Ferroelectric Transistors for Memory and Neuromorphic Device Applications

An Electrode Design Strategy to Minimize Ferroelectric Imprint Effect

The phenomenon of ferroelectric imprint, characterized by an asymmetric polarization switching behavior, poses significant challenges in the reliability and performance of ultra-low-voltage ferroelectric devices, including MagnetoElectric Spin-Orbit devices, Ferroelectric Random-Access Memory, Ferroelectric Field-Effect Transistors, and Ferroelectric Tunnel Junctions. In this study, the influence of electrode configuration in different device architectures are systematically investigated on their imprint effect. By tuning the work function of La0.7Sr0.3MnO3 (LSMO) electrodes through oxygen pressure during deposition, precise control over the built-in voltage offset (Voffset) in ferroelectric capacitors are demonstrated. This results reveal that higher oxygen pressures increase the work function of LSMO, effectively compensating for Voffset and enhancing device stability. Finally, a ferroelectric device with a hybrid bottom electrode of LSMO and SrRuO3 is optimized to mitigate the imprint effect. The optimal device showcases small coercive voltage of 0.3 V, a minimal Voffset of 0.06 V, excellent endurance (electrical cycle up to 109), and robust zero bias applied polarization retention. These findings provide a practical guideline for electrode design in ferroelectric devices, addressing the imprint effect and improving operational reliability. This approach, combining material tuning and in situ diagnostics, offers a pathway to optimize ferroelectric device performance, with implications for advancing ultra-low-power electronics.

Ferroelectric Hf0.5Zr0.5O2 with Enhanced Intermediate Polarization: A Platform for Neuromorphic and Logic-in-Memory Computing

Ferroelectric materials, known for their nonvolatile and reversible polarization states, are emerging as promising candidates for innovative computing paradigms such as neuromorphic computing and logic-in-memory (LiM) architectures. Their polarization dynamics in response to external stimuli closely emulates biological synapses, a feature crucial for learning and adaptation in neural networks. Achieving multiple intermediate states between fully polarized states is critical for energy-efficient computation. However, the exploitation of switching properties for weight modulation in ferroelectric materials remain underexplored. In this study, we demonstrate improved intermediate and cumulative polarization levels in Hf0.5Zr0.5O2 (HZO) through phase engineering. Consequently, HZO-based synaptic ferroelectric field-effect transistors (FeFETs) achieve a wide range of synaptic weights (up to 8 bits) with remarkable linearity, resulting in high classification accuracies of 98% for MNIST and 88% for Fashion-MNIST in neuromorphic computing tasks. Additionally, we present reconfigurable in-memory NOR and NAND logic functions along with 3-bit logic state generation using a multigate FeFET, demonstrating the potential for LiM operations. This work underscores the successful cointegration of neuromorphic and LiM computing functionalities within a unified platform, addressing key challenges in developing efficient and versatile computing architectures. Our findings highlight the potential of HZO to enable next-generation computing systems that seamlessly integrate learning and logic capabilities.

Ion-Electron Interactions in 2D Nanomaterials-Based Artificial Synapses for Neuromorphic Applications

With the increasing limitations of conventional computing techniques, particularly the von Neumann bottleneck, the brain's seamless integration of memory and processing through synapses offers a valuable model for technological innovation. Inspired by biological synapse facilitating adaptive, low-power computation by modulating signal transmission via ionic conduction, iontronic synaptic devices have emerged as one of the most promising candidates for neuromorphic computing. Meanwhile, the atomic-scale thickness and tunable electronic properties of van der Waals two-dimensional (2D) materials enable the possibility of designing highly integrated, energy-efficient devices that closely replicate synaptic plasticity. This review comprehensively analyzes advancements in iontronic synaptic devices based on 2D materials, focusing on electron-ion interactions in both iontronic transistors and memristors. The challenges of material stability, scalability, and device integration are evaluated, along with potential solutions and future research directions. By highlighting these developments, this review offers insights into the potential of 2D materials in advancing neuromorphic systems.

Suppression of Tin Oxidation via Sn→B Bonding Interactions for High-Resolution Lead-Free Perovskite Neuromorphic Imaging Sensors

Lead-free tin-based perovskites, specifically (4-Cl-PEA)2SnI4, possess significant potential for the development of high-performance, robust neuromorphic imaging sensors, owing to their superior optoelectronic properties and compatibility with conventional complementary metal-oxide-semiconductor fabrication techniques and silicon-based readout circuits. However, the excessive oxidation of Sn2+ remains a significant obstacle, leading to suboptimal synaptic performance and low resolution in the neuromorphic imaging sensors due to increased recombination losses and poor film uniformity. This study first demonstrates that the introduction of novel Sn→B donor-acceptor bonding interactions effectively suppresses Sn2+ oxidation, enhancing uniformity, reducing nonradiative recombination, and improving synaptic plasticity. A vertical optoelectronic synapse demonstrates diverse synaptic behaviors, attributed to hole trapping and detrapping at the device interface. Additionally, the device enables applications in associative learning, neuromorphic computation, letter encoding, and handwritten digit recognition. Ultimately, integration with silicon circuits results in a high-resolution (32 × 32) neuromorphic imaging array, one of the highest reported resolutions for perovskite optoelectronic synapse arrays. The improved uniformity of boric acid-added (4-Cl-PEA)2SnI4 perovskite films significantly reduces photo response non-uniformity, enhances resolution, and improves memory capabilities. This neuromorphic imaging array successfully integrates sensing, storage, and computation, enabling advanced functionalities like letter recognition, memory, and processing, surpassing conventional image sensors.

Customizing Room-Temperature Perovskite Ferroelectrics toward the Multichannel Domain Manipulation

Manipulating domain structure in ferroelectrics by external stimuli presents a fascinating avenue for new-generation electronic devices. However, multichannel controlling of ferroelectric domains is still a challenge, due to the lack of knowledge on their bistability to diverse physical stimuli. Herein, we have customized a series of perovskite ferroelectrics, (CnH2n+1NH3)2(CH3NH3)2Pb3Br10 (n = 2-7), of which the Curie temperatures are modulated in a wide temperature range (ΔT = 74 K) by tailoring chain length of organic spacers. Strikingly, the n = 7 member is a room-temperature ferroelectric with bistable characteristics, thus endowing the manipulation of domains via four channels (i.e., thermal, stress, light, and electric fields). Such a non-volatile memory behavior of the stress-switching domain is unprecedented in hybrid perovskite ferroelectrics. This manipulation of domains reveals the unique bistability of its ferroelectric orders, which sheds light on the future advance of customizing electric-ordered materials toward smart device applications.

Realization of Tunable Ferroelectricity in Perovskite Crystals for Multidirectional Self-Driven Photodetection

Halide perovskite ferroelectrics endowed with a distinctive spontaneous polarization effect have been regarded as prospective electroactive materials and are prevalently utilized in solar cells, photoelectric detection, and other domains. Among them, multipolar-axis ferroelectrics featuring multiple equivalent polarization directions are particularly desirable for diverse areas of applications. Nevertheless, the design and regulation of multipolar axis perovskite ferroelectrics remains a significant challenge. Here, guided by the strategy of layer regulation, we successfully designed and regulated a series of 2D homologous perovskites OA2Csn -1PbnBr3 n +1 (OA = n-octylammonium, n = 1-3). Notably, OA2Csn -1PbnBr3 n +1 exhibits layer-dependent ferroelectricity: OA2PbBr4 exhibits non-ferroelectricity, OA2CsPb2Br7 displays uniaxial ferroelectricity, while OA2Cs2Pb3Br10 has multiaxial ferroelectricity. Moreover, the devices fabricated based on OA2Cs2Pb3Br10 achieve high-performance self-driven photodetection in multiple directions. This precise layer-regulation strategy offers an efficient approach to obtaining and regulating multipolar-axis perovskite ferroelectrics, presenting the potential for next-generation optoelectronic devices.

Advances in Single-Crystal Films: Synergistic Insights from Perovskites and Organic Molecules for High-Performance Optoelectronics

Semiconductor single-crystal thin films are crucial for the advancement of high-performance optoelectronic devices. Despite significant progress in fabricating perovskite and organic single-crystal films, interdisciplinary insights between these domains remain unexplored. This review aims to bridge this gap by summarizing recent advances in fabrication strategies for perovskite and organic molecular single-crystal films. Five preparation methods-solution-phase epitaxy, solid-phase epitaxy, meniscus-induced crystallization, antisolvent-induced crystallization, and space-confined growth-are analyzed with a focus on their principles, functional properties, and distinct advantages. By comparing these approaches across material systems, this review identifies transferable insights that can drive the development of large-scale, high-quality single-crystal films. Furthermore, the optoelectronic applications of these films are explored, including solar cells, photodetectors, light-emitting devices, and transistors, while addressing challenges such as scalability, defect control, and integration. This work highlights the importance of cross-disciplinary innovation and provides an effective pathway for integrating perovskite and organic molecular processing to advance the next generation of single-crystal film technologies.

Ultralow Power Cold-Fuse Memory Based on Metal-Oxide-CNT Structure

One-time programmable (OTP) memory is an essential component in chips, which has extremely high security to protect the stored critical information from being altered. However, traditional OTP memory based on the thermal breakdown of the dielectric has a large programming current, which leads to high power consumption. Here, we report a gate tunneling-induced "cold" breakdown phenomenon in carbon nanotube (CNT) field-effect transistors, and based on this we construct a "cold" fuse (C-fuse) memory where applying a mild gate voltage can break down the CNT channel without damaging the gate dielectric. The C-fuse is intrinsically different from dielectric-breakdown OTP, and it exhibits extremely low programming current (10-12 A), a large high-low resistance ratio (>1011), and a long retention time (>10 years). As the first reported OTP memory based on low-dimensional nanomaterials, C-fuse memory exhibits excellent storage performance and good uniformity, demonstrating great potential in constructing next-generation secure storage circuits.

Precise weight tuning in quantum dot-based resistive-switching memory for neuromorphic systems

In this study, nonvolatile bipolar resistive switching and synaptic emulation behaviors are performed in an InGaP quantum dots (QDs)/HfO2-based memristor device. First, the physical and chemical properties of InGaP QDs are investigated by high-resolution transmission electron microscopy and spectrophotometric analysis. Through comparative experiments, it is proven that the HfO2 layer improves the variations in resistive switching characteristics. Additionally, the Al/QDs/HfO2/ITO device exhibits reversible switching performances with excellent data retention. Fast switching speeds in the order of nanoseconds were confirmed, which could be explained by trapping/detrapping and quantum tunneling effects by the trap provided by nanoscale InGaP QDs. In addition, the operating voltage is decreased when the device is exposed to ultraviolet light for low-power switching. Biological synapse features such as spike-timing-dependent plasticity are emulated for neuromorphic systems. Finally, the incremental step pulse using proven algorithm method enabled the implementation of four-bit states (16 states), markedly enhancing the inference precision of neuromorphic systems.

Organic Solid-State Electrolyte Synaptic Transistors with Photoinduced Thiol-Ene Cross-linked Polymer Electrolytes for Deep Neural Networks

In this work, we describe a solid-state polymer electrolyte (SPE)-based electrolyte-gated organic field-effect transistors (EGOFETs) consisting of a thiol-ene-assisted photo-cross-linked nitrile butadiene rubber (NBR) network embedded with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) electrolyte. The photocurable SPE film can be patterned with different dimensions by photolithography and exhibits excellent electronic properties and crucial synaptic behavior. The photocurable NBR/LiTFSI EGOFET exhibits a high transconductance of 11.9 mS and a high on/off ratio of 105 at a scan rate of 40 mV/s. Due to the strongly polarized nature of the photo-cross-linked NBR network and Li-ion diffusion, the NBR/LiTFSI device exhibits a significant current hysteresis, enabling synaptic-like learning and memory behavior. The NBR/LiTFSI device demonstrates a DNN of 91.9% handwritten digit recognition accuracy. This work demonstrates the potential of the solid-state NBR/LiTFSI EGOFET in creating highly efficient and low-energy neuromorphic devices.

Multiple Polarization States in Hf1- xZrxO2 Thin Films by Ferroelectric and Antiferroelectric Coupling

HfO2-based multi-bit ferroelectric memory combines non-volatility, speed, and energy efficiency, rendering it a promising technology for massive data storage and processing. However, some challenges remain, notably polarization variation, high operation voltage, and poor endurance performance. Here we show Hf1- xZrxO2 (x = 0.65 to 0.75) thin films grown through sequential atomic layer deposition (ALD) of HfO2 and ZrO2 exhibiting three-step domain switching characteristic in the form of triple-peak coercive electric field (EC) distribution. This long-sought behavior shows nearly no changes even at up to 125 °C and after 1 × 108 electric field cycling. By combining the electrical characterizations and integrated differential phase-contrast scanning transmission electron microscopy (iDPC-STEM), we reveal that the triple-peak EC distribution is driven by the coupling of ferroelectric switching and reversible antiferroelectric-ferroelectric transition. We further demonstrate the 3-bit per cell operation of the Hf1- xZrxO2 capacitors with excellent device-to-device variation and long data retention, by the full switching of individual peaks in the triple-peak EC. The work represents a significant step in implementing reliable non-volatile multi-state ferroelectric devices.

Analysis and fully memristor-based reservoir computing for temporal data classification

Reservoir computing (RC) offers a neuromorphic framework that is particularly effective for processing spatiotemporal signals. Known for its temporal processing prowess, RC significantly lowers training costs compared to conventional recurrent neural networks. A key component in its hardware deployment is the ability to generate dynamic reservoir states. Our research introduces a novel dual-memory RC system, integrating a short-term memory via a WOx-based memristor, capable of achieving 16 distinct states encoded over 4 bits, and a long-term memory component using a TiOx-based memristor within the readout layer. We thoroughly examine both memristor types and leverage the RC system to process temporal data sets. The performance of the proposed RC system is validated through two benchmark tasks: isolated spoken digit recognition and with only a fraction of complete samples forecasting the Mackey-Glass (MG) time series prediction. The system delivered an impressive 98.84% accuracy in speech digit recognition and sustained a low normalized root mean square error (NRMSE) of 0.036 in the time series prediction task, underscoring its capability. This study illuminates the adeptness of memristor-based RC systems in managing intricate temporal challenges, laying the groundwork for further innovations in neuromorphic computing.

Optical Detection of Sliding Ferroelectric Switching in hBN with a WSe2 Monolayer

When two BN layers are stacked in parallel in an AB or BA arrangement, a spontaneous out-of-plane electric polarization arises due to charge transfer in the out-of-plane B-N bonds. The ferroelectric switching from AB to BA (or BA to AB) can be achieved with a relatively small out-of-plane electric field through the in-plane sliding of one atomic layer over the other. However, the optical detection of such ferroelectric switching in hBN has not yet been demonstrated. In this study, we utilize an adjacent WSe2 monolayer to detect the ferroelectric switching in BN. This dynamic coupling between a two-dimensional (2D) ferroelectric and a 2D semiconductor allows for the fundamental investigation of the ferroelectric material using a nondestructive, local optical probe, offering promising applications for compact and nonvolatile memory devices.

Organic Nonvolatile 2T Memory Cell Employing a NOT-Gate-Like Architecture Toward Binary Output Level With Enhanced Noise Tolerance

Organic nonvolatile memory has been considered a low-cost memory technology for flexible electronics and Internet-of-things (IoT). However, a major concern is the nonuniformity of memory units, which is primarily caused by random grain boundaries, interface defects, and charge traps, making it difficult to develop high-density reliable memory arrays. This nonuniformity problem would induce read error, which is directly caused by the narrow distribution margin of memory states and low noise tolerance in conventional organic memory cells. To break this limitation, a novel 2T memory cell employing a NOT-gate-like architecture achieving self-enhancing noise tolerance is presented. This unique cell consists of a pair of commonly-gated memory transistors with contradictory "write-and-erase" features. It functions as a voltage divider, producing a well-distinguished binary voltage output capability. The concept and design model of this brand-new 2T memory cell is thoroughly discussed. It is originally characterized by noise-tolerant memory cells irrespective of device nonuniformity. The noise tolerance range of this 2T memory cell is also investigated. The binary voltage-readable memory state with a large noise tolerance range is obtained. Moreover, the conceptual design of the 1T2T FeRAM cell is further developed for low-cost voltage-readable memory technology in wearable electronic applications.

Nanomaterials for Flexible Neuromorphics

The quest to imbue machines with intelligence akin to that of humans, through the development of adaptable neuromorphic devices and the creation of artificial neural systems, has long stood as a pivotal goal in both scientific inquiry and industrial advancement. Recent advancements in flexible neuromorphic electronics primarily rely on nanomaterials and polymers owing to their inherent uniformity, superior mechanical and electrical capabilities, and versatile functionalities. However, this field is still in its nascent stage, necessitating continuous efforts in materials innovation and device/system design. Therefore, it is imperative to conduct an extensive and comprehensive analysis to summarize current progress. This review highlights the advancements and applications of flexible neuromorphics, involving inorganic nanomaterials (zero-/one-/two-dimensional, and heterostructure), carbon-based nanomaterials such as carbon nanotubes (CNTs) and graphene, and polymers. Additionally, a comprehensive comparison and summary of the structural compositions, design strategies, key performance, and significant applications of these devices are provided. Furthermore, the challenges and future directions pertaining to materials/devices/systems associated with flexible neuromorphics are also addressed. The aim of this review is to shed light on the rapidly growing field of flexible neuromorphics, attract experts from diverse disciplines (e.g., electronics, materials science, neurobiology), and foster further innovation for its accelerated development.

Hafnia-Based Ferroelectric Transistor with Poly-Si Gates for Gate-First Three-Dimensional NAND Structures

Ferroelectric transistors based on hafnia-based ferroelectrics have emerged as promising candidates for next-generation memory devices. Additionally, hafnia-based ferroelectric transistors are suggested for three-dimensional (3D) memory devices, such as 3D ferroelectric NAND. This paper investigates the utilization of poly-Si as a gate material for hafnia-based ferroelectric transistors in 3D NAND structures. Conventional gate materials, such as TiN or W, are usually deposited in 3D NAND structures by using the gate-last process, which requires an additional gate replacement process. We demonstrate that poly-Si can be used as a gate material for hafnia-based ferroelectric transistors. We show that the 3D ferroelectric NAND based on the poly-Si gate can be fabricated by a simpler gate-first process without requiring a gate replacement process. Our findings underscore the potential of poly-Si as a gate material for ferroelectric transistors and 3D ferroelectric NAND.

Recent advances in artificial neuromorphic applications based on perovskite composites

High-performance perovskite materials with excellent physical, electronic, and optical properties play a significant role in artificial neuromorphic devices. However, the development of perovskites in microelectronics is inevitably hindered by their intrinsic non-ideal properties, such as high defect density, environmental sensitivity, and toxicity. By leveraging materials engineering, integrating various materials with perovskites to leverage their mutual strengths presents great potential to enhance ion migration, energy level alignment, photoresponsivity, and surface passivation, thereby advancing optoelectronic and neuromorphic device development. This review initially provides an overview of perovskite materials across different dimensions, highlighting their physical properties and detailing their applications and metrics in two- and three-terminal devices. Subsequently, we comprehensively summarize the application of perovskites in combination with other materials, including organics, nanomaterials, oxides, ferroelectrics, and crystalline porous materials (CPMs), to develop advanced devices such as memristors, transistors, photodetectors, sensors, light-emitting diodes (LEDs), and artificial neuromorphic systems. Lastly, we outline the challenges and future research directions in synthesizing perovskite composites for neuromorphic devices. Through the review and analysis, we aim to broaden the utilization of perovskites and their composites in neuromorphic research, offering new insights and approaches for grasping the intricate physical working mechanisms and functionalities of perovskites.

A Near-Infrared Retinomorphic Device with High Dimensionality Reservoir Expression

Physical reservoir-based reservoir computing (RC) systems for intelligent perception have recently gained attention because they require fewer computing resources. However, the system remains limited in infrared (IR) machine vision, including materials and physical reservoir expression power. Inspired by biological visual perception systems, the study proposes a near-infrared (NIR) retinomorphic device that simultaneously perceives and encodes narrow IR spectral information (at ≈980 nm). The proposed device, featuring core-shell upconversion nanoparticle/poly (3-hexylthiophene) (P3HT) nanocomposite channels, enables the absorption and conversion of NIR into high-energy photons to excite more photo carriers in P3HT. The photon-electron-coupled dynamics under the synergy of photovoltaic and photogating effects influence the nonlinearity and high dimensionality of the RC system under narrow-band NIR irradiation. The device also exhibits multilevel data storage capability (≥8 levels), excellent stability (≥2000 s), and durability (≥100 cycles). The system accurately identifies NIR static and dynamic handwritten digit images, achieving recognition accuracies of 91.13% and 90.07%, respectively. Thus, the device tackles intricate computations like solving second-order nonlinear dynamic equations with minimal errors (normalized mean squared error of 1.06 × 10⁻3 during prediction).

Polarization Pruning: Reliability Enhancement of Hafnia-Based Ferroelectric Devices for Memory and Neuromorphic Computing

Ferroelectric (FE) materials are key to advancing electronic devices owing to their non-volatile properties, rapid state-switching abilities, and low-energy consumption. FE-based devices are used in logic circuits, memory-storage devices, sensors, and in-memory computing. However, the primary challenge in advancing the practical applications of FE-based memory is its reliability. To address this problem, a novel polarization pruning (PP) method is proposed. The PP is designed to eliminate weakly polarized domains by applying an opposite-sign pulse immediately after a program or erase operation. Significant improvements in the reliability of ferroelectric devices are achieved by reducing the depolarization caused by weakly polarized domains and mitigating the fluctuations in the ferroelectric dipole. These enhancements include a 25% improvement in retention, a 50% reduction in read noise, a 45% decrease in threshold voltage variation, and a 72% improvement in linearity. The proposed PP method significantly improves the memory storage efficiency and performance of neuromorphic systems.

Ultrafast Switching of Sliding Polarization and Dynamical Magnetic Field in van der Waals Bilayers Induced by Light

Sliding ferroelectricity is a unique type of polarity recently observed in van der Waals bilayers with a suitable stacking. However, electric-field control of sliding ferroelectricity is hard and could induce large coercive electric fields and serious leakage currents that corrode the ferroelectricity and electronic properties, which are essential for modern two-dimensional electronics and optoelectronics. Here, we proposed laser-pulse deterministic control of sliding polarization in bilayer hexagonal boron nitride by first principles and molecular dynamics simulation with machine-learned force fields. The laser pulses excite shear modes that exhibit certain directional movements of lateral sliding between bilayers. The vibration of excited modes under laser pulses is predicted to overcome the energy barrier and achieve the switching of sliding polarization. Furthermore, it is found that three possible sliding transitions-between AB (BA) and BA (AB) stacking-can lead to the occurrence of dynamical magnetic fields along three different directions. Remarkably, the magnetic fields are generated by the simple linear motion of nonmagnetic species, without any need for more exotic (circular, spiral) pathways. Such predictions of deterministic control of sliding polarization and multistates of dynamical magnetic field thus expand the potential applications of sliding ferroelectricity in memory and electronic devices.

Spiking Neural Network Integrated with Impact Ionization Field-Effect Transistor Neuron and a Ferroelectric Field-Effect Transistor Synapse

The integration of artificial spiking neurons based on steep-switching logic devices and artificial synapses with neuromorphic functions enables an energy-efficient computer architecture that mimics the human brain well, known as a spiking neural network (SNN). 2D materials with impact ionization or ferroelectric characteristics have the potential for use in such devices. However, research on 2D spiking neurons remains limited and investigations of 2D artificial synapses far more common. An innovative 2D spiking neuron is implemented using a WSe2 impact ionization transistor (I2FET), while a spiking neural network is formed by combining it with a 2D ferroelectric synaptic device (FeFET). The suggested 2D spiking neuron demonstrates precise spiking behavior that closely resembles that of actual neurons. In addition, it achieves a low energy consumption of 2 pJ/spike. The better impact ionization properties of WSe2 are responsible for this efficiency. Furthermore, an all-2D SNN consisting of 2D I2FET neurons and 2D FeFET synapses is constructed, which achieves high accuracy of 87.5% in a face classification task by unsupervised learning. The integration of a 2D SNN with 2D steep-switching spiking neuronal devices and 2D synaptic devices shows great potential for the development of neuromorphic systems with improved energy efficiency and computational capabilities.

Reconfigurable aJ-Level Ferroelectric Transistor-Based Boolean Logic for Logic-in-Memory

Logic-in-memory (LIM) architecture holds great potential to break the von Neumann bottleneck. Despite the extensive research on novel devices, challenges persist in developing suitable engineering building blocks for such designs. Herein, we propose a reconfigurable strategy for efficient implementation of Boolean logics based on a hafnium oxide-based ferroelectric field effect transistor (HfO2-based FeFET). The logic results are stored within the device itself (in situ) during the computation process, featuring the key characteristics of LIM. The fast switching speed and low power consumption of a HfO2-based FeFET enable the execution of Boolean logics with an ultralow energy of lower than 8 attojoule (aJ). This represents a significant milestone in achieving aJ-level computing energy consumption. Furthermore, the system demonstrates exceptional reliability with computing endurance exceeding 108 cycles and retention properties exceeding 1000 s. These results highlight the remarkable potential of a FeFET for the realization of high performance beyond the von Neumann LIM computing architectures.

Optical-Electrical Coordinately Modulated Memristor Based on 2D Ferroelectric RP Perovskite for Artificial Vision Applications

Traditional artificial vision systems built using separate sensing, computing, and storage units have problems with high power consumption and latency caused by frequent data transmission between functional units. An effective approach is to transfer some memory and computing tasks to the sensor, enabling the simultaneous perception-storage-processing of light signals. Here, an optical-electrical coordinately modulated memristor is proposed, which controls the conductivity by means of polarization of the 2D ferroelectric Ruddlesden-Popper perovskite film at room temperature. The residual polarization shows no significant decay after 109-cycle polarization reversals, indicating that the device has high durability. By adjusting the pulse parameters, the device can simulate the bio-synaptic long/short-term plasticity, which enables the control of conductivity with a high linearity of ≈0.997. Based on the device, a two-layer feedforward neural network is built to recognize handwritten digits, and the recognition accuracy is as high as 97.150%. Meanwhile, building optical-electrical reserve pool system can improve 14.550% for face recognition accuracy, further demonstrating its potential for the field of neural morphological visual systems, with high density and low energy loss.

Optical Control of Adaptive Nanoscale Domain Networks

Adaptive networks can sense and adjust to dynamic environments to optimize their performance. Understanding their nanoscale responses to external stimuli is essential for applications in nanodevices and neuromorphic computing. However, it is challenging to image such responses on the nanoscale with crystallographic sensitivity. Here, the evolution of nanodomain networks in (PbTiO3)n/(SrTiO3)n superlattices (SLs) is directly visualized in real space as the system adapts to ultrafast repetitive optical excitations that emulate controlled neural inputs. The adaptive response allows the system to explore a wealth of metastable states that are previously inaccessible. Their reconfiguration and competition are quantitatively measured by scanning x-ray nanodiffraction as a function of the number of applied pulses, in which crystallographic characteristics are quantitatively assessed by assorted diffraction patterns using unsupervised machine-learning methods. The corresponding domain boundaries and their connectivity are drastically altered by light, holding promise for light-programable nanocircuits in analogy to neuroplasticity. Phase-field simulations elucidate that the reconfiguration of the domain networks is a result of the interplay between photocarriers and transient lattice temperature. The demonstrated optical control scheme and the uncovered nanoscopic insights open opportunities for the remote control of adaptive nanoscale domain networks.

Mapping Ferroelectric Fields Reveals the Origins of the Coercivity Distribution

Better techniques for imaging ferroelectric polarization would aid the development of new ferroelectrics and the refinement of old ones. Here we show how scanning transmission electron microscope (STEM) electron beam-induced current (EBIC) imaging reveals ferroelectric polarization with obvious, simply interpretable contrast. Planar imaging of an entire ferroelectric hafnium zirconium oxide (Hf0.5Zr0.5O2, HZO) capacitor shows an EBIC response that is linearly related to the polarization determined in situ with the positive-up, negative-down (PUND) method. The contrast is easily calibrated in MV/cm. The underlying mechanism is magnification-independent, operating equally well on micrometer-sized devices and individual nanoscale domains. Coercive-field mapping reveals that individual domains are biased "positive" and "negative", as opposed to being "easy" and "hard" to switch. The remanent background E-fields generating this bias can be isolated and mapped. Coupled with STEM's native capabilities for structural identification, STEM EBIC imaging provides a revolutionary tool for characterizing ferroelectric materials and devices.

Fermi level pinning in metal oxides: influence on photocatalysis and photoelectrochemistry

Photocatalysis and photoelectrochemical (PEC) reactions are complex processes involving both the physical properties and surface chemistry of the semiconductor photocatalyst. Their interplay applies specific limitations on the performance of different materials in light-driven reactions, often despite their optimal band structure and optical absorption. One of the ways to properly characterize the photocatalytic and PEC properties of semiconductors remains the measurement of the photopotential, which characterizes a driving force of photoinduced processes in the material. In this work, we give a general scope on the photopotential in PEC reactions that finds its origin in semiconductor physics. It is shown that the photopotential does not always play an interchangeable role with the photocurrent in comparative analysis of the photocatalytic performance of different materials. Furthermore, a correlation between the photopotential and the kinetics of methylene blue dye photocatalysis is shown for anatase-TiO2, CeO2and WO3as photocatalysts. Fermi level pinning (FLP) in the bandgap of CeO2is observed limiting the photoactivity of the compound, which is attributed to the high defectivity of CeO2. A short review is given on the possible origins of FLP in metal oxides and ways to overcome it. It is pointed out that the shift of the Fermi level after illumination of CeO2can trigger the chemical instability of the material accompanied by the FLP process.

Free-standing two-dimensional ferro-ionic memristor

Two-dimensional (2D) ferroelectric materials have emerged as significant platforms for multi-functional three-dimensional (3D) integrated electronic devices. Among 2D ferroelectric materials, ferro-ionic CuInP2S6 has the potential to achieve the versatile advances in neuromorphic computing systems due to its phase tunability and ferro-ionic characteristics. As CuInP2S6 exhibits a ferroelectric phase with insulating properties at room temperature, the external temperature and electrical field should be required to activate the ferro-ionic conduction. Nevertheless, such external conditions inevitably facilitate stochastic ionic conduction, which completely limits the practical applications of 2D ferro-ionic materials. Herein, free-standing 2D ferroelectric heterostructure is mechanically manipulated for nano-confined conductive filaments growth in free-standing 2D ferro-ionic memristor. The ultra-high mechanical bending is selectively facilitated at the free-standing area to spatially activate the ferro-ionic conduction, which allows the deterministic local positioning of Cu+ ion transport. According to the local flexoelectric engineering, 5.76×102-fold increased maximum current is observed within vertical shear strain 720 nN, which is theoretically supported by the 3D flexoelectric simulation. In conclusion, we envision that our universal free-standing platform can provide the extendable geometric solution for ultra-efficient self-powered system and reliable neuromorphic device.

Unlocking large memory windows and 16-level data per cell memory operations in hafnia-based ferroelectric transistors

Ferroelectric transistors based on hafnia-based ferroelectrics exhibit tremendous potential as next-generation memories owing to their high-speed operation and low power consumption. Nevertheless, these transistors face limitations in terms of memory window, which directly affects their ability to support multilevel characteristics in memory devices. Furthermore, the absence of an efficient operational technique capable of achieving multilevel characteristics has hindered their development. To address these challenges, we present a gate stack engineering method and an efficient operational approach for ferroelectric transistors to achieve 16-level data per cell operation. By using the suggested engineering method, we demonstrate the attainment of a substantial memory window of 10 V without increasing the device area. Additionally, we propose a displacement current control method, facilitating one-shot programming to the desired state. Remarkably, we suggest the compatibility of these proposed methods with three-dimensional (3D) structures. This study underscores the potential of ferroelectric transistors for next-generation 3D memory applications.

The Investigation of Neuromimetic Dynamics in Ferroelectrics via In Situ TEM

The core task of neuromorphic devices is to effectively simulate the behavior of neurons and synapses. Based on the functionality of ferroelectric domains with the advantages of low power consumption and high-speed response, great progress has been made in realizing neuromimetic behaviors such as ferroelectric synaptic devices. However, the correlation between the ferroelectric domain dynamics and neuromimetic behavior remains unclear. Here, we reveal the correlation between domain/domain wall dynamics and neuromimetic behaviors from a microscopic perspective in real-time by using high temporal and spatial resolution in situ transmission electron microscopy. Furthermore, we propose utilizing ferroelectric microstructures for the simultaneous simulation of neuronal and synaptic plasticity, which is expected to improve the integration and performance of ferroelectric neuromorphic devices. We believe that this work to study neuromimetic behavior from the perspective of domain dynamics is instructive for the development of ferroelectric neuromorphic devices.

Optical Phenomena in Molecule-Based Magnetic Materials

Since the last century, we have witnessed the development of molecular magnetism which deals with magnetic materials based on molecular species, i.e., organic radicals and metal complexes. Among them, the broadest attention was devoted to molecule-based ferro-/ferrimagnets, spin transition materials, including those exploring electron transfer, molecular nanomagnets, such as single-molecule magnets (SMMs), molecular qubits, and stimuli-responsive magnetic materials. Their physical properties open the application horizons in sensors, data storage, spintronics, and quantum computation. It was found that various optical phenomena, such as thermochromism, photoswitching of magnetic and optical characteristics, luminescence, nonlinear optical and chiroptical effects, as well as optical responsivity to external stimuli, can be implemented into molecule-based magnetic materials. Moreover, the fruitful interactions of these optical effects with magnetism in molecule-based materials can provide new physical cross-effects and multifunctionality, enriching the applications in optical, electronic, and magnetic devices. This Review aims to show the scope of optical phenomena generated in molecule-based magnetic materials, including the recent advances in such areas as high-temperature photomagnetism, optical thermometry utilizing SMMs, optical addressability of molecular qubits, magneto-chiral dichroism, and opto-magneto-electric multifunctionality. These findings are discussed in the context of the types of optical phenomena accessible for various classes of molecule-based magnetic materials.

UV/Ozone-Treated and Sol-Gel-Processed Y2O3 Insulators Prepared Using Gelation-Delaying Precursors

In this study, a Y2O3 insulator was fabricated via the sol-gel process and the effect of precursors and annealing processes on its electrical performance was studied. Yttrium(III) acetate hydrate, yttrium(III) nitrate tetrahydrate, yttrium isopropoxide oxide, and yttrium(III) tris (isopropoxide) were used as precursors, and UV/ozone treatment and high-temperature annealing were performed to obtain Y2O3 films from the precursors. The structure and surface morphologies of the films were characterized via grazing-incidence X-ray diffraction and scanning probe microscopy. Chemical component analysis was performed via X-ray spectroscopy. Electrical insulator characteristics were analyzed based on current density versus electrical field data and frequency-dependent dielectric constants. The Y2O3 films fabricated using the acetate precursor and subjected to the UV/ozone treatment showed a uniform and flat surface morphology with the lowest number of oxygen vacancy defects and unwanted byproducts. The corresponding fabricated capacitors showed the lowest current density (Jg) value of 10-8 A/cm2 at 1 MV/cm and a stable dielectric constant in a frequency range of 20 Hz-100 KHz. At 20 Hz, the dielectric constant was 12.28, which decreased to 10.5 at 105 Hz. The results indicate that high-quality, high-k insulators can be fabricated for flexible electronics using suitable precursors and the suggested low-temperature fabrication methods.

Polar Crystals Using Molecular Chirality: Pseudosymmetric Crystallization toward Polarization Switching Materials

Polar compounds with switchable polarization properties are applicable in various devices such as ferroelectric memory and pyroelectric sensors. However, a strategy to prepare polar compounds has not been established. We report a rational synthesis of a polar CoGa crystal using chiral cth ligands (SS-cth and RR-cth, cth = 5,7,7,12,14,14-hexamethyl-1,4,8,11-tetraazacyclotetradecane). Both the original homo metal Co crystal and Ga crystal exhibit a centrosymmetric isostructure, where the dipole moment of metal complexes with the SS-cth ligand and those with the RR-cth ligand are canceled out. To obtain a polar compound, the Co valence tautomeric complex with SS-cth in the homo metal Co crystal is replaced with the Ga complex with SS-cth by mixing Co valence tautomeric complexes with RR-cth and Ga complexes with SS-cth. The CoGa crystal exhibits polarization switching between the pseudononpolar state at a low temperature and the polar state at a high temperature because only Co complexes exhibit changes in electric dipole moment due to metal-to-ligand charge transfer. Following the same strategy, the polarization-switchable CoZn complex was synthesized. The CoZn crystal exhibits polarization switching between the polar state at a low temperature and the pseudononpolar state at a high temperature, which is the opposite temperature dependence to that of the CoGa crystal. These results revealed that the polar crystal can be synthesized by design, using a chiral ligand. Moreover, our method allows for the control of temperature-dependent polarization changes, which contrasts with typical ferroelectric compounds, in which the polar ferroelectric phase typically occurs at low temperatures.

Ferroelectric 2D SnS2 Analog Synaptic FET

In this study, the development and characterization of 2D ferroelectric field-effect transistor (2D FeFET) devices are presented, utilizing nanoscale ferroelectric HfZrO2 (HZO) and 2D semiconductors. The fabricated device demonstrated multi-level data storage capabilities. It successfully emulated essential biological characteristics, including excitatory/inhibitory postsynaptic currents (EPSC/IPSC), Pair-Pulse Facilitation (PPF), and Spike-Timing Dependent Plasticity (STDP). Extensive endurance tests ensured robust stability (107 switching cycles, 105 s (extrapolated to 10 years)), excellent linearity, and high Gmax/Gmin ratio (>105), all of which are essential for realizing multi-level data states (>7-bit operation). Beyond mimicking synaptic functionalities, the device achieved a pattern recognition accuracy of ≈94% on the Modified National Institute of Standards and Technology (MNIST) handwritten dataset when incorporated into a neural network, demonstrating its potential as an effective component in neuromorphic systems. The successful implementation of the 2D FeFET device paves the way for the development of high-efficiency, ultralow-power neuromorphic hardware which is in sub-femtojoule (48 aJ/spike) and fast response (1 µs), which is 104 folds faster than human synapse (≈10 ms). The results of the research underline the potential of nanoscale ferroelectric and 2D materials in building the next generation of artificial intelligence technologies.

Ferroelectric Organic Semiconductor: [1]Benzothieno[3,2-b][1]benzothiophene-Bearing Hydrogen-Bonding -CONHC14H29 Chain

An alkylamide-substituted [1]benzothieno[3,2-b][1]benzothiophene (BTBT) derivative of BTBT-CONHC14H29 (1) and C8H17-BTBT-CONHC14H29 (2) were prepared to design the multifunctional organic materials, which can show both ferroelectric and semiconducting properties. Single-crystal X-ray structural analyses of short-chain (-CONHC3H7) derivatives revealed the coexistence of two-dimensional (2D) electronic band structures brought from a herringbone arrangement of the BTBT π core and the one-dimensional (1D) hydrogen-bonding chains of -CONHC3H7 chains. The thin films of 1 and 2 fabricated on the Si/SiO2 substrate surface have monolayer and bilayer structures, respectively, resulting in conducting layers parallel to the substrate surface, which is suitable for a channel layer of organic field-effect transistors (OFETs). The thin film of 1 indicated a hole mobility μFET = 2.4 × 10-5 cm2 V-1 s-1 and threshold voltage VTh = - 29 V, whereas that of 2 showed a μFET = 2.1 × 10-2 cm2 V-1 s-1 and threshold voltage VTh = -9.7 V. Both 1 and 2 formed the smectic E (SmE) phase above 410 and 369 K, respectively, where the existence of a hole transport pathway was confirmed in the SmE phase. The ferroelectric hysteresis behavior was observed in bulk 1 and 2 in the polarization-electric field (P-E) curves at the SmE phase. 1 showed the remanent polarization Pr = 2.3 μC cm-2 and coercive electric field Ec = 5.2 V μm-1, whereas the Pr and Ec of 2 were 3.4 μC cm-2 and 7.0 V μm-1 at the conditions of 453 K and 1 Hz. Introduction of alkylamide units into the BTBT π core has the potential to develop the external stimulus-responsive organic semiconductors brought from both ferroelectricity and semiconducting properties.

Single Wavelength Operating Neuromorphic Device Based on a Graphene-Ferroelectric Transistor

As global data generation continues to rise, there is an increasing demand for revolutionary in-memory computing methodologies and efficient machine learning solutions. Despite recent progress in electrical and electro-optical simulations of machine learning devices, the all-optical nonthermal function remains challenging, with single wavelength operation still elusive. Here we report on an optical and monochromatic way of neuromorphic signal processing for brain-inspired functions, eliminating the need for electrical pulses. Multilevel synaptic potentiation-depression cycles are successfully achieved optically by leveraging photovoltaic charge generation and polarization within the photoferroelectric substrate interfaced with the graphene sensor. Furthermore, the demonstrated low-power prototype device is able to reproduce exact signal profile of brain tissues yet with more than 2 orders of magnitude faster response. The reported properties should trigger all-optical and low power artificial neuromorphic development based on photoferroelectric structures.

Dopant Engineering of Hafnia-Based Ferroelectrics for Long Data Retention and High Thermal Stability

Hafnia-based ferroelectrics have gained much attention because they can be used in highly scaled, advanced complementary metal-oxide semiconductor (CMOS) memory devices. However, thermal stability should be considered when integrating hafnia-based ferroelectric transistors in advanced CMOS devices, as they can be exposed to high-temperature processes. This work proposed that doping of Al in hafnia-based ferroelectric material can lead to high thermal stability. A ferroelectric capacitor based on Al-doped hafnia, which can be used for one-transistor-one-capacitor applications, exhibits stable operation even after annealing at 900 °C. Moreover, it demonstrates that the ferroelectric transistors based on Al-doped hafnia for one-transistor applications, such as ferroelectric NAND, retain their memory states for 10 years at 100 °C. This study presents a practical method to achieve thermally stable ferroelectric memories capable of enduring high-temperature processes and operation conditions.

Mixed-Dimensional Nanoparticle-Nanowire Channels for Flexible Optoelectronic Artificial Synapse with Enhanced Photoelectric Response and Asymmetric Bidirectional Plasticity

A mixed-dimensional dual-channel synaptic transistor composed of inorganic nanoparticles and organic nanowires was fabricated to expand the photoelectric gain range. The device can actualize the sensitization features of the nociceptor and shows improved responsiveness to visible light. Under electrical pulses with different polarities, the apparatus exhibits reconfigurable asymmetric bidirectional plasticity. Moreover, the devices demonstrate good operational tolerance and mechanical stability, retaining more than 60% of their maximum responsiveness after 100 consecutive/bidirectional and 1000 flex/flat operations. The improved photoelectric response of the device endows a high image recognition accuracy of greater than 80%. Asymmetric bidirectional plasticity is used as punishment/reward in a psychological experiment to emulate the improvement of learning motivation and enables real-time forward and backward deflection (+7 and -25°) of artificial muscle. The mixed-dimensional optoelectronic artificial synapses with switchable behavior and electron/hole transport type have important prospects for neuromorphic processing and artificial somatosensory nerves.

Ultralow Subthreshold Swing of a MOSFET Caused by Ferroelectric Polarization Reversal of Hf0.5Zr0.5O2 Thin Films

The emergence of complementary metal-oxide semiconductor (CMOS)-compatible HfO2-based ferroelectric materials provides a promising way to achieve ferroelectric field-effect transistors (FeFETs) with a steep subthreshold swing (SS) reduced to below the Boltzmann thermodynamics limit (∼60 mV/dec at room temperature), which has important implications for lowering power consumption. In this work, a metal-oxide-semiconductor field-effect transistor (MOSFET) is connected with Hf0.5Zr0.5O2 (HZO)-based ferroelectric capacitors with different capacitances. By adjusting the capacitance of ferroelectric capacitors, an ultralow SS of ∼0.34 mV/dec in HfO2-based FeFETs can be achieved. More interestingly, by designing the sweeping voltage sequences, the SS can be adjusted to be 0 mV/dec with the drain current ranging over six orders of magnitude, and the threshold voltage for turning on the MOSFET can be further reduced. The manipulated SS could be attributed to the evolution of ferroelectric switching. Our work contributes to understanding the origin of ultralow SS in ferroelectric MOSFETs and the realization of low-power devices.

Ferroelectric-Gated All 2D Field-Effect Transistors with Sub-60 mV/dec Subthreshold Swing

With the continuous scaling down of the modern integrated circuits, conventional metal-oxide-semiconductor field effect transistors are becoming inefficient due to various nonideal effects such as enhanced short-channel effects. Recently, emerging two-dimensional (2D) ferroelectrics have demonstrated their ability to maintain ferroelectricity at the nanoscale and have shown superior properties compared to three-dimensional ferroelectrics. Here, we report a ferroelectric field effect transistor composed of all 2D van der Waals (vdWs) heterostructures and provide a comprehensive study of the modulation of ferroelectric polarization on the carrier transport properties. Remarkably, the ferroelectric polarization allowed for achieving an ultralow subthreshold swing of just 26 mV/dec and a high carrier mobility of up to 72.3 cm²/(V s) at a smaller drain voltage of 10 mV. These impressive characteristics offer new insights into evaluating the regulatory effect of ferroelectric polarization on the electrical properties of all 2D vdWs heterostructures.