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A promising approach for implementing biomimetic systems relies on organic electronic devices designed to emulate neural synapses. However, organic artificial synapses face challenges in achieving high yield and robustness, rendering them difficult to use in practical applications. In this work, a high-yield and highly stable bulk heterojunction (BHJ) synaptic device composed of Poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) was fabricated via a simple solution process followed by thermal treatments. The crystallinity of P3HT and the precipitation of PCBM in BHJ films can be controlled by the thermal annealing temperatures. At 80 °C, P3HT reaches its highest crystallinity, while PCBM remains uniformly distributed. This thermal treatment significantly contributes to the fabrication of devices characterized by a high yield rate, reaching 98.43%. Additionally, this device remained operational even after being immersed in deionized water, ethanol, and seawater for 100 h. More importantly, it exhibited high elasticity over a wide temperature range from -90 to 310 °C. Finally, this device was utilized to construct a biomimetic vehicle with autonomous memory learning capabilities. After repeated training, the avoidance time was optimized by 31.4%. The robust P3HT:PCBM artificial synapses hold great promise for advancing the development of biomimetic electronic products in extreme environments.
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Visuomorphic computing aims to simulate and potentially surpass the human retina by mimicking biological visual perception with an artificial retina. Despite significant progress, challenges persist in perceiving complex interactive environments. Negative photoconductivity transistors (NPTs) mimic synaptic behavior by achieving adjustable positive photoconductivity (PPC) and negative photoconductivity (NPC), simulating "excitation" and "inhibition" akin to sensory cell signals. In complex interactive environments, NPTs are desired for visuomorphic computing that can achieve a better sense of information, lower power consumption, and reduce hardware complexity. In this review, it is started by introducing the development process of NPTs, while placing a strong emphasis on the device structures, working mechanisms, and key performance parameters. The common material systems employed in NPTs based on their functions are then summarized. Moreover, it is proceeded to summarize the noteworthy applications of NPTs in optoelectronic devices, including advanced multibit nonvolatile memory, optoelectronic logic gates, optical encryption, and visual perception. Finally, the challenges and prospects that lie ahead in the ongoing development of NPTs are addressed, offering valuable insights into their applications in optoelectronics and a comprehensive understanding of their significance.
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Photoadaptive synaptic devices enable in-sensor processing of complex illumination scenes, while second-order adaptive synaptic plasticity improves learning efficiency by modifying the learning rate in a given environment. The integration of above adaptations in one phototransistor device will provide opportunities for developing high-efficient machine vision system. Here, a dually adaptable organic heterojunction transistor as a working unit in the system, which facilitates precise contrast enhancement and improves convergence rate under harsh lighting conditions, is reported. The photoadaptive threshold sliding originates from the bidirectional photoconductivity caused by the light intensity-dependent photogating effect. Metaplasticity is successfully implemented owing to the combination of ambipolar behavior and charge trapping effect. By utilizing the transistor array in a machine vision system, the details and edges can be highlighted in the 0.4% low-contrast images, and a high recognition accuracy of 93.8% with a significantly promoted convergence rate by about 5 times are also achieved. These results open a strategy to fully implement metaplasticity in optoelectronic devices and suggest their vision processing applications in complex lighting scenes.
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In the era of the Internet of Things and the rapid progress of artificial intelligence, there is a growing demand for advanced dynamic vision systems. Vision systems are no longer confined to static object detection and recognition, as the detection and recognition of moving objects are becoming increasingly important. To meet the requirements for more precise and efficient dynamic vision, the development of adaptive multimodal motion detection devices becomes imperative. Inspired by the varied response rates in biological vision, we introduce the concept of critical flicker fusion frequency (cFFF) and develop an organic optoelectronic synaptic transistor with adjustable cFFF. In situ Kelvin probe force microscopy analysis reveals that light signal recognition in this device originates from charge transfer in the poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene)-co-(1,3-di(5-thiophene-2-yl)-5,7-bis(2-ethylhexyl)-benzo[1,2-c:4,5-c']dithiophene-4,8-dione)] (PBDB-T)/pentacene heterojunction, which can be effectively modulated by gate voltage. Building upon this, we implement different cFFF within a single device to facilitate the detection and recognition of objects moving at different speeds. This approach allows for resource allocation during dynamic detection, resulting in a reduction in power consumption. Our research holds great potential for enhancing the capabilities of dynamic visual systems.
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Inkjet printing is of great interest in the preparation of optoelectronic and microelectronic devices due to its low cost, low process temperature, versatile material compatibility, and ability to precisely manufacture multi-layer devices on demand. However, interlayer solvent erosion is a typical problem that limits the printing of organic semiconductor devices with multi-layer structures. In this study, we proposed a solution to address this erosion problem by designing polystyrene-block-poly(4-vinyl pyridine)-grafted Au nanoparticles (Au@PS-b-P4VP NPs). With a colloidal ink containing the Au@PS-b-P4VP NPs, we obtained a uniform monolayer of Au nano-crystal floating gates (NCFGs) embedded in the PS-b-P4VP tunneling dielectric (TD) layer using direct-ink-writing (DIW). Significantly, PS-b-P4VP has high erosion resistance against the semiconductor ink solvent, which enables multi-layer printing. An active layer of semiconductor crystals with high crystallinity and well-orientation was obtained by DIW. Moreover, we developed a strategy to improve the quality of the TD/semiconductor interface by introducing a polystyrene intermediate layer. We show that the NCFG memory devices exhibit a low threshold voltage (<3 V), large memory window (66 V), stable endurance (>100 cycles), and long-term retention (>10 years). This study provides universal guidance for printing functional coatings and multi-layer devices.
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To investigate the impact of interfacial layer effects on the thermal conductivity of nanofluids and the microscopic mechanisms of enhanced thermal conductivity, this study employed non-equilibrium molecular dynamics to compute the thermal conductivity, number density, radial distribution function, and mean square displacement distribution of SiC nanofluids. The impact of nanoparticle volume fraction and particle size parameters on the thermal conductivity of nanofluids and the structure of interfacial adsorption layers was discussed. The simulation calculation results show that the coefficient of thermal conductivity of nanofluid is positively related to the volume fraction of nanoparticles, increasing from 0.6529 W/(m·K) to 0.8159 W/(m·K), and the enhancement of thermal conductivity by the volume fraction can be up to 33.97 %. The thermal conductivity is inversely correlated with the change in particle size, and the maximum improvement in thermal conductivity by particle size can reach up to 12.05 %. The simulated results of the thermal conductivity of nanofluid are almost consistent with the predicted results of the Yu&Choi model, and the error is controlled within 5 %. Simultaneously, the thickness of the interfacial adsorption layer decreases with an increase in particle size. This reduction arises due to larger particles having a smaller specific surface area, resulting in fewer particle surfaces covered by the interface layer. Moreover, the impact of particle size on the arrangement and affinity of molecules within the interface layer contributes to this decrease. Overall, interface layer effects exhibit a dual impact on the thermal conduction of nanofluids. The structured formation and high-density distribution of the adsorption layer contribute to enhanced heat transfer, while thermal resistance between nanoparticle surfaces and the fluid restricts heat transmission.
Assuntos
Temperatura Alta , Simulação de Dinâmica Molecular , Condutividade Térmica , Adsorção , ÁguaRESUMO
Aiming at the difficulty of traditional machining of Y2O3-ZrO2 (YSZ) inert ceramic materials, a different method using focused ion beam to selectively create nanoscale microscale structures on the surface of materials was proposed. The sputtering yield, surface damage, and the energy loss of YSZ materials was investigated using the SRIM software using the Monte Carlo method. It is shown that the sputtering yield increases with ion energy in the range 0-30 keV, reaching a maximum of 9.4 atoms/ion at 30 keV. At an ion beam voltage of 30 keV, the most severe damage to the material is 8 mm on the surface. At the same time, the main forms of energy loss in the treatment are phonon energy loss and ionization energy loss, of which phonon energy loss due to the recoil atoms is the largest. In addition, we continue to perform focused ion beam processing experiments on YSZ materials, combining previous MC modeling to optimize different operating conditions such as ion beam, voltage and processing mode. The optimized processing parameters are 30 keV and 2.5 nA. It is shown that the quality of the deep grooves gradually improves with decreasing ion beam current at the same ion beam voltage. However, an excessively small ion beam current leads to an excessively large depth of the deep grooves and lengthy processing times.
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Organic memory has attracted tremendous attention for next-generation electronic elements for the molecules' striking ease of structural design. However, due to them being hardly controllable and their low ion transport, it is always essential and challenge to effectively control their random migration, pathway, and duration. There are very few effective strategies, and specific platforms with a view to molecules with specific coordination-groups-regulating ions have been rarely reported. In this work, as a generalized rational design strategy, the well-known tetracyanoquinodimethane (TCNQ) is introduced with multiple coordination groups and small plane structure into a stable polymers framework to modulate Ag migration and then achieve high-performance devices with ideal productivity, low operation voltage and power, stable switching cycles, and state retention. Raman mapping demonstrates that the migrated Ag can specially coordinate with the embedded TCNQ molecules. Notably, the TCNQ molecule distribution can be modulated inside the polymer framework and regulate the memristive behaviors through controlling the formed Ag conductive filaments (CFs) as demonstrated by Raman mapping, in situ conductive atomic force microscopy (C-AFM), X-ray diffraction (XRD) and depth-profiling X-ray photoelectron spectroscopy (XPS). Thus the controllable molecule-mediated Ag movements show its potential in rationally designing high-performance devices and versatile functions and is enlightening in constructing memristors with molecule-mediated ion movements.
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Ti1-xAlxN coating is formed by replacing some Ti atoms in TiN with Al atoms, and their properties are closely related to Al content (0 < x < 1). Recently, Ti1-xAlxN-coated tools have been widely used in the machining of Ti-6Al-4V alloy. In this paper, the hard-to-machine material Ti-6Al-4V alloy is used as the study material. Ti1-xAlxN-coated tools are used for milling experiments. The evolution of the wear form and the wear mechanism of Ti1-xAlxN-coated tools are studied, and the influence of Al content (x = 0.52, 0.62) and cutting speed on tool wear are analyzed. The results show that the wear on the rake face changes from the initial adhesion and micro-chipping to coating delamination and chipping. Wear on the flank face varies from the initial adhesion and grooves to boundary wear, build-up layer, and ablation. The main wear mechanisms of Ti1-xAlxN-coated tools are dominated by adhesion, diffusion, and oxidation wear. Ti0.48Al0.52N coating protects the tool well and extends its service life.
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Cutting force in lathe work is closely related to tool wear and affects the turning quality. Direct measurement of the cutting force by measuring the strain of the tool holder is challenging because the tool holder design aims to be highly rigid in order to undertake large cutting forces. Accordingly, the most popular dynamometer designs modify the standard tool holder by decreasing the structural rigidity of the holder, which reduces the machining precision and is not widely accepted. In order to solve the issue of the low stiffness of the dynamometer reducing the machining precision, in this paper, the ultra-low strain on the tool holder was successfully detected by the highly sensitive semiconductor strain gauges (SCSG) adjacent to the blade cutting insert. However, the cutting process would generate much heat, which increases the force measuring area temperature of the tool holder by about 30 °C. As a result, the readout drifted significantly with the temperature changes due to the high temperature coefficient of SCSG. To solve this problem, the temperature on the tool holder was monitored and a BP neural network was proposed to compensate for temperature drift errors. Our methods improved the sensitivity (1.14 × 10-2 mV/N) and the average relative error of the BP neural network prediction (≤1.48%) while maintaining the original stiffness of the tool holder. The smart tool holder developed possesses high natural frequency (≥6 kHz), it is very suitable for dynamic cutting-force measurement. The cutting experiment data in the lathe work show comparable performance with the traditional dynamometers and the resolution of the smart tool holder is 2 N (0.25% of total range).
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In this work, it is reported that large-area (centimeter-scale) arrays of non-close-packed polystyrene-tethered gold nanorod (AuNR@PS) can be prepared through a liquid-liquid interfacial assembly method. Most importantly, the orientation of AuNRs in the arrays can be controlled by changing the intensity and direction of electric field applied in the solvent annealing process. The interparticle distance of AuNR can be tuned by varying the length of polymer ligands. Moreover, the AuNR@PS with short PS ligand are favorited to form orientated arrays with the assistance of electric field, while long PS ligands make the orientation of AuNRs difficult. The orientated AuNR@PS arrays are employed as the nano-floating gate of field-effect transistor memory device. Tunable charge trapping and retention characteristics in the device can be realized by electrical pulse with visible light illumination. The memory device with orientated AuNR@PS array required less illumination time (1 s) at the same onset voltage in programming operation, compared to the control device with disordered AuNR@PS array (illumination time: 3 s). Moreover, the orientated AuNR@PS array-based memory device can maintain the stored data for more than 9000 s, and exhibits stable endurance characteristic without significant degradation in 50 programming/reading/erasing/reading cycles.
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Neuromorphic electronics, being inspired by how the brain works, hold great promise to the successful implementation of smart artificial systems. Among several neuromorphic hardware issues, a robust device functionality under extreme temperature is of particular importance for practical applications. Given that the organic memristors for artificial synapse applications are demonstrated under room temperature, achieving a robust device performance at extremely low or high temperature is still utterly challenging. In this work, the temperature issue is addressed by tuning the functionality of the solution-based organic polymeric memristor. The optimized memristor demonstrates a reliable performance under both the cryogenic and high-temperature environments. The unencapsulated organic polymeric memristor shows a robust memristive response under test temperature ranging from 77 to 573 K. Utilizing X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary-ion mass spectrometry (ToF-SIMS) depth profiling, the device working mechanism is unveiled by comparing the compositional profiles of the fresh and written organic polymeric memristors. A reversible ion migration induced by an applied voltage contributes to the characteristic switching behavior of the memristor. Herein, both the robust memristive response achieved at extreme temperatures and the verified device working mechanism will remarkably accelerate the development of memristors in neuromorphic systems.
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As an attractive prototype for neuromorphic computing, the difficultly attained three-terminal platforms have specific advantages in implementing the brain-inspired functions. Also, in these devices, the most utilized mechanisms are confined to the electrical gate-controlled ionic migrations, which are sensitive to the device defects and stoichiometric ratio. The resultant memristive responses have fluctuant characteristics, which have adverse influences on the neural emulations. Herein, we designed a specific transistor platform with light-regulated ambipolar memory characteristics. Also, based on its gentle processes of charge trapping, we obtain the impressive memristive performances featured by smooth responses and long-term endurable characteristics. The optoelectronic samples were also fabricated on flexible substrates successfully. Interestingly, based on the optoelectronic signals of the flexible devices, we endow the desirable optical processes with the brain-inspired emulations. We can flexibly emulate the light-inspired learning-memory functions in a synapse and further devise the advanced synapse array. More importantly, through this versatile platform, we investigate the mutual regulation of excitation and inhibition and implement their sensitive-mode transformations and the homeostasis property, which is conducive to ensuring the stability of overall neural activity. Furthermore, our flexible optoelectronic platform achieves high classification accuracy when implemented in artificial neural network simulations. This work demonstrates the advantages of the optoelectronic platform in implementing the significant brain-inspired functions and provides an insight into the future integration of visible sensing in flexible optoelectronic transistor platforms.
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In situ fabrication of macroscale ordered monolayers of nanoparticles (NPs) on targeted substrates is highly desirable for precision electronic and optical devices, while it remains a great challenge. In this study, a solution is provided to address this challenge by developing a colloidal ink formulation and employing the direct-ink-writing (DIW) technique, where on-demand delivery of ink at a targeted location and directional evaporation with controllable rate are leveraged to precisely guide the deposition of polystyrene-grafted gold NPs (Au@PS NPs) into a macroscale monolayer with an ordered Au NP array embedded in a PS thin film. A 2D steady-state diffusion-controlled evaporation model, which explains the parameter dependence of the experimental results and gives semiquantitative agreement with the experimental evaporation kinetics is proposed. The ordered monolayer is used as both nanocrystal floating gates and the tunneling layer for nonvolatile memory devices. It shows significantly enhanced performance compared with a disordered NP film prepared by spin coating. This approach allows for fine control of NP self-assembly to print macroscaleordered monolayers directly onto substrates, which has great promise for application in broad fields, including microelectronic and photoelectronic devices, sensors, and functional coatings.
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The addition of CaF2@SiO2 and SiC whiskers to ceramic tools can improve their flexural strength and fracture toughness, reduce surface damage, and improve their cutting performance. The cutting experiments showed that under the same cutting conditions, the surface roughness of the workpiece processed with the Al2O3/TiC/SiC/CaF2@SiO2 (ATSC10) tool was significantly lower than that of the workpiece processed with the Al2O3/TiC/ SiC (ATS) tool. Additionally, the main cutting force and cutting temperature when cutting with the ATSC10 tool were lower by 30 and 31.7%, respectively. These results were attributed to the precipitation of CaF2 from the nanocoated particles during cutting and the formation of a uniform and continuous lubricating film on the surface of the tool. The wear on the front surface of the ATS tool was mainly adhesive, and that on the back tool surface was mainly abrasive. For ATSC10, the main forms of wear on the tool front surface were adhesive and abrasive, whereas the main form of wear on the tool back surface was abrasive with slight adhesive wear. The addition of nano-coated particles and whiskers improved the mechanical properties of the cutting tool while maintaining good cutting performance.
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Herein, we report a feasible molecular design of the binuclear clusters featuring the n-p-n heterojunction of biligand-sandwiched inorganic units, which can be used as the effective charge trapper in ambipolar transistor memories with the large memory windows and the energy-saving operation. We found that the hole confinement on the p-type inorganic units is enhanced by spatial electronic anisotropy provided by the peripheral n-type organic phosphine ligands. The steric hindrance of the coordination sites, the insulating effect of the carbon-phosphorous single bonds and the parallel dual-ligand coordination mode jointly elongate the interunit distances to nanometer scale and restrain the intramolecular electronic communications, leading to the tunable and reliable charge trapping. Our results show that the spatial effect is crucial to further amplifying the electronic differences between organic and inorganic units for function enhancement.
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Neural systems can selectively filter and memorize spatiotemporal information, thus enabling high-efficient information processing. Emulating such an exquisite biological process in electronic devices is of fundamental importance for developing neuromorphic architectures with efficient in situ edge/parallel computing, and probabilistic inference. Here a novel multifunctional memristor is proposed and demonstrated based on metalloporphyrin/oxide hybrid heterojunction, in which the metalloporphyrin layer allows for dual electronic/ionic transport. Benefiting from the coordination-assisted ionic diffusion, the device exhibits smooth, gradual conductive transitions. It is shown that the memristive characteristics of this hybrid system can be modulated by altering the metal center for desired metal-oxygen bonding energy and oxygen ions migration dynamics. The spike voltage-dependent plasticity stemming from the local/extended movement of oxygen ions under low/high voltage is identified, which permits potentiation and depression under unipolar different positive voltages. As a proof-of-concept demonstration, memristive arrays are further built to emulate the signal filtering function of the biological visual system. This work demonstrates the ionic intelligence feature of metalloporphyrin and paves the way for implementing efficient neural-signal analysis in neuromorphic hardware.
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Cutting heat conduction undergoes three stages that include intensity transient-state, transient-state, and steady-states. Especially during machining with coated cutting tools, in the conduction process, cutting heat needs to pass through a few micron thick coatings and then flow into the tool body. This heat conduction presents typical non-Fourier heat conduction characteristics. This paper focuses on the cutting temperature in transient heat conduction with a coated tool. A new analytical model to characterize the thermal shock based on the non-Fourier heat conduction was proposed. The distribution of cutting temperature in mono-layer coated tools during the machining was then illustrated. The cutting temperature distribution predicted by the Fourier heat conduction model was employed to compare with that by non-Fourier heat conduction in order to reveal the non-Fourier heat conduction effect in transient heat conduction. The results show that the transient heat conduction analytical model is more suitable for the intensity transient-state and transient-state in the process of cutting heat conduction.
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We demonstrated a facile yet effective strategy for self-assembly of polymer end-tethered gold nanorods (GNRs) into tunable two-dimensional (2D) arrays with the assistance of supramolecules of hydrogen bonded poly(4-vinyl pyridine) (P4VP) and 3-n-pentadecylphenol (PDP). Well-ordered 2D arrays with micrometer size were obtained by rupturing the assembled supramolecular matrix with a selective solvent. The formation of long-range ordered 2D arrays during a drying process was observed via small-angle X-ray scattering. Interestingly, the packing structure of the ordered arrays strongly depends on the molecular weight (Mw) of the polymer ligands and the size of the GNRs. By increasing Mw of the polymer ligands, tilted arrays can be obtained. The average angle between GNRs and the surface normal direction of the layered 2D arrays changes from 0 to 37° with the increase in Mw of the polymer ligands. A mechanism for assembly behavior of dumbbell shapes with a soft shell structure has been proposed. The resulting GNR arrays with different orientations showed anisotropic surface-enhanced Raman scattering (SERS) performance. We showed that the vertically ordered GNR arrays exhibited â¼3 times higher SERS signals than the tilt ordered arrays. The results prove that the polymer end-tethered GNRs can be used as a building block for preparing the tilted 2D arrays with tunable physicochemical properties, which could have a wide range of potential applications in photonics, electronics, plasmonics, etc.
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In this paper, the Voronoimosaic model and the cohesive element method were used to simulate crack propagation in the microstructure of alumina/graphene composite ceramic tool materials. The effects of graphene characteristic size and volume content on the crack propagation behavior of microstructure model of alumina/graphene composite ceramics under different interfacial bonding strength were studied. When the phase interface is weak, the average energy release rate is the highest as the short diameter of graphene is 10-50 nm and the long diameter is 1600-2000 nm. When the phase interface is strong, the average energy release rate is the highest as the short diameter of graphene is 50-100 nm and the long diameter is 800-1200 nm. When the volume content of graphene is 0.50 vol.%, the average energy release rate reaches the maximum. When the velocity load is 0.005 m s-1, the simulation result is convergent. It is proven that the simulation results are in good agreement with the experimental phenomena.