Unoptimized Device Research Articles

Engineering Graphene Phototransistors for High Dynamic Range Applications.

Phototransistors are light-sensitive devices featuring a high dynamic range, low-light detection, and mechanisms to adapt to different ambient light conditions. These features are of interest for bioinspired applications such as artificial and restored vision. In this work, we report on a graphene-based phototransistor exploiting the photogating effect that features picowatt- to microwatt-level photodetection, a dynamic range covering six orders of magnitude from 7 to 107 lux, and a responsivity of up to 4.7 × 103 A/W. The proposed device offers the highest dynamic range and lowest optical power detected compared to the state of the art in interfacial photogating and further operates air stably. These results have been achieved by a combination of multiple developments. For example, by optimizing the geometry of our devices with respect to the graphene channel aspect ratio and by introducing a semitransparent top-gate electrode, we report a factor 20-30 improvement in responsivity over unoptimized reference devices. Furthermore, we use a built-in dynamic range compression based on a partial logarithmic optical power dependence in combination with control of responsivity. These features enable adaptation to changing lighting conditions and support high dynamic range operation, similar to what is known in human visual perception. The enhanced performance of our devices therefore holds potential for bioinspired applications, such as retinal implants.

Buried interface modification and light outcoupling strategy for efficient blue perovskite light-emitting diodes

Perovskite light-emitting diodes (PeLEDs) exhibit remarkable potential in the field of displays and solid-state lighting. However, blue PeLEDs, a key element for practical applications, still lag behind their green and red counterparts, due to a combination of strong nonradiative recombination losses and unoptimized device structures. In this report, we propose a buried interface modification strategy to address these challenges by focusing on the bottom-hole transport layer (HTL) of the PeLEDs. On the one hand, a multifunctional molecule, aminoacetic acid hydrochloride (AACl), is introduced to modify the HTL/perovskite interface to regulate the perovskite crystallization. Experimental investigations and theoretical calculations demonstrate that AACl can effectively reduce the nonradiative recombination losses in bulk perovskites by suppressing the growth of low-n perovskite phases and also the losses at the bottom interface by passivating interfacial defects. On the other hand, a self-assembly nanomesh structure is ingeniously developed within the HTLs. This nanomesh structure is meticulously crafted through the blending of poly-(9,9-dioctyl-fluorene-co-N-(4-butyl phenyl) diphenylamine) and poly (n-vinyl carbazole), significantly enhancing the light outcoupling efficiency in PeLEDs. As a result, our blue PeLEDs achieve remarkable external quantum efficiencies, 20.4% at 487 nm and 12.5% at 470 nm, which are among the highest reported values. Our results offer valuable insights and effective methods for achieving high-performance blue PeLEDs.

Improving Carbon Nanotube-Based Radiofrequency Field-Effect Transistors by the Device Architecture and Doping Process.

The semiconducting carbon nanotube (CNT) has been considered a promising candidate for future radiofrequency (RF) electronics due to its excellent electrical properties of high mobility and small capacitance. After decades of development, great progress has been achieved on CNT-based RF field-effect transistors (FETs). However, almost all elevations are owing to advancement of the CNT materials and fabrication process, while the study of device architecture is seldom considered and reported. In this work, we innovatively combined device architecture and related doping processes to further optimize CNT-based RF FETs by guiding process or materials with collaborative optimization for the first time and explore their effect on device performance carefully and statistically. Based on more mature random-oriented CNT materials, we fabricated CNT-based RF FETs having three different gate positions of device architecture variation accompanied by suitable doping schemes. The optimized FETs obtained 2-3 times of current density (transconductance) and 1.3 times the cutoff frequency and maximum oscillation frequency compared with unoptimized devices at the same channel length. After transistor-level verification of effect, we further built a CNT RF amplifier and demonstrated almost 10 dB of transducer gain improvement operating at 8 GHz for X-band application. The achieved results from this work would help further improve CNT RF performance beyond the materials and process point of view.

Achieving efficient and stable blue organic light-emitting diodes via suppressing triplet–polaron annihilation processes

It is still challenging to achieve blue OLEDs with sufficient color purity, lifetime and efficiency for applications. Thermally activated delayed fluorescence (TADF) materials become the most promising. However, the internal mechanism of the efficiency roll-off and long-term stability degradation still needs deep research. In this work, the energy transfer and exciton quenching processes in TADF-based blue OLEDs were analyzed under steady-state conditions and their relative contributions to efficiency roll-off were quantified. Furthermore, the degradation mechanism in the TADF-based blue OLEDs was investigated both theoretically and experimentally by a comprehensive exciton quenching model. It was demonstrated that suppressing the triplet–polaron annihilation processes and reducing the accumulation of triplet excitons through reasonable energy transfer can decrease the effect of exciton quenching, thereby significantly reduce the efficiency roll-off and improve device lifetime. It can be seen that the external quantum efficiency (EQE) of the resulting blue OLEDs was enhanced to 30.3 % with CIE coordinates of (0.16, 0.25) and kept 20.9 % at the luminance of 1000 cd/m2. More importantly, the device lifetime was also significantly enhanced, which is over three times longer than that of the unoptimized devices due to the suppress of triplet-polaron annihilation and triplet accumulation.

Fourier modal method for inverse design of metasurface-enhanced micro-LEDs.

We present a simulation capability for micro-scale light-emitting diodes (µLEDs) that achieves comparable accuracy to CPU-based finite-difference time-domain simulation but is more than 107 times faster. Our approach is based on the Fourier modal method (FMM)-which, as we demonstrate, is well suited to modeling thousands of incoherent sources-with extensions that allow rapid convergence for µLED structures that are challenging to model with standard approaches. The speed of our method makes the inverse design of µLEDs tractable, which we demonstrate by designing a metasurface-enhanced µLED that doubles the light extraction efficiency of an unoptimized device.

An Ultracompact Single‐Ferroelectric Field‐Effect Transistor Binary and Multibit Associative Search Engine

Content addressable memory (CAM) is widely used in associative search tasks due to its parallel pattern matching capability. As more complex and data‐intensive tasks emerge, it is becoming increasingly important to enhance CAM density for improved performance and better area efficiency. To reduce the area overheads, various nonvolatile memory (NVM) devices, such as ferroelectric field‐effect transistors (FeFETs), are used in CAM design. Herein, a novel ultracompact 1FeFET CAM design that enables parallel associative search and in‐memory hamming distance calculation is used, as well as a multibit CAM for exact search using the same CAM cell. The proposed CAM design leverages the 1FeFET1R structure, and compact device designs that integrate the series resistor current limiter into the intrinsic FeFET structure are demonstrated to turn the 1FeFET1R structure into an effective 1FeFET cell. A two‐step search operation of the proposed binary and multibit 1FeFET CAM array through both experiments and simulations is proposed, showing a sufficient sensing margin despite unoptimized FeFET device variation. In genome pattern matching applications, using the hyperdimensional computing paradigm, the design results in a 89.9× speedup and 66.5× improvement in energy efficiency over the state‐of‐the‐art alignment tools on GPU.

Machine learning and numerical simulations for electrical, thermodynamic, and mechanical assessment of modified solar thermoelectric generators

The frustum leg thermoelectric generator (FLTEG) was recently proposed as a high-performing power generator. However, there is no basis for proposing this device since its thermo-mechanical performance was not compared with the trapezoidal and conventional rectangular-leg design. Furthermore, solutions to the problems associated with designing variable area leg TEGs on numerical computational solvers have never been proposed. This work seeks to solve this challenge by introducing neural networks that predict the thermo-mechanical performance of variable area leg thermoelectric generators much faster with high accuracies. Therefore, this work compares the thermo-mechanical performances of the three shapes of TEGs using a numerical approach. The three-dimensional finite element models are set up by employing ANSYS software, and the numerical results are validated with experimental results, showing an almost perfect correlation. The power and efficiency of the FLTEG are 5.7 % and 5.6 % higher than the trapezoidal-leg thermoelectric, respectively, under a solar flux of 100 Suns. The former also reduces the thermal stresses of the latter by 2.7 %. The neural network, with an almost perfect regressive correlation and low mean squared error of 7.2 × 10-4, was 702 times faster than the numerical method in predicting the performance of the TEG when diverse input parameters are being varied. Finally, the minimized thermal stress of the optimized device is 0.67 GPa, which is 5.6 times lower than that of the unoptimized device design.

Deep neural networks for quick and precise geometry optimization of segmented thermoelectric generators

To solve the problems of the current optimization methods for solar segmented thermoelectric generator performance based on numerical methods, this paper applied deep neural networks to optimize the device geometry for improved thermo-mechanical performance. The motivation for using the deep neural network is to overcome the lengthy computational time and very high computational energy required by the traditional numerical method in optimizing the segmented thermoelectric generator performance. The numerical model is built using ANSYS software and the effects of temperature dependency in the 4 thermoelectric materials are considered to ensure result accuracy. Furthermore, 16 possible geometry parameters which were previously not considered, encompassing the individual and combined segment's heights and cross-sectional areas are optimized to find which set of parameters are the best in maximizing the device performance. The deep neural network is a regressive multilayer perceptron with network hyperparameters comprising 2 hidden layers with 5 neurons per layer. The training process is governed by the Levenberg-Marquardt standard backpropagation algorithm to minimize the mean squared error and maximize the regression correlation between the neural network forecasted outputs and the numerical-generated dataset. The most significant contribution of the proposed deep neural network is that it was able to quickly and accurately forecast the device performance in just 10 s, which was 2880 times faster than the conventional numerical-based optimization approach. Additionally, the optimized device had a maximum efficiency of 18%, which was 78% higher than that of the unoptimized device. Also, the thermal stress of the optimized device was 73% less than that of the unoptimized device design, indicating an extension in the device mechanical reliability and service lifetime. The results reported in this paper will accelerate the ease at which efficient, long-lasting segmented thermoelectric generators are manufactured by harnessing the power of artificial intelligence.

Predicting the Optimal Performance of a Concentrated Solar Segmented Variable Leg Thermoelectric Generator Using Neural Networks

The production of high-performing thermoelectrics is limited by the high computational energy and time required by the current finite element method solvers that are used to analyze these devices. This paper introduces a new concentrating solar thermoelectric generator made of segmented materials that have non-uniform leg geometry to provide high efficiency. After this, the optimum performance of the device is obtained using the finite element method conducted using ANSYS software. Finally, to solve the high energy and time requirements of the conventional finite element method, the data generated by finite elements are used to train a regressive artificial neural network with 10 neurons in the hidden layer. Results are that the power and efficiency obtained from the optimized device design are 3× and 2× higher than the original unoptimized device design. Furthermore, the developed neural network has a high accuracy of 99.95% in learning the finite element data. Finally, the neural network predicts the modified device performance about 800× faster than the conventional finite element method. Overall, the paper provides insights into how thermoelectric manufacturing companies can harness the power of artificial intelligence to design very high-performing devices while saving time and cost.

Vertical organic phototransistors realized by femtosecond laser ablation patterned metal/insulator bilayer source electrodes: Performance and numerical modeling

Compared with their conventional lateral counter parts, vertical organic phototransistors (VOPTs) have the advantage of fast response speed due to short channel lengths, and may find wide applications in the field of high speed photo detection. By operation of VOPTs, the source electrode plays the vital role. We report on fabrication, characterization and analysis of VOPTs with pulsed laser ablation patterned Al/LiF bilayer source electrode. A maximal photoresponsivity of 760 mA/W, external quantum efficiency ( EQE ) of 145%, specific detectivity of 1.6 × 10 11 Jones were obtained for un-optimized devices. For describing the output characteristics of the devices, a rough numerical model was developed by combining the theory of thermionic emission at metal/organic interface and space charge limited current conduction. • We innovatively achieved the manufacture of vertical channel field-effect transistors by using a porous metal/insulator bilayer source electrode. • We patterned the porous electrode by femtosecond laser ablation. • We proposed a phenomenological device model to getting quantitative insight into the working mechanism of VOPTs. • The un-optimized device in this work showed a maximal photoresponsivity of 760 mA/W, EQE of 145%, specific detectivity of 1.6 × 10 11 Jones.

Strain-tuning PtSe2 for high ON-current lateral tunnel field-effect transistors

We use full-band quantum transport simulations to show that monolayer platinum diselenide (PtSe2) tunnel field-effect transistors (TFETs) can deliver high ON currents (ION) under biaxial tensile strain, while maintaining a sub-60 mV/dec subthreshold swing. When strained, monolayer PtSe2 develops a lower effective mass and a small gap across which an efficient tunneling can occur, translating to a high ION when used in a TFET channel. At a drain voltage of 0.8 V and OFF current of 1×10−7 μA/μm, a simulated device with a 5% strained channel has an ION > 116 μA/μm, which is three orders of magnitude greater than that of the unstrained unoptimized device. The corresponding I60 is also increased by 600 times. This improvement comes at a reasonable cost of degradation in the OFF state and has a minimal effect on the switching characteristics down to 10 nm channel length. Our results present the mechanical flexibility of 2D materials as a powerful tuning parameter toward their use in high-performance tunneling devices.

Tailored Design‐of‐Experiments Approach for Device Performance Prediction and Optimization of Flash‐Evaporated Organic–Inorganic Halide Perovskite‐Based Photodetectors

AbstractSingle‐source flash evaporation method has recently gained attention for its potential as a rapid and solvent‐free deposition method for producing organic–inorganic halide perovskite (OHP) films in large‐scale. However, due to a complex nature of the different experimental parameters involved in the deposition process, it is not straightforward to obtain the optimal condition for producing high‐quality OHP films. In this study, this problem is tackled by employing the design‐of‐experiment (DoE) process, which is an efficient statistical analysis for finding an optimized condition with a minimized number of experiments. The DoE process is used for optimizing the responsivity of the OHP photodetector devices against the input variables used in the deposition that yielded an enhanced responsivity of 112.2 mA W−1, which is up to an order of magnitude higher than that of the unoptimized devices. The experimental results using the DoE method provide not only the conditions required for enhancing the device performance but also the guidelines for improving the overall film quality through exploring the variable space of the flash evaporation technique.

Impact of Al2O3 Passivation on the Photovoltaic Performance of Vertical WSe2 Schottky Junction Solar Cells.

Transition metal dichalcogenide (TMD) materials have emerged as promising candidates for thin-film solar cells due to their wide bandgap range across the visible wavelengths, high absorption coefficient, and ease of integration with both arbitrary substrates and conventional semiconductor technologies. However, reported TMD-based solar cells suffer from relatively low external quantum efficiencies (EQE) and low open circuit voltage due to unoptimized design and device fabrication. This paper studies Pt/WSe2 vertical Schottky junction solar cells with various WSe2 thicknesses in order to find the optimum absorber thickness. Also, we show that the devices' photovoltaic performance can be improved via Al2O3 passivation, which increases the EQE up to 29.5% at 410 nm wavelength incident light. The overall resulting short circuit current improves through antireflection coating, surface doping, and surface trap passivation effects. Thanks to the Al2O3 coating, this work demonstrates a device with an open circuit voltage (VOC) of 380 mV and a short circuit current density (JSC) of 10.7 mA/cm2. Finally, the impact of Schottky barrier height inhomogeneity at the Pt/WSe2 contact is investigated as a source of open circuit voltage lowering in these devices.

Metal-Assisted Delayed Fluorescent Pd(II) Complexes and Phosphorescent Pt(II) Complex Based on [1,2,4]Triazolo[4,3-a]pyridine-Containing Ligands: Synthesis, Characterization, Electrochemistry, Photophysical Studies, and Application.

The synthesis and photophysical characterization of a series of tetradentate cyclometalated M(tzpPh-O-CzPy-R) complexes and their analogues are reported, where M is palladium or platinum and a tetradentate cyclometalating ligand contains tzpPh (3-phenyl-[1,2,4]triazolo[4,3-a]pyridine) and CzPy (carbazolylpyridine) moieties linked with an oxygen atom. Variations of the σ-electron-donating group R on the ligand significantly affect the photophysical properties of the complexes. By using the strong electron-withdrawing tzp portion as an acceptor and the carbazole portion as a donor, a series of Pd(II)-based metal-assisted delayed fluorescence (MADF) materials was developed. Electrochemical analysis demonstrates the irreversible reduction process occurs on the tzp ring and the irreversible oxidation process mainly occurs on the metal-phenyl moiety. This is in agreement with the HOMO and LUMO distributions by the DFT calculations, which also shows that the Pt(II) complex has more metal orbital character than those of the Pd(II) complexes. Most of the Pd(II) complexes reported here are highly emissive at 77 K in 2-MeTHF with luminescent lifetimes in the millisecond range (τ = 1.96-2.36 ms) and λmax = 488-499 nm; however, the luminescent lifetimes are shortened to the microsecond range (τ = 26.7-152.9 μs in solution and 57.0-109.9 μs in thin film respectively) at room temperature. The quantum efficiency of the Pd(II) complexes can be increased by more than 8-fold through structure modification with σ-donating groups on the ligand. Especially, the Pd(tzp-3) has a small ΔEST of 0.228 eV and exhibits strong typical MADF in PMMA film. The Pt(II) complex Pt(tzp-2) exhibits high thermal stability (ΔT0.5% = 440 °C) and high quantum efficiency (Φ = 50.1%) in dichloromethane solution with τ of 15.8 μs. The Pt(tzp-2) based bright green OLED achieved a peak EQE of 8.7% and a maximum brightness of 28280 cd/m2 using an unoptimized device structure.

Enhanced Power Output in Polymer Thermoelectric Devices through Thermal and Electrical Impedance Matching

Maximizing the power outputs of devices using benchmark materials is critical for the application of organic thermoelectrics. We report the fabrication of thermoelectric devices using poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) with a Ni foil and polyimide film. The shape of the Ni foil was designed to match the thermal and electrical resistance of the poly(3,4-ethylenedioxythiophene)/poly(styrenesulfonate) film. Due to the low thermal conductivity of the organic materials, a stable temperature difference of 50 K was achieved under natural cooling conditions without a heat sink at 100 °C. As a result, the device exhibited a power density of 40 μW/cm2, nearly double that of the unoptimized device.

Field-effect transistors with the three-dimensional Dirac semimetal cadmium arsenide

Cadmium arsenide (Cd3As2) is a three-dimensional Dirac semimetal with many unique electronic properties that are of interest for future device applications. Here, we demonstrate field effect transistors using Cd3As2 as the channel material. We show that current densities exceed 5 A/mm and that very low contact resistances can be achieved even in unoptimized device structures. These properties make Cd3As2 of great interest for future high-speed electronics. We report on the current modulation characteristics of field effect transistors as a function of temperature. At low temperatures, the modulation exceeds 70%. We discuss material and device engineering approaches that can improve the device performance at room temperature.

High-Performance Copper Oxide Visible-Light Photodetector via Grain-Structure Model

Recently, copper oxide (CuO)-based visible-light photodetectors have attracted great interest due to their narrow bandgap (1.2 eV), low cost, and ease of fabrication. However, there has been insufficient theoretical analysis and study of CuO-based photodetectors, resulting in inferior performance in terms of responsivity, detectivity, and response speed. This work develops a method to enhance the performance of CuO photodetectors by engineering a grain structure based on a newly-developed theoretical model. In the developed theoretical grain-structure model, the grain size and the connections between grains are considered because they can strongly affect the optoelectronic characteristics of CuO photodetectors. Based upon the proposed model, the engineered CuO device achieves enhanced optoelectronic performance. The engineered device shows high responsivity of 15.3 A/W and detectivity of 1.08 × 1011 Jones, which are 18 and 50 times better than those of the unoptimized device, and also shows fast rising and decaying response speeds of 0.682 s and 1.77 s, respectively. In addition, the proposed method is suitable for the mass-production of performance-enhanced, reliable photodetectors. By using a conventional semiconductor fabrication process, a photodetector-array is demonstrated on a 4-inch wafer. The fabricated devices show uniform, high, and stable optoelectronic performance for a month.

Optimized single-crystal diamond scanning probes for high sensitivity magnetometry

The negatively-charged nitrogen-vacancy center (NV) in diamond forms a versatile system for quantum sensing applications. Combining the advantageous properties of this atomic-sized defect with scanning probe techniques such as atomic force microscopy (AFM) enables nanoscale imaging of e.g. magnetic fields. To form a scanning probe device, we place single NVs shallowly (i.e. < 20 nm) below the top facet of a diamond nanopillar, which is located on a thin diamond platform of typically below 1 μm thickness. This device can be attached to an AFM head, forming an excellent scanning probe tip. Furthermore, it simultaneously influences the collectible photoluminescence (PL) rate of the NV located inside. Especially sensing protocols using continuous optically-detected magnetic resonance benefit from an enhanced collectible PL rate, improving the achievable sensitivity. This work presents a comprehensive set of simulations to quantify the influence of the device geometry on the collectible PL rate for individual NVs. Besides geometric parameters (e.g. pillar length, diameter and platform thickness), we also focus on fabrication uncertainties such as the exact position of the NV or the taper geometry of the pillar introduced by imperfect etching. As a last step, we use these individual results to optimize our current device geometry, yielding a realistic gain in collectible PL rate by a factor of 13 compared to bulk diamond and 1.8 compared to our unoptimized devices.

High performance photodiode based on MoS2/pentacene heterojunction

Photodiodes based on monomolecular layer MoS2/pentacene heterojunction were fabricated and characterized. Similar to other organic photodetectors, the device performances are strongly dependent on the incident optical power. The unoptimized device with Al top electrode, exhibited a fairly high photo responsivity of 0.27 A/W, external quantum efficiency (EQE) of 51.3% and specific detectivity (D∗) of 4.81 × 1011 Jones for red light of 655 nm wavelength. These performances exceed not only the Schottky photodiode based on pentacene, and mono or few layer MoS2 based photodiodes, but also the most organic photodiodes reported recently. More importantly, with Au as the top electrode, the device performances could be further improved, the photoresponsivity, EQE and D∗ reached 0.31 A/W, 58.1%, and 1.55 × 1013 Jones, respectively at the same voltage biasing.

Improving electron transport in the hybrid perovskite solar cells using CaMnO3-based buffer layer

In the present article, the detailed analyses of interface properties and device performance of inorganic perovskite CaMnO3-based buffer layer hybrid perovskite solar cell have been undertaken. Analyses are based on ab initio simulations and macroscopic modelling. A thorough study of electronic and optical properties and interface charge dynamics revealed that CaMnO3 presents a better candidate for the electron transport material in thin film hole transporting material free hybrid perovskite solar cells with the planar architecture than the most common anatase TiO2. This result is founded on the more appropriate band gap and better band alignment with the hybrid perovskite, leading to the faster charge carrier mobility, improved charge transfer and reduced exciton recombination. The results from theoretical simulations are justified by the solar cell model, which explored the basic cell characteristics and parameters: open circuit voltage, short circuit current, fill factor and efficiency, as the functions of cell performance factors, like defect density, diffusion length, absorber layer thickness and band offset. Our model suggests an unoptimized device with a photo-conversion efficiency of almost 10% for the low defect concentrations under 1015. With efficiency in the upper range for HTM free perovskite solar cells, we propose that the CaMnO3-based solar cell poses as an improvement upon the up to now most frequently used ones and provides important step toward their commercialisation.