Adaptive tactile interaction transfer via digitally embroidered smart gloves.

Human-machine interfaces for capturing, conveying, and sharing tactile information across time and space hold immense potential for healthcare, augmented and virtual reality, human-robot collaboration, and skill development. To realize this potential, such interfaces should be wearable, unobtrusive, and scalable regarding both resolution and body coverage. Taking a step towards this vision, we present a textile-based wearable human-machine interface with integrated tactile sensors and vibrotactile haptic actuators that are digitally designed and rapidly fabricated. We leverage a digital embroidery machine to seamlessly embed piezoresistive force sensors and arrays of vibrotactile actuators into textiles in a customizable, scalable, and modular manner. We use this process to create gloves that can record, reproduce, and transfer tactile interactions. User studies investigate how people perceive the sensations reproduced by our gloves with integrated vibrotactile haptic actuators. To improve the effectiveness of tactile interaction transfer, we develop a machine-learning pipeline that adaptively models how each individual user reacts to haptic sensations and then optimizes haptic feedback parameters. Our interface showcases adaptive tactile interaction transfer through the implementation of three end-to-end systems: alleviating tactile occlusion, guiding people to perform physical skills, and enabling responsive robot teleoperation.

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.

Scalable biomimetic sensing system with membrane receptor dual-monolayer probe and graphene transistor arrays.

Affinity-based biosensing can enable point-of-care diagnostics and continuous health monitoring, which commonly follows bottom-up approaches and is inherently constrained by bioprobes' intrinsic properties, batch-to-batch consistency, and stability in biofluids. We present a biomimetic top-down platform to circumvent such difficulties by combining a "dual-monolayer" biorecognition construct with graphene-based field-effect-transistor arrays. The construct adopts redesigned water-soluble membrane receptors as specific sensing units, positioned by two-dimensional crystalline S-layer proteins as dense antifouling linkers guiding their orientations. Hundreds of transistors provide statistical significance from transduced signals. System feasibility was demonstrated with rSbpA-ZZ/CXCR4QTY-Fc combination. Nature-like specific interactions were achieved toward CXCL12 ligand and HIV coat glycoprotein in physiologically relevant concentrations, without notable sensitivity loss in 100% human serum. The construct is regeneratable by acidic buffer, allowing device reuse and functional tuning. The modular and generalizable architecture behaves similarly to natural systems but gives electrical outputs, which enables fabrication of multiplex sensors with tailored receptor panels for designated diagnostic purposes.

Low-thermal-budget synthesis of monolayer molybdenum disulfide for silicon back-end-of-line integration on a 200 mm platform.

Two-dimensional (2D) materials are promising candidates for future electronics due to their excellent electrical and photonic properties. Although promising results on the wafer-scale synthesis (≤150 mm diameter) of monolayer molybdenum disulfide (MoS2) have already been reported, the high-quality synthesis of 2D materials on wafers of 200 mm or larger, which are typically used in commercial silicon foundries, remains difficult. The back-end-of-line (BEOL) integration of directly grown 2D materials on silicon complementary metal-oxide-semiconductor (CMOS) circuits is also unavailable due to the high thermal budget required, which far exceeds the limits of silicon BEOL integration (<400 °C). This high temperature forces the use of challenging transfer processes, which tend to introduce defects and contamination to both the 2D materials and the BEOL circuits. Here we report a low-thermal-budget synthesis method (growth temperature < 300 °C, growth time ≤ 60 min) for monolayer MoS2 films, which enables the 2D material to be synthesized at a temperature below the precursor decomposition temperature and grown directly on silicon CMOS circuits without requiring any transfer process. We designed a metal-organic chemical vapour deposition reactor to separate the low-temperature growth region from the high-temperature chalcogenide-precursor-decomposition region. We obtain monolayer MoS2 with electrical uniformity on 200 mm wafers, as well as a high material quality with an electron mobility of ~35.9 cm2 V-1 s-1. Finally, we demonstrate a silicon-CMOS-compatible BEOL fabrication process flow for MoS2 transistors; the performance of these silicon devices shows negligible degradation (current variation < 0.5%, threshold voltage shift < 20 mV). We believe that this is an important step towards monolithic 3D integration for future electronics.

Chemiresistive Hydrogen Sensing with Size-Limited Palladium Nanoparticles in Iptycene-Containing Poly(arylene ether)s.

Metal nanoparticles have been widely employed in chemical sensing due to their high reactivity toward various gases. The size of the metal nanoparticles often dictates their reactivity and hence their performance as chemiresistive sensors. Herein, we report that iptycene-containing poly(arylene ether)s (PAEs) have been shown to limit the growth of palladium nanoparticles (Pd NPs) and stabilize the Pd NPs dispersion. These porous PAEs also facilitate the efficient transport of analytes. Single-walled carbon nanotube (SWCNT)-based chemiresistors and graphene field-effect transistors (GFETs) using these PAE-supported small Pd NPs are sensitive, selective, and robust sensory materials for hydrogen gas under ambient conditions. Generalizable strategies including presorting SWCNTs with pentiptycene-containing poly(p-phenylene ethynylene)s (PPEs) and thermal annealing demonstrated significant improvements in the chemiresistive performance. The polymer:NP colloids produced in this study are readily synthesized and solution processable, and these methods are of general utility.

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.

Chip-less wireless electronic skins by remote epitaxial freestanding compound semiconductors.

Recent advances in flexible and stretchable electronics have led to a surge of electronic skin (e-skin)-based health monitoring platforms. Conventional wireless e-skins rely on rigid integrated circuit chips that compromise the overall flexibility and consume considerable power. Chip-less wireless e-skins based on inductor-capacitor resonators are limited to mechanical sensors with low sensitivities. We report a chip-less wireless e-skin based on surface acoustic wave sensors made of freestanding ultrathin single-crystalline piezoelectric gallium nitride membranes. Surface acoustic wave-based e-skin offers highly sensitive, low-power, and long-term sensing of strain, ultraviolet light, and ion concentrations in sweat. We demonstrate weeklong monitoring of pulse. These results present routes to inexpensive and versatile low-power, high-sensitivity platforms for wireless health monitoring devices.

Unraveling the Correlation between Raman and Photoluminescence in Monolayer MoS2 through Machine-Learning Models.

2D transition metal dichalcogenides (TMDCs) with intense and tunable photoluminescence (PL) have opened up new opportunities for optoelectronic and photonic applications such as light-emitting diodes, photodetectors, and single-photon emitters. Among the standard characterization tools for 2D materials, Raman spectroscopy stands out as a fast and non-destructive technique capable of probing material's crystallinity and perturbations such as doping and strain. However, a comprehensive understanding of the correlation between photoluminescence and Raman spectra in monolayer MoS2 remains elusive due to its highly nonlinear nature. Here, the connections between PL signatures and Raman modes are systematically explored, providing comprehensive insights into the physical mechanisms correlating PL and Raman features. This study's analysis further disentangles the strain and doping contributions from the Raman spectra through machine-learning models. First, a dense convolutional network (DenseNet) to predict PL maps by spatial Raman maps is deployed. Moreover, a gradient boosted trees model (XGBoost) with Shapley additive explanation (SHAP) to bridge the impact of individual Raman features in PL features is applied. Last, a support vector machine (SVM) to project PL features on Raman frequencies is adopted. This work may serve as a methodology for applying machine learning to characterizations of 2D materials.

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.

Soft-lock drawing of super-aligned carbon nanotube bundles for nanometre electrical contacts.

The assembly of single-walled carbon nanotubes (CNTs) into high-density horizontal arrays is strongly desired for practical applications, but challenges remain despite myriads of research efforts. Herein, we developed a non-destructive soft-lock drawing method to achieve ultraclean single-walled CNT arrays with a very high degree of alignment (angle standard deviation of ~0.03°). These arrays contained a large portion of nanometre-sized CNT bundles, yielding a high packing density (~400 µm-1) and high current carrying capacity (∼1.8 × 108 A cm-2). This alignment strategy can be generally extended to diverse substrates or sources of raw single-walled CNTs. Significantly, the assembled CNT bundles were used as nanometre electrical contacts of high-density monolayer molybdenum disulfide (MoS2) transistors, exhibiting high current density (~38 µA µm-1), low contact resistance (~1.6 kΩ µm), excellent device-to-device uniformity and highly reduced device areas (0.06 µm2 per device), demonstrating their potential for future electronic devices and advanced integration technologies.

Designing artificial two-dimensional landscapes via atomic-layer substitution.

Technology advancements in history have often been propelled by material innovations. In recent years, two-dimensional (2D) materials have attracted substantial interest as an ideal platform to construct atomic-level material architectures. In this work, we design a reaction pathway steered in a very different energy landscape, in contrast to typical thermal chemical vapor deposition method in high temperature, to enable room-temperature atomic-layer substitution (RT-ALS). First-principle calculations elucidate how the RT-ALS process is overall exothermic in energy and only has a small reaction barrier, facilitating the reaction to occur at room temperature. As a result, a variety of Janus monolayer transition metal dichalcogenides with vertical dipole could be universally realized. In particular, the RT-ALS strategy can be combined with lithography and flip-transfer to enable programmable in-plane multiheterostructures with different out-of-plane crystal symmetry and electric polarization. Various characterizations have confirmed the fidelity of the precise single atomic layer conversion. Our approach for designing an artificial 2D landscape at selective locations of a single layer of atoms can lead to unique electronic, photonic, and mechanical properties previously not found in nature. This opens a new paradigm for future material design, enabling structures and properties for unexplored territories.

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.

Resonance-Enhanced Excitation of Interlayer Vibrations in Atomically Thin Black Phosphorus.

The strength of interlayer coupling critically affects the physical properties of 2D materials such as black phosphorus (BP), where the electronic structure depends sensitively on layer thickness. Rigid-layer vibrations reflect directly the interlayer coupling strength in 2D van der Waals solids, but measurement of these characteristic frequencies is made difficult by sample instability and small Raman scattering cross sections in atomically thin elemental crystals. Here, we overcome these challenges in BP by performing resonance-enhanced low-frequency Raman scattering under an argon-protective environment. Interlayer breathing modes for atomically thin BP were previously unobservable under conventional (nonresonant) excitation but became strongly enhanced when the excitation energy matched the sub-band electronic transitions of few-layer BP, down to bilayer thicknesses. The measured out-of-plane interlayer force constant was found to be 10.1 × 1019 N/m3 in BP, which is comparable to graphene. Accurate characterization of the interlayer coupling strength lays the foundation for future exploration of BP twisted structures and heterostructures.

Ultralow contact resistance between semimetal and monolayer semiconductors.

Advanced beyond-silicon electronic technology requires both channel materials and also ultralow-resistance contacts to be discovered1,2. Atomically thin two-dimensional semiconductors have great potential for realizing high-performance electronic devices1,3. However, owing to metal-induced gap states (MIGS)4-7, energy barriers at the metal-semiconductor interface-which fundamentally lead to high contact resistance and poor current-delivery capability-have constrained the improvement of two-dimensional semiconductor transistors so far2,8,9. Here we report ohmic contact between semimetallic bismuth and semiconducting monolayer transition metal dichalcogenides (TMDs) where the MIGS are sufficiently suppressed and degenerate states in the TMD are spontaneously formed in contact with bismuth. Through this approach, we achieve zero Schottky barrier height, a contact resistance of 123 ohm micrometres and an on-state current density of 1,135 microamps per micrometre on monolayer MoS2; these two values are, to the best of our knowledge, the lowest and highest yet recorded, respectively. We also demonstrate that excellent ohmic contacts can be formed on various monolayer semiconductors, including MoS2, WS2 and WSe2. Our reported contact resistances are a substantial improvement for two-dimensional semiconductors, and approach the quantum limit. This technology unveils the potential of high-performance monolayer transistors that are on par with state-of-the-art three-dimensional semiconductors, enabling further device downscaling and extending Moore's law.

Flexible and high-performance electrochromic devices enabled by self-assembled 2D TiO2/MXene heterostructures.

Transition metal oxides (TMOs) are promising electrochromic (EC) materials for applications such as smart windows and displays, yet the challenge still exists to achieve good flexibility, high coloration efficiency and fast response simultaneously. MXenes (e.g. Ti3C2Tx) and their derived TMOs (e.g. 2D TiO2) are good candidates for high-performance and flexible EC devices because of their 2D nature and the possibility of assembling them into loosely networked structures. Here we demonstrate flexible, fast, and high-coloration-efficiency EC devices based on self-assembled 2D TiO2/Ti3C2Tx heterostructures, with the Ti3C2Tx layer as the transparent electrode, and the 2D TiO2 layer as the EC layer. Benefiting from the well-balanced porosity and connectivity of these assembled nanometer-thick heterostructures, they present fast and efficient ion and electron transport, as well as superior mechanical and electrochemical stability. We further demonstrate large-area flexible devices which could potentially be integrated onto curved and flexible surfaces for future ubiquitous electronics.

Impact of Al2O3 Passivation on the Photovoltaic Performance of Vertical WSe2 Schottky Junction Solar Cells.

Transition metal dichalcogenide (TMD) materials have emerged as promising candidates for thin-film solar cells due to their wide bandgap range across the visible wavelengths, high absorption coefficient, and ease of integration with both arbitrary substrates and conventional semiconductor technologies. However, reported TMD-based solar cells suffer from relatively low external quantum efficiencies (EQE) and low open circuit voltage due to unoptimized design and device fabrication. This paper studies Pt/WSe2 vertical Schottky junction solar cells with various WSe2 thicknesses in order to find the optimum absorber thickness. Also, we show that the devices' photovoltaic performance can be improved via Al2O3 passivation, which increases the EQE up to 29.5% at 410 nm wavelength incident light. The overall resulting short circuit current improves through antireflection coating, surface doping, and surface trap passivation effects. Thanks to the Al2O3 coating, this work demonstrates a device with an open circuit voltage (VOC) of 380 mV and a short circuit current density (JSC) of 10.7 mA/cm2. Finally, the impact of Schottky barrier height inhomogeneity at the Pt/WSe2 contact is investigated as a source of open circuit voltage lowering in these devices.

Deep-Learning-Enabled Fast Optical Identification and Characterization of 2D Materials.

Advanced microscopy and/or spectroscopy tools play indispensable roles in nanoscience and nanotechnology research, as they provide rich information about material processes and properties. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, the optical characterization of 2D materials is used as a case study, and a neural-network-based algorithm is demonstrated for the material and thickness identification of 2D materials with high prediction accuracy and real-time processing capability. Further analysis shows that the trained network can extract deep graphical features such as contrast, color, edges, shapes, flake sizes, and their distributions, based on which an ensemble approach is developed to predict the most relevant physical properties of 2D materials. Finally, a transfer learning technique is applied to adapt the pretrained network to other optical identification applications. This artificial-intelligence-based material characterization approach is a powerful tool that would speed up the preparation, initial characterization of 2D materials and other nanomaterials, and potentially accelerate new material discoveries.

Realization of 2D crystalline metal nitrides via selective atomic substitution.

Two-dimensional (2D) transition metal nitrides (TMNs) are new members in the 2D materials family with a wide range of applications. Particularly, highly crystalline and large area thin films of TMNs are desirable for applications in electronic and optoelectronic devices; however, the synthesis of these TMNs has not yet been achieved. Here, we report the synthesis of few-nanometer thin Mo5N6 crystals with large area and high quality via in situ chemical conversion of layered MoS2 crystals. The versatility of this general approach is demonstrated by expanding the method to synthesize W5N6 and TiN. Our strategy offers a new direction for preparing 2D TMNs with desirable characteristics, opening a door for studying fundamental physics and facilitating the development of next-generation electronics.