio Forni.
Fri 02 May 14:00: Frontiers in Embodied AI for Autonomous Driving
Over the last decade, we’ve seen unprecedented progress in AI across many disciplines and applications. However, autonomous vehicles are still far from mainstream even after billions of dollars of investment. In this talk we’ll explore what’s been holding progress back, and how by adopting a modern embodied AI approach to the problem, Wayve is finally unlocking the potential of scalable autonomous driving across the globe.
We’ll also explore some of our latest research in multimodal learning to combine the power of large language models with the driving problem, and in controllable generative world models as learned simulators.
Bio: Jamie leads Wayve’s Science department, where he guides our research teams to unlock new research breakthroughs, to enable those breakthroughs to have meaningful impact for the business, and to disrupt both our technical and business strategy to ensure Wayve stays at the forefront of innovation. Jamie has been at the forefront of applied AI research for the past 20 years. Before joining Wayve, Jamie was Partner Director of Science at Microsoft and Head of the Mixed Reality & AI Labs. While at Microsoft, Jamie shipped foundational features for Microsoft’s Kinect (Microsoft’s line of motion sensing input devices) and the hand- and eye-tracking that enable HoloLens 2’s interaction model (smart glasses). Jamie has a PhD in computer vision from the University of Cambridge and has received multiple Best Paper and Best Demo Awards at top-tier academic conferences. He was elected a Fellow of the Royal Academy of Engineering in 2021.
- Speaker: Jamie Shotton, Wayyve
- Friday 02 May 2025, 14:00-15:00
- Venue: Computer Lab, LT1.
- Series: Cambridge ML Systems Seminar Series; organiser: Sally Matthews.
Electric‐Field‐Driven Reversal of Ferromagnetism in (110)‐Oriented, Single Phase, Multiferroic Co‐Substituted BiFeO3 Thin Films
Electric-field-induced magnetization reversal is a long-sought-after achievement in materials engineering for use in next-generation, ultra-low power consumption memory devices. This work demonstrates fully electric-field-driven switching of the out-of-plane component of magnetization in (110)-oriented Co-substituted BiFeO3 thin films at room temperature, enabled through careful engineering of thin film boundary conditions and crystallography.
Abstract
While multiferroic materials are attractive systems for the promise of ultra-low-power-consumption computational technologies, electric-field-induced magnetization reversal is a key challenge for realizing devices at scale. Though significant research efforts have been working toward the realization of a material which couples ferroelectricity and ferromagnetism, there are few, even composite, systems which are practical for device scale applications at room temperature. Co-substituted multiferroic BiFe0.9Co0.1O3 is a promising candidate system, due to coupled ferroelectricity and weak ferromagnetism at room temperature. Here, it is theoretically indicated that the ferroic orders in this material are statically coupled, where an in-plane 109° ferroelectric switching event can result in the reversal of this out-of-plane component of magnetization, and the electric field-induced magnetization reversal is experimentally observed. Such an in-plane poling configuration is particularly desirable for device applications.
Hybrid Formative‐Additive Manufacturing
Hybrid Formative-Additive Manufacturing (HyFAM) integrates formative processes into additive manufacturing. HyFAM 3D-prints exterior walls and complex geometries, then formatively fills interior material. By tuning rheological properties, the study can achieve both 3D-printable ink and self-leveling, moldable ink of the same material. HyFAM speeds up part production and eliminates internal defects by replacing interior 3D-printed sections with bulk-filled material.
Abstract
Material extrusion additive manufacturing (AM) provides extensive design flexibility and exceptional material versatility, enabling the fabrication of complex, multifunctional objects ranging from embedded electronics to soft robotics and vascularized tissues. The bottom-up creation of these objects typically requires discretization into layers and voxels. However, the voxel size, determined by the nozzle diameter, limits extrusion rate, creating a conflict between resolution and speed. To address these inherent scalability challenges, the study proposes a hybrid formative-additive manufacturing technology that combines the respective strengths of each method—speed and quality with complexity and flexibility. The approach involves 3D-printing complex geometries, multimaterial features, and bounding walls of bulky, lower-resolution volumes, which are rapidly filled via casting or molding. By precisely controlling the materials’ rheological properties—while maintaining similar solidified properties and high interfacial strength—several typical AM flaws, such as bulging and internal voids, are eliminated, achieving exponentially faster production speeds for objects with varying feature sizes.
Modulating Crystal Growth with Sacrificial Coordination for High‐Performance Perovskite Solar Cells via Intense Pulsed Light Annealing
DodecylMSO, a sacrificial Lewis base additive, modulates perovskite crystallization during intense pulsed light annealing by strongly binding PbI₂ and volatilizing at high temperatures. This results in larger grains, lower defect density, and minimum trace residues, achieving the highest efficiency in its class.
Abstract
Intense pulsed light (IPL) annealing has emerged as a transformative technology for the high-throughput, low-cost fabrication of perovskite films, enabling the rapid conversion of precursor wet films into perovskite films within milliseconds. Despite their potential, the efficiencies of IPL-processed devices have yet to match those achieved through conventional thermal annealing (TA), primarily due to the challenges of uncontrolled crystallization and defect formation during the IPL process. In this study, a solid Lewis base additive, dodecyl methyl sulfoxide (DodecylMSO) is introduced, to modulate perovskite crystal growth and improve film morphology and uniformity under IPL conditions. DodecylMSO acts as a sacrificial additive, with X-ray photoelectron spectroscopy (XPS) confirming the majority of it is removed in the final films. Compared to the control films, DodecylMSO-modified films exhibited significantly reduced defect densities and enhanced carrier extraction and transport properties. Leveraging this approach, p-i-n perovskite solar cells (PSCs) is demonstrated with a champion power conversion efficiency of 23.5% fabricated via IPL. This sacrificial coordination strategy not only addresses key challenges in IPL processing but also opens new avenues for advancing the manufacturability and scalability of high-performance PSCs.
Fri 20 Jun 12:00: Title to be confirmed
Abstract not available
- Speaker: Szilvia Ujvary (University of Cambridge)
- Friday 20 June 2025, 12:00-13:00
- Venue: ONLINE ONLY. Here is the Zoom link: https://cam-ac-uk.zoom.us/j/4751389294?pwd=Z2ZOSDk0eG1wZldVWG1GVVhrTzFIZz09.
- Series: NLIP Seminar Series; organiser: Suchir Salhan.
Luminescent Liquid Crystalline Elastomer Promoted Self‐Adaptive Smart Active Optical Waveguide with Ultra‐Low Optical Loss
Smart optical waveguides with ultra-low optical loss have been fabricated using luminescent liquid crystalline elastomers. These waveguides exhibit excellent self-adaptive properties, making them promising for integrated photonic systems enabling low-loss, high-speed data transmission.
Abstract
Currently, optical waveguides show extensive application in photonics and optoelectronic devices due to their high information capacity and transmission capabilities. However, developing self-adaptive, smart optical waveguide materials with ultra-low optical loss remains a significant challenge. To address this issue, luminescent liquid crystalline elastomers (LLCEs) with remarkable flexibility and minimal optical loss through one-pot synthetic method is synthesized, marking the first example of such an approach. The resultant organic optical waveguide materials (OOWMs) demonstrate exceptional mechanical performance and low optical loss, even under significant deformation. An optical loss coefficient of 0.0375 dB mm−1 has been achieved in LLCE-based OOWMs through synergistic Förster resonance energy transfer. Additionally, these flexible OOWMs can endure large deformations and be shaped into arbitrary forms within macro-scale dimensions. Notably, LLCE-based OOWMs demonstrate smart, self-adaptive behavior with ultra-low optical loss when exposed to heat or light. Consequently, these OOWMs can be used to fabricate photo switches of various shapes. This work provides a feasible approach to achieving integrated photonic systems with low optical loss for intelligent high-speed data transmission.
Highly Coupled Dynamically Modulated Electrocatalysts on Wafer‐Scale InGaN/GaN Nanowires on Silicon for Successive Acidic Photoelectrochemical Water Oxidation
The sluggish water oxidation kinetics on photoanodes under strongly acidic conditions not only limit the photocurrent but also induce severe photocorrosion. Here, loading a CoRuOX cocatalyst—exhibiting a unique dynamic electron modulation effect—onto wafer-scale InGaN nanowires achieves a dual breakthrough in both oxidation activity and stability for photoelectrochemical (PEC) water oxidation under strongly acidic conditions. This strategy offers a promising pathway for sustained PEC water oxidation in acidic environments.
Abstract
Photoelectrochemical water splitting is considered one of the most promising paths for sustainable hydrogen production. However, the sluggish kinetics of the water oxidation reaction and poor stability of the photoanode significantly limit the overall performance of the photoelectrochemical device, particularly under acidic conditions, which poses great challenges for practical applications. Herein, the coupling of unique CoRuOx nanoclusters with dynamic electronic modulation effects to wafer-scale InGaN nanowires is proposed, demonstrating superior photoelectrochemical activity and stability for acidic water oxidation. Compared with InGaN nanowires loaded with typical RuO₂ cocatalysts, CoRuOx/InGaN photoanodes achieve a remarkable improvement in applied bias photon-to-current efficiency from 0.77% to 2.25%, with stable operation for over 500 min under strongly acidic conditions. Such boosted performance is attributed mainly to Co induced dynamic electronic modulation, which enhances oxygen evolution while maintaining the stable operation of CoRuOx/InGaN photoanodes. Initially, the Co sites increased the oxidation state of Ru, enhancing the activity of oxygen evolution. Moreover, during PEC operation, the Co sites stabilized the Ru sites, preventing dissolution of cocatalyst. This unique self-adaptive process significantly enhances the stability and activity of the photoanode, opening an effective avenue to achieve efficient and durable photoanodes for PEC applications.
Material Selection and Device Design of Scalable Flexible Brain‐Computer Interfaces: A Balance Between Electrical and Mechanical Performance
This review explores the balance between electrical and mechanical performance of flexible BCIs through the careful selection of electronic materials and probe design to achieve long-term stable neural recordings with high signal-to-noise ratios.
Abstract
Brain-computer interfaces (BCIs) hold the potential to revolutionize brain function restoration, enhance human capability, and advance our understanding of cognitive mechanisms by directly linking neural signals with hardware. However, the mechanical mismatch between conventional rigid BCIs and soft brain tissue limits long-term interface stability. Next-generation BCIs must achieve long-term biocompatibility while maintaining high performance, enabling the integration of millions of sensors within tissue-level flexible and soft, stable neural interfaces. Lithographic fabrication techniques provide scalable thin-film flexible electronics, but traditional electronic materials often fail to meet the unique requirements of BCIs. This review examines the selection of materials and device design for flexible BCIs, starting with an analysis of intrinsic material properties—Young's modulus, electrical conductivity and dielectric constant. It then explores the integration of material selection with electrode design to optimize electrical circuits and assess key mechanical factors. Next, the correlation between electrical and mechanical performance is analyzed to guide material selection and device design. Finally, recent advances in neural probes are reviewed, highlighting improvements in signal quality, recording stability, and scalability. This review focuses on scalable, lithography-based BCIs, aiming to identify optimal materials and designs for long-term, reliable neural recordings.
Neighboring Iron Single Atomic Sites Boost PtCo Intermetallic for High-Durability ORR Electrocatalysis
DOI: 10.1039/D5EE00624D, PaperKai Chen, Junheng Huang, Junxiang Chen, Jiyuan Gao, zhiwen lu, Xi Liu, Senchen Lan, Guohua Jia, Suqin Ci, Zhenhai Wen
Advancing fuel cell technology hinges on developing stable, efficient Pt-based catalysts for the oxygen reduction reaction (ORR), yet challenges like the high cost and limited durability of Pt-based materials persist....
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