PBDB-T/Pentacene-Based Organic Optoelectronic Synaptic Transistor with Adjustable Critical Flicker Fusion Frequency for Dynamic Vision

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.

Retina-inspired organic neuromorphic vision sensor with polarity modulation for decoding light information

The neuromorphic vision sensor (NeuVS), which is based on organic field-effect transistors (OFETs), uses polar functional groups (PFGs) in polymer dielectrics as interfacial units to control charge carriers. However, the mechanism of modulating charge transport on basis of PFGs in devices is unclear. Here, the carboxyl group is introduced into polymer dielectrics in this study, and it can induce the charge transfer process at the semiconductor/dielectric interfaces for effective carrier transport, giving rise to the best device mobility up to 20 cm2 V-1 s-1 at a low operating voltage of -1 V. Furthermore, the polarity modulation effect could further increase the optical figures of merit in NeuVS devices by at least an order of magnitude more than the devices using carboxyl group-free polymer dielectrics. Additionally, devices containing carboxyl groups improved image sensing for light information decoding with 52 grayscale signals and memory capabilities at an incredibly low power consumption of 1.25 fJ/spike. Our findings provide insight into the production of high-performance polymer dielectrics for NeuVS devices.

Tetrachromatic vision-inspired neuromorphic sensors with ultraweak ultraviolet detection

Sensing and recognizing invisible ultraviolet (UV) light is vital for exploiting advanced artificial visual perception system. However, due to the uncertainty of the natural environment, the UV signal is very hard to be detected and perceived. Here, inspired by the tetrachromatic visual system, we report a controllable UV-ultrasensitive neuromorphic vision sensor (NeuVS) that uses organic phototransistors (OPTs) as the working unit to integrate sensing, memory and processing functions. Benefiting from asymmetric molecular structure and unique UV absorption of the active layer, the as fabricated UV-ultrasensitive NeuVS can detect 370 nm UV-light with the illumination intensity as low as 31 nW cm^-2, exhibiting one of the best optical figures of merit in UV-sensitive neuromorphic vision sensors. Furthermore, the NeuVS array exbibits good image sensing and memorization capability due to its ultrasensitive optical detection and large density of charge trapping states. In addition, the wavelength-selective response and multi-level optical memory properties are utilized to construct an artificial neural network for extract and identify the invisible UV information. The NeuVS array can perform static and dynamic image recognition from the original color image by filtering red, green and blue noise, and significantly improve the recognition accuracy from 46 to 90%.

A BN-Doped U-Shaped Heteroacene as a Molecular Floating Gate for Ambipolar Charge Trapping Memory

Two wide-bandgap U-shaped polycyclic aromatic hydrocarbons with/without boron and nitrogen (BN-) doping (BN-1 and C-1) were synthesized to tune the electronic features to suit the performance requirements in organic field-effect transistor memory (OFET-NVM). The chemical structures were characterized by scanning tunneling microscopy and single crystal diffraction. Owing to the electron donor effect of N and the high electron affinity of B, the BN-1-based OFET-NVM displays large ambipolar memory windows and an enhanced charge storage density compared to C-1 and most of the reported small molecules. A novel supramolecular system formed via BN-1 and PMMA contributes to fabricating uniform films with homogeneous microstructures, which serve as a two-in-one tunnelling dielectric and charge trapping layer to realize long-term charge retention and reliable endurance. Our results demonstrate that both BN doping and supramolecular engineering are crucial for the charge trapping of OFET-NVM.

Pseudo-transistors for emerging neuromorphic electronics

Artificial synaptic devices are the cornerstone of neuromorphic electronics. The development of new artificial synaptic devices and the simulation of biological synaptic computational functions are important tasks in the field of neuromorphic electronics. Although two-terminal memristors and three-terminal synaptic transistors have exhibited significant capabilities in the artificial synapse, more stable devices and simpler integration are needed in practical applications. Combining the configuration advantages of memristors and transistors, a novel pseudo-transistor is proposed. Here, recent advances in the development of pseudo-transistor-based neuromorphic electronics in recent years are reviewed. The working mechanisms, device structures and materials of three typical pseudo-transistors, including tunneling random access memory (TRAM), memflash and memtransistor, are comprehensively discussed. Finally, the future development and challenges in this field are emphasized.

A Reconfigurable Optoelectronic Synaptic Transistor with Stable Zr-CsPbI3 Nanocrystals for Visuomorphic Computing

Reconfigurable phototransistor memory attracts considerable attention for adaptive visuomorphic computing, with highly efficient sensing, memory, and processing functions integrated onto a single device. However, developing reconfigurable phototransistor memory remains a challenge due to the lack of an all-optically controlled transition between short-term plasticity (STP) and long-term plasticity (LTP). Herein, an air-stable Zr-CsPbI₃ perovskite nanocrystal (PNC)-based phototransistor memory is designed, which is capable of broadband photoresponses. Benefitting from the different electron capture ability of Zr-CsPbI₃ PNCs to 650 and 405 nm light, an artificial synapse and non-volatile memory can be created on-demand and quickly reconfigured within a single device for specific purposes. Owing to the optically reconfigurable and wavelength-aware operation between STP and LTP modes, the integrated blue feature extraction and target recognition can be demonstrated in a homogeneous neuromorphic vision sensor array. This work suggests a new way in developing perovskite optoelectronic transistors for highly efficient in-sensor computing.

Photoexcitation dynamics and energy engineering in supramolecular doping of organic conjugated molecules

Doping and blending strategies are crucial means to precisely control the excited states and energy level in conjugated molecular systems. However, effective models and platforms are rarely proposed to systematically explore the effects of the formation of trapped doped centers on heterogeneous structures, energy level and ultrafast photophysical process. Herein, for deeply understanding the impact of molecular doping in film energy levels and photoexcitation dynamics, we set a supramolecular N-B coordination composed by the conjugated molecules of pyridine functionalized diarylfluorene (host material), named as ODPF-Phpy and ODPF-(Phpy)₂, and the molecule of tris(perfluorophenyl)borane (BCF) (guest material). The generation of the molecular-level coordination bond increased the binding energy of N atoms and tuned the band-gap, leading to a new fluorescent emission center with longer excitation wavelength and emission wavelength. The intermolecular Förster resonance energy transfer (FRET) in blending films make it present inconsistent fluorescent behaviors compared to that in solution. The charge transfer (CT) state of N-B coordinated compounds and the changed dielectric constant of blending films resulted in a large PL spectra red-shift with the increased dopant ratio, causing a wide-tunable fluorescent color. The excited state behaviors of two compounds in blending system was further investigated by the transient absorption (TA) spectroscopy. Finally, we found supramolecular coordination blending can effectively improve the films' photoluminescence quantum yield (PLQY) and conductivity. We believe this exploration in the internal coordination mechanisms would deepen the insights about doped semiconductors and is helpful in developing novel high-efficient fluorescent systems.

Low-power flexible organic memristor based on PEDOT:PSS/pentacene heterojunction for artificial synapse

Organic synaptic memristors are of considerable interest owing to their attractive characteristics and potential applications to flexible neuromorphic electronics. In this work, an organic type-II heterojunction consisting of poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS) and pentacene was adopted for low-voltage and flexible memristors. The conjugated polymer PEDOT:PSS serves as the flexible resistive switching (RS) layer, while the thin pentacene layer plays the role of barrier adjustment. This heterojunction enabled the memristor device to be triggered with low-energy RS operations (V < ± 1.0 V and I < 9.0 μA), and simultaneously providing high mechanical bending stability (bending radius of ≈2.5 mm, bending times = 1,000). Various synaptic properties have been successfully mimicked. Moreover, the memristors presented good potentiation/depression stability with a low cycle-to-cycle variation (CCV) of less than 8%. The artificial neural network consisting of this flexible memristor exhibited a high accuracy of 89.0% for the learning with MNIST data sets, even after 1,000 tests of 2.5% stress-strain. This study paves the way for developing low-power and flexible synaptic devices utilizing organic heterojunctions.

Cross-Scale Synthesis of Organic High-k Semiconductors Based on Spiro-Gridized Nanopolymers

High dielectric constants in organic semiconductors have been identified as a central challenge for the improvement in not only piezoelectric, pyroelectric, and ferroelectric effects but also photoelectric conversion efficiency in OPVs, carrier mobility in OFETs, and charge density in charge-trapping memories. Herein, we report an ultralong persistence length (l _p ≈ 41 nm) effect of spiro-fused organic nanopolymers on dielectric properties, together with excitonic and charge carrier behaviors. The state-of-the-art nanopolymers, namely, nanopolyspirogrids (NPSGs), are synthesized via the simple cross-scale Friedel-Crafts polygridization of A₂B₂-type nanomonomers. The high dielectric constant (k = 8.43) of NPSG is firstly achieved by locking spiro-polygridization effect that results in the enhancement of dipole polarization. When doping into a polystyrene-based dielectric layer, such a high-k feature of NPSG increases the field-effect carrier mobility from 0.20 to 0.90 cm² V^-1 s^-1 in pentacene OFET devices. Meanwhile, amorphous NPSG film exhibits an ultralow energy disorder (<50 meV) for an excellent zero-field hole mobility of 3.94 × 10^-3 cm² V^-1 s^-1, surpassing most of the amorphous π-conjugated polymers. Organic nanopolymers with high dielectric constants open a new way to break through the bottleneck of efficiency and multifunctionality in the blueprint of the fourth-generation semiconductors.

Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing

Neuromorphic computing holds promise for building next-generation intelligent systems in a more energy-efficient way than the conventional von Neumann computing architecture. Memristive hardware, which mimics biological neurons and synapses, offers high-speed operation and low power consumption, enabling energy- and area-efficient, brain-inspired computing. Here, recent advances in memristive materials and strategies that emulate synaptic functions for neuromorphic computing are highlighted. The working principles and characteristics of biological neurons and synapses, which can be mimicked by memristive devices, are presented. Besides device structures and operation with different external stimuli such as electric, magnetic, and optical fields, how memristive materials with a rich variety of underlying physical mechanisms can allow fast, reliable, and low-power neuromorphic applications is also discussed. Finally, device requirements are examined and a perspective on challenges in developing memristive materials for device engineering and computing science is given.

Signal Filtering Enabled by Spike Voltage-Dependent Plasticity in Metalloporphyrin-Based Memristors

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.

Highly sensitive detection of caspase-3 activity based on peptide-modified organic electrochemical transistor biosensors

Caspase-3 is an important proteolytic enzyme that cleaves several key substrates in apoptotic processes, resulting in DNA fragmentation, the degradation of nuclear proteins, and the formation of apoptotic bodies. However, it is challenging to detect caspase-3 due to its low expression levels in cells. In this work, organic electrochemical transistors (OECTs) are used in the detection of caspase-3 for the first time. A self-assembled monolayer of the peptide is bonded to the Au gate electrode (GE) of an OECT via gold-sulphur bonds. It is found that the transfer curve of the transistor shifts to a lower gate voltage due to the modulation of the surface potential of the GE by the peptides. Then, the device is used in the detection of caspase-3 in aqueous solutions and shows a detection limit of 0.1 pM. Due to its high sensitivity, the device can detect caspase-3 in induced apoptotic HeLa cells. The system is low-cost, conveniently used and applicable for biological and medical monitoring where caspase-3 detection and quantification are required.

A Monochloro Copper Phthalocyanine Memristor with High-Temperature Resilience for Electronic Synapse Applications

Memristors are considered to be one of the most promising device concepts for neuromorphic computing, in particular thanks to their highly tunable resistive states. To realize neuromorphic computing architectures, the assembly of large memristive crossbar arrays is necessary, but is often accompanied by severe heat dispassion. Organic materials can be tailored with on-demand electronic properties in the context of neuromorphic applications. However, such materials are more susceptible to heat, and detrimental effects such as thermally induced degradation directly lead to failure of device operation. Here, an organic memristive synapse formed of monochloro copper phthalocyanine, which remains operational and capable of memristive switching at temperatures as high as 300 °C in ambient air without any encapsulation, is demonstrated. The change in the electrical conductance is found to be a result of ion movement, closely resembling what takes place in biological neurons. Furthermore, the high viability of this approach is showcased by demonstrating flexible memristors with stable switching behaviors after repeated mechanical bending as well as organic synapses capable of emulating a trainable and reconfigurable memristor array for image information processing. The results set a precedent for thermally resilient organic synapses to impact organic neuromorphic devices in progressing their practicality.

Role and mechanism of action of butyrate in atherosclerotic diseases: a review

Butyrate is a bioactive molecule produced by the intestinal flora and plays a major role in a variety of inflammatory diseases. Increasing evidence indicates that butyrate can regulate the occurrence and development of atherosclerosis (AS). Coincidentally, it reduces hyperlipidemia and hyperglycemia, which are major risk factors of AS. However, the mechanism by which butyrate regulates the development of AS remains unclear. In this article, we review the effect of butyrate treatment on AS with a focus on the mechanisms of butyrate-mediated modulation of several atherosclerotic processes. These include the improvement of monocyte-endothelial interactions, macrophage lipid accumulation, smooth muscle cell proliferation and migration, and lymphocyte differentiation and function. The existing research indicates that butyrate treatment may be a potentially effective strategy for the prevention of AS. Identity and underlying mechanisms of the molecular pathways of these interactions should be explored in the future to counter AS effectively.

Novel clinicopathological characteristics differentiate dementia with Lewy bodies from Parkinson's disease dementia

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) known as Lewy body dementias have overlapping clinical and neuropathological features. Neuropathology in both includes combination of Lewy body and Alzheimer's disease (AD) pathology. Cerebral amyloid angiopathy (CAA), often seen in AD, is increasingly recognized for its association with dementia.

AIMS

This study investigated clinical and neuropathological differences between DLB and PDD.

METHODS

52 PDD and 16 DLB cases from the Queen Square Brain Bank (QSBB) for Neurological disorders were included. Comprehensive clinical data of motor and cognitive features were obtained from medical records. Neuropathological assessment included examination of CAA, Lewy body and AD pathology.

RESULTS

CAA was more common in DLB than in PDD (P = 0.003). The severity of CAA was greater in DLB than in PDD (P = 0.009), with significantly higher CAA scores in the parietal lobe (P = 0.043), and the occipital lobe (P = 0.008), in DLB than in PDD. The highest CAA scores were observed in cases with APOE ε4/4 and ε2/4. Survival analysis showed worse prognosis in DLB, as DLB reached each clinical milestone sooner than PDD. Absence of dyskinesia in DLB is linked to the significantly lower lifetime cumulative dose of levodopa in comparison with PDD.

CONCLUSIONS

This is the first study which identified prominent concurrent CAA pathology as a pathological substrate of DLB. More prominent CAA and rapid disease progression as measured by clinical milestones distinguish DLB from PDD.

Three-dimensional printing of metals for biomedical applications

Three-dimensional (3D) printing technology has received great attention in the past decades in both academia and industry because of its advantages such as customized fabrication, low manufacturing cost, unprecedented capability for complex geometry, and short fabrication period. 3D printing of metals with controllable structures represents a state-of-the-art technology that enables the development of metallic implants for biomedical applications. This review discusses currently existing 3D printing techniques and their applications in developing metallic medical implants and devices. Perspective about the current challenges and future directions for development of this technology is also presented.

Review: Clinical, neuropathological and genetic features of Lewy body dementias

Lewy body dementias are the second most common neurodegenerative dementias after Alzheimer's disease and include dementia with Lewy bodies and Parkinson's disease dementia. They share similar clinical and neuropathological features but differ in the time of dementia and parkinsonism onset. Although Lewy bodies are their main pathological hallmark, several studies have shown the emerging importance of Alzheimer's disease pathology. Clinical amyloid-β imaging using Pittsburgh Compound B (PiB) supports neuropathological studies which found that amyloid-β pathology is more common in dementia with Lewy bodies than in Parkinson's disease dementia. Nevertheless, other co-occurring pathologies, such as cerebral amyloid angiopathy, TDP-43 pathology and synaptic pathology may also influence the development of neurodegeneration and dementia. Recent genetic studies demonstrated an important role of APOE genotype and other genes such as GBA and SNCA which seem to be involved in the pathophysiology of Lewy body dementias. The aim of this article is to review the main clinical, neuropathological and genetic aspects of dementia with Lewy bodies and Parkinson's disease dementia. This is particularly relevant as future management for these two conditions may differ.

Abstract P1-08-25: Withdrawn

This abstract was withdrawn by the authors.

Citation Format: Zhao H, Gong Y, Ye F, Ling H, Hu X. Withdrawn [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-08-25.

[A meta-analysis of the effect of occupational exposure to 1-bromopropane on workers' nerve conduction velocity]

Objective: To analysis the occupational exposure to 1-bromopropane on the worker's nerve conduc-tion velocity. Methods: To PubMed, Wanfang, VIP, Chinese Journal Full-text Database (CNKI) and other databases as a data source, searched and screened database to October 2017 on occupational exposure to 1-bromopropane workers on the role of nerve conduction in the paper. According to inclusion and exclusion criteria, we screened literatures, extracted data and evaluated the quality of the included studies, using RevMan5.3 software to test the heterogeneity of the results and us-ing the corresponding mathematical model for data combination analysis. Results: A total of 5 articles were included in the literature. The results showed that the tibial nerve MCV of workers in the 1-bromopropane exposure group was slower than that in the control group (SMD=-0.47,95%CI=-0.70~-0.24) , the difference was statistically significant (Z=4.06, P<0.01). The tibial nerve DL of the exposure group was more prolonged than that of the control group (SMD=0.35,95%CI=0.00~0.69) , with a statistically significant difference (Z=1.99, P=0.05). The sural nerve SCV of the exposure group was slower than that of the control group (SMD=-0.47, 95%CI=-0.78~-0.15), with a statistically significant difference (Z=2.88,P<0.01). Conclusion: Occupational exposure to 1-bromopropane may have an effect on the worker's nerve conduction ve-locity.It's necessary to do broader and deeper neurotoxicity studies about 1-bromopropane.

A Centimeter-Scale Inorganic Nanoparticle Superlattice Monolayer with Non-Close-Packing and its High Performance in Memory Devices

Due to the near-field coupling effect, non-close-packed nanoparticle (NP) assemblies with tunable interparticle distance (d) attract great attention and show huge potential applications in various functional devices, e.g., organic nano-floating-gate memory (NFGM) devices. Unfortunately, the fabrication of device-scale non-close-packed 2D NPs material still remains a challenge, limiting its practical applications. Here, a facile yet robust "rapid liquid-liquid interface assembly" strategy is reported to generate a non-close-packed AuNP superlattice monolayer (SM) on a centimeter scale for high-performance pentacene-based NFGM. The d and hence the surface plasmon resonance spectra of SM can be tailored by adjusting the molecular weight of tethered polymers. Precise control over the d value allows the successful fabrication of photosensitive NFGM devices with highly tunable performances from short-term memory to nonvolatile data storage. The best performing nonvolatile memory device shows remarkable 8-level (3-bit) storage and a memory ratio over 10⁵ even after 10 years compared with traditional devices with a AuNP amorphous monolayer. This work provides a new opportunity to obtain large area 2D NPs materials with non-close-packed structure, which is significantly meaningful to microelectronic, photovoltaics devices, and biochemical sensors.

Topic-based hierarchical Bayesian linear regression models for niche items recommendation

A vital research concern for a personalised recommender system is to target items in the long tail. Studies have shown that sales of the e-commerce platform possess a long-tail character, and niche items in the long tail are challenging to be involved in the recommendation list. Since niche items are defined by the niche market, which is a small market segment, traditional recommendation algorithms focused more on popular items promotion and they do not apply to the niche market. In this article, we aim to find the best users for each niche item and proposed a topic-based hierarchical Bayesian linear regression model for niche item recommendation. We first identify niche items and build niche item subgroups based on descriptive information of items. Moreover, we learn a hierarchical Bayesian linear regression model for each niche item subgroup. Finally, we predict the relevance between users and niche items to provide recommendations. We perform a series of validation experiments on Yahoo Movies dataset and compare the performance of our approach with a set of representative baseline recommender algorithms. The result demonstrates the superior performance of our recommendation approach for niche items.

Evolving concepts of chronic traumatic encephalopathy as a neuropathological entity

Chronic traumatic encephalopathy (CTE) is a long-term neurodegenerative consequence of repetitive head impacts which can only be definitively diagnosed in post-mortem. Recently, the consensus neuropathological criteria for the diagnosis of CTE was published requiring the presence of the accumulation of abnormal tau in neurons and astroglia distributed around small blood vessels at the depths of cortical sulci in an irregular pattern as the mandatory features. The clinical diagnosis and antemortem prediction of CTE pathology remain challenging if not impossible due to the common co-existing underlying neurodegenerative pathologies and the lack of specific clinical pointers and reliable biomarkers. This review summarizes the historical evolution of CTE as a neuropathological entity and highlights the latest advances and future directions of research studies on the topic of CTE.

Solution-Processed Wide-Bandgap Organic Semiconductor Nanostructures Arrays for Nonvolatile Organic Field-Effect Transistor Memory

In this paper, the development of organic field-effect transistor (OFET) memory device based on isolated and ordered nanostructures (NSs) arrays of wide-bandgap (WBG) small-molecule organic semiconductor material [2-(9-(4-(octyloxy)phenyl)-9H-fluoren-2-yl)thiophene]3 (WG₃ ) is reported. The WG₃ NSs are prepared from phase separation by spin-coating blend solutions of WG₃ /trimethylolpropane (TMP), and then introduced as charge storage elements for nonvolatile OFET memory devices. Compared to the OFET memory device with smooth WG₃ film, the device based on WG₃ NSs arrays exhibits significant improvements in memory performance including larger memory window (≈45 V), faster switching speed (≈1 s), stable retention capability (>10⁴ s), and reliable switching properties. A quantitative study of the WG₃ NSs morphology reveals that enhanced memory performance is attributed to the improved charge trapping/charge-exciton annihilation efficiency induced by increased contact area between the WG₃ NSs and pentacene layer. This versatile solution-processing approach to preparing WG₃ NSs arrays as charge trapping sites allows for fabrication of high-performance nonvolatile OFET memory devices, which could be applicable to a wide range of WBG organic semiconductor materials.

Controllable Organic Resistive Switching Achieved by One-Step Integration of Cone-Shaped Contact

Conductive filaments (CFs)-based resistive random access memory possesses the ability of scaling down to sub-nanoscale with high-density integration architecture, making it the most promising nanoelectronic technology for reclaiming Moore's law. Compared with the extensive study in inorganic switching medium, the scientific challenge now is to understand the growth kinetics of nanoscale CFs in organic polymers, aiming to achieve controllable switching characteristics toward flexible and reliable nonvolatile organic memory. Here, this paper systematically investigates the resistive switching (RS) behaviors based on a widely adopted vertical architecture of Al/organic/indium-tin-oxide (ITO), with poly(9-vinylcarbazole) as the case study. A nanoscale Al filament with a dynamic-gap zone (DGZ) is directly observed using in situ scanning transmission electron microscopy (STEM) , which demonstrates that the RS behaviors are related to the random formation of spliced filaments consisting of Al and oxygen vacancy dual conductive channels growing through carbazole groups. The randomicity of the filament formation can be depressed by introducing a cone-shaped contact via a one-step integration method. The conical electrode can effectively shorten the DGZ and enhance the localized electric field, thus reducing the switching voltage and improving the RS uniformity. This study provides a deeper insight of the multiple filamentary mechanisms for organic RS effect.

High-Performance Nonvolatile Organic Field-Effect Transistor Memory Based on Organic Semiconductor Heterostructures of Pentacene/P13/Pentacene as Both Charge Transport and Trapping Layers

Nonvolatile organic field-effect transistor (OFET) memory devices based on pentacene/N,N'-ditridecylperylene-3,4,9,10-tetracarboxylic diimide (P13)/pentacene trilayer organic heterostructures have been proposed. The discontinuous n-type P13 embedded in p-type pentacene layers can not only provide electrons in the semiconductor layer that facilitates electron trapping process; it also works as charge trapping sites, which is attributed to the quantum well-like pentacene/P13/pentacene organic heterostructures. The synergistic effects of charge trapping in the discontinuous P13 and the charge-trapping property of the poly(4-vinylphenol) (PVP) layer remarkably improve the memory performance. In addition, the trilayer organic heterostructures have also been successfully applied to multilevel and flexible nonvolatile memory devices. The results provide a novel design strategy to achieve high-performance nonvolatile OFET memory devices and allow potential applications for different combinations of various organic semiconductor materials in OFET memory.

A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks

In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced parameters and protein concentrations similar to the original RNN system. Results thus demonstrated the reliability of the proposed RNN method for modelling relatively large networks by modularisation for practical settings. Advantages of the method are its ability to represent accurate continuous system dynamics and ease of: parameter estimation through training with data from a practical setting, model analysis (40% faster than ODE), fine tuning parameters when more data are available, sub-model extension when new elements and/or interactions come to light and model expansion with addition of sub-models.

One-step preparation of conjugated homopolymer sub-microspheres via a controllable supramolecular approach toward optoelectronic applications

Supramolecular PPFOH-based conjugated polymer sub-microspheres (CPSMs) are constructed via “one step” solvent evaporation induced interface self-assembly (SEIS), which pave a way to construct colloidal crystal and light-emitting diodes.

Long-Term Homeostatic Properties Complementary to Hebbian Rules in CuPc-Based Multifunctional Memristor

Most simulations of neuroplasticity in memristors, which are potentially used to develop artificial synapses, are confined to the basic biological Hebbian rules. However, the simplex rules potentially can induce excessive excitation/inhibition, even collapse of neural activities, because they neglect the properties of long-term homeostasis involved in the frameworks of realistic neural networks. Here, we develop organic CuPc-based memristors of which excitatory and inhibitory conductivities can implement both Hebbian rules and homeostatic plasticity, complementary to Hebbian patterns and conductive to the long-term homeostasis. In another adaptive situation for homeostasis, in thicker samples, the overall excitement under periodic moderate stimuli tends to decrease and be recovered under intense inputs. Interestingly, the prototypes can be equipped with bio-inspired habituation and sensitization functions outperforming the conventional simplified algorithms. They mutually regulate each other to obtain the homeostasis. Therefore, we develop a novel versatile memristor with advanced synaptic homeostasis for comprehensive neural functions.