Impact of scleral tunnel length on the position of intraocular lenses in flanged intrascleral haptic fixation.

PURPOSE: To investigate the effect of scleral tunnel length on the effective lens position and tilt of the intraocular lens (IOL) in flanged intrascleral haptic fixation (ISHF) using anterior segment optical coherence tomography (AS-OCT). SETTING: Tertiary institution. DESIGN: Retrospective case-control study. METHODS: This study included 55 and 42 eyes that underwent ISHF with 1.0 and 2.0 mm scleral tunnels, respectively. 23 eyes that underwent sutured fixation were used as a control. The anterior chamber depth (ACD), scleral tunnel length, incident angle of haptic, and tilting of optic were analyzed using AS-OCT. RESULTS: The mean postoperative ACD, vertical tilt angle, and spherical equivalent of the 1.0 mm were 5.27 ± 0.39 mm, 6.04 ± 4.87 degrees, and 0.38 ± 1.03 diopters, respectively. The ACD and vertical tilt angle of the 1.0 mm were larger than those of the others ( P < .001 and P < .05, respectively), and the postoperative spherical equivalent was more hyperopic ( P < .05). The 2.0 mm exhibited a lower frequency of tilting greater than 7 degrees. The intereye difference in ACD between in-the-bag fixation and ISHF of the 1.0 mm tunnel was significantly greater than that in the 2.0 mm tunnel ( P < .05). The 1.0 mm tunnel had a significantly larger incident angle and a longer tunnel length ( P < .001, respectively) and showed a greater difference in the tunnel length on both sides ( P < .05). CONCLUSIONS: A shorter tunnel yielded a more unstable IOL position, greater variation in angle and tunnel length, and longer ACD during ISHF. An exact 2.0 mm tunnel must be created on both sides to achieve a stable and predictable IOL position.

Area-selective atomic layer deposition on 2D monolayer lateral superlattices.

The advanced patterning process is the basis of integration technology to realize the development of next-generation high-speed, low-power consumption devices. Recently, area-selective atomic layer deposition (AS-ALD), which allows the direct deposition of target materials on the desired area using a deposition barrier, has emerged as an alternative patterning process. However, the AS-ALD process remains challenging to use for the improvement of patterning resolution and selectivity. In this study, we report a superlattice-based AS-ALD (SAS-ALD) process using a two-dimensional (2D) MoS2-MoSe2 lateral superlattice as a pre-defining template. We achieved a minimum half pitch size of a sub-10 nm scale for the resulting AS-ALD on the 2D superlattice template by controlling the duration time of chemical vapor deposition (CVD) precursors. SAS-ALD introduces a mechanism that enables selectivity through the adsorption and diffusion processes of ALD precursors, distinctly different from conventional AS-ALD method. This technique facilitates selective deposition even on small pattern sizes and is compatible with the use of highly reactive precursors like trimethyl aluminum. Moreover, it allows for the selective deposition of a variety of materials, including Al2O3, HfO2, Ru, Te, and Sb2Se3.

Layer-Controlled Growth of Single-Crystalline 2D Bi2O2Se Film Driven by Interfacial Reconstruction.

As semiconductor scaling continues to reach sub-nanometer levels, two-dimensional (2D) semiconductors are emerging as a promising candidate for the post-silicon material. Among these alternatives, Bi2O2Se has risen as an exceptionally promising 2D semiconductor thanks to its excellent electrical properties, attributed to its appropriate bandgap and small effective mass. However, unlike other 2D materials, growth of large-scale Bi2O2Se films with precise layer control is still challenging due to its large surface energy caused by relatively strong interlayer electrostatic interactions. Here, we present the successful growth of a wafer-scale (∼3 cm) Bi2O2Se film with precise thickness control down to the monolayer level on TiO2-terminated SrTiO3 using metal-organic chemical vapor deposition (MOCVD). Scanning transmission electron microscopy (STEM) analysis confirmed the formation of a [BiTiO4]1- interfacial structure, and density functional theory (DFT) calculations revealed that the formation of [BiTiO4]1- significantly reduced the interfacial energy between Bi2O2Se and SrTiO3, thereby promoting 2D growth. Additionally, spectral responsivity measurements of two-terminal devices confirmed a bandgap increase of up to 1.9 eV in monolayer Bi2O2Se, which is consistent with our DFT calculations. Finally, we demonstrated high-performance Bi2O2Se field-effect transistor (FET) arrays, exhibiting an excellent average electron mobility of 56.29 cm2/(V·s). This process is anticipated to enable wafer-scale applications of 2D Bi2O2Se and facilitate exploration of intriguing physical phenomena in confined 2D systems.

Real-time Neural Connectivity Inference with Presynaptic Spike-driven Spike Timing-Dependent Plasticity.

Brain-like artificial intelligence in electronics can be built efficiently by understanding the connectivity of neuronal circuitry. The concept of neural connectivity inference with a two-dimensional cross-bar structure memristor array is indicated in recent studies; however, large-scale implementation is challenging owing to device variations and the requirement of online parameter adaptation. This study proposes a neural connectivity inference method with one-dimensional spiking neurons using spike timing-dependent plasticity and presynaptic spike-driven spike timing-dependent plasticity learning rules, designed for a large-scale neuromorphic system. The proposed learning process decreases the number of spiking neurons by half. We simulate 12 ground-truth neural networks comprising one-dimensional eight and 64 neurons. We analyze the correlation between the neural connectivity of the ground truth and spiking neural networks using the Matthews correlation coefficient. In addition, we analyze the sensitivity and specificity of inference. Validation using the presynaptic spike-driven spike timing-dependent plasticity learning rule implies a potential approach for large-scale neural network inference with real hardware realization of large-scale neuromorphic systems.

Indium-Gallium-Zinc Oxide-Based Synaptic Charge Trap Flash for Spiking Neural Network-Restricted Boltzmann Machine.

Recently, neuromorphic computing has been proposed to overcome the drawbacks of the current von Neumann computing architecture. Especially, spiking neural network (SNN) has received significant attention due to its ability to mimic the spike-driven behavior of biological neurons and synapses, potentially leading to low-power consumption and other advantages. In this work, we designed the indium-gallium-zinc oxide (IGZO) channel charge-trap flash (CTF) synaptic device based on a HfO2/Al2O3/Si3N4/Al2O3 layer. Our IGZO-based CTF device exhibits synaptic functions with 128 levels of synaptic weight states and spike-timing-dependent plasticity. The SNN-restricted Boltzmann machine was used to simulate the fabricated CTF device to evaluate the efficiency for the SNN system, achieving the high pattern-recognition accuracy of 83.9%. We believe that our results show the suitability of the fabricated IGZO CTF device as a synaptic device for neuromorphic computing.

Evolution of Organic Solvent-Resistant DNA Polymerases.

The introduction of thermostable polymerases revolutionized the polymerase chain reaction (PCR) and biotechnology. However, many GC-rich genes cannot be PCR-amplified with high efficiency in water, irrespective of temperature. Although polar organic cosolvents can enhance nucleic acid polymerization and amplification by destabilizing duplex DNA and secondary structures, nature has not selected for the evolution of solvent-tolerant polymerase enzymes. Here, we used ultrahigh-throughput droplet-based selection and deep sequencing along with computational free-energy and binding affinity calculations to evolve Taq polymerase to generate enzymes that are both stable and highly active in the presence of organic cosolvents, resulting in up to 10% solvent resistance and over 100-fold increase in stability at 97.5 °C in the presence of 1,4-butanediol, as well as tolerance to up to 10 times higher concentrations of the potent cosolvents sulfolane and 2-pyrrolidone. Using these polymerases, we successfully amplified a broad spectrum of GC-rich templates containing regions with over 90% GC content, including templates recalcitrant to amplification with existing polymerases, even in the presence of cosolvents. We also demonstrated dramatically reduced GC bias in the amplification of genes with widely varying GC content in quantitative polymerase chain reaction (qPCR). By expanding the scope of solvent systems compatible with nucleic acid polymerization, these organic solvent-resistant polymerases enable a dramatic reduction of sequence bias not achievable through thermal resistance alone, with significant implications for a wide range of applications including sequencing and synthetic biology in mixed aqueous-organic media.

Multifunctional Crystalline InGaSnO Phototransistor Exhibiting Photosensing and Photosynaptic Behavior Using Oxygen Vacancy Engineering.

A multifunctional optoelectronic device implementing photodetector, photosynapse, and photomemory is of increasing attention for neuromorphic system. This enables multiple devices to be replaced with a single device, which simplifies the structure of complex, highly integrated electronics. Here, a multifunctional c-axis-aligned crystalline indium gallium tin oxide thin-film transistor (TFT) optoelectronic device is demonstrated. The photodetecting and photosynaptic behaviors could be demonstrated by tuning of gate pulse. The device shows a high responsivity of 1.1 × 106  A W-1 to blue light (467 nm) and cutoff frequency (f-3dB ) of 2400 Hz exhibiting high frequency switching using a gate reset pulse. It is possible to implement photosynaptic behavior using persistent photoconductivity effect by applying a gate bias to make the TFT depletion mode. When potentiation and depression of synaptic weight are implemented with light pulse and gate voltage pulse, respectively, 64-state potentiation-depression curves are demonstrated with excellent nonlinearity of 1.13 and 2.03, respectively. When an artificial neural network is constructed with this device for the Modified National Institute of Standards and Technology training pattern recognition simulation, it shows a high pattern recognition accuracy of 90.4%.

Surface-Dominated HfO2 Nanorod-Based Memristor Exhibiting Highly Linear and Symmetrical Conductance Modulation for High-Precision Neuromorphic Computing.

The switching characteristics and performance of oxide-based memristors are predominately determined by oxygen- or oxygen-vacancy-mediated redox reactions and the consequent formation of conducting filaments (CFs). Devices using oxide thin films as the switching layer usually require an electroforming process for subsequent switching operations, which induces large device-to-device variations. In addition, the hard-to-control redox reaction during repeated switching causes random fluctuations or degradation of each resistance state, hindering reliable switching operations. In this study, an HfO2 nanorod (NR)-based memristor is proposed for simultaneously achieving highly uniform, electroforming-free, fast, and reliable analogue switching properties. The well-controlled redox reaction due to the easy gas exchange with the environment at the surface of the NRs enhances the generation of oxygen or oxygen vacancies during the switching operation, resulting in electroforming-free and reliable switching behavior. In addition, the one-dimensional surface growth of CFs facilitates highly linear conductance modulation with smaller conductance changes compared with the two-dimensional volume growth in thin-film-based memristors, resulting in a high accuracy of >92% in the Modified National Institute of Standards and Technology pattern-recognition test and desirable spike-timing-dependent plasticity.

Large Memory Window of van der Waals Heterostructure Devices Based on MOCVD-Grown 2D Layered Ge4 Se9.

Van der Waals (vdW) heterostructures have drawn much interest over the last decade owing to their absence of dangling bonds and their intriguing low-dimensional properties. The emergence of 2D materials has enabled the achievement of significant progress in both the discovery of physical phenomena and the realization of superior devices. In this work, the group IV metal chalcogenide 2D-layered Ge4 Se9 is introduced as a new selection of insulating vdW material. 2D-layered Ge4 Se9 is synthesized with a rectangular shape using the metalcorganic chemical vapor deposition system using a liquid germanium precursor at 240 °C. By stacking the Ge4 Se9 and MoS2 , vdW heterostructure devices are fabricated with a giant memory window of 129 V by sweeping back gate range of ±80 V. The gate-independent decay time reveals that the large hysteresis is induced by the interfacial charge transfer, which originates from the low band offset. Moreover, repeatable conductance changes are observed over the 2250 pulses with low non-linearity values of 0.26 and 0.95 for potentiation and depression curves, respectively. The energy consumption of the MoS2 /Ge4 Se9 device is about 15 fJ for operating energy and the learning accuracy of image classification reaches 88.3%, which further proves the great potential of artificial synapses.

Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing.

Memristors, or memristive devices, have attracted tremendous interest in neuromorphic hardware implementation. However, the high electric-field dependence in conventional filamentary memristors results in either digital-like conductance updates or gradual switching only in a limited dynamic range. Here, we address the switching parameter, the reduction probability of Ag cations in the switching medium, and ultimately demonstrate a cluster-type analogue memristor. Ti nanoclusters are embedded into densified amorphous Si for the following reasons: low standard reduction potential, thermodynamic miscibility with Si, and alloy formation with Ag. These Ti clusters effectively induce the electrochemical reduction activity of Ag cations and allow linear potentiation/depression in tandem with a large conductance range (~244) and long data retention (~99% at 1 hour). Moreover, according to the reduction potentials of incorporated metals (Pt, Ta, W, and Ti), the extent of linearity improvement is selectively tuneable. Image processing simulation proves that the Ti4.8%:a-Si device can fully function with high accuracy as an ideal synaptic model.

Gas-Phase Alkali Metal-Assisted MOCVD Growth of 2D Transition Metal Dichalcogenides for Large-Scale Precise Nucleation Control.

Advances in large-area and high-quality 2D transition metal dichalcogenides (TMDCs) growth are essential for semiconductor applications. Here, the gas-phase alkali metal-assisted metal-organic chemical vapor deposition (GAA-MOCVD) of 2D TMDCs is reported. It is determined that sodium propionate (SP) is an ideal gas-phase alkali-metal additive for nucleation control in the MOCVD of 2D TMDCs. The grain size of MoS2 in the GAA-MOCVD process is larger than that in the conventional MOCVD process. This method can be applied to the growth of various TMDCs (MoS2 , MoSe2 , WSe2 , and WSe2 ) and the generation of large-scale continuous films. Furthermore, the growth behaviors of MoS2 under different SP and oxygen injection time conditions are systematically investigated to determine the effects of SP and oxygen on nucleation control in the GAA-MOCVD process. It is found that the combination of SP and oxygen increases the grain size and nucleation suppression of MoS2 . Thus, the GAA-MOCVD with a precise and controllable supply of a gas-phase alkali metal and oxygen allows achievement of optimum growth conditions that maximizes the grain size of MoS2 . It is expected that GAA-MOCVD can provide a way for batch fabrication of large-scale atomically thin electronic devices based on 2D semiconductors.

Demonstration of Efficient Ultrathin Side-Emitting InGaN/GaN Flip-Chip Light-Emitting Diodes by Double Side Reflectors.

This work proposes an InGaN/GaN multiple-quantum-well flip-chip blue ultrathin side-emitting (USE) light-emitting diode (LED) and describes the sidewall light emission characteristics for the application of backlight units in display technology. The USE-LEDs are fabricated with top (ITO/distributed Bragg reflector) and bottom (Ag) mirrors that cause light emission from the four sidewalls in a lateral direction. The effect of light output power (LOP) on lateral direction is consistently investigated for improving the optoelectronic performances of USE-LEDs. Initially, the reference USE-LED suffers from very low LOP because of poor light extraction efficiency (LEE). Therefore, the LEE is improved by fabricating ZnO nanorods at each sidewall through hydrothermal method. The effects of ZnO nanorod lengths and diameters on LOP are systematically investigated for optimizing the dimensions of ZnO nanorods. The optimized ZnO nanorods improve the LEE of USE-LED, which thus results in increasing the LOP > 80% compared to the reference LED. In addition, the light-tools simulator is also used for elucidating the increase in LEE of ZnO nanorods USE-LED.

Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons.

Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (Vth). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.

Bottom-Up Evolution of Diamond-Graphite Hybrid Two-Dimensional Nanostructure: Underlying Picture and Electrochemical Activity.

The diamond-graphite hybrid thin film with low-dimensional nanostructure (e.g., nitrogen-included ultrananocrystalline diamond (N-UNCD) or the alike), has been employed in many impactful breakthrough applications. However, the detailed picture behind the bottom-up evolution of such intriguing carbon nanostructure is far from clarified yet. Here, the authors clarify it, through the concerted efforts of microscopic, physical, and electrochemical analyses for a series of samples synthesized by hot-filament chemical vapor deposition using methane-hydrogen precursor gas, based on the hydrogen-dependent surface reconstruction of nanodiamond and on the substrate-temperature-dependent variation of the growth species (atomic hydrogen and methyl radical) concentration near substrate. The clarified picture provides insights for a drastic enhancement in the electrochemical activities of the hybrid thin film, concerning the detection of important biomolecule, that is, ascorbic acid, uric acid, and dopamine: their limits of detections are 490, 35, and 25 nm, respectively, which are among the best of the all-carbon thin film electrodes in the literature. This work also enables a simple and effective way of strongly enhancing AA detection.

32 × 32 Pixelated High-Power Flip-Chip Blue Micro-LED-on-HFET Arrays for Submarine Optical Communication.

This work proposes the use of integrated high-power InGaN/GaN multiple-quantum-well flip-chip blue micro light-emitting diode (µ-LED) arrays on an AlGaN/GaN-based heterojunction field-effect transistor (HFET), also known as a high electron mobility transistor (HEMT), for various applications: underwater wireless optical communication (UWOC) and smart lighting. Therefore, we demonstrate high-power µ-LED-on-HEMT arrays that consist of 32 × 32 pixelated µ-LED arrays and 32 × 32 pixelated HEMT arrays and that are interconnected by a solder bump bonding technique. Each pixel of the µ-LED arrays emits light in the HEMT on-state. The threshold voltage, the off-state leakage current, and the drain current of the HEMT arrays are -4.6 V, <~1.1 × 10-9 A at gate-to-source voltage (VGS) = -10 V, and 21 mA at VGS = 4 V, respectively. At 12 mA, the forward voltage and the light output power (LOP) of µ-LED arrays are ~4.05 V and ~3.5 mW, respectively. The LOP of the integrated µ-LED-on-HEMT arrays increases from 0 to ~4 mW as the VGS increases from -6 to 4 V at VDD = 10 V. Each pixel of the integrated µ-LEDs exhibits a modulated high LOP at a peak wavelength of ~450 nm, showing their potential as candidates for use in UWOC.

Polarity Control and Weak Fermi-Level Pinning in PdSe2 Transistors.

Two-dimensional (2D) materials have been considered key materials for the future logic devices due to the excellent electrostatic integrity originating from their ultrathin nature. However, the carrier polarity control of 2D material field-effect transistors (FETs) still remains a challenging issue, hindering the realization of complementary logic function in the 2D material platform. Here, we report a comprehensive study on the electrical characteristics of PdSe2 FETs with different metal contacts. It is found that the carrier polarity in PdSe2 FETs can be modulated simply by changing the metal contact due to the weak Fermi-level pinning in PdSe2. We demonstrate a complementary metal-oxide-semiconductor (CMOS) inverter using the same channel material PdSe2 for n- and p-MOSFETs but with different metal contacts, suggesting the possible realization of PdSe2-based CMOS logic circuits.

Low-Temperature and High-Quality Growth of Bi2O2Se Layered Semiconductors via Cracking Metal-Organic Chemical Vapor Deposition.

Ternary metal-oxy-chalcogenides are emerging as next-generation layered semiconductors beyond binary metal-chalcogenides (i.e., MoS2). Among ternary metal-oxy-chalcogenides, especially Bi2O2Se has been demonstrated in field-effect transistors and photodetectors, exhibiting ultrahigh performance with robust air stability. The growth method for Bi2O2Se that has been reported so far is a powder sublimation based chemical vapor deposition. The first step for pursuing the practical application of Bi2O2Se as a semiconductor material is developing a gas-phase growth process. Here, we report a cracking metal-organic chemical vapor deposition (c-MOCVD) for the gas-phase growth of Bi2O2Se. The resulting Bi2O2Se films at very low growth temperature (∼300 °C) show single-crystalline quality. By taking advantage of the gas-phase growth, the precise phase control was demonstrated by modulating the partial pressure of each precursor. In addition, c-MOCVD-grown Bi2O2Se exhibits outstanding electrical and optoelectronic performance at room temperature without passivation, including maximum electron mobility of 127 cm2/(V·s) and photoresponsivity of 45134 A/W.

Spiking Neural Network (SNN) With Memristor Synapses Having Non-linear Weight Update.

Among many artificial neural networks, the research on Spike Neural Network (SNN), which mimics the energy-efficient signal system in the brain, is drawing much attention. Memristor is a promising candidate as a synaptic component for hardware implementation of SNN, but several non-ideal device properties are making it challengeable. In this work, we conducted an SNN simulation by adding a device model with a non-linear weight update to test the impact on SNN performance. We found that SNN has a strong tolerance for the device non-linearity and the network can keep the accuracy high if a device meets one of the two conditions: 1. symmetric LTP and LTD curves and 2. positive non-linearity factors for both LTP and LTD. The reason was analyzed in terms of the balance between network parameters as well as the variability of weight. The results are considered to be a piece of useful prior information for the future implementation of emerging device-based neuromorphic hardware.

Effect of Thermal Interface Materials on Heat Dissipation of Light-Emitting Diode Headlamps with Thermally-Conductive Plastics.

We study the effect of thermal interface material such as thermal-conductive plastic on the dissipation of generated heat from the light-emitting diodes (LEDs) based headlamp for the application of environment-friendly green energy in vehicles. The thermal distribution and the performances of thermal-conductive plastic with heatsink are consistently investigated by using experimental and numerical results. Various thicknesses of thermal-conductive plastics from 0.3 mm to 1.0 mm used in this research work. Basically the thermal-conductive plastic reduces the thermal interface resistance between the contact of two solid surfaces. As a result, High electrical power of about 15 W (1 A and 15 V) can be possible for applying to the high-power LED package without any damage. The soldering temperature of LED package without thermal-conductive plastic shows approximately 138.7 °C which is higher compared to the LED package with thermal-conductive plastic (124.3 °C). On the other hand, the soldering temperature increases from 124.3 to 127.6 °C with increasing the thicknesses of thermal-conductive plastic. In addition, the soldering temperature decreases from 138.7 to 124.3 °C with increasing the thermal conductivities of thermal-conductive plastic. Finally, a highly thermal conductive property of thermal-conductive plastic will propose for optimum dissipation of generated heat from the LEDs-based headlamp. We also successfully estimate the junction temperature of packaged LEDs by using soldering temperature.

Novel nano-plasmonic sensing platform based on vertical conductive bridge.

A novel nano-plasmonic sensing platform based on vertical conductive bridge was suggested as an alternative geometry for taking full advantages of unique properties of conductive junction while substantially alleviating burdens in lithographic process. The effects of various geometrical parameters on the plasmonic properties were systematically investigated. Theoretical simulation on this structure demonstrates that the presence of vertical conductive bridge with smaller diameter sandwiched between two adjacent thin nanodiscs excites a bridged mode very similar to the charge transfer plasmon and exhibits a remarkable enhancement in the extinction efficiency and the sensitivity when the electric field of incident light is parallel to the conductive bridge. Furthermore, for the electric field perpendicular to the bridge, another interesting feature is observed that two magnetic resonance modes are excited symmetrically through open-gaps on both sides of the bridge together with strongly enhanced electric field intensity, which provides a very favorable environment as a surface enhanced Raman scattering substrate for fluid analysis. These results verify a great potential and versatility of our approach for use as a nanoplasmonic sensing platform. In addition, we demonstrated the feasibility of fabrication process of vertical conductive bridge and high tunability in controlling the bridge width.