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At the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes. Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal.

2D materials have attracted considerable attention in the past decade for their superlative physical properties. These materials consist of atomically thin sheets exhibiting covalent in-plane bonding and weak interlayer and layer–substrate bonding. Following the example of graphene, most emerging 2D materials are derived from structures that can be isolated from bulk phases of layered materials, which form a limited library for new materials discovery. Entirely synthetic 2D materials provide access to a greater range of properties through the choice of constituent elements and substrates. Of particular interest are elemental 2D materials, because they provide the most chemically tractable case for synthetic exploration. In this Review, we explore the progress made in the synthesis and chemistry of synthetic elemental 2D materials, and offer perspectives and challenges for the future of this emerging field. This Review covers recent progress and current challenges in the synthesis and stabilization of elemental 2D materials — topical species with peculiar properties. The further development of preparative methodologies will help to expand the 2D materials library well beyond naturally occurring layered materials, and afford products with unique structures and functions.

Techniques that can dexterously manipulate single particles, cells, and organisms are invaluable for many applications in biology, chemistry, engineering, and physics. Here, we demonstrate standing surface acoustic wave based “acoustic tweezers” that can trap and manipulate single microparticles, cells, and entire organisms (i.e., Caenorhabditis elegans) in a single-layer microfluidic chip. Our acoustic tweezers utilize the wide resonance band of chirped interdigital transducers to achieve real-time control of a standing surface acoustic wave field, which enables flexible manipulation of most known microparticles. The power density required by our acoustic device is significantly lower than its optical counterparts (10,000,000 times less than optical tweezers and 100 times less than optoelectronic tweezers), which renders the technique more biocompatible and amenable to miniaturization. Cell-viability tests were conducted to verify the tweezers’ compatibility with biological objects. With its advantages in biocompatibility, miniaturization, and versatility, the acoustic tweezers presented here will become a powerful tool for many disciplines of science and engineering.

The quest to implement machine learning algorithms in hardware has focused on combining various materials, each mimicking a computational primitive, to create device functionality. Ultimately, these piecewise approaches limit functionality and efficiency, while complicating scaling and on-chip learning, necessitating new approaches linking physical phenomena to machine learning models. Here, we create an atomic spin system that emulates a Boltzmann machine directly in the orbital dynamics of one well-defined material system. Utilizing the concept of orbital memory based on individual cobalt atoms on black phosphorus, we fabricate the prerequisite tuneable multi-well energy landscape by gating patterned atomic ensembles using scanning tunnelling microscopy. Exploiting the anisotropic behaviour of black phosphorus, we realize plasticity with multi-valued and interlinking synapses that lead to tuneable probability distributions. Furthermore, we observe an autonomous reorganization of the synaptic weights in response to external electrical stimuli, which evolves at a different time scale compared to neural dynamics. This self-adaptive architecture paves the way for autonomous learning directly in atomic-scale machine learning hardware.Stochastic orbital dynamics of individually coupled Co atoms on black phosphorus enables the realization of a Boltzmann machine capable of self-adaption.

A magnetic atom epitomizes the scaling limit for magnetic information storage. Individual atomic spins have recently exhibited magnetic remanence, a requirement for magnetic memory. However, such memory has been only realized on thin insulating surfaces, removing potential tunability via electronic gating or exchange-driven magnetic coupling. Here, we show a previously unobserved mechanism for single-atom magnetic storage based on bistability in the orbital population, or so-called valency, of an individual Co atom on semiconducting black phosphorus (BP). Ab initio calculations reveal that distance-dependent screening from the BP surface stabilizes the two distinct valencies, each with a unique orbital population, total magnetic moment, and spatial charge density. Excellent correspondence between the measured and predicted charge densities reveal that such orbital configurations can be accessed and manipulated without a spin-sensitive readout mechanism. This orbital memory derives stability from the energetic barrier to atomic relaxation, demonstrating the potential for high-temperature single-atom information storage. Single-atom storage can dramatically exceed the limit of traditional high-density memory devices but is challenging. Here the authors show the bistability in the orbital configuration of a single Co atom on black phosphorus which can be accessed, manipulated and has potential for high-temperature single-atom information storage.

Graphene can be transformed from a semimetal into a semiconductor if it is confined into nanoribbons narrower than 10 nm with controlled crystallographic orientation and well-defined armchair edges. However, the scalable synthesis of nanoribbons with this precision directly on insulating or semiconducting substrates has not been possible. Here we demonstrate the synthesis of graphene nanoribbons on Ge(001) via chemical vapour deposition. The nanoribbons are self-aligning 3° from the Ge〈110〉 directions, are self-defining with predominantly smooth armchair edges, and have tunable width to <10 nm and aspect ratio to >70. In order to realize highly anisotropic ribbons, it is critical to operate in a regime in which the growth rate in the width direction is especially slow, <5 nm h −1 . This directional and anisotropic growth enables nanoribbon fabrication directly on conventional semiconductor wafer platforms and, therefore, promises to allow the integration of nanoribbons into future hybrid integrated circuits. Semiconducting armchair graphene nanoribbons with sub-10 nm width are of great technological importance but yet to realize. Here, the authors report growth of such nanoribbons on germanium and controlled crystallographic orientation and well-defined armchair edges are obtained.

Silver is a desirable platform for graphene growth because of the potential for hybrid graphene plasmonics and its emerging role as a preferred growth substrate for other two-dimensional materials, such as silicene. Here we demonstrate the direct growth of monolayer graphene on a single-crystal Ag(111) substrate. The inert nature of Ag has made it difficult to use for graphene synthesis using standard chemical vapour deposition techniques, which we have overcome by using an elemental carbon source. Atomic-scale scanning tunnelling microscopy reveals that the atomically clean graphene–silver substrate is free of organic residue and other contaminants. The dendritic graphene possesses a variety of edge terminations, many of which give rise to quantum interferences previously seen only on insulating substrates. This scattering supports spectroscopic evidence that the graphene electronic structure is minimally perturbed by the underlying silver, providing a new system in which graphene is decoupled from its growth substrate. The integration of graphene with silver offers the promise of combining the electronic and plasmonic properties of both materials. Here, Kiraly et al. achieve the growth of graphene on a silver substrate, with the graphene electronic structure only minimally affected by the silver.

Charge transfer is fundamentally dependent on the overlap of the orbitals comprising the transport pathway. This has key implications for molecular, nanoscale, and quantum technologies, for which delocalization (and decoherence) rates are essential figures of merit. Here, we apply the core hole clock technique—an energy-domain variant of ultrafast spectroscopy—to probe the delocalization of a photoexcited electron inside a closed molecular cage, namely the Ar 2 p 5 4 s 1 state of Ar@C 60 . Despite marginal frontier orbital mixing in the ground configuration, almost 80% of the excited state density is found outside the buckyball due to the formation of a markedly diffuse hybrid orbital. Far from isolating the intracage excitation, the surrounding fullerene is instead a remarkably efficient conduit for electron transfer: we measure characteristic delocalization times of 6.6 ± 0.3 fs and  ≲ 500 attoseconds, respectively, for a 3D Ar@C 60 film and a 2D monolayer on Ag(111). Charge transfer is facilitated in molecular systems through orbital coupling. Here the authors use core-hole-clock spectroscopy to show that electron transfer from an argon atom caged in a fullerene can be up to two orders of magnitude faster than for the isolated atom.

The optical excitation of surface plasmons in metal nanoparticles leads to nanoscale spatial confinement of electromagnetic fields. The confined electromagnetic fields can generate intense, localized thermal energy and large near-field optical forces. The interaction between these effects and nearby molecules has led to the emerging field known as molecular plasmonics. Recent advances in molecular plasmonics have enabled novel optical materials and devices with applications in biology and nanomedicine. In this article, we categorize three main types of interactions between molecules and surface plasmons: optical, thermal and mechanical. Within the scope of each type of interaction, we will review applications of molecular plasmonics in biology and nanomedicine. We include a wide range of applications that involve sensing, spectral analysis, imaging, delivery, manipulation and heating of molecules, biomolecules or cells using plasmonic effects. We also briefly describe the physical principles of molecular plasmonics and progress in the nanofabrication, surface functionalization and bioconjugation of metal nanoparticles.