Nanoscale Horizons最新文献

Two-dimensional (2D) self-driven photodetectors have emerged as a compelling area of research, offering advantages such as miniaturization, weak light detection, high photosensitivity, and low noise levels. However, current type-III 2D heterojunction photodetectors often suffer from low self-driven responsivity and medium I_light/I_dark ratios. In this work, a novel device architecture that addresses these challenges is constructed by incorporating Cu-doped InP/ZnSeS/ZnS core-shell quantum dots (QDs) onto a type-III SnSe₂/MoTe₂ 2D heterojunction. The strategically engineered energy band structure of the Cu-doped QDs facilitates carrier transport with SnSe₂/MoTe₂ to form back-to-back type-II and type-III band alignments. As a result, under 532 nm illumination, the hybrid device exhibits remarkable visible light self-driven performance metrics with the help of the photogating effect: an ultra-low dark current of 23 fA, with responsivity and external quantum efficiency enhanced to 459 mA W^-1 and 109%, respectively, surpassing theoretical values by fourfold compared to those of pure SnSe₂/MoTe₂, a low noise equivalent power (NEP) of 0.87 × 10^-2 pW Hz^-1/2, a realistic specific detectivity of 1.45 × 10¹¹ Jones, a large I_light/I_dark ratio of 10⁶ and a swift response time of 1.16 ms/1.14 ms with stable operation. These results demonstrate that energy band engineering of Cu-doped QDs can significantly enhance the performance of 2D type-III heterojunctions in the visible range, laying a foundation for future gate-tunable optoelectronic devices.

Expression of concern for 'Electrothermal patches driving the transdermal delivery of insulin' by Quentin Pagneux et al., Nanoscale Horiz., 2020, 5, 663-670, https://doi.org/10.1039/C9NH00576E.

Electrons confined within the 2D layer of metals grown on silicon substrates exhibit exotic properties due to strong correlation effects. Their properties, such as their 2D superconductivity, have been frequently subjected to possible tuning by doping using charge transfer from adsorbed layers. Doping relies on adding electrons or holes to the system and the resulting shift of the Fermi level E_F in the otherwise robust surface electronic structure. This strategy has not been sufficiently controlled in the case of an indium double layer grown on the Si(111) surface. This study provides an alternative approach relying on spatially periodic modification of the surface electronic structure of the 2D metal. Derivatives of diketopyrrolopyrroles (DPP) are used for the growth of perfectly ordered 1D-like molecular superstructures on top of the In double layer, imaged by scanning tunneling microscopy. The integral changes of electronic structure are measured by angle-resolved photoelectron spectroscopy and density functional theory calculations show local modification of the surface states near E_F by the adsorbed molecules. This study demonstrates that the surface electronic states can be controllably patterned, using a proper bonding scheme. It is anticipated that the combination of the original 2D superconductor and the 1D-like patterning will motivate further research.

The development of hard carbon materials with high plateau capacity as anode materials for sodium-ion batteries (SIBs) is crucial to improving the energy density of SIBs, while the closed pores are closely related to the low-voltage (<0.1 V) plateau capacity of hard carbon anodes. Herein, through a simple ZnO template method and acid treatment, a wealth of closed pores were created in the hard carbon material derived from camellia shells. Experimental results reveal the mechanism of sodium ions adsorption at the defect sites and the formation of sodium clusters in the closed pores, which corresponds to the slope region and the plateau region, respectively. Notably, being beneficial to the considerable closed pore content and suitable microstructure, the optimized sample exhibits a high reversible capacity of 340 mA h g^-1, which is mainly contributed by the low-voltage plateau process (51%). This work provides a new strategy for precisely regulating the microstructure of biomass-derived hard carbon for sodium-ion storage.

Expression of concern for 'Innovative transdermal delivery of insulin using gelatin methacrylate-based microneedle patches in mice and mini-pigs' by Bilal Demir et al., Nanoscale Horiz., 2022, 7, 174-184, https://doi.org/10.1039/D1NH00596K.

Achieving high target cell avidity in combination with cell selectivity are fundamental, but largely unachieved goals in the development of biomedical nanoparticle systems, which are intricately linked to the quantity of targeting functionalities on their surface. Viruses, regarded as almost ideal role models for nanoparticle design, are evolutionary optimized, so that they cope with this challenge bearing an extremely low number of spikes, and thus binding domains, on their surface. In comparison, nanoparticles are usually equipped with more than an order of magnitude more ligands. It is therefore obvious that one key factor for increasing nanoparticle efficiency in terms of avidity and selectivity lies in optimizing their ligand number. A first step along this way is to know how many ligands per nanoparticle are involved in specific binding with target cell receptors. This question is addressed experimentally for a block copolymer nanoparticle model system. The data confirm that only a fraction of the nanoparticle ligands is involved in the binding processes: with a total ligand valency of 29 ligands/100 nm² surface area a maximum 5.3 ligands/100 nm² are involved in specific receptor binding. This corresponds to an average number of 251 binding ligands per nanoparticle, a number that can be rationalized within the biological context of the model system.

Intracellular reactive oxygen species (ROS) are associated with various inflammatory physiological processes and diseases, highlighting the need for their regulation to mitigate the detrimental effects of oxidative stress and to reduce cellular damage and disease progression. Here, we demonstrate cerium oxide (ceria) nanorods synthesized using a sol-gel method followed by heat treatment, called "AHT-CeNRs", as an efficient intracellular ROS scavenger. The synthesized AHT-CeNRs exhibited exceptional superoxide dismutase (SOD) and catalase (CAT)-like activities, both of which are crucial for converting ROS into harmless products. This was attributed to their high crystallinity, large surface area, numerous defects including oxygen vacancies, and abundant Ce³⁺ species. AHT-CeNRs exhibited higher CAT-like activities than natural CAT and conventional nanozymes, with a more than five-fold lower K_m. When tested on HaCaT human keratinocyte cells, AHT-CeNRs primarily localized to the membrane but effectively scavenged intracellular ROS, potentially through their transmembrane catalytic action without disrupting the membrane. This contrasts with conventional antioxidant nanoparticles that act within the cytosol after penetrating the plasma membrane. AHT-CeNRs maintained cell viability by efficiently scavenging ROS, resulting in approximately 4-fold and 2-fold lower levels of inducible nitric oxide synthase (iNOS) and lactate dehydrogenase (LDH) compared to those in ROS-induced inflammation-stimulator lipopolysaccharide (LPS)-treated control groups, respectively. This simple yet effective method for intracellular ROS scavenging using AHT-CeNRs holds great potential for applications in cell and in vivo therapeutics to regulate intracellular ROS levels.

Our Emerging Investigator Series features exceptional work by early-career nanoscience and nanotechnology researchers. Read Jovana Milić's Emerging Investigator Series article 'Resistive switching memories with enhanced durability enabled by mixed-dimensional perfluoroarene perovskite heterostructures' (https://doi.org/10.1039/D4NH00104D) and read more about her in the interview below.

Mapping the weights of an Artificial Neural Network (ANN) onto the resistance values of analog memristors can significantly enhance the throughput and energy efficiency of artificial intelligence (AI) applications, while also supporting AI deployment on edge devices. However, unlike traditional digital-based processing units, implementing AI computation on analog memristors presents certain challenges. The non-linear resistance switching characteristics and limited numerical bit precision, determined by the number of program levels, can become bottlenecks affecting the accuracy of ANN models. In this study, we introduce a resistance control method, a feedforward pulse scheme that enhances resistance configuration precision and increases the number of programmable levels. Additionally, we propose an evaluation method to explore the impact of setting multi-level resistance states on ANN accuracy. Through demonstrations on a TiO_2-x-based memristor, our method achieves 512 states on a device with a high resistance state to a low resistance state ratio of just 1.19. Our approach achieves 95.5% accuracy on ResNet-34 with over 20 million parameters through weight transfer, thereby demonstrating the potential of analog memristors in AI model inference. Furthermore, our findings pave the way for future advancements in increasing resistance states, which will enable more complex AI tasks and enhance the in-memory computational capabilities required for AI edge applications.

Polarization-sensitive photodetectors based on two-dimensional (2D) materials have garnered significant research attention owing to their distinctive architectures and exceptional photophysical properties. Specifically, anisotropic 2D materials, including semiconductors such as black phosphorus (BP), tellurium (Te), transition metal dichalcogenides (TMDs), and tantalum nickel pentaselenide (Ta₂NiSe₅), as well as semimetals like 1T'-MoTe₂ and PdSe₂, and their diverse van der Waals (vdW) heterojunctions, exhibit broad detection spectral ranges and possess inherent functional advantages. To date, numerous polarization-sensitive photodetectors based on 2D materials have been documented. This review initially provides a concise overview of the detection mechanisms and performance metrics of 2D polarization-sensitive photodetectors, which are pivotal for assessing their photodetection capabilities. It then examines the latest advancements in polarization-sensitive photodetectors based on individual 2D materials, 2D vdW heterojunctions, nanoantenna/electrode engineering, and structural strain integrated with 2D structures, encompassing a range of devices from the ultraviolet to infrared bands. However, several challenges persist in developing more comprehensive and functional 2D polarization-sensitive photodetectors. Further research in this area is essential. Ultimately, this review offers insights into the current limitations and challenges in the field and presents general recommendations to propel advancements and guide the progress of 2D polarization-sensitive photodetectors.