Nanoscale Horizons最新文献

This article highlights the recent work of Coleman et al. (Nanoscale Horiz., 2024, 9, 1774-1784, https://doi.org/10.1039/D4NH00224E) on investigating nanosheet thickness and its impact on piezoresistivity in graphene strain sensors.

The use of health-relevant bacteria originating from human microbiomes for the control or therapy of diseases, including neurodegenerative disorders or diabetes, is currently gaining increasing importance in medicine. Directed and successful engineering of microbiomes via probiotic supplementation requires subtle, precise as well as, more importantly, easy, fast and convenient monitoring of its success, e.g., in patients' gut. Based on a previously described polyclonal SELEX aptamer library evolved against the human gut bacterium Blautia producta, we finally isolated three individual aptamers that proved their performance concerning affinity, specificity and robustness in reliably labeling the target bacterium and in combination with "contaminating" control bacteria. Using biofunctionalization molecules on gFETs, we could specifically quantify 10¹-10⁶ cells per mL, retrace their number in mixtures and determine aptamer K_d-values around 2 nM. These measurements were possible even in the context of a real human stool sample. Our results qualify gFETs in combination with BL2, BL7 and BL8 aptamers as a promising foundation for the construction of respective sensing devices, which will open new avenues towards developing an intended monitoring technique for probiotic therapy and microbiome engineering approaches.

Our Emerging Investigator Series features exceptional work by early-career nanoscience and nanotechnology researchers. Read Pengzhan Sun’s Emerging Investigator Series article ‘Catalytic selectivity of nanorippled graphene’ (https://doi.org/10.1039/D3NH00462G) and read more about him in the interview below.

Our Emerging Investigator Series features exceptional work by early-career nanoscience and nanotechnology researchers. Read Valentina Castagnola’s Emerging Investigator Series article ‘Sources of biases in the in vitro testing of nanomaterials: the role of the biomolecular corona’ (https://doi.org/10.1039/D3NH00510K) and read more about her in the interview below.

In the field of electromagnetic interference (EMI) shielding with materials based on highly porous constructs, such as foams, cryogels, aerogels and xerogels, a significant challenge lies in designing structures that primarily absorb rather than reflect incident electromagnetic waves (EMWs). This goal necessitates a dual focus on the electrical conductivity and the internal porosity of the given porous material. To explore these issues, we fabricated various graphene oxide (GO)-based cryogels by molding, emulsion templating, chemically-induced gelation, freeze-casting, and liquid-in-liquid streaming. Following thermal annealing to enhance electrical conductivity for effective EMI shielding, we assessed the physicochemical, mechanical and structural characteristics of these cryogels. Notably, the cryogels exhibited distinct EMI shielding behaviors, varying significantly in terms of primary shielding mechanisms and overall shielding effectiveness (SE_T). For example, chemically-crosslinked cryogels, which showed the highest electrical conductivity, predominantly reflected EMWs, achieving a reflectance of approximately 70% and a SE_T of 43.2 dB. In contrast, worm-like cryogels, despite having a similar SE_T of 42.9 dB, displayed a unique absorption-dominant shielding mechanism. This was attributed to their multi-scale porosities and numerous internal interfaces, which significantly enhanced their ability to absorb EMWs, reflected in an absorbance of 54.7%. Through these experiments, our aim is to provide key heuristic rules for the structural design of EMI shields.

Increasing the InN content in the In_xGa_1−xN compound is paramount for optoelectronic applications. It has been demonstrated in homogeneous nanowires or deliberately grown nanowire heterostructures. Here, we present spontaneous core–shell In_xGa_1−xN nanowires grown by molecular beam epitaxy on Si substrates at 625 °C. These heterostructures have a high InN fraction in the cores around 0.4 and sharp interfaces, and exhibit bright photoluminescence at 650 nm. The surprising effect of material separation is attributed to the periodically changing environment for instantaneous growth of single monolayers on top of nanowires. Due to a smaller collection length of N adatoms, each monolayer nucleates under a balanced V/III ratio, but then continues under highly group III rich conditions. As a result, the miscibility gap is suppressed in the cores but remains in the shells. These results provide a simple method for obtaining high-quality InGaN heterostructures emitting in the extended wavelength range.

Intermetallic compound (IMC) catalysts have garnered significant attention due to their unique surface and electronic properties, which can lead to enhanced catalytic performance compared to traditional monometallic catalysts. However, developing IMC materials as high-performance catalysts has been hindered by the inherent complexity of synthesizing nanoparticles with well-defined bulk and surface compositions. Achieving precise control over the composition of supported bimetallic IMC catalysts, especially those with high surface area and stability, has proven challenging. This review provides a comprehensive overview of the recent progress in developing supported IMC catalysts. We first examine the various synthetic approaches that have been explored to prepare supported IMC nanoparticles with phase-pure bulk structures and tailored surface compositions. Key factors influencing the formation kinetics and compositional control of these materials are discussed in detail. Then the strategies for manipulating the surface composition of supported IMCs are delved into. Applications of high-performance supported IMCs in important reactions such as selective hydrogenation, reforming, dehydrogenation, and deoxygenation are comprehensively reviewed, showcasing the unique advantages offered by these materials. Finally, the prevailing research challenges associated with supported IMCs are identified, including the need for a better understanding of the composition-property relationships and the development of scalable synthesis methods. The prospects for the practical implementation of these versatile catalysts in industrial processes are also highlighted, underscoring the importance of continued research in this field.

Semiconducting single-wall carbon nanotubes (SWCNTs) are a promising material platform for near-infrared in vivo imaging, optical sensing, and single-photon emission at telecommunication wavelengths. The functionalization of SWCNTs with luminescent defects can lead to significantly enhanced photoluminescence (PL) properties due to efficient trapping of highly mobile excitons and red-shifted emission from these trap states. Among the most studied luminescent defect types are oxygen and aryl defects that have largely similar optical properties. So far, no direct comparison between SWCNTs functionalized with oxygen and aryl defects under identical conditions has been performed. Here, we employ a combination of spectroscopic techniques to quantify the number of defects, their distribution along the nanotubes and thus their exciton trapping efficiencies. The different slopes of Raman D/G⁺ ratios versus calculated defect densities from PL quantum yield measurements indicate substantial dissimilarities between oxygen and aryl defects. Supported by statistical analysis of single-nanotube PL spectra at cryogenic temperatures they reveal clustering of oxygen defects. The clustering of 2–3 oxygen defects, which act as a single exciton trap, occurs irrespective of the functionalization method and thus enables the use of simple equations to determine the density of oxygen defects and defect clusters in SWCNTs based on standard Raman spectroscopy. The presented analytical approach is a versatile and sensitive tool to study defect distribution and clustering in SWCNTs and can be applied to any new functionalization method.

In-sensor computing has gained attention as a solution to overcome the von Neumann computing bottlenecks inherent in conventional sensory systems. This attention is due to the ability of sensor elements to directly extract meaningful information from external signals, thereby simplifying complex data. The advantage of in-sensor computing can be maximized with the sampling principle of a restricted Boltzmann machine (RBM) to extract significant features. In this study, a stochastic photo-responsive neuron is developed using a TiN/In–Ga–Zn–O/TiN optoelectronic memristor and an Ag/HfO₂/Pt threshold-switching memristor, which can be configured as an input neuron in an in-sensor RBM. It demonstrates a sigmoidal switching probability depending on light intensity. The stochastic properties allow for the simultaneous exploration of various neuron states within the network, making identifying optimal features in complex images easier. Based on semi-empirical simulations, high recognition accuracies of 90.9% and 95.5% are achieved using handwritten digit and face image datasets, respectively. In addition, the in-sensor RBM effectively reconstructs abnormal face images, indicating that integrating in-sensor computing with probabilistic neural networks can lead to reliable and efficient image recognition under unpredictable real-world conditions.

Understanding the mechanisms underlying viral entry is crucial for controlling viral diseases. In this study, we investigated the interactions between reovirus and Nogo-receptor 1 (NgR1), a key mediator of reovirus entry into the host central nervous system. NgR1 exhibits a unique bivalent interaction with the reovirus capsid, specifically binding at the interface between adjacent heterohexamers arranged in a precise structural pattern on the curved virus surface. Using single-molecule techniques, we explored for the first time how the capsid molecular architecture and receptor polymorphism influence virus binding. We compared the binding affinities of human and mouse NgR1 to reovirus μ1/σ3 proteins in their isolated form, self-assembled in 2D capsid patches, and within the native 3D viral topology. Our results underscore the essential role of the concave side of NgR1 and emphasize that the spatial organization and curvature of the virus are critical determinants of the stability of the reovirus–NgR1 complex. This study highlights the importance of characterizing interactions in physiologically relevant spatial configurations, providing precise insights into virus–host interactions and opening new avenues for therapeutic interventions against viral infections.