Journal: Nature nanotechnology
Currently, there is no available needle-free approach for diabetics to monitor glucose levels in the interstitial fluid. Here, we report a path-selective, non-invasive, transdermal glucose monitoring system based on a miniaturized pixel array platform (realized either by graphene-based thin-film technology, or screen-printing). The system samples glucose from the interstitial fluid via electroosmotic extraction through individual, privileged, follicular pathways in the skin, accessible via the pixels of the array. A proof of principle using mammalian skin ex vivo is demonstrated for specific and ‘quantized’ glucose extraction/detection via follicular pathways, and across the hypo- to hyper-glycaemic range in humans. Furthermore, the quantification of follicular and non-follicular glucose extraction fluxes is clearly shown. In vivo continuous monitoring of interstitial fluid-borne glucose with the pixel array was able to track blood sugar in healthy human subjects. This approach paves the way to clinically relevant glucose detection in diabetics without the need for invasive, finger-stick blood sampling.
Graphene oxide membranes show exceptional molecular permeation properties, with promise for many applications. However, their use in ion sieving and desalination technologies is limited by a permeation cutoff of ∼9 Å (ref. 4), which is larger than the diameters of hydrated ions of common salts. The cutoff is determined by the interlayer spacing (d) of ∼13.5 Å, typical for graphene oxide laminates that swell in water. Achieving smaller d for the laminates immersed in water has proved to be a challenge. Here, we describe how to control d by physical confinement and achieve accurate and tunable ion sieving. Membranes with d from ∼9.8 Å to 6.4 Å are demonstrated, providing a sieve size smaller than the diameters of hydrated ions. In this regime, ion permeation is found to be thermally activated with energy barriers of ∼10-100 kJ mol(-1) depending on d. Importantly, permeation rates decrease exponentially with decreasing sieve size but water transport is weakly affected (by a factor of <2). The latter is attributed to a low barrier for the entry of water molecules and large slip lengths inside graphene capillaries. Building on these findings, we demonstrate a simple scalable method to obtain graphene-based membranes with limited swelling, which exhibit 97% rejection for NaCl.
Although cellular therapies represent a promising strategy for a number of conditions, current approaches face major translational hurdles, including limited cell sources and the need for cumbersome pre-processing steps (for example, isolation, induced pluripotency). In vivo cell reprogramming has the potential to enable more-effective cell-based therapies by using readily available cell sources (for example, fibroblasts) and circumventing the need for ex vivo pre-processing. Existing reprogramming methodologies, however, are fraught with caveats, including a heavy reliance on viral transfection. Moreover, capsid size constraints and/or the stochastic nature of status quo approaches (viral and non-viral) pose additional limitations, thus highlighting the need for safer and more deterministic in vivo reprogramming methods. Here, we report a novel yet simple-to-implement non-viral approach to topically reprogram tissues through a nanochannelled device validated with well-established and newly developed reprogramming models of induced neurons and endothelium, respectively. We demonstrate the simplicity and utility of this approach by rescuing necrotizing tissues and whole limbs using two murine models of injury-induced ischaemia.
The advent of devices based on single dopants, such as the single-atom transistor, the single-spin magnetometer and the single-atom memory, has motivated the quest for strategies that permit the control of matter with atomic precision. Manipulation of individual atoms by low-temperature scanning tunnelling microscopy provides ways to store data in atoms, encoded either into their charge state, magnetization state or lattice position. A clear challenge now is the controlled integration of these individual functional atoms into extended, scalable atomic circuits. Here, we present a robust digital atomic-scale memory of up to 1 kilobyte (8,000 bits) using an array of individual surface vacancies in a chlorine-terminated Cu(100) surface. The memory can be read and rewritten automatically by means of atomic-scale markers and offers an areal density of 502 terabits per square inch, outperforming state-of-the-art hard disk drives by three orders of magnitude. Furthermore, the chlorine vacancies are found to be stable at temperatures up to 77 K, offering the potential for expanding large-scale atomic assembly towards ambient conditions.
Nanoelectromechanical systems (NEMS) resonators can detect mass with exceptional sensitivity. Previously, mass spectra from several hundred adsorption events were assembled in NEMS-based mass spectrometry using statistical analysis. Here, we report the first realization of single-molecule NEMS-based mass spectrometry in real time. As each molecule in the sample adsorbs on the resonator, its mass and position of adsorption are determined by continuously tracking two driven vibrational modes of the device. We demonstrate the potential of multimode NEMS-based mass spectrometry by analysing IgM antibody complexes in real time. NEMS-based mass spectrometry is a unique and promising new form of mass spectrometry: it can resolve neutral species, provide a resolving power that increases markedly for very large masses, and allow the acquisition of spectra, molecule-by-molecule, in real time.
Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a ‘programming language’ and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.
The highest possible resolution for printed colour images is determined by the diffraction limit of visible light. To achieve this limit, individual colour elements (or pixels) with a pitch of 250 nm are required, translating into printed images at a resolution of ∼100,000 dots per inch (d.p.i.). However, methods for dispensing multiple colourants or fabricating structural colour through plasmonic structures have insufficient resolution and limited scalability. Here, we present a non-colourant method that achieves bright-field colour prints with resolutions up to the optical diffraction limit. Colour information is encoded in the dimensional parameters of metal nanostructures, so that tuning their plasmon resonance determines the colours of the individual pixels. Our colour-mapping strategy produces images with both sharp colour changes and fine tonal variations, is amenable to large-volume colour printing via nanoimprint lithography, and could be useful in making microimages for security, steganography, nanoscale optical filters and high-density spectrally encoded optical data storage.
Artificial neuromorphic systems based on populations of spiking neurons are an indispensable tool in understanding the human brain and in constructing neuromimetic computational systems. To reach areal and power efficiencies comparable to those seen in biological systems, electroionics-based and phase-change-based memristive devices have been explored as nanoscale counterparts of synapses. However, progress on scalable realizations of neurons has so far been limited. Here, we show that chalcogenide-based phase-change materials can be used to create an artificial neuron in which the membrane potential is represented by the phase configuration of the nanoscale phase-change device. By exploiting the physics of reversible amorphous-to-crystal phase transitions, we show that the temporal integration of postsynaptic potentials can be achieved on a nanosecond timescale. Moreover, we show that this is inherently stochastic because of the melt-quench-induced reconfiguration of the atomic structure occurring when the neuron is reset. We demonstrate the use of these phase-change neurons, and their populations, in the detection of temporal correlations in parallel data streams and in sub-Nyquist representation of high-bandwidth signals.
Seamless and minimally invasive three-dimensional interpenetration of electronics within artificial or natural structures could allow for continuous monitoring and manipulation of their properties. Flexible electronics provide a means for conforming electronics to non-planar surfaces, yet targeted delivery of flexible electronics to internal regions remains difficult. Here, we overcome this challenge by demonstrating the syringe injection (and subsequent unfolding) of sub-micrometre-thick, centimetre-scale macroporous mesh electronics through needles with a diameter as small as 100 μm. Our results show that electronic components can be injected into man-made and biological cavities, as well as dense gels and tissue, with >90% device yield. We demonstrate several applications of syringe-injectable electronics as a general approach for interpenetrating flexible electronics with three-dimensional structures, including (1) monitoring internal mechanical strains in polymer cavities, (2) tight integration and low chronic immunoreactivity with several distinct regions of the brain, and (3) in vivo multiplexed neural recording. Moreover, syringe injection enables the delivery of flexible electronics through a rigid shell, the delivery of large-volume flexible electronics that can fill internal cavities, and co-injection of electronics with other materials into host structures, opening up unique applications for flexible electronics.
Molecular electronics aims to miniaturize electronic devices by using subnanometre-scale active components. A single-molecule diode, a circuit element that directs current flow, was first proposed more than 40 years ago and consisted of an asymmetric molecule comprising a donor-bridge-acceptor architecture to mimic a semiconductor p-n junction. Several single-molecule diodes have since been realized in junctions featuring asymmetric molecular backbones, molecule-electrode linkers or electrode materials. Despite these advances, molecular diodes have had limited potential for applications due to their low conductance, low rectification ratios, extreme sensitivity to the junction structure and high operating voltages. Here, we demonstrate a powerful approach to induce current rectification in symmetric single-molecule junctions using two electrodes of the same metal, but breaking symmetry by exposing considerably different electrode areas to an ionic solution. This allows us to control the junction’s electrostatic environment in an asymmetric fashion by simply changing the bias polarity. With this method, we reliably and reproducibly achieve rectification ratios in excess of 200 at voltages as low as 370 mV using a symmetric oligomer of thiophene-1,1-dioxide. By taking advantage of the changes in the junction environment induced by the presence of an ionic solution, this method provides a general route for tuning nonlinear nanoscale device phenomena, which could potentially be applied in systems beyond single-molecule junctions.