We here demonstrate the multifunctional properties of atomically thin heterojunctions that are enabled by their strong interfacial interactions and their application toward self-powered sensors with unprecedented performance. Bonding between tin diselenide and graphene produces thermoelectric and mechanoelectric properties beyond the ability of either component. A record-breaking ZT of 2.43 originated from the synergistic combination of graphene’s high carrier conductivity and SnSe2-mediated thermal conductivity lowering. Moreover, spatially varying interaction at the SnSe2/graphene interface produces stress localization that results in a novel 2D-crack-assisted strain sensing mechanism whose sensitivity (GF = 450) is superior to all other 2D materials. Finally, a graphene-assisted growth process permits the formation of high-quality heterojunctions directly on polymeric substrates for flexible and transparent sensors that achieve self-powered strain sensing from a small temperature gradient. Our work enhances the fundamental understanding of multifunctionality at the atomic scale and provides a route toward structural health monitoring through ubiquitous and smart devices.

Lateral heterojunctions in two-dimensional (2D) materials have demonstrated potential for high-performance sensors because of the unique electrostatic conditions at the interface. The increased complexity of producing such structures, however, has prevented their widespread use. We here demonstrate the simple and scalable fabrication of heterojunctions by a one-step synthesis process that yields photodetectors with superior device performance. Catalytic conversion of a solid precursor at optimized conditions was found to produce lateral nanostructured junctions between graphene domains and 3 nm thin amorphous carbon films. Carrier transport in these heterojunctions was found to proceed by minimizing the path through the amorphous carbon barriers, which results in a self-selective Schottky emission process with high uniformity and low emission barriers. We demonstrate the potential of thus produced heterojunctions by realizing a photodetector that combines an ultrahigh detectivity of 10 13 Jones with microsecond response time, which represents the highest performance of 2D material heterojunction devices. These attractive features are retained even for millimeter-scale devices, and the demonstrated ability to produce transparent, patterned, and flexible sensors extends lateral heterojunction sensors toward wearable and large-scale electronics.

We here report on the direct observation of ferroelectric properties of water ice in its 2D phase. Upon nanoelectromechanical confinement between two graphene layers, water forms a 2D ice phase at room temperature that exhibits a strong and permanent dipole which depends on the previously applied field, representing clear evidence for ferroelectric ordering. Characterization of this permanent polarization with respect to varying water partial pressure and temperature reveals the importance of forming a monolayer of 2D ice for ferroelectric ordering which agrees with ab-initio and molecular dynamics simulations conducted. The observed robust ferroelectric properties of 2D ice enable novel nanoelectromechanical devices that exhibit memristive properties. A unique bipolar mechanical switching behavior is observed where previous charging history controls the transition voltage between low-resistance and high-resistance state. This advance enables the realization of rugged, non-volatile, mechanical memory exhibiting switching ratios of 106, 4 bit storage capabilities and no degradation after 10,000 switching cycles.

Light-based information processing has the potential to increase speed, security, and scalability of electronic devices if issues in the device complexity could be resolved. We here demonstrate an integrated nanoelectronic device that can combine, store, and manipulate optical and electronic information. Employing a mechanically flexible and multilayered structure, a device is realized that shows memristive behavior. Illumination is shown to control the device operation in several unique ways. First, the device produces photocurrent that allows us to read out the device state in a self-powered manner. More importantly, a varying light intensity modulates the switching transition in a proportional manner that is akin to a neuron with variable plasticity and which can be taught and queried using either light or electrical inputs. This behavior enables a multilevel light-controlled logic and teaching schemes that can be applied to light-based communication devices and provides a route toward ubiquitous and lowcost sensors for future internet of things applications.