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Energy Environ. Sci., 2025, Accepted Manuscript
DOI: 10.1039/D4EE06191H, Review Article Open Access &nbsp This article is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported Licence.Alireza Lotfollahzade Moghaddam, Sohrab Hejazi, Moslem Fattahi, Md Golam Kibria, Murray Thomson, Rashed AlEisa, Mohd Adnan Khan
The global push to keep global warming to less than 1.5 ºC, will require us to quickly adopt zero-emission energy carriers. Hydrogen, a versatile energy vector, is pivotal in this...
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Ferroelectric BiFeO3 nanowire photodiodes enable in-sensor polarization extraction through aligned nanowire-induced anisotropic photoresponse and reconfigurable photovoltaic effects. With two-order anisotropic ratio tunability, the devices perform polarization-based convolutions, boosting object recognition accuracy to 89.6% in adverse weather conditions. This innovation advances intelligent vision systems with efficient in-sensor polarization processing.

Abstract

In-sensor computing can enhance the imaging system performance by putting part of the computations into the sensor. While substantial advancements have been made in latency, spectral range, and functionalities, the strategy for in-sensor light polarization computing has remained unexplored. Here, it is shown that ferroelectric-reconfigurable polarization-sensitive photodiodes (FPPDs) based on BiFeO3 nanowire arrays can perform in-sensor computations on polarization information. This innovation leverages the anisotropic photoresponse from the 1D structure of nanowires and the non-volatile reconfigurability of ferroelectrics. The devices show programmable anisotropic ratios as high as 5219, surpassing most state-of-the-art polarization-sensitive photodetectors and commercial polarization image sensors. Employing tunable photoresponse as kernel, FPPDs can perform convolutions to directly extract feature maps containing polarization information, which raises the recognition accuracy on road-scene objects under adverse weather up to 89.6%. The research highlights the potential of FPPDs as a highly efficient vision sensor and extends the boundaries of advanced intelligent imaging systems.

A multifunctional “Trojan” molecule based on membrane-mimicking and zwitterionic conjugated electrolyte is developed for advanced drug delivery systems. By integrating into and rigidifying lipid bilayer structures, it prevents premature payload leakage and enables reliable in vivo visualization of carriers. Upon remote 808 nm excitation, this light-responsive molecule triggers rapid drug release at tumor sites, inducing synergistic multimodal therapies.

Abstract

Enhancing payload encapsulation stability while enabling controlled drug release are both critical objectives in drug delivery systems but are challenging to reconcile. This study introduces a zwitterionic conjugated electrolyte (CE) molecule named Zwit, which acts as a molecular Trojan by mimicking the lipid bilayers. When integrated into liposome membranes, Zwit rigidifies the bilayer structure likely due to its hydrophobic interactions providing structural support, thus inhibiting drug leakage. Upon 808 nm laser excitation, Zwit rapidly accelerates DOX release from liposome core, likely due to light-triggered conformational changes or photothermal effects that compromise membrane permeability. These findings demonstrate Zwit’s ability to overcome the challenge of simultaneously preventing premature payload leakage and enabling stimuli-responsive drug release with a single component. Additionally, Zwit exhibits excellent biocompatibility with membranes, outperforming its quaternary ammonium counterpart and commonly used dye indocyanine green (ICG). By harnessing its NIR-II emission, Zwit enables durable in vivo biodistribution tracking of nanocarriers, whereas ICG suffers from significant dye leakage. In subcutaneous tumor models, the synergistic effects of chemotherapy and thermotherapy facilitated by this light-triggered system induced a potent antitumor immune response, further enhancing anticancer efficacy. This work underscores the potential of membrane-mimicking CEs as multifunctional tools in advanced drug delivery systems.

A universal thick anode composed of polymer and carbon nanotubes has been developed, demonstrating stable operation across 15 simple-ion and 3 complex-ion systems. It achieves exceptional cycle life in supercapacitors, ultrahigh areal capacities in batteries, and high compatibility with seawater electrolytes. With ultrahigh-loading capability (100 mg cm⁻2) and cost-effectiveness, this thick electrode is promising for practical aqueous (seawater) energy devices.

Abstract

Aqueous and seawater energy storage devices hold great potential for electrical grids application due to safety, affordability, and sustainability. However, their broader deployment has been constrained by the absence of a durable thick anode. Here, the first universal thick anode operating stably across 15 simple-ion and 3 complex-ion systems, including nonmetallic (H+, NH4 +), monovalent (Li+, Na+, K+), multivalent ions (Zn2+, Ca2+, Mg2+, Al3+), and seawater ions (>5 cations) is reported. Composed of polymer nanosheets and carbon nanotubes, this anode supports thick electrode fabrication (e.g., 100 mg cm−2 and 1 mm) with low porosity/tortuosity, superior electrical conductivity, mechanical robustness, and chemical stability. Consequently, it achieves exceptionable cycle life (up to 380 000 cycles) in supercapacitors and ultrahigh areal capacities (6.5 mAh cm−2) in batteries, even under practical/extreme conditions, attributed to the formation of a water-scarce, cation-rich electrical double-layer structure, as revealed by simulations. Compatible with sea salt-based electrolytes and paired with a metal-free cathode, the anode enables seawater batteries with thousands-cycle life and high energy/power density. Of universal ion storage, ultrahigh-loading capability, unlimited resources, and cost-effectiveness, this polymer electrode is promising for practical aqueous (seawater) energy devices.

This study demonstrates novel magnetic tunnel junctions with low resistance-area product by integrating chemically vapor-deposited 2D Cr3Te4/WS2 heterostructures with 2D Fe3GeTe2 magnets. Leveraging spin-orbit torque to manipulate spins in Fe3GeTe2, the authors fabricate an energy-efficient magnetic memory device. This breakthrough not only advances high-performance spintronics but also paves the way for next-generation low-power electronic devices.

Abstract

Spin-orbit torque (SOT) magnetic memory technology has garnered significant attention due to its ability to enable field-free switching of magnets with strong perpendicular magnetic anisotropy (PMA). However, concerns regarding power consumption of SOT-memory are persisting. Here, this work proposes a method to construct magnetic tunnel junction (MTJ) by transferring chemically vapor-deposited two-dimensional (2D) Cr3Te4/WS2 van der Waals (vdW) heterostructures onto 2D Fe3GeTe2 (FGT) magnet. The robustness and tunability of 2D magnets allow MTJs to exhibit non-volatility, multiple output states, and impressive cycling durability. MTJs with thin WS2 barriers (fewer than six layers) exhibit a linear tunneling effect, achieving a low resistance-area product (RA) of 15.5 kΩ·µm2 using bilayer WS2, which facilitats low-power operation. Furthermore, the different 2D magnets display a significant anti-parallel window of up to 8 kOe. SOT-memory based on the typical MTJ demonstrates a low write consumption of 0.3 mJ and read consumption of 9.7 nJ, marking a significant advancement in 2D vdW SOT-memory. This research has pointed out a new direction for constructing low power consumption SOT-memory with PMA field-free switching.

Title to be confirmed

Abstract not available

• Speaker: Louis Schatzki (University of Illinois Urbana-Champaign)
• Thursday 13 March 2025, 14:00-15:00
• Venue: Computer Laboratory, William Gates Building, Room FW11.
• Series: Quantum Computing Seminar; organiser: Tom Gur.

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Freshwater displacement effect on the Weddell Gyre carbon budget

The Weddell Gyre mediates carbon exchange between the abyssal ocean and atmosphere, which is critical to global climate. This region also features large and highly variable freshwater fluxes due to seasonal sea ice, net precipitation, and glacial melt; however, the impact of these freshwater fluxes on the regional carbon cycle has not been fully explored. Using a novel budget analysis of dissolved inorganic carbon (DIC) mass in the Biogeochemical Southern Ocean State Estimate and revisiting hydrographic analysis from the ANDREX cruises, we highlight two freshwater-driven transports. Where freshwater with minimal DIC enters the ocean, it displaces DIC -rich seawater outwards, driving a lateral transport of 75±5 Tg DIC /year. Additionally, sea ice export requires a compensating import of seawater, which carries 48±11 Tg DIC /year into the gyre. Though often overlooked, these freshwater displacement effects are of leading order in the Weddell Gyre carbon budget in the state estimate and in regrouped box-inversion estimates. Implications for evaluating basin-scale carbon transports are considered. [Time permitting, I’ll also share some results on the role of heat addition in driving circulation change and warming patterns in the Indian sector of the Southern Ocean.]

• Speaker: Benjamin Taylor, Scripps Institution of Oceanography
• Wednesday 26 February 2025, 15:30-16:30
• Venue: BAS Seminar Room 1.
• Series: British Antarctic Survey - Polar Oceans seminar series; organiser: Dr Birgit Rogalla.

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A glucose metabolism-targeted nanoformulation (NP/OXA-ASP2) is designed to inhibit lactate efflux while inducing mitochondrial stress to boost immunogenic cell death, thus synergistically reversing the immunosuppressive tumor microenvironments by decreasing the proportion of immunosuppressive cells (Tregs and MDSCs) and increasing the proportion of cytotoxic T lymphocytes (CTLs), and plays an enhanced efficacy of chemo-immunotherapy to colon cancer.

Abstract

Inappropriate glucose metabolism in cancer cells is associated with immunosuppressive tumor microenvironments (TMEs). Although glycolysis inhibition enhances T cell-mediated immune responses, the integrated platforms combining glycolysis inhibition with immunotherapy remain underdeveloped. To address this gap, a glucose metabolism-targeted poly(amino acid) nanoformulation of oxaliplatin(IV)-aspirin prodrug (NP/OXA-ASP2) is developed to improve chemo-immunotherapy by suppressing tumor glycolysis. This poly(amino acid) nanoparticle exhibits selective release, discharging 90.0% of OXA-ASP2 under reductive conditions within 36 h. Furthermore, over 80% of the prodrug converts to OXA and ASP within 12 h, promoting mitochondrial damage and glycolysis inhibition, which amplifies immunogenic cell death induced by OXA. In addition, suppressing glycolytic flux reduces lactate leakage, mitigating the immunosuppressive TMEs. Together, these mechanisms contribute to stronger chemo-immunotherapy efficacy. Compared to the OXA plus ASP formulation, NP/OXA-ASP2 demonstrates superior performances, reducing lactate levels at the tumor site by 25.4%, increasing the proportion of cytotoxic T lymphocytes by 1.53 times, decreasing the proportion of regulatory T cells by 2.20 times, and improving 1.39-fold of the tumor inhibition rate. These findings underscore that NP/OXA-ASP2 is a promising platform for integrating tumor metabolic regulation with immunomodulation and holds significant potential for advancing clinical chemo-immunotherapy.

Sono-metabolic nano-composites (TiO2-Au@DON) produce huge amounts of ROS (type I and type II) under ultrasound irradiation, effectively inducing immunogenic cell death via TiO2-Au-induced-SDT phenomena. The released DON disrupts NADPH and tumor redox homeostasis by reprogramming metabolic pathways while it intensifies the activities of immune cells. This metabolic disruption amplifies SDT-mediated oxidative stress, offering a precise combination of SDT and immunotherapy.

Abstract

Sonodynamic therapy (SDT) is a promising therapeutic modality known for its non-invasiveness, temporal-spatial controllability, and deeper tissue penetration. However, the SDT treatment efficacy is still hampered by the scarcity of ideal sonosensitizers and complex tumor microenvironment (TME). To address these challenges, a sono-metabolic nano-composite (TiO2-Au@DON) using the metabolic reprogramming prodrugs of 6-Diazo-5-oxo-l-norleucine (DON) grafted on TiO2-Au Janus nanoparticles (NPs) is fabricated. The coupling of TiO2 and gold in the TiO2-Au@DON effectively prevents the fast recombination of excited electrons and holes under ultrasound irradiation. The result is the generation of higher levels of both type I and II reactive oxygen species (ROS) compared to pure TiO2, which helps overcome the limitations of SDT in the hypoxic TME. Furthermore, the TiO2-Au Janus NPs act as nano-carriers, delivering DON prodrugs to the tumor site. The released DON can disrupt nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) and tumor redox homeostasis by reprogramming the metabolic pathways while it intensifies the activities of immune cells. This metabolic disruption amplifies SDT-mediated oxidative stress, resulting in the increase of tumor sensitivity to ROS through TiO2-Au@DON-integrated synergistic effects of SDT and glutamine reprogramming strategies. This increased sensitivity ultimately induces robust immunogenic cell death (ICD), enhancing antitumor therapeutic efficacy and remodeling the tumor's immunosuppressive microenvironment.

Hopfield Networks: From Neuroscience to Machine Learning and Back

Hopfield networks, originally introduced in the 1980s, are recurrent neural networks that function as content-addressable memory systems. While classical Hopfield networks have limited capacity, modern variants leverage continuous states and attention-like energy functions to achieve exponential storage capacity. The influential work Hopfield Networks is All You Need bridges these advancements to transformer architectures, highlighting their significance in deep learning. In the first part of this talk, we will trace the evolution of Hopfield networks, examining their mathematical foundations and key applications in optimization. We will explore how these networks have transformed from their original binary state models to powerful continuous-state systems with deep learning applications. In the second part, we will step back to consider content-addressable memory in the brain, beginning with the hippocampal memory indexing theory. We will introduce a kernel-based formulation of key-value memory and discuss biologically plausible mechanisms for learning and organizing representations of queries, keys, and values. A key focus will be the recently proposed Vector-HaSH algorithm (Chandra et al., 2025, Nature), which offers a compelling model for efficient memory retrieval. Finally, we will review the main lines of evidence supporting key-value memory structures in the brain, drawing connections between neuroscience and modern machine learning.

• Speaker: Youjing Yu; Tim Lin
• Tuesday 18 February 2025, 15:00-16:30
• Venue: CBL Seminar Room, Engineering Department, 4th floor Baker building.
• Series: Computational Neuroscience; organiser: .

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Exoplanet Detection with SPIRIT: Infrared CMOS Photometry and the Discovery of the Hot Neptune TOI-2407b

The SPECULOOS project is dedicated to the discovery of transiting exoplanets around ultracool dwarfs using high-precision ground-based observations. To enhance sensitivity to these cool stars, we have implemented SPIRIT , a new infrared detector utilizing CMOS technology instead of traditional CCDs. In this talk, I will present my work on developing the data pipeline for SPIRIT and optimizing its performance for detecting exoplanet transits. I will also highlight the discovery of TOI -2407b, a Neptune-like planet observed with this system.

• Speaker: Clàudia Janó Muñoz (University of Cambridge)
• Tuesday 25 February 2025, 11:15-12:00
• Venue: Coffee area, Battcock Centre.
• Series: Hills Coffee Talks; organiser: Charles Walker.

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Title to be confirmed

Abstract not available

• Speaker: Víctor Navarro-Fernández, Imperial College London
• Monday 17 March 2025, 14:00-15:00
• Venue: MR13.
• Series: Partial Differential Equations seminar; organiser: Amelie Justine Loher.

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From accurate quantum mechanics to converged thermodynamics in solution with machine learning potentials

Obtaining accurate predictions of thermodynamic properties, especially free energies which define the state of a system, is one of the key goals in atomistic simulations. This can enable a direct understanding of atomic-scale processes and provide a direct link to experiment. Achieving this requires converged statistical sampling from accurate wavefunction based potential energy surfaces, which is a formidable challenge due to the very high computational cost of such methods. Here, we leverage advances in machine learning potentials to efficiently obtain converged thermodynamic properties at increasing levels of theory. To showcase the potential of this approach, I will use the ion pairing of CaCO3 as a benchmark system, since it presents a significant challenge from both electronic structure and sampling perspectives. I will show that a machine learning framework based on second order Møller-Plesset Perturbation Theory delivers excellent agreement with experiment for the ion-pair association free energy—a challenging property for first principles atomistic simulations. Furthermore I will show that classical force fields get the right answer for the wrong reasons. Finally, I will discuss steps towards developing CCSD accuracy machine learning models, the ‘gold-standard’ of quantum chemical methods.

• Speaker: Niamh O'Neill, University of Cambridge
• Wednesday 26 February 2025, 15:00-15:30
• Venue: Unilever Lecture Theatre, Yusuf Hamied Department of Chemistry.
• Series: Theory - Chemistry Research Interest Group; organiser: Lisa Masters.

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Title to be confirmed

=== Hybrid talk ===

Join Zoom Meeting https://cam-ac-uk.zoom.us/j/87143365195?pwd=SELTNkOcfVrIE1IppYCsbooOVqenzI.1

Meeting ID: 871 4336 5195

Passcode: 541180

NOTE UNUSUAL DAY

• Speaker: Francisco Ferreira Ruiz (Royal Holloway, University of London)
• Wednesday 12 March 2025, 17:00-18:00
• Venue: MR14 Centre for Mathematical Sciences.
• Series: Formalisation of mathematics with interactive theorem provers ; organiser: Anand Rao Tadipatri.

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Nature Energy, Published online: 14 February 2025; doi:10.1038/s41560-025-01718-8

Cheaper and more sustainable batteries are key to decarbonize the global energy system, and sodium-ion batteries that use far fewer critical materials are an important option. Research now shows that rapidly improving techno-economics of sodium-ion batteries could soon make them competitive with lithium-ion phosphate batteries under a range of scenarios.

Nature Energy, Published online: 14 February 2025; doi:10.1038/s41560-025-01716-w

There is growing interest in designing electrolytes to enable Li-metal batteries. Here the authors show that asymmetric solvents improve lithium redox kinetics and achieve long cycle life in anode-free cells under electric vertical take-off and landing conditions, demonstrating potential for future high-power applications.

Nature Materials, Published online: 14 February 2025; doi:10.1038/s41563-025-02117-w

A multi-layer wafer-scale 2D gate-all-around system with an atomically smooth interface fabricated via epitaxial monolithic 3D integration shows good performance and power efficiency, holding promise for the forthcoming ångström technology node.

Nature Materials, Published online: 14 February 2025; doi:10.1038/s41563-025-02130-z

Here a strategy is proposed to increase the temperature stability of polymer dielectrics by using mechanical bonding from cyclic polyethers to damp the local vibrations of polymer chains, thus inhibiting high-temperature charge transport and enabling a discharged energy density of 4.1 J cm−3 with 90% efficiency at 250 °C.

Algebraising foundations of elliptic curves

Elliptic curves are one of the simplest non-trivial objects in algebraic geometry, which are pervasive in modern number theory, but also see applications in point counting algorithms and public key cryptography. Due to their geometric nature, formalising a working definition typically requires a lot of technical machinery, let alone any non-trivial results. Yet, the Lean community has managed to formalise two of the most fundamental theorems in the theory of elliptic curves, with scope for many more projects. In this talk, I will explain these theorems, and how we inadvertently discovered new proofs in our formalisation attempts.

Slides: https://multramate.github.io/talks/afoec/main.pdf

• Speaker: David Angdinata (University College London)
• Thursday 13 February 2025, 17:00-18:00
• Venue: MR14 Centre for Mathematical Sciences.
• Series: Formalisation of mathematics with interactive theorem provers ; organiser: Anand Rao Tadipatri.

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Free conformally-rescaled hyperboloidal evolution: status and applications

Gravitational wave radiation is only unambiguously defined at future null infinity – the location in spacetime where light rays arrive and where global properties of spacetimes can be measured. Reaching future null infinity is thus very important for extracting correct waveforms. A convenient way to include it in numerical relativity simulations is via hyperboloidal foliations. I will focus on conformal compactification as method to implement free hyperboloidal evolution, in the BSSN / conformal Z4 formulations. After illustrating its advantages, I will report on some ongoing applications in spherical symmetry: an extension to include the Maxwell equations, scattering simulations on a given background, and wave equation(s) evolved on some FLRW -type spacetimes with time-dependent scale factor. I will conclude giving an update on ongoing work in 3D evolutions.

• Speaker: Alex Vañó-Viñuales (IST Lisbon)
• Friday 21 February 2025, 13:00-14:00
• Venue: Potter room.
• Series: DAMTP Friday GR Seminar; organiser: Daniela Cors.

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