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We here present a planarized solid-state chemical reaction that can produce transition metal monochalcogenide (TMMC) 2D crystals with large lateral extent and finely controllable thickness down to individual layers. The enhanced lateral diffusion of a gaseous reactant at the interface between a solid precursor and graphene was found to provide a universal route towards layered TMMCs of different compositions. A unique layer-by-layer growth mechanism yields atomically abrupt crystal interfaces and kinetically controllable thickness down to a single TMMC layer. Our approach stabilizes 2D crystals with commonly unattainable thermodynamic phases, such as β-Cu2S and γ-CuSe, and spectroscopic characterization reveals ultra-large phase transition depression and interesting electronic properties. The presented ability to produce large-scale 2D crystals with high environmental stability was applied to highly sensitive and fast optoelectronic sensors. Our approach extends the morphological, compositional, and thermodynamic complexity of 2D materials.

The carrier conduction in 2D materials is more sensitive to surface-bound disorder than bulk materials and is thought to limit their achievable performance in electronic devices. To date, charged impurity scattering is considered the main source of interaction between ionic adsorbates and carriers in 2D materials. We here observe a previously unknown source of carrier scattering in graphene upon interaction with ionic impurities. Different from charged impurity scattering, these “neutral scatterers” do not depend on carrier concentration and yield a sixfold mobility variation at similar doping. Comparison of different ionic residue from various metal etchants reveals a universal mechanism that controls the carrier mean free path. Raman spectroscopy suggests that inhomogeneous charge distribution is the source of neutral scatterers and we extract an optical fingerprint for their presence. The charge heterogeneity thus acts as an additional degree of freedom in graphene’s carrier transport and its consideration can explain the transition from ambipolar to unipolar charge transport in graphene. Our results not only provide new insight into the carrier transport of 2D materials in the presence of disorder and provide guidelines for enhancing the performance of graphene devices but also enable novel device concepts in graphene.

Despite significant progress in the fabrication and application of semiconductor materials for optical emitters and sensors, few materials can cover the cyan-gap between 450 and 500 nm. We here introduce a robust and facile method to deposit amorphous Sb2S3 films with a bandgap of 2.8 eV. By exploiting the tunable functionality of graphene, a two-dimensional material, efficient deposition from a chemical was achieved. Ozone-generated defects in the graphene were shown to be required to enhance the morphology and quality of the material and comprehensive characterization of the seed layer and the Sb2S3 film were applied to design an optimal deposition process. The resulting material exhibits efficient carrier transport and high photodetector performance as evidenced by unprecedented responsivity and detectivity in semiconductor/graphene/glass vertical heterostructures. (112 A/W, 2.01 × 1012 Jones, respectively).

The assembly of graphene and other two-dimensional (2D) materials into artificial crystals termed van-der-Waals stacks has great potential to produce new materials without precedence in nature and develop novel electronic devices. To reliably assemble 2D materials into such structures, however, a better understanding of the transfer process is required. Here we report a quantitative approach to examining the adhesion behavior during viscoelastic stamping of 2D materials. By measuring the adhesion of graphene to different carrier substrates and varying the peeling speed we have identified the range of adhesion of samples. The result shows that the adhesion occurs between graphene-graphene and graphene-SiO2 substrate have a higher value than the ability of polydimethylsiloxane (PDMS) stamp to pick up. The impact of surface modification and alternative substrates is investigated and our results provide guidelines to realize an effective fabrication method for two-dimensional heterostructure devices.

Two-dimensional (2D) material nanocomposites have emerged as a material system for discovering new physical phenomena and developing novel devices. However, because of the low density of states of most two-dimensional materials such as graphene, the heterostructure of nanocomposites suffers from an enhanced depletion region, which can greatly reduce the efficiency of the charge carrier transfer and deteriorate the device performance. To circumvent this difficulty, here we propose an alternative approach by inserting a second 2D mediator with a heavy effective mass having a large density of states in-between the heterojunction of 2D nanocomposites. The mediator can effectively reduce the depletion region and form a type-II band alignment, which can speed up the dissociation of electron-hole pairs and enhance charge carrier transfer. To illustrate the principle, we demonstrate a novel stretchable photodetector based on the combination of graphene/ReS

Barrier-guided CVD growth could provide a new route to printed electronics by combining high quality 2D materials synthesis with scalable and cost-effective deposition methods. Unfortunately, we observe the limited stability of the barrier at growth conditions which results in its removal within minutes due to hydrogen etching. This work describes a route towards enhancing the stability of an ink-jet deposited barrier for high resolution patterning of high quality graphene. By modifying the etching kinetics under confinement, the barrier film could be stabilized and high resolution barriers could be retained even after 6 hours of graphene growth. Thus produced microscopic graphene devices exhibited an increase in conductivity by 6 orders of magnitude and a decrease in defectiveness by 48 times yielding performances that are superior to devices produced by traditional lithographical patterning which indicates the potential of our approach for future electronic applications.

Upon laser irradiation, the sensitivity gets enhanced up to 22 times by the insertion of two-dimensional materials having a large density of state due to the speeding up of carrier dissociation at the heterojunction interface.

Graphene has shown great potential as electrochemical electrodes in energy storage and sensor applications due to its unique combination of semiconducting and metallic properties. We here demonstrate that graphene’s semimetallic nature imparts it with a continuously tunable electrochemical reactivity. Extrinsic doping was shown to modify the reaction rate of graphene microelectrode arrays and a direct correlation between graphene’s linearly varying density of states and its electron transfer rate was established. Dynamic control of the charge transfer process enabled the variation of graphene’s reaction rate over 1 order of magnitude and was confirmed by a simple Gerischer–Marcus charge transfer kinetics model. The observed fine control over graphene’s electrochemical properties enabled a 2-fold increase in the resolution of an electrochemical impedance sensor. These results not only explain previous observations of graphene’s spatially varying electrochemical reactivity and highlight the importance of do...

Corrosion protection of complex surface is an active area of research due to its importance to commercial applications such as electrochemical fabrication. However, conventional coatings exhibit limited conductivity, thermal stability, and durability and are thus not suitable. Recent work has shown the potential of graphene, a two-dimensional carbon allotrope, for corrosion protection. The studies, however, limited themselves to simple planar geometries that provide limited insight in the applicability to relevant morphologies such as mesh electrodes and roughened surfaces. We here study the corrosion protection ability of tubular graphene (TG) on Ni-wires as a model system for such complex geometries. TG-covered Ni wires of approximately 50 μm diameters were produced by the annealing of cellulose acetate (CA) on Ni. The high quality of the TG coating was confirmed by Raman spectroscopy, scanning electron microscopy, and electrical measurements. We show that the graphene layer number could be controlled by adjusting the CA membrane quantity. We found a direct relation between the degree of corrosion inhibition with the variation of graphene layer number. The increase of graphene layers on a Ni surface could enhance its corrosion inhibition in acidic, basic, and marine environments, which shows the potential of our approach for future applications.

The quality of CVD-grown graphene is intimately linked to the morphology of the employed catalyst. One commonly employed route to enhanced catalyst quality is recrystallization prior to graphene growth. The dimensions of a catalyst's single-crystalline domains, however, are limited by the stability of dislocations at the grain boundaries. We here employ a solid material in contact with the catalyst as a sink for dislocations. It was found that the interaction between Cu-foil and a solid cap significantly alters the recrystallization kinetics and achievable grain size. This development originates from an improved strain-relaxation of up to 1% during recrystallization which can support the formation of commonly unstable surface orientations. Correlation of diffraction measurements and atomic force microscopy reveals a direct impact of the strain relaxation on the decrease in copper surface roughness. Finally, we demonstrate the improvement of the quality of graphene grown on thus prepared foils through spectroscopic and carrier transport measurements.

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., Ferroelectric ordering of water has been at the heart of intense debates due to its importance in enhancing our understanding of the condensed matter. Here, the authors observe ferroelectric properties of water ice in a two dimensional phase under confinement between two graphene layers.

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

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 low-cost sensors for future internet of things applications.

Nanoscrolls are a class of nanostructures where atomic layers of 2D materials are stacked consecutively in a coaxial manner to form a 1D spiral topography. Self-assembly of chemical vapor deposition grown 2D WS2 monolayer into quasi-1D van der Waals scroll structure instigates a plethora of unique physiochemical properties significantly different from its 2D counterparts. The physical properties of such nanoscrolls can be greatly manipulated upon hybridizing them with high-quantum-yield colloidal quantum dots, forming 0D/2D structures. The efficient dissociation of excitons at the heterojunctions of QD/2D hybridized nanoscrolls exhibits a 3000-fold increased photosensitivity compared to the pristine 2D-material-based nanoscroll. The synergistic effects of confined geometry and efficient QD scatterers produce a nanocavity with multiple feedback loops, resulting in coherent lasing action with an unprecedentedly low lasing threshold. Predominant localization of the excitons along the circumference of this helical scroll results in a 12-fold brighter emission for the parallel-polarized transition compared to the perpendicular one, as confirmed by finite-difference time-domain simulation. The versatility of hybridized nanoscrolls and their unique properties opens up a powerful route for not-yet-realized devices toward practical applications.

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.

Two-dimensional materials have shown great promise to enable novel wearable electronic devices ranging from sensors to energy generators. These developments are due to their high mechanical robustness, which allow them to retain high performance even at large deformations. Under these conditions, however, good electrical contacts become an important issue that cannot be addressed with conventional materials. Liquid metals could overcome this limitation by providing soft and compliant electrodes but to date no realistic heterointegration of nanomaterials and complex liquid metal contacts has been attempted. We here demonstrate the application of micrometer-sized electrical contacts to flexible, fragile and rough 2D materials using patterned liquid metal contacts. A novel deposition method enables the scalable and facile production of large arrays of contacts in arbitrary geometries. This ability permitted the single-step, fabrication-free and contamination-free production of concentric liquid metal-contacted graphene field effect transistors of comparable performance to traditional devices. We demonstrate that the contacts can be removed without damaging the 2D materials allowing the contacts to be reused. Finally, good contact could be made to complex morphologies and three-dimensional substrates, which highlights the potential of our approach to the characterization and application of nanomaterials in electronics.

We study convex optimization problems that feature low-rank matrix solutions. In such scenarios, non-convex methods offer significant advantages over convex methods due to their lower space complexity, as well as practical faster convergence. Under mild assumptions, these methods feature global convergence guarantees. In this paper, we extend the results on this matter by following a different path. We derive a non-Euclidean optimization framework in the non-convex setting that takes nonlinear gradient steps on the factors. Our framework enables the possibility to further exploit the underlying problem structures, such as sparsity or low-rankness on the factorized domain, or better dimensional dependence of the smoothness parameters of the objectives. We prove that the non-Euclidean methods enjoy the same rigorous guarantees as their Euclidean counterparts under appropriate assumptions. Numerical evidence with Fourier ptychography and FastText applications, using real data, shows that our approach can enhance solution quality, as well as convergence speed over the standard non-convex approaches.

Chemical vapor deposition (CVD) is promising for the large scale production of graphene and other two-dimensional materials. Optimization of the CVD process for enhancing their quality is a focus of ongoing effort and significant progress has been made in decreasing the defectiveness associated with grain boundaries and nucleation spots. However, little is known about the quality and origin of structural defects in the outgrowing lattice which are present even in single-crystalline material and represent the limit of current optimization efforts. We here investigate the formation kinetics of such defects by controlling graphene’s growth rate over a wide range using nanoscale confinements. Statistical analysis of Raman spectroscopic results shows a clear trend between growth rate and defectiveness that is in quantitative agreement with a model where defects are healed preferentially at the growth front. Our results suggest that low growth rates are required to avoid the freezing of lattice defects and form high quality material. This conclusion is confirmed by a fourfold enhancement in graphene’s carrier mobility upon optimization of the growth rate.

Graphene’s attractiveness in many applications is limited by its high resistance. Extrinsic doping has shown promise to overcome this challenge but graphene’s performance remains below industry requirements. This issue is caused by a limited charge transfer efficiency (CTE) between dopant and graphene. Using AuCl3 as a model system, we measure CTE as low as 5% of the expected values due to the geometrical capacitance of small adsorbate clusters. We here demonstrate a strategy for enhancing the CTE by a two-step optimization of graphene’s surface energy prior to AuCl3 doping. First, exposure to UV ozone modified the hydrophilicity of graphene and was found to decrease the cluster’s geometric capacitance, which had a direct effect on the CTE. Occurrence of lattice defects at high UV exposure, however, deteriorated graphene’s transport characteristics and limited the effectiveness of this pretreatment step. Thus, prior to UV exposure, a functionalized polymer layer was introduced that could further enhance graphene’s surface energy while protecting it from damage. Combination of these treatment steps were found to increase the AuCl3 charge transfer efficiency to 70% and lower the sheet resistance to 106 Ω/γ at 97% transmittance which represents the highest reported performance for doped single layer graphene and is on par with commercially available transparent conductors.

The growth of two-dimensional materials into three-dimensional geometries holds the promise for high performance hybrid materials and novel architectures. The synthesis of such structures, however, proceeds in fundamentally different flow regimes compared to conventional CVD where pressure differences and wall collisions are neglected. We here demonstrate the remarkable stability of graphene growth under varying fluid dynamic flow regimes. We investigate the growth process across different flow conditions using confined growth in refractory pores. Analysis of the growth rate reveals a transport-limited process which allows experimental determination of the gas diffusion coefficient. The diffusion coefficient was found to be constant for large pore dimension but scales with pore dimension as the pore size decreases below the mean free path providing clear evidence for previously predicted Knudsen molecular-flow conditions for atomic confinement. Surprisingly, changes to the flow conditions by two orders of magnitude do not cause qualitative changes of the graphene growth process. This unique behavior was attributed to rarefied flow conditions by scaling analysis and an analytical relation between growth rate and constriction could be extracted that proves accurate throughout the investigated conditions. Our results demonstrate a fundamentally different growth process compared to traditional CVD processes that is akin to atomic layer deposition and highlight the feasibility of high-quality 2D-material growth on 3D morphologies with ultra-high aspect ratios.

Carbon produces a wealth of different materials ranging from organic molecules to diamond crystals. One common challenge for the synthesis, application, and understanding of these materials is their characterization.

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional ($n \ll p$) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be estimated is not exactly sparse (e.g., when it is weakly sparse), and shows explicitly the effect of over-estimating the $\ell_1$-norm of the parameter to be estimated on the estimation performance. The results of this paper show that the constrained lasso is minimax optimal for estimating a parameter with bounded $\ell_1$-norm, and also for estimating a weakly sparse parameter if its $\ell_1$-norm is accessible.

We study a phase retrieval problem in the Poisson noise model. Motivated by the PhaseLift approach, we approximate the maximum-likelihood estimator by solving a convex program with a nuclear norm constraint. While the Frank-Wolfe algorithm, together with the Lanczos method, can efficiently deal with nuclear norm constraints, our objective function does not have a Lipschitz continuous gradient, and hence existing convergence guarantees for the Frank-Wolfe algorithm do not apply. In this paper, we show that the Frank-Wolfe algorithm works for the Poisson phase retrieval problem, and has a global convergence rate of O(1/t), where t is the iteration counter. We provide rigorous theoretical guarantee and illustrating numerical results.

A high carrier mobility is an important parameter for graphene-based electronics. While the recent reports have shown impressive results for individual micro-scale devices, scalable production of high mobility graphene has been challenging. We here show that centimeter-scale graphene devices with room temperature carrier mobilities in excess of 10 000 cm(2) V(-1) s(-1) can be achieved on polyolefinic substrates. Measurements on Parafilm-supported graphene devices show, on average, a fivefold-enhancement in mobility over traditional devices. We find that a decreased charged-impurity scattering is the origin of this behavior. Spectroscopic characterization reveals oxygen-containing polymer residue as the main source of such charged impurities. A comparison of different polyolefins highlights the positive impact of oxygen-free polymers as support materials for high mobility graphene devices. Finally, moldable and wearable graphene devices for biosensors were shown to be enabled by polyolefinic substrates.

Graphene's unique semimetallic band structure yields carriers with widely tunable energy levels that enable novel electronic devices and energy generators. To enhance the potential of this feature, a scalable synthesis method for graphene with adjustable Fermi levels is required. We here show that the electrochemical intercalation of FeCl3 and subsequent electrochemical exfoliation produces graphene whose energy levels can be finely tuned by the intercalation parameters. X-ray photoelectron spectroscopy reveals that a gradual transition in the bonding character of the intercalant is the source of this behavior. The intercalated graphene exhibits a significantly increased work function that can be varied between 4.8 eV and 5.2 eV by the intercalation potential. Transparent conducting electrodes produced by these graphene flakes exhibit a threefold improvement in performance and the doping effect was found to be stable for more than a year. These findings open up a new route for the scalable production of graphene with adjustable properties for future applications.

We demonstrate a series of InGaN/GaN double quantum well nanostructure elements. We grow a layer of 2 {\mu}m undoped GaN template on top of a (0001)-direction sapphire substrate. A 100 nm SiO2 thin film is deposited on top as a masking pattern layer. This layer is then covered with a 300 nm aluminum layer as the anodic aluminum oxide (AAO) hole pattern layer. After oxalic acid etching, we transfer the hole pattern from the AAO layer to the SiO2 layer by reactive ion etching. Lastly, we utilize metal-organic chemical vapor deposition to grow GaN nanorods approximately 1.5 {\mu}m in size. We then grow two layers of InGaN/GaN double quantum wells on the semi-polar face of the GaN nanorod substrate under different temperatures. We then study the characteristics of the InGaN/GaN quantum wells formed on the semi-polar faces of GaN nanorods. We report the following findings from our study: first, using SiO2 with repeating hole pattern, we are able to grow high-quality GaN nanorods with diameters of approximately 80-120 nm; second, photoluminescence (PL) measurements enable us to identify Fabry-Perot effect from InGaN/GaN quantum wells on the semi-polar face. We calculate the quantum wells' cavity thickness with obtained PL measurements. Lastly, high resolution TEM images allow us to study the lattice structure characteristics of InGaN/GaN quantum wells on GaN nanorod and identify the existence of threading dislocations in the lattice structure that affects the GaN nanorod's growth mechanism., Comment: 8 pages, 6 figures

A self-powered photodetector with ultrahigh sensitivity, fast photoresponse, and wide spectral detectivity covering from 1000 nm to 400 nm based on graphene/ZnO/Si triple junctions has been designed, fabricated, and demonstrated. In this device, graphene serves as a transparent electrode as well as an efficient collection layer for photogenerated carriers due to its excellent tunability of Fermi energy. The ZnO layer acts as an antireflection layer to trap the incident light and enhance the light absorption. Furthermore, the insertion of the ZnO layer in between graphene and Si layers can create build-in electric field at both graphene/ZnO and ZnO/Si interfaces, which can greatly enhance the charge separation of photogenerated electron and hole pairs. As a result, the sensitivity and response time can be significantly improved. It is believed that our methodology for achieving a high-performance self-powered photodetector based on an appropriate design of band alignment and optical parameters can be implemented to many other material systems, which can be used to generate unique optoelectronic devices for practical applications.

The production of large-scale, single crystalline graphene is a requirement for enhancing its electronic, mechanical, and chemical properties. Chemical vapor deposition (CVD) has shown the potential to grow high quality graphene but the simultaneous nucleation of many grains limits their achievable domain size. We report here that ultralow nucleation densities can be achieved through multi-step optimization of the catalyst morphology. First, annealing in a hydrogen-free environment is required to retain a surface copper oxide which decreases the nucleation density. Second, CuO was found to be the relevant copper species for this process and air oxidation of the copper foil at 200 °C maximizes its concentration. Both pre-treatment steps were found to affect the morphology of the catalyst and a direct correlation between nucleation density and surface roughness was found which indicates that the primary role of the oxidation step is the decrease in catalyst roughness. To further enhance this determining parameter, confined CVD was carried out after sample oxidation and hydrogen-free annealing. Each of these three steps reduces the grain density by approximately one order of magnitude resulting in ultralow nucleation densities of 1.23 grains/mm(2) and high quality, single-crystalline graphene grains of several millimeter sizes were grown using this method.

Interest in deep probabilistic graphical models has increased in recent years, due to their state-of-the-art performance on many machine learning applications. Such models are typically trained with the stochastic gradient method, which can take a significant number of iterations to converge. Since the computational cost of gradient estimation is prohibitive even for modestly sized models, training becomes slow and practically usable models are kept small. In this paper we propose a new, largely tuning-free algorithm to address this problem. Our approach derives novel majorization bounds based on the Schatten- $\infty$ norm. Intriguingly, the minimizers of these bounds can be interpreted as gradient methods in a non-Euclidean space. We thus propose using a stochastic gradient method in non-Euclidean space. We both provide simple conditions under which our algorithm is guaranteed to converge, and demonstrate empirically that our algorithm leads to dramatically faster training and improved predictive ability compared to stochastic gradient descent for both directed and undirected graphical models.