Resistive memory-based zero-shot liquid state machine for multimodal event data learning.

The human brain is a complex spiking neural network (SNN) capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains minimal power consumption through event-based signal propagation. However, replicating the human brain in neuromorphic hardware presents both hardware and software challenges.

Charge-Selective 2D Heterointerface-Driven Multifunctional Floating Gate Memory for In Situ Sensing-Memory-Computing.

Flash memory, dominating data storage due to its substantial storage density and cost efficiency, faces limitations such as slow response, high operating voltages, absence of optoelectronic response, etc., hindering the development of sensing-memory-computing capability. Here, we present an ultrathin platinum disulfide (PtS)/hexagonal boron nitride (hBN)/multilayer graphene (MLG) van der Waals heterojunction with atomically sharp interfaces, achieving selective charge tunneling behavior and demonstrating ultrafast operations, a high on/off ratio (10), extremely low operating voltage, robust endurance (10 cycles), and retention exceeding 10 years.

Integrative Analyses of Metabolites and Transcriptome Reveal the Metabolic Pattern of Glucosinolates in Potherb Mustard ( var. ).

Potherb mustard ( var. ) is one of the most commonly consumed leafy vegetable mustards, either fresh or in pickled form. It is rich in glucosinolates, whose hydrolyzed products confer potherb mustard's distinctive flavor and chemopreventive properties.

Ultra-low power carbon nanotube/porphyrin synaptic arrays for persistent photoconductivity and neuromorphic computing.

Developing devices with a wide-temperature range persistent photoconductivity (PPC) and ultra-low power consumption remains a significant challenge for optical synaptic devices used in neuromorphic computing. By harnessing the PPC properties in materials, it can achieve optical storage and neuromorphic computing, surpassing the von Neuman architecture-based systems. However, previous research implemented PPC required additional gate voltages and low temperatures, which need additional energy consumption and PPC cannot be achieved across a wide temperature range.

2D Reconfigurable Memory Device Enabled by Defect Engineering for Multifunctional Neuromorphic Computing.

In this era of artificial intelligence and Internet of Things, emerging new computing paradigms such as in-sensor and in-memory computing call for both structurally simple and multifunctional memory devices. Although emerging two-dimensional (2D) memory devices provide promising solutions, the most reported devices either suffer from single functionalities or structural complexity. Here, this work reports a reconfigurable memory device (RMD) based on MoS/CuInPS heterostructure, which integrates the defect engineering-enabled interlayer defects and the ferroelectric polarization in CuInPS, to realize a simplified structure device for all-in-one sensing, memory and computing.

Local Gate Enhanced Correlated Phases in Twisted Monolayer-Bilayer Graphene.

Manipulating the flat band degeneracy and thus getting the correlated insulating phases has been an ideal thread for realizing the exotic quantum phenomenon in the moiré system. To achieve this goal, the delicately tuned twist angle and a substantial displacement field () are rigorously requested. Here, we report our scanning tunneling microscope (STM) work on reaching these correlated insulating states in twisted monolayer-bilayer graphene through a decorated tip.

Faith in frames: unveiling therapeutic narratives in religion-related cinema through computational analysis.

Introduction: This study explores the emotional impact of religion-related films through a "cinematherapy" lens. It aims to analyze the emotional patterns in a curated selection of religion-related films compared to a broader sample of acclaimed movies using facial recognition with YOLOv5 object detection. The study aims to uncover the potential therapeutic application of religion-related films.

Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance.

Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons.

Gate-Tunable Positive and Negative Photoconductance in Near-Infrared Organic Heterostructures for In-Sensor Computing.

The rapid growth of sensor data in the artificial intelligence often causes significant reductions in processing speed and power efficiency. Addressing this challenge, in-sensor computing is introduced as an advanced sensor architecture that simultaneously senses, memorizes, and processes images at the sensor level. However, this is rarely reported for organic semiconductors that possess inherent flexibility and tunable bandgap.

MEMS Oscillators-Network-Based Ising Machine with Grouping Method.

Combinatorial optimization (CO) has a broad range of applications in various fields, including operations research, computer science, and artificial intelligence. However, many of these problems are classified as nondeterministic polynomial-time (NP)-complete or NP-hard problems, which are known for their computational complexity and cannot be solved in polynomial time on traditional digital computers. To address this challenge, continuous-time Ising machine solvers have been developed, utilizing different physical principles to map CO problems to ground state finding.

Ultralow-power optoelectronic synaptic transistors based on polyzwitterion dielectrics for in-sensor reservoir computing.

Bio-inspired transistor synapses use solid electrolytes to achieve low-power operation and rich synaptic behaviors via ion diffusion and trapping. While these neuromorphic devices hold great promise, they still suffer from challenges such as high leakage currents and power consumption, electrolysis risk, and irreversible conductance changes due to long-range ion migrations and permanent ion trapping. In addition, their response to light is generally limited because of "exciton-polaron quenching", which restricts their potential in in-sensor neuromorphic visions.

Oscillatory Neural Network-Based Ising Machine Using 2D Memristors.

Neural networks are increasingly used to solve optimization problems in various fields, including operations research, design automation, and gene sequencing. However, these networks face challenges due to the nondeterministic polynomial time (NP)-hard issue, which results in exponentially increasing computational complexity as the problem size grows. Conventional digital hardware struggles with the von Neumann bottleneck, the slowdown of Moore's law, and the complexity arising from heterogeneous system design.

Optically Tunable Electrical Oscillations in Oxide-Based Memristors for Neuromorphic Computing.

The application of hardware-based neural networks can be enhanced by integrating sensory neurons and synapses that enable direct input from external stimuli. This work reports direct optical control of an oscillatory neuron based on volatile threshold switching in VO. The devices exhibit electroforming-free operation with switching parameters that can be tuned by optical illumination.

miR-29a-KLF4 signaling inhibits breast tumor initiation by regulating cancer stem cells.

Cancer stem cells (CSCs) are known for their potent ability to drive tumor initiation and recurrence, yet the molecular mechanisms regulating CSCs are still unclear. Our study found a positive correlation between increased levels of miR-29a and better survival rates in early-stage breast cancer patients, but a negative correlation in late-stage patients, suggesting a dual function of miR-29a in regulating breast cancer. Furthermore, miR-29a showed significant downregulation in the ALDH+ breast cancer stem cell population compared to non-stem cancer cells.

Lithium Niobate MEMS Antisymmetric Lamb Wave Resonators with Support Structures.

The piezoelectric thin film composed of single-crystal lithium niobate (LiNbO) exhibits a remarkably high electromechanical coupling coefficient and minimal intrinsic losses, making it an optimal material for fabricating bulk acoustic wave resonators. However, contemporary first-order antisymmetric (A1) Lamb mode resonators based on LiNbO thin films face specific challenges, such as inadequate mechanical stability, limited power capacity, and the presence of multiple spurious modes, which restrict their applicability in a broader context. In this paper, we present an innovative design for A1 Lamb mode resonators that incorporates a support-pillar structure.

A 2D Heterostructure-Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing.

The demand for economical and efficient data processing has led to a surge of interest in neuromorphic computing based on emerging two-dimensional (2D) materials in recent years. As a rising van der Waals (vdW) p-type Weyl semiconductor with many intriguing properties, tellurium (Te) has been widely used in advanced electronics/optoelectronics. However, its application in floating gate (FG) memory devices for information processing has never been explored.

miR-186-ANXA9 signaling inhibits tumorigenesis in breast cancer.

Breast cancer (BC) ranks as the highest incidence among cancer types in women all over the world. MicroRNAs (miRNAs) are a class of short endogenous non-coding RNA in cells mostly functioning to silence the target mRNAs. In the current study, a miRNA screening analysis identified miR-186-5p to be downregulated in human breast cancer tumors.

A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing.

Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the multi-dendritic branch structure of neurons to enhance the processing capability of artificial neural networks. While there has been a recent surge of interest in implementing dendritic computing using emerging devices, achieving artificial dendrites with throughputs and energy efficiency comparable to those of the human brain has proven challenging.

CMOS backend-of-line compatible memory array and logic circuitries enabled by high performance atomic layer deposited ZnO thin-film transistor.

The development of high-performance oxide-based transistors is critical to enable very large-scale integration (VLSI) of monolithic 3-D integrated circuit (IC) in complementary metal oxide semiconductor (CMOS) backend-of-line (BEOL). Atomic layer deposition (ALD) deposited ZnO is an attractive candidate due to its excellent electrical properties, low processing temperature below copper interconnect thermal budget, and conformal sidewall deposition for novel 3D architecture. An optimized ALD deposited ZnO thin-film transistor achieving a record field-effect and intrinsic mobility (µ /µ) of 85/140 cm/V·s is presented here.

Breaking the Trade-Off Between Polymer Dielectric Constant and Loss via Aluminum Oxo Macrocycle Dopants for High-Performance Neuromorphic Electronics.

The dielectric layer is crucial in regulating the overall performance of field-effect transistors (FETs), the key component in central processing units, sensors, and displays. Despite considerable efforts being devoted to developing high-permittivity (k) dielectrics, limited progress is made due to the inherent trade-off between dielectric constant and loss. Here, a solution is presented by designing a monodispersed disk-shaped Ce-Al-O-macrocycle as a dopant in polymer dielectrics.