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Electrically tunable optical properties in materials are desirable for many applications ranging from displays to lasing and optical communication. In most two-dimensional thin films and other quan...

In 1963, Moll and Tarui suggested that the field-effect conductance of a semiconductor could be controlled by the remanent polarization of a ferroelectric (FE) material to create a ferroelectric field-effect transistor (FE-FET). However, subsequent efforts to produce a practical, compact FE-FET have been plagued by low retention and incompatibility with Complementary Metal Oxide Semiconductor (CMOS) process integration. These difficulties led to the development of trapped-charge based memory devices (also called floating gate or flash memory), and these are now the mainstream non-volatile memory (NVM) technology. Over the past two decades, advances in oxide FE materials have rejuvenated the field of ferroelectrics and made FE random access memories (FE-RAM) a commercial reality. Despite these advances, commercial FE-RAM based on lead zirconium titanate (PZT) has stalled at the 130 nm due to process challenges.The recent discovery of scandium doped aluminum nitride (AlScN) as a CMOS compatible ferroelectric presents new opportunities for direct memory integration with logic transistors due to the low temperature of AlScN deposition (approx. 350 C). This temperature is compatible with CMOS back end of line processes. Here, we present a FE-FET device composed of an AlScN FE dielectric layer integrated with a channel layer of a van der Waals two-dimensional (2D) semiconductor, MoS2. Our devices show an ON/OFF ratio ~ 10^6, concurrent with a normalized memory window of 0.3 V/nm. The devices also demonstrate stable, two-state memory retention for up to 10^4 seconds. Our simulations and experimental results suggest that the combination of AlScN and 2D semiconductors is nearly ideal for low power FE-FET memory. These results demonstrate a new approach in embedded memory and in-memory computing, and could even lead to effective neuromorphic computing architectures.

Van der Waals (vdW) semiconductors are attractive for highly scaled devices and heterogeneous integration since they can be isolated into self-passivated, two-dimensional (2D) layers that enable superior electrostatic control. These attributes have led to numerous demonstrations of field-effect devices ranging from transistors to triodes. By exploiting the controlled, substitutional doping schemes in covalently-bonded, three-dimensional (3D) semiconductors and the passivated surfaces of 2D semiconductors, one can construct devices that can exceed performance metrics of 'all-2D' vdW heterojunctions. Here, we demonstrate, 2D/3D semiconductor heterojunctions using MoS2 as the prototypical 2D semiconductor laid upon Si and GaN as the 3D semiconductor layers. By tuning the Fermi levels in MoS2, we demonstrate devices that concurrently exhibit over seven orders of magnitude modulation in rectification ratios and conductance. Our results further suggest that the interface quality does not necessarily affect Fermi-level tuning at the junction opening up possibilities for novel 2D/3D heterojunction device architectures., Manuscript plus supporting information, 4 Figures

Purpose This study aims to reveal the landscape and trends of graphene research in the world by using data from Chemical Abstracts Service (CAS). Design/methodology/approach Index data from CAS have been retrieved on 78,756 papers and 23,057 patents on graphene from 1985 to March 2016, and scientometric methods were used to analyze the growth and distribution of R&D output, topic distribution and evolution, and distribution and evolution of substance properties and roles. Findings In recent years R&D in graphene keeps in rapid growth, while China, South Korea and United States are the largest producers in research but China is relatively weak in patent applications in other countries. Research topics in graphene are continuously expanding from mechanical, material, and electrical properties to a diverse range of application areas such as batteries, capacitors, semiconductors, and sensors devices. The roles of emerging substances are increasing in Preparation and Biological Study. More techniques have been included to improve the preparation processes and applications of graphene in various fields. Research limitations Only data from CAS is used and some R&D activities solely reported through other channels may be missed. Also more detailed analysis need to be done to reveal the impact of research on development or vice verse, development dynamics among the players, and impact of emerging terms or substance roles on research and technology development. Practical implications This will provide a valuable reference for scientists and developers, R&D managers, R&D policy makers, industrial and business investers to understand the landscape and trends of graphene research. Its methodologies can be applied to other fields or with data from other similar sources. Originality/value The integrative use of indexing data on papers and patents of CAS and the systematic exploration of the distribution trends in output, topics, substance roles are distinctive and insightful.

The effect of thermal fluctuation of two-dimensional electron gases (2DEGs) on the leakage in AlGaN/GaN heterostructure-based high-electron-mobility transistors was investigated. Results indicate that the gate leakage current in AlGaN/GaN heterojunction was enhanced by the increase of the 2DEG density at low voltages. The gate leakage current was also associated with bias voltages, in which it increases with bias voltage to a saturation value because of the limit in the increase of 2DEG density. The results for the gate leakage current at room temperature are in order of 10 − 2 to 10 − 1 A/cm 2 at low voltages. It is shown that the thermal fluctuation mechanism is one of the gate leakage currents in AlGaN/GaN heterostructure.

In this Letter, we report a back-end-of-line (BEOL), complementary metal–oxide–semiconductor (CMOS)-compatible Al0.64Sc0.36N-based ferroelectric diode that shows polarization-dependent hysteresis in its leakage currents. Our device comprises a metal/insulator/ferroelectric/metal structure (Pt/native oxide/Al0.64Sc0.36N/Pt) that is compatible with BEOL temperatures (≤ 350 °C) grown on top of a 4-in. silicon wafer. The device shows self-selective behavior as a diode with > 105 rectification ratio (for 5 V). It can suppress sneak currents without the need for additional access transistors or selectors. Furthermore, given the polarization-dependent leakage, the diode current–voltage sweeps are analogous to that of a memristor with an on/off ratio of ∼ 50 000 between low and high resistance states. Our devices also exhibit stable programed resistance states during DC cycling and a retention time longer than 1000 s at 300 K. These results demonstrate that this system has significant potential as a future high-performance post-CMOS compatible nonvolatile memory technology.

Solid-phase extraction (SPE) is a popular technique for environmental sample pretreatment. However, SPE usually requires complex sample pretreatment processes, which is time-consuming and inconvenient for real-time and on-site monitoring. Herein, a solvent-free, rapid, and user-friendly SPE device was developed by coating the polydimethylsiloxane (PDMS)/divinylbenzene (DVB) sorbent on the inner wall of a sample bottle. The extraction process and desorption process were both carried out in the bottle. The analytes trapped in the sorbent were thermally desorbed and simultaneously sucked out from the bottle by an air sampling tube equipped on field-portable GC-MS. Different to previous work, the sample pretreatment process didn’t require any complicated and time-consuming steps, such as centrifugation or filtration. The total analysis time for each sample was less than 25 min, which was feasible for rapid on-site detection, and thus avoided the losses and contamination of samples in conventional sample storage and transportation processes. Under optimal conditions, the proposed SPE method exhibited wide linear ranges, low detection limits (0.010–0.036 μg L−1, which were much lower than the maximum levels restricted by the US Environmental Protection Agency and the Chinese GB3838-2002 standard), good intra-bottle repeatability (6.13–7.17%, n = 3) and satisfactory inter-bottle reproducibility (4.73–6.47%, n = 3). Finally, the method was successfully applied to the rapid detection of BTEX in the field. The recoveries of BTEX in spiked water samples ranged from 89.1% to 116.2%. This work presents a novel SPE approach for rapid on-site monitoring in water samples.

In this paper, the impact of gate voltage on the electron injection in a recently reported tunneling contact IGZO TFT has been studied. The dependence of the injection current on the temperature indicates thermionic emission dominates at small gate bias, while tunneling begins to contribute at large gate bias. The Schottky-barrier height at the metal/graphene/IGZO interface has been extracted, which is consistent with that obtained from previous photocurrent characterizations. The extracted barrier height implies the simplified contact physics and the applicability of the band alignment theory at the graphene inserted metal/IGZO interface.

In this manuscript, a novel probe RHBI based on the rhodamine-benzimidazole conjugate was designed and synthesized. RHBI showed an extreme selectivity for Fe(3+) over other metal ions such as Pb(2+), Ni(2+), Co(2+), Mn(2+), Zn(2+), Hg(2+), Cd(2+), Ag(+), Mg(2+), Ca(2+), Ba(2+), Na(+) and K(+) in acetonitrile. Upon the addition of 10 equiv. of Fe(3+), a 1098-fold fluorescence intensity enhancement was observed at the maximum emission wavelength of 582 nm. Both the Job's plot and ESI-MS showed that RHBI coordinated with Fe(3+) in a 1:1 stoichomitry and the calculated binding constant was 1.01 × 10(4) M(-1). The competition experiment for Fe(3+) ions mixed with other metal ions exhibited no obvious change except Cu(2+) that could induce a mild fluorescence quenching. Moreover, the fluorescence emission increased linearly with the Fe(3+) concentration in the range of 6 × 10(-6)-4 × 10(-5) M and the detection limit was 1.5 × 10(-8) M.

An Artificial Neural Network (ANN) model of molten pool depth for Gas Metal Arc Welding process on plate with single-V groove and its intelligent control method are proposed in this paper. That how to select welding parameters as ANN models' input is mainly discussed, and fuzzy theory is used for molten pool depth control. The effectiveness of the proposed methods is demonstrated by the real experiments.

According to the image characteristics in weld seam tracking with laser vision, Radon transform is first used to find the location of the laser stripe; then, the transformed image is processed by using the way the information from laser stripe is reserved and the other information from noises is removed, after that inverse Radon transform is applied for image recovery. Finally, improved fast FCM clustering is used for image segmentation so that the groove area can be recognized. These methods can bring good effects with little time cost, and the anti-disturbance performance is well, therefore they are suitable for weld seam tracking with laser vision.

Welding molten pool depth control system based on single neuron self-tuning PID is designed, and several learning algorithms for neuron weights are simulated, the simulation results show that this controller reacts quickly and has good stability. Adopting the improved Hebb learning algorithm can bring best effect. The experiment with various cross-section and seam-gap workpiece is perfect, showing that single-neuron self-tuning PID controller is suitable to the complicated welding system.

Fuzzy enhancement algorithm and KSW entropy algorithm are proposed for pre-welding seam image segmentation. Before automatic welding, the welding seam image is often segmented so that it can be recognized by robot. KSW entropy algorithm is an effective way for segmentation. Image enhancement is often applied before segmentation in order to get better result. As the pre-welding seam image is not uniform, the effect is not ideal after applying regular enhancement algorithm and KSW entropy algorithms to it. Fuzzy enhancement algorithm can eliminate the noises and preserve the details of the image intelligently. The image dividing point has close relation with the result of fuzzy enhancement algorithm. Self adapting algorithm about how to get the proper image dividing point is discussed. When fuzzy enhancement algorithm and KSW entropy segmentation algorithm are used to pre-welding seam image, the experiment results prove that the best effect can be got and little time will be cost.

The processing ways of welding seam image based on single-stripe laser are discussed. The wavelet transform is applied to get the horizontal detail part of the image. Taking this part for subsequent seam recognition, its remaining noises are eliminated by median filtering in vertical direction. KSW entropy algorithm is used for image segmentation. Good effects can be got by using these ways, and the cost time is short enough to meet the requirement of real-time tracking or control.

The mobilities of single-layer graphene combined with AlGaN/GaN heterostructures on two-dimensional electron gases in graphene/AlGaN/GaN double heterojunction are calculated. The impact of electron density in single-layer graphene is also studied. Remote surface roughness (RSR) and remote interfacial charge (RIC) scatterings are introduced into this heterostructure. The mobilities limited by RSR and RIC are an order of magnitude higher than that of interface roughness and misfit dislocation. This study contributes to designing structures for generation of higher electron mobility in graphene/AlGaN/GaN double heterojunction.