High-Performance Quantum Dot Near-Infrared Upconversion Devices Based on the Hole-Only Injection Mechanidsm.

Colloidal quantum dot (CQD) near-infrared (NIR) upconversion devices (UCDs) can directly convert low-energy NIR light into higher energy visible light without the need for additional integrated circuits, which is advantageous for NIR sensing and imaging. However, the state-of-the-art CQD NIR upconverters still face challenges, including high turn-on voltage (), low photon-to-photon (p-p) upconversion efficiency, and low current on/off ratio, primarily due to inherent limitations in the device structure and operating mechanisms. In this work, we developed a CQD NIR UCD based on a hole-only injection mechanism.

Uncovering the Performance Enhancing Mechanism of Methanesulfonate Ligands in Perovskite Quantum Dots for Light-Emitting Devices.

Perovskite quantum dots (PQDs) have attracted more and more attention in light-emitting diode (LED) devices due to their outstanding photoelectric properties. Surface ligands not only enable size control of quantum dots but also enhance their optoelectronic performance. However, the efficiency of exciton recombination in PQDs is often hindered by the desorption dynamics of surface ligands, leading to suboptimal electrical performance.

Advancements in Nanowire-Based Devices for Neuromorphic Computing: A Review.

Neuromorphic computing, inspired by the highly interconnected and energy-efficient way the human brain processes information, has emerged as a promising technology for post-Moore's law era. This emerging technology can emulate the structures and the functions of the human brain and is expected to overcome the fundamental limitation of the current von Neumann computing architecture. Neuromorphic devices stand out as the key components of future electronic systems, exhibiting potential in shaping the landscape of neuromorphic computing.

High-Performance, High-Resolution Quantum Dot Light-Emitting Diodes with Self-Assembly Single-Molecular Interface Modification.

With the development of near-eye displays, the demands for display resolution and performance are increasing. Quantum dot performance is virtually independent of pixel size, making it an efficient way to display ultrahigh resolution. However, the low efficiency of high-resolution quantum dot devices has been an urgent technical bottleneck to be solved.

Perovskite-Doped Modulated Color-Selective Photosynaptic Transistors for Target Object Recognition.

The processing of multicolor noisy images in visual neuromorphic devices requires selective absorption at specific wavelengths; however, it is difficult to achieve this because the spectral absorption range of the device is affected by the type of material. Surprisingly, the absorption range of perovskite materials can be adjusted by doping. Herein, a CdCl co-doped CsPbBr nanocrystal-based photosensitive synaptic transistor (PST) is reported.

Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output.

Memristor-based physical reservoir computing holds significant potential for efficiently processing complex spatiotemporal data, which is crucial for advancing artificial intelligence. However, owing to the single physical node mapping characteristic of traditional memristor reservoir computing, it inevitably induces high repeatability of eigenvalues to a certain extent and significantly limits the efficiency and performance of memristor-based reservoir computing for complex tasks. Hence, this work firstly reports an artificial light-emitting synaptic (LES) device with dual photoelectric output for reservoir computing, and a reservoir system with mixed physical nodes is proposed.

Memory-electroluminescence for multiple action-potentials combination in bio-inspired afferent nerves.

The development of optoelectronics mimicking the functions of the biological nervous system is important to artificial intelligence. This work demonstrates an optoelectronic, artificial, afferent-nerve strategy based on memory-electroluminescence spikes, which can realize multiple action-potentials combination through a single optical channel. The memory-electroluminescence spikes have diverse morphologies due to their history-dependent characteristics and can be used to encode distributed sensor signals.

Broadband beam collimation metasurface for full-color micro-LED displays.

Near-eye displays are widely recognized as a groundbreaking technological advancement with the potential to significantly impact daily life. Within the realm of near-eye displays, micro-LEDs have emerged as a highly promising technology owing to their exceptional optical performance, compact form factor, and low power consumption. However, a notable challenge in integrating micro-LEDs into near-eye displays is the efficient light collimation across a wide spectrum range.

Toward Intelligent Display with Neuromorphic Technology.

In the era of the Internet and the Internet of Things, display technology has evolved significantly toward full-scene display and realistic display. Incorporating "intelligence" into displays is a crucial technical approach to meet the demands of this development. Traditional display technology relies on distributed hardware systems to achieve intelligent displays but encounters challenges stemming from the physical separation of sensing, processing, and light-emitting modules.

Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability.

Deep neural networks have revolutionized several domains, including autonomous driving, cancer detection, and drug design, and are the foundation for massive artificial intelligence models. However, hardware neural network reports still mainly focus on shallow networks (2 to 5 layers). Implementing deep neural networks in hardware is challenging due to the layer-by-layer structure, resulting in long training times, signal interference, and low accuracy due to gradient explosion/vanishing.

Boosting the Efficiency of High-Resolution Quantum Dot Light-Emitting Devices Based on Localized Surface Plasmon Resonance.

With pixel miniaturization, the performance of high-resolution quantum dot light-emitting diodes (QLEDs) usually degrades. Considering the dimension of ultrasmall pixels, herein, a barrier architecture based on localized surface plasmon resonance (LSPR) that promotes the radiative recombination of neighboring quantum dots is rationally designed to improve the device performance. Au nanoparticles (NPs) are embedded in an insulating polymer to form a honeycomb-patterned barrier layer via the nanoimprint process.

Silver Nanowire Networks with Moisture-Enhanced Learning Ability.

The human brain possesses a remarkable ability to memorize information with the assistance of a specific external environment. Therefore, mimicking the human brain's environment-enhanced learning abilities in artificial electronic devices is essential but remains a considerable challenge. Here, a network of Ag nanowires with a moisture-enhanced learning ability, which can mimic long-term potentiation (LTP) synaptic plasticity at an ultralow operating voltage as low as 0.

Effect of polymethyl methacrylate on in situ patterning of perovskite quantum dots by inkjet printing.

The preparation of perovskite quantum dots (PQDs) using an in situ inkjet printing method is beneficial for improving the problems of aggregation and photoluminescence (PL) quenching during long-term storage. However, the stability of PQDs prepared using this method is still not ideal, and the morphology of in situ-printed patterns needs to be optimized. To address these problems, this study introduced polymethyl methacrylate (PMMA) into the process of in situ inkjet printing of PQDs and explored the effect of PMMA on the in situ patterning effect of PQDs.

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction.

Reservoir computing has attracted considerable attention due to its low training cost. However, existing neuromorphic hardware, focusing mainly on shallow-reservoir computing, faces challenges in providing adequate spatial and temporal scales characteristic for effective computing. Here, we report an ultra-short channel organic neuromorphic vertical transistor with distributed reservoir states.

Ligand-Nondestructive Direct Photolithography Assisted by Semiconductor Polymer Cross-Linking for High-Resolution Quantum Dot Light-Emitting Diodes.

The photolithographic patterning of fine quantum dot (QD) films is of great significance for the construction of QD optoelectronic device arrays. However, the photolithography methods reported so far either introduce insulating photoresist or manipulate the surface ligands of QDs, each of which has negative effects on device performance. Here, we report a direct photolithography strategy without photoresist and without engineering the QD surface ligands.

Uniformity improvement of a mini-LED backlight by a quantum-dot color conversion film with nonuniform thickness.

Mini-LED backlights energized by quantum-dot color conversion (QDCC) hold great potential for technological breakthroughs of liquid crystal displays. However, luminance uniformity issues should still be urgently solved owing to the large interval of direct-lit mini-LEDs, especially when covering with a QDCC film (QDCCF) with uniform thickness. Herein, we propose a uniformity improvement approach of mini-LED backlights by employing a QDCCF with nonuniform thickness based on the Lambertian distribution of mini-LEDs, which is demonstrated by screen-printing preparation and ray-tracing simulation.

Research on Hydrodynamic Characteristics of Electronic Paper Pixels Based on Electrowetting.

In this paper, we propose a driving waveform with a complex ramp pulse for an electrowetting display system. The relationship between the contact angle and viscosity of inks was calculated based on the fluid-motion characteristics of different viscosities. We obtained the suitable range of viscosity and voltage in the liquid-oil-solid three-phase contact display system.

Electron Oscillation-Induced Splitting Electroluminescence from Nano-LEDs for Device-Level Encryption.

Data security is a major concern in digital age, which generally relies on algorithm-based mathematical encryption. Recently, encryption techniques based on physical principles are emerging and being developed, leading to the new generation of encryption moving from mathematics to the intersection of mathematics and physics. Here, device-level encryption with ideal security is ingeniously achieved using modulation of the electron-hole radiative recombination in a GaN-light-emitting diode (LED).

Metamaterials for light extraction and shaping of micro-scale light-emitting diodes: from the perspective of one-dimensional and two-dimensional photonic crystals.

Metamaterials have attracted broad attention owing to their unique versatile micro- and nano-structures. As a kind of typical metamaterial, photonic crystals (PhCs) are capable of controlling light propagation and constraining spatial light distribution from the chip level. However, introducing metamaterial into micro-scale light-emitting diodes (µLED) still exists many unknowns to explore.

Omnidirectional color shift suppression of full-color micro-LED displays with enhanced light extraction efficiency.

The three-primary-color chip array is the most straightforward to realize full-color micro-LED displays. However, the luminous intensity distribution shows high inconsistency between the AlInP-based red micro-LED and GaN-based blue / green micro-LEDs, resulting in the issue of angular color shift with different viewing angles. This Letter analyzes the angular dependence of color difference of conventional three-primary-color micro-LEDs, and proves that the inclined sidewall with homogeneous Ag coating has a limited angular regulation effect for micro-LEDs.

A sensory memory processing system with multi-wavelength synaptic-polychromatic light emission for multi-modal information recognition.

Realizing multi-modal information recognition tasks which can process external information efficiently and comprehensively is an urgent requirement in the field of artificial intelligence. However, it remains a challenge to achieve simple structure and high-performance multi-modal recognition demonstrations owing to the complex execution module and separation of memory processing based on the traditional complementary metal oxide semiconductor (CMOS) architecture. Here, we propose an efficient sensory memory processing system (SMPS), which can process sensory information and generate synapse-like and multi-wavelength light-emitting output, realizing diversified utilization of light in information processing and multi-modal information recognition.

Structural, vibrational, photoelectrochemical, and optical properties of two-dimensional Ruddlesden-Popper perovskite BAPbI crystals.

Two-dimensional organic-inorganic hybrid Ruddlesden-Popper perovskites have attracted a lot of attention due to their unique photochemical properties and enhanced stability towards photoluminescence devices. Compared with three-dimensional materials, two-dimensional perovskites show great potential for photoelectric applications due to their tunable band gap, great excitation binding energy, and large crystal anisotropy. Although the synthesis and optical properties of BAPbI crystals have been extensively studied, the role of their microstructure in photoelectric applications, their electronic structure, and their electron-phonon interaction are still poorly understood.