Enhanced Safety in Autonomous Driving: Integrating a Latent State Diffusion Model for End-to-End Navigation.

Ensuring safety in autonomous driving is crucial for effective motion planning and navigation. However, most end-to-end planning methodologies lack sufficient safety measures. This study tackles this issue by formulating the control optimization problem in autonomous driving as Constrained Markov Decision Processes (CMDPs). We introduce an innovative, model-based approach for policy optimization, employing a conditional Value-at-Risk (VaR)-based soft actor-critic (SAC) to handle constraints in complex, high-dimensional state spaces. Our method features a worst-case actor to ensure strict compliance with safety requirements, even in unpredictable scenarios. The policy optimization leverages the augmented Lagrangian method and leverages latent diffusion models to forecast and simulate future trajectories. This dual strategy ensures safe navigation through environments and enhances policy performance by incorporating distribution modeling to address environmental uncertainties. Empirical evaluations conducted in both simulated and real environments demonstrate that our approach surpasses existing methods in terms of safety, efficiency, and decision-making capabilities.

High-Yield Production of Solution-Processed Highly Robust Organic Artificial Synapses by Thermal Treatments.

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.

Double C-H Amination of Naphthylamine Derivatives by the Cross-Dehydrogenation Coupling Reaction.

A high-efficiency tandem process has been developed for the formation of two C-N bonds through a cross-dehydrogenative coupling (CDC) amination of spiro[acridine-9,9'-fluorene]s (SAFs) with amines. This method offers a strategically innovative and atom-economical approach to obtaining diamine-substituted SAFs. Notably, the approach eliminates the need for metal catalysts and other additives, relying solely on O2 as the oxidant. A self-activation mechanism has been proposed to elucidate the effective double amination in the CDC process.

Negative Photoconductivity Transistors for Visuomorphic Computing.

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.

Dual-Adaptive Heterojunction Synaptic Transistors for Efficient Machine Vision in Harsh Lighting Conditions.

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.

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-band gap 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 for 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 reported small molecules. A novel supramolecular system formed from 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.

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.

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.

Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control.

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

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.

Oxidation-boosted charge trapping in ultra-sensitive van der Waals materials for artificial synaptic features.

Exploitation of the oxidation behaviour in an environmentally sensitive semiconductor is significant to modulate its electronic properties and develop unique applications. Here, we demonstrate a native oxidation-inspired InSe field-effect transistor as an artificial synapse in device level that benefits from the boosted charge trapping under ambient conditions. A thin InOx layer is confirmed under the InSe channel, which can serve as an effective charge trapping layer for information storage. The dynamic characteristic measurement is further performed to reveal the corresponding uniform charge trapping and releasing process, which coincides with its surface-effect-governed carrier fluctuations. As a result, the oxide-decorated InSe device exhibits nonvolatile memory characteristics with flexible programming/erasing operations. Furthermore, an InSe-based artificial synapse is implemented to emulate the essential synaptic functions. The pattern recognition capability of the designed artificial neural network is believed to provide an excellent paradigm for ultra-sensitive van der Waals materials to develop electric-modulated neuromorphic computation architectures.