Nature nanotechnology最新文献

The recent discovery of superconductivity and magnetism in trilayer rhombohedral graphene (RG) establishes an ideal, untwisted platform to study strong correlation electronic phenomena. However, the correlated effects in multilayer RG have received limited attention, and, particularly, the evolution of the correlations with increasing layer number remains an unresolved question. Here we show the observation of layer-dependent electronic structures and correlations—under surprising liquid nitrogen temperature—in RG multilayers from 3 to 9 layers by using scanning tunnelling microscopy and spectroscopy. We explicitly determine layer-enhanced low-energy flat bands and interlayer coupling strengths. The former directly demonstrates the further flattening of low-energy bands in thicker RG, and the latter indicates the presence of varying interlayer interactions in RG multilayers. Moreover, we find significant splittings of the flat bands, ranging from ~50 meV to 80 meV, at 77 K when they are partially filled, indicating the emergence of interaction-induced strongly correlated states. Particularly, the strength of the correlated states is notably enhanced in thicker RG and reaches its maximum in the six-layer, validating directly theoretical predictions and establishing abundant new candidates for strongly correlated systems. Our results provide valuable insights into the layer dependence of the electronic properties in RG and demonstrate it as a suitable system for investigating robust and highly accessible correlated phases.

Olefin metathesis, as a powerful metal-catalysed carbon–carbon bond-forming method, has achieved considerable progress in recent years. However, the complexity originating from multicomponent interactions has long impeded a complete mechanistic understanding of olefin metathesis, which hampers further optimization of the reaction. Here, we clarify both productive and hidden degenerate pathways of ring-closing metathesis by focusing on one individual catalyst, using a sensitive single-molecule electrical detection platform. In addition to visualizing the full pathway, we found that the conventionally unwanted degenerate pathways have an unexpected constructive coupling effect on the productive pathway, and both types of pathway can be regulated by an external electric field. We then pushed forward this ability to ring-opening metathesis polymerization involving more interactive components. With single-monomer-insertion-event resolution, precise on-device synthesis of a single polymer was achieved by online manipulation of monomer insertion dynamics, intramolecular chain transfer, stereoregularity, degree of polymerization and block copolymerization. These results offer a comprehensive mechanistic understanding of olefin metathesis, exemplifying infinite opportunities for practical precise manufacturing.

In-sensor computing, which integrates sensing, memory and processing functions, has shown substantial potential in artificial vision systems. However, large-scale monolithic integration of in-sensor computing based on emerging devices with complementary metal–oxide–semiconductor (CMOS) circuits remains challenging, lacking functional demonstrations at the hardware level. Here we report a fully integrated 1-kb array with 128 × 8 one-transistor one-optoelectronic memristor (OEM) cells and silicon CMOS circuits, which features configurable multi-mode functionality encompassing three different modes of electronic memristor, dynamic OEM and non-volatile OEM (NV-OEM). These modes are configured by modulating the charge density within the oxygen vacancies via synergistic optical and electrical operations, as confirmed by differential phase-contrast scanning transmission electron microscopy. Using this OEM system, three visual processing tasks are demonstrated: image sensory pre-processing with a recognition accuracy enhanced from 85.7% to 96.1% by the NV-OEM mode, more advanced object tracking with 96.1% accuracy using both dynamic OEM and NV-OEM modes and human motion recognition with a fully OEM-based in-sensor reservoir computing system achieving 91.2% accuracy. A system-level benchmark further shows that it consumes over 20 times less energy than graphics processing units. By monolithically integrating the multi-functional OEMs with Si CMOS, this work provides a cost-effective platform for diverse in-sensor computing applications.

Biosensors play key roles in medical research and diagnostics. However, the development of biosensors for new biomolecular targets of interest often involves tedious optimization steps to ensure a high signal response at the analyte concentration of interest. Here we show a modular nanosensor platform that facilitates these steps by offering ways to decouple and independently tune the signal output as well as the response window. Our approach utilizes a dynamic DNA origami nanostructure to engineer a high optical signal response based on fluorescence resonance energy transfer. We demonstrate mechanisms to tune the sensor’s response window, specificity and cooperativity as well as highlight the modularity of the proposed platform by extending it to different biomolecular targets including more complex sensing schemes. This versatile nanosensor platform offers a promising starting point for the rapid development of biosensors with tailored properties.

Nerve–cancer crosstalk has gained substantial attention owing to its impact on tumour growth, metastasis and therapy resistance. Effective therapeutic strategies targeting tumour-associated nerves within the intricate tumour microenvironment remain a major challenge in pancreatic cancer. Here we develop Escherichia coli Nissle 1917-derived outer membrane vesicles conjugated with nerve-binding peptide NP41, loaded with the tropomyosin receptor kinase (Trk) inhibitor larotrectinib (Lar@NP-OMVs) for tumour-associated nerve targeting. Lar@NP-OMVs achieve efficient nerve intervention to diminish neurite growth by disrupting the neurotrophin/Trk signalling pathway. Moreover, OMV-mediated repolarization of M2-like tumour-associated macrophages to an M1-like phenotype results in nerve injury, further accentuating Lar@NP-OMV-induced nerve intervention to inhibit nerve-triggered proliferation and migration of pancreatic cancer cells and angiogenesis. Leveraging this strategy, Lar@NP-OMVs significantly reduce nerve infiltration and neurite growth promoted by gemcitabine within the tumour microenvironment, leading to augmented chemotherapy efficacy in pancreatic cancer. This study sheds light on a potential avenue for nerve-targeted therapeutic intervention for enhancing pancreatic cancer therapy.

Blue lasers play a pivotal role in laser-based display, printing, manufacturing, data recording and medical technologies. Colloidal quantum dots (QDs) are solution-grown materials with strong, tunable emission covering the whole visible spectrum, but the development of QD lasers has largely relied on Cd-containing red-emitting QDs, with technologically viable blue QD lasers remaining out of reach. Here we report on the realization of tunable and robust lasing using low-toxicity blue-emitting ZnSe–ZnS core–shell QDs that are compact in size yet still feature suppressed Auger recombination and long optical gain lifetime approaching 1 ns. These characteristics allow us to handle the blue QDs like laser dyes for liquid-state amplified spontaneous emission and lasing. The blue QD laser is operated under quasi-continuous-wave excitation by solid-state nanosecond lasers. A Littrow-configuration cavity enables narrow linewidth (<0.2 nm), wavelength-tunable, coherent and stable laser outputs without circulating the solution. These results indicate the promise of ZnSe–ZnS QDs to fill the ‘blue gap’ of QD lasers and to replace less stable blue laser dyes for a multitude of applications.

The coherent control of interacting spins in semiconductor quantum dots is of strong interest for quantum information processing and for studying quantum magnetism from the bottom up. Here we present a 2 × 4 germanium quantum dot array with full and controllable interactions between nearest-neighbour spins. As a demonstration of the level of control, we define four singlet–triplet qubits in this system and show two-axis single-qubit control of each qubit and SWAP-style two-qubit gates between all neighbouring qubit pairs, yielding average single-qubit gate fidelities of 99.49(8)–99.84(1)% and Bell state fidelities of 73(1)–90(1)%. Combining these operations, we experimentally implement a circuit designed to generate and distribute entanglement across the array. A remote Bell state with a fidelity of 75(2)% and concurrence of 22(4)% is achieved. These results highlight the potential of singlet–triplet qubits as a competing platform for quantum computing and indicate that scaling up the control of quantum dot spins in extended bilinear arrays can be feasible.

Extracellular vesicles (EVs) are diverse nanoparticles with large heterogeneity in size and molecular composition. Although this heterogeneity provides high diagnostic value for liquid biopsy and confers many exploitable functions for therapeutic applications in cancer detection, wound healing and neurodegenerative and cardiovascular diseases, it has also impeded their clinical translation—hence heterogeneity acts as a double-edged sword. Here we review the impact of subpopulation heterogeneity on EV function and identify key cornerstones for addressing heterogeneity in the context of modern analytical platforms with single-particle resolution. We outline concrete steps towards the identification of key active biomolecules that determine EV mechanisms of action across different EV subtypes. We describe how such knowledge could accelerate EV-based therapies and engineering approaches for mimetic artificial nanovesicle formulations. This approach blunts one edge of the sword, leaving only a single razor-sharp edge on which EV heterogeneity can be exploited for therapeutic applications across many diseases.

Currently, intravascular optical coherence tomography (IV-OCT) is limited to anatomical imaging, providing structural information about atherosclerotic plaque morphology, thrombus and dissection. Earlier detection and risk stratification would be possible through molecular characterization of endothelium but necessitates a purpose-engineered IV-OCT contrast agent. Here we developed gold superclusters (AuSCs) tailored to clinical instrumentation and integrated into clinically relevant workflows. AuSCs are aqueously dispersible clusters of closely packed small gold nanoparticles, affording plasmon hybridization to maximize light scattering at the IV-OCT laser line (~1,350 nm). A polymer coating fosters AuSC uniformity and provides a functionalizable handle, which we targeted to intravascular P-selectin, an early vascular endothelial marker of inflammation. In a rat model of intravascular inflammation, P-selectin-targeted AuSC facilitated IV-OCT molecular imaging, where the strength of the signal correlates with the severity of vascular inflammation.