Zengguang Cheng

Toward Intrinsic Graphene Surfaces: A Systematic Study on Thermal Annealing and Wet-Chemical Treatment of SiO2-Supported Graphene Devices

By combining atomic force microscopy and trans-port measurements, we systematically investigated effects of thermal annealing on surface morphologies and electrical properties of single-layer graphene devices fabricated by electron beam lithography on silicon oxide (SiO(2)) substrates. Thermal treatment above 300 °C in vacuum was required to effectively remove resist residues on graphene surfaces. However, annealing at high temperature was found to concomitantly bring graphene in close contact with SiO(2) substrates and induce increased coupling between them, which leads to heavy hole doping and severe degradation of mobilities in graphene devices. To address this problem, a wet-chemical approach employing chloroform was developed in our study, which was shown to enable both intrinsic surfaces and enhanced electrical properties of graphene devices. Upon the recovery of intrinsic surfaces of graphene, the adsorption and assisted fibrillation of amyloid β-peptide (Aβ1-42) on graphene were electrically measured in real time.

Suspended Graphene Sensors with Improved Signal and Reduced Noise

We report enhanced performance of suspended graphene field effect transistors (Gra-FETs) as sensors in aqueous solutions. Etching of the silicon oxide (SiO(2)) substrate underneath graphene was carried out in situ during electrical measurements of devices, which enabled systematic comparison of transport properties for same devices before and after suspension. Significantly, the transconductance of Gra-FETs in the linear operating modes increases 1.5 and 2 times when the power of low-frequency noise concomitantly decreases 12 and 6 times for hole and electron carriers, respectively, after suspension of graphene in solution from the SiO(2) substrate. Suspended graphene devices were further demonstrated as direct and real-time pH sensors, and complementary pH sensing with the same nanodevice working as either a p-type or n-type transistor was experimentally realized by offsetting the electrolyte gate potential in solution. Our results highlight the importance to quantify fundamental parameters that define resolution of graphene-based bioelectronics and demonstrate that suspended nanodevices represent attractive platforms for chemical and biological sensors.

Syringe-injectable electronics

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.

Self-Assembled 1-Octadecanethiol Monolayers on Graphene for Mercury Detection

We report studies on surface modification of graphene with 1-octadecanethiol and its application as heavy metal sensors. The alkanethiol molecules can self-assemble into large-scale highly ordered monolayers on single-layer graphene regardless of the roughness of graphene surfaces inherited from the underlying amorphorous silicon oxide (SiO2) dielectric substrates. Atomically resolved scanning tunneling microscopy imaging of modified graphene sheets on SiO2 was conducted to reveal configuration details of the self-assembled structure. Functionalization of graphene field effect transistors (Gra-FETs) with 1-octadecanethiol was realized and successfully explored for mercury(II) (Hg2+) detection at 10 ppm.

Spontaneous Formation of Nanostructures in Graphene

We report in-depth studies of nanostructures formed in graphene on soft substrates. Periodic buckles with amplitude of nanometer scale spontaneously appear at edges of single-layer membranes after cooling of samples from above the substrates glass-transition temperature. Stress modulation at step-edges between single- and few-layer further induces penetrating nanobuckles into the few-layer. The evolvement of single-layer folding into double and triple-layer stacks at elevated temperature was also probed in detail, and we show that the developed interfaces are clear of polymer contamination. Our results underscore the possibility to construct diverse nanostructures and to design novel devices based on graphene.

Sub-10-nm intracellular bioelectronic probes from nanowire–nanotube heterostructures

Significance The miniaturization of bioelectronic probes to enable interrogation of small subcellular structures could impact significantly biology and medicine. This paper describes the design, fabrication, and demonstration of the sub-10-nm bioelectronic devices by exploiting a unique three-dimension nanowire–nanotube structure, where a nanowire detector is synthetically integrated with a nanotube probe. Devices with nanotube probe dimensions as small as 5 nm, which approach the size of a single ion channel, have been realized. Experimental measurements and numerical simulations show that these devices have sufficient time resolution to record the fastest electrical signals in neurons and other cells. Measurement of the cell transmembrane resting potential with these ultrasmall bioelectronic devices further demonstrates their capability for intracellular electrophysiology studies. The miniaturization of bioelectronic intracellular probes with a wide dynamic frequency range can open up opportunities to study biological structures inaccessible by existing methods in a minimally invasive manner. Here, we report the design, fabrication, and demonstration of intracellular bioelectronic devices with probe sizes less than 10 nm. The devices are based on a nanowire–nanotube heterostructure in which a nanowire field-effect transistor detector is synthetically integrated with a nanotube cellular probe. Sub-10-nm nanotube probes were realized by a two-step selective etching approach that reduces the diameter of the nanotube free-end while maintaining a larger diameter at the nanowire detector necessary for mechanical strength and electrical sensitivity. Quasi-static water-gate measurements demonstrated selective device response to solution inside the nanotube, and pulsed measurements together with numerical simulations confirmed the capability to record fast electrophysiological signals. Systematic studies of the probe bandwidth in different ionic concentration solutions revealed the underlying mechanism governing the time response. In addition, the bandwidth effect of phospholipid coatings, which are important for intracellular recording, was investigated and modeled. The robustness of these sub-10-nm bioelectronics probes for intracellular interrogation was verified by optical imaging and recording the transmembrane resting potential of HL-1 cells. These ultrasmall bioelectronic probes enable direct detection of cellular electrical activity with highest spatial resolution achieved to date, and with further integration into larger chip arrays could provide a unique platform for ultra-high-resolution mapping of activity in neural networks and other systems.

Graphene, a material for high temperature devices - intrinsic carrier density, carrier drift velocity, and lattice energy

Heat has always been a killing matter for traditional semiconductor machines. The underlining physical reason is that the intrinsic carrier density of a device made from a traditional semiconductor material increases very fast with a rising temperature. Once reaching a temperature, the density surpasses the chemical doping or gating effect, any p-n junction or transistor made from the semiconductor will fail to function. Here, we measure the intrinsic Fermi level (|EF| = 2.93 kBT) or intrinsic carrier density (nin = 3.87 × 106 cm−2K−2·T2), carrier drift velocity, and G mode phonon energy of graphene devices and their temperature dependencies up to 2400 K. Our results show intrinsic carrier density of graphene is an order of magnitude less sensitive to temperature than those of Si or Ge, and reveal the great potentials of graphene as a material for high temperature devices. We also observe a linear decline of saturation drift velocity with increasing temperature, and identify the temperature coefficients of the intrinsic G mode phonon energy. Above knowledge is vital in understanding the physical phenomena of graphene under high power or high temperature.

Sensitivity limits and scaling of bioelectronic graphene transducers.

Semiconducting nanomaterials are being intensively studied as active elements in bioelectronic devices, with the aim of improving spatial resolution. Yet, the consequences of size-reduction on fundamental noise limits, or minimum resolvable signals, and their impact on device design considerations have not been defined. Here, we address these key issues by quantifying the size-dependent performance and limiting factors of graphene (Gra) transducers under physiological conditions. We show that suspended Gra devices represent the optimal configuration for cardiac extracellular electrophysiology in terms of both transducer sensitivity, systematically ~5× higher than substrate-supported devices, and forming tight bioelectronic interfaces. Significantly, noise measurements on free-standing Gra together with theoretical calculations yield a direct relationship between low-frequency 1/f noise and water dipole-induced disorders, which sets fundamental sensitivity limits for Gra devices in physiological media. As a consequence, a square-root-of-area scaling of Gra transducer sensitivity was experimentally revealed to provide a critical design rule for their implementation in bioelectronics.

On-chip photonic synapse

An on-chip photonic device mimics the function of synaptic connections between neurons. The search for new “neuromorphic computing” architectures that mimic the brain’s approach to simultaneous processing and storage of information is intense. Because, in real brains, neuronal synapses outnumber neurons by many orders of magnitude, the realization of hardware devices mimicking the functionality of a synapse is a first and essential step in such a search. We report the development of such a hardware synapse, implemented entirely in the optical domain via a photonic integrated-circuit approach. Using purely optical means brings the benefits of ultrafast operation speed, virtually unlimited bandwidth, and no electrical interconnect power losses. Our synapse uses phase-change materials combined with integrated silicon nitride waveguides. Crucially, we can randomly set the synaptic weight simply by varying the number of optical pulses sent down the waveguide, delivering an incredibly simple yet powerful approach that heralds systems with a continuously variable synaptic plasticity resembling the true analog nature of biological synapses.

On-chip phase-change photonic memory and computing

The use of photonics in computing is a hot topic of interest, driven by the need for ever-increasing speed along with reduced power consumption. In existing computing architectures, photonic data storage would dramatically improve the performance by reducing latencies associated with electrical memories. At the same time, the rise of ‘big data’ and ‘deep learning’ is driving the quest for non-von Neumann and brain-inspired computing paradigms. To succeed in both aspects, we have demonstrated non-volatile multi-level photonic memory avoiding the von Neumann bottleneck in the existing computing paradigm and a photonic synapse resembling the biological synapses for brain-inspired computing using phase-change materials (Ge2Sb2Te5).