No abstract

To realise molecular scale electrical operations beyond the von Neumann bottleneck, new types of multi-functional switches are needed that mimic selflearning or neuromorphic computing by dynamically toggling between multiple operations that depend on their past. Here we report a molecule that switches from high to low conductance states with massive negative memristive behaviour that depends on the drive speed and number of past switching events, with all measurements fully modelled using atomistic and analytical models. This dynamic molecular switch (DMS) emulates synaptic behaviour and Pavlovian learning, all within a 2.4 nm thick layer that is three orders of magnitude thinner than a neuronal synapse. The DMS provides all fundamental logic gates necessary for deep learning because of its time-domain and voltage-dependent plasticity. The synapse-mimicking multi-functional DMS represents adaptable molecular scale hardware operable in solid-state devices opening a pathway to simplify dynamic complex electrical operations encoded within a single ultra-compact component.

Understanding and controlling the orbital alignment of molecules placed between electrodes is essential in the design of practically-applicable molecular and nanoscale electronic devices. The orbital alignment is highly determined by...

Atom interferometers are a useful tool for precision measurements of fundamental physical phenomena, ranging from local gravitational field strength to the atomic fine structure constant. In such experiments, it is desirable to implement a high momentum transfer "beam-splitter," which may be achieved by inducing quantum resonance in a finite-temperature laser-driven atomic gas. We use Monte Carlo simulations to investigate these quantum resonances in the regime where the gas receives laser pulses of finite duration, and demonstrate that an -classical model for the dynamics of the gas atoms is capable of reproducing quantum resonant behavior for both zero-temperature and finite-temperature non-interacting gases. We show that this model agrees well with the fully quantum treatment of the system over a time-scale set by the choice of experimental parameters. We also show that this model is capable of correctly treating the time-reversal mechanism necessary for implementing an interferometer with this physical configuration. arXiv:1604.08108v1 [quant-ph]

Liquid metal droplets, such as eutectic gallium–indium (EGaIn), are important in many research areas, such as soft electronics, catalysis, and energy storage. Droplet contact on solid surfaces is typically achieved without control over the applied force and without optimizing the wetting properties in different environments (e.g., in air or liquid), resulting in poorly defined contact areas. In this work, we demonstrate the direct manipulation of EGaIn microdroplets using an atomic force microscope (AFM) to generate repeated, on-demand making and breaking of contact on self-assembled monolayers (SAMs) of alkanethiols. The nanoscale positional control and feedback loop in an AFM allow us to control the contact force at the nanonewton level and, consequently, tune the droplet contact areas at the micrometer length scale in both air and ethanol. When submerged in ethanol, the droplets are highly nonwetting, resulting in hysteresis-free contact forces and minimal adhesion; as a result, we are able to create reproducible geometric contact areas of 0.8–4.5 μm2 with the alkanethiolate SAMs in ethanol. In contrast, there is a larger hysteresis in the contact forces and larger adhesion for the same EGaIn droplet in air, which reduced the control over the contact area (4–12 μm2). We demonstrate the usefulness of the technique and of the gained insights in EGaIn contact mechanics by making well-defined molecular tunneling junctions based on alkanethiolate SAMs with small geometric contact areas of between 4 and 12 μm2 in air, 1 to 2 orders of magnitude smaller than previously achieved.