Colloidal robotics.

Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.

Integrated biosensor platform based on graphene transistor arrays for real-time high-accuracy ion sensing.

Two-dimensional materials such as graphene have shown great promise as biosensors, but suffer from large device-to-device variation due to non-uniform material synthesis and device fabrication technologies. Here, we develop a robust bioelectronic sensing platform  composed of  more than 200 integrated sensing units, custom-built high-speed readout electronics, and machine learning inference that overcomes these challenges to achieve rapid, portable, and reliable measurements. The platform demonstrates reconfigurable multi-ion electrolyte sensing capability and provides highly sensitive, reversible, and real-time response for potassium, sodium, and calcium ions in complex solutions despite variations in device performance. A calibration method leveraging the sensor redundancy and device-to-device variation is also proposed, while a machine learning model trained with multi-dimensional information collected through the multiplexed sensor array is used to enhance the sensing system's functionality and accuracy in ion classification.

Waveguide-integrated mid-infrared photodetection using graphene on a scalable chalcogenide glass platform.

The development of compact and fieldable mid-infrared (mid-IR) spectroscopy devices represents a critical challenge for distributed sensing with applications from gas leak detection to environmental monitoring. Recent work has focused on mid-IR photonic integrated circuit (PIC) sensing platforms and waveguide-integrated mid-IR light sources and detectors based on semiconductors such as PbTe, black phosphorus and tellurene. However, material bandgaps and reliance on SiO2 substrates limit operation to wavelengths λ ≲ 4 µm. Here we overcome these challenges with a chalcogenide glass-on-CaF2 PIC architecture incorporating split-gate photothermoelectric graphene photodetectors. Our design extends operation to λ = 5.2 µm with a Johnson noise-limited noise-equivalent power of 1.1 nW/Hz1/2, no fall-off in photoresponse up to f = 1 MHz, and a predicted 3-dB bandwidth of f3dB > 1 GHz. This mid-IR PIC platform readily extends to longer wavelengths and opens the door to applications from distributed gas sensing and portable dual comb spectroscopy to weather-resilient free space optical communications.

SynCells: A 60 × 60 µm2 Electronic Platform with Remote Actuation for Sensing Applications in Constrained Environments.

Autonomous electronic microsystems smaller than the diameter of a human hair (<100 µm) are promising for sensing in confined spaces such as microfluidic channels or the human body. However, they are difficult to implement due to fabrication challenges and limited power budget. Here we present a 60 × 60 µm electronic microsystem platform, or SynCell, that overcomes these issues by leveraging the integration capabilities of two-dimensional material circuits and the low power consumption of passive germanium timers, memory-like chemical sensors, and magnetic pads. In a proof-of-concept experiment, we magnetically positioned SynCells in a microfluidic channel to detect putrescine. After we extracted them from the channel, we successfully read out the timer and sensor signal, the latter of which can be amplified by an onboard transistor circuit. The concepts developed here will be applicable to microsystems targeting a variety of applications from microfluidic sensing to biomedical research.

Additive manufacturing of patterned 2D semiconductor through recyclable masked growth.

The 2D van der Waals crystals have shown great promise as potential future electronic materials due to their atomically thin and smooth nature, highly tailorable electronic structure, and mass production compatibility through chemical synthesis. Electronic devices, such as field effect transistors (FETs), from these materials require patterning and fabrication into desired structures. Specifically, the scale up and future development of "2D"-based electronics will inevitably require large numbers of fabrication steps in the patterning of 2D semiconductors, such as transition metal dichalcogenides (TMDs). This is currently carried out via multiple steps of lithography, etching, and transfer. As 2D devices become more complex (e.g., numerous 2D materials, more layers, specific shapes, etc.), the patterning steps can become economically costly and time consuming. Here, we developed a method to directly synthesize a 2D semiconductor, monolayer molybdenum disulfide (MoS2), in arbitrary patterns on insulating SiO2/Si via seed-promoted chemical vapor deposition (CVD) and substrate engineering. This method shows the potential of using the prepatterned substrates as a master template for the repeated growth of monolayer MoS2 patterns. Our technique currently produces arbitrary monolayer MoS2 patterns at a spatial resolution of 2 µm with excellent homogeneity and transistor performance (room temperature electron mobility of 30 cm2 V-1 s-1 and on-off current ratio of 107). Extending this patterning method to other 2D materials can provide a facile method for the repeatable direct synthesis of 2D materials for future electronics and optoelectronics.

Characterizing percolative materials by straining.

Carrier transport in a wide range of nanomaterial assemblies proceeds by percolation through discontinuous networks of constituents. Improving percolative nanomaterials could enhance transparent conductors, sensors, and electronic devices. A significant obstacle in optimizing percolative materials is the challenge in their characterization. The critical connection pathways which determine a percolative material's conductivity are not easily accessible with existing metrology tools and traditional investigation approaches rely on indirect methods based on many samples and on simplifying assumptions. We here demonstrate the direct extraction of characteristic parameters from a single sample by analyzing the strain-dependent resistance of percolative materials. An analytical model is derived that can explain experimental data for various percolative materials, morphologies, and straining conditions. The relationship of the extracted parameters with previously introduced figures of merit allows us to compare nanostructures of diverse dimensionalities and compositions for applications such as strain gauges and transparent conductors.

Fast water transport in graphene nanofluidic channels.

Superfast water transport discovered in graphitic nanoconduits, including carbon nanotubes and graphene nanochannels, implicates crucial applications in separation processes and energy conversion. Yet lack of complete understanding at the single-conduit level limits development of new carbon nanofluidic structures and devices with desired transport properties for practical applications. Here, we show that the hydraulic resistance and slippage of single graphene nanochannels can be accurately determined using capillary flow and a novel hybrid nanochannel design without estimating the capillary pressure. Our results reveal that the slip length of graphene in the graphene nanochannels is around 16 nm, albeit with a large variation from 0 to 200 nm regardless of the channel height. We corroborate this finding with molecular dynamics simulation results, which indicate that this wide distribution of the slip length is due to the surface charge of graphene as well as the interaction between graphene and its silica substrate.

A novel class of strain gauges based on layered percolative films of 2D materials.

Here we report on the fabrication and characterization of a novel type of strain gauge based on percolative networks of 2D materials. The high sensitivity of the percolative carrier transport to strain induced morphology changes was exploited in strain sensors that can be produced from a wide variety of materials. Highly reliable and sensitive graphene-based thin film strain gauges were produced from solution processed graphene flakes by spray deposition. Control of the gauge sensitivity could be exerted through deposition-induced changes to the film morphology. This exceptional property was explained through modeling of the strain induced changes to the flake-flake overlap for different percolation networks. The ability to directly deposit strain gauges on complex-shaped and transparent surfaces was presented. The demonstrated scalable fabrication, superior sensitivity over conventional sensors, and unique properties of the described strain gauges have the potential to improve existing technology and open up new fields of applications for strain sensors.