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.

Designs and Applications for the Multimodal Flexible Hybrid Epidermal Electronic Systems.

Research on the flexible hybrid epidermal electronic system (FHEES) has attracted considerable attention due to its potential applications in human-machine interaction and healthcare. Through material and structural innovations, FHEES combines the advantages of traditional stiff electronic devices and flexible electronic technology, enabling it to be worn conformally on the skin while retaining complex system functionality. FHEESs use multimodal sensing to enhance the identification accuracy of the wearer's motion modes, intentions, or health status, thus realizing more comprehensive physiological signal acquisition. However, the heterogeneous integration of soft and stiff components makes balancing comfort and performance in designing and implementing multimodal FHEESs challenging. Herein, multimodal FHEESs are first introduced in 2 types based on their different system structure: all-in-one and assembled, reflecting totally different heterogeneous integration strategies. Characteristics and the key design issues (such as interconnect design, interface strategy, substrate selection, etc.) of the 2 multimodal FHEESs are emphasized. Besides, the applications and advantages of the 2 multimodal FHEESs in recent research have been presented, with a focus on the control and medical fields. Finally, the prospects and challenges of the multimodal FHEES are discussed.

Performance Limits and Advancements in Single 2D Transition Metal Dichalcogenide Transistor.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) allow for atomic-scale manipulation, challenging the conventional limitations of semiconductor materials. This capability may overcome the short-channel effect, sparking significant advancements in electronic devices that utilize 2D TMDs. Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance. This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor. It delves into the impacts of miniaturization, including the reduction of channel length, gate length, source/drain contact length, and dielectric thickness on transistor operation and performance. In addition, this review provides a detailed analysis of performance parameters such as source/drain contact resistance, subthreshold swing, hysteresis loop, carrier mobility, on/off ratio, and the development of p-type and single logic transistors. This review details the two logical expressions of the single 2D-TMD logic transistor, including current and voltage. It also emphasizes the role of 2D TMD-based transistors as memory devices, focusing on enhancing memory operation speed, endurance, data retention, and extinction ratio, as well as reducing energy consumption in memory devices functioning as artificial synapses. This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices. This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications. It underscores the anticipated challenges, opportunities, and potential solutions in navigating the dimension and performance boundaries of 2D transistors.

All-Solution-Processed Electronics with Sub-Microscale Resolution and Nanoscale Fidelity Fabricated Via a Humidity-Controlled, Surface Energy-Directed Assembly Process.

Solution-based processes have received considerable attention in the fabrication of electronics and sensors owing to their merits of being low-cost, vacuum-free, and simple in equipment. However, the current solution-based processes either lack patterning capability or have low resolution (tens of micrometers) and low pattern fidelity in terms of line edge roughness (LER, several micrometers). Here, we present a surface energy-directed assembly (SEDA) process to fabricate metal oxide patterns with up to 2 orders of magnitude improvement in resolution (800 nm) and LER (16 nm). Experiment results show that high pattern fidelity can be achieved only at low relative humidities of below 30%. The reason for this phenomenon lies in negligible water condensation on the solution droplet. Employing the SEDA process, all-solution-processed metal oxide thin film transistors (TFTs) are fabricated by using indium oxide as channel layers, indium tin oxide as source/drain electrodes and gate electrodes, and aluminum oxide as gate dielectrics. TFT-based logic gate circuits, including NOT, NOR, NAND, and AND are fabricated as well, demonstrating the applicability of the SEDA process in fabricating large area functional electronics.

All-Fiber Flexible Electrochemical Sensor for Wearable Glucose Monitoring.

Wearable sensors, specifically microneedle sensors based on electrochemical methods, have expanded extensively with recent technological advances. Today's wearable electrochemical sensors present specific challenges: they show significant modulus disparities with skin tissue, implying possible discomfort in vivo, especially over extended wear periods or on sensitive skin areas. The sensors, primarily based on polyethylene terephthalate (PET) or polyimide (PI) substrates, might also cause pressure or unease during insertion due to the skin's irregular deformation. To address these constraints, we developed an innovative, wearable, all-fiber-structured electrochemical sensor. Our composite sensor incorporates polyurethane (PU) fibers prepared via electrospinning as electrode substrates to achieve excellent adaptability. Electrospun PU nanofiber films with gold layers shaped via thermal evaporation are used as base electrodes with exemplary conductivity and electrochemical catalytic attributes. To achieve glucose monitoring, gold nanofibers functionalized by gold nanoflakes (AuNFs) and glucose oxidase (GOx) serve as the working electrode, while Pt nanofibers and Ag/AgCl nanofibers serve as the counter and reference electrode. The acrylamide-sodium alginate double-network hydrogel synthesized on electrospun PU fibers serves as the adhesive and substance-transferring layer between the electrodes. The all-fiber electrochemical sensor is assembled layer-by-layer to form a robust structure. Given the stretchability of PU nanofibers coupled with a high specific surface area, the manufactured porous microneedle glucose sensor exhibits enhanced stretchability, superior sensitivity at 31.94 µA (lg(mM))-1 cm-2, a broad detection range (1-30 mM), and a significantly low detection limit (1 mM, S/N = 3), as well as satisfactory biocompatibility. Therefore, the novel electrochemical microneedle design is well-suited for wearable or even implantable continuous monitoring applications, thereby showing promising significant potential within the global arena of wearable medical technology.

Single Crystal Perovskite/Graphene Self-Driven Photodetector with Fast Response Speed.

Recently, the combination of two-dimensional (2D) materials and perovskites has gained increasing attention in optoelectronic applications owing to their excellent optical and electrical characteristics. Here, we report a self-driven photodetector consisting of a monolayer graphene sheet and a centimeter-sized CH3NH3PbBr3 single crystal, which was prepared using an optimized wet transfer method. The photodetector exhibits a short response time of 2/30 µs by virtue of its high-quality interface, which greatly enhances electron-hole pair separation in the heterostructure under illumination. In addition, a responsivity of ~0.9 mA/W and a detectivity over 1010 Jones are attained at zero bias. This work inspires new methods for preparing large-scale high-quality perovskite/2D material heterostructures, and provides a new direction for the future enhancement of perovskite optoelectronics.

A Large-Scale and Low-Cost Thermoacoustic Loudspeaker Based on Three-Dimensional Graphene Foam.

Graphene is a promising material for thermoacoustic sources due to its extremely low heat capacity per unit area and high thermal conductivity. However, current graphene thermoacoustic devices have limited device area and relatively high cost, which limit their applications of daily use. Here, we adopt a dip-coating method to fabricate a large-scale and cost-effective graphene sound source. This sound source has the three-dimensional (3D) porous structure that can increase the contact area between graphene and air, thus assisting heat to release into the air. In this method, polyurethane (PU) is used as a support, and graphene nanoplates are attached onto the PU skeleton so that a highly flexible graphene foam (GrF) device is obtained. At a measuring distance of 1 mm, it can emit sound at up to 70 dB under the normalized input power of 1 W. Considering its unique porous structure, we establish a thermoacoustic analysis model to simulate the acoustic performance of GrF. Furthermore, the obtained GrF can be made up to 44 in. (100 cm × 50 cm) in size, and it has good flexibility and processability, which broadens the application fields of GrF loudspeakers. It can be attached to the surfaces of objects with different shapes, making it suitable to be used as a large-area speaker in automobiles, houses, and other application scenarios, such as neck mounted speaker. In addition, it can also be widely used as a fully flexible in-ear earphone.

An Artificial LiSiOx Nociceptor with Neural Blockade and Self-Protection Abilities.

An artificial nociceptor, as a critical and special bionic receptor, plays a key role in a bioelectronic device that detects stimuli and provides warnings. However, fully exploiting bioelectronic applications remains a major challenge due to the lack of the methods of implementing basic nociceptor functions and nociceptive blockade in a single device. In this work, we developed a Pt/LiSiOx/TiN artificial nociceptor. It had excellent stability under the 104 endurance test with pulse stimuli and exhibited a significant threshold current of 1 mA with 1 V pulse stimuli. Other functions such as relaxation, inadaptation, and sensitization were all realized in a single device. Also, the pain blockade function was first achieved in this nociceptor with over a 25% blocking degree, suggesting a self-protection function. More importantly, an obvious depression was activated by a stimulus over 1.6 V due to the cooperative effects of both lithium ions and oxygen ions in LiSiOx and the dramatic accumulation of Joule heat. The conducting channel ruptured partially under sequential potentiation, thus achieving nociceptive blockade, besides basic functions in one single nociceptor, which was rarely reported. These results provided important guidelines for constructing high-performance memristor-based artificial nociceptors and opened up an alternative approach to the realization of bioelectronic systems for artificial intelligence.

Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with ß-Cyclodextrins.

A surface-enhanced Raman scattering (SERS) method for measuring nitrate nitrogen in aquaculture water was developed using a substrate of ß-cyclodextrin-modified gold nanoparticles (SH-ß-CD@AuNPs). Addressing the issues of low sensitivity, narrow linear range, and relatively poor selectivity of single metal nanoparticles in the SERS detection of nitrate nitrogen, we combined metal nanoparticles with cyclodextrin supramolecular compounds to prepare a AuNPs substrate enveloped by cyclodextrin, which exhibits ultra-high selectivity and Raman activity. Subsequently, vanadium(III) chloride was used to convert nitrate ions into nitrite ions. The adsorption mechanism between the reaction product benzotriazole (BTAH) of o-phenylenediamine (OPD) and nitrite ions on the SH-ß-CD@AuNPs substrate was studied through SERS, achieving the simultaneous detection of nitrate nitrogen and nitrite nitrogen. The experimental results show that BTAH exhibits distinct SERS characteristic peaks at 1168, 1240, 1375, and 1600 cm-1, with the lowest detection limits of 3.33 × 10-2, 5.84 × 10-2, 2.40 × 10-2, and 1.05 × 10-2 µmol/L, respectively, and a linear range of 0.1-30.0 µmol/L. The proposed method provides an effective tool for the selective and accurate online detection of nitrite and nitrate nitrogen in aquaculture water.

Laser-Induced Skin-like Flexible Pressure Sensor for Artificial Intelligence Speech Recognition.

Skin-like flexible pressure sensors with good sensing performance have great application potential, but their development is limited owing to the need for multistep, high-cost, and low-efficiency preparation processes. Herein, a simple, low-cost, and efficient laser-induced forming process is proposed for the first time to prepare a skin-like flexible piezoresistive sensor. In the laser-induced forming process, based on the photothermal effect of graphene and the foaming effect of glucose, a skin-like polydimethylsiloxanes (PDMS) film with porous structures and surface protrusions is obtained by using infrared laser irradiation of the glucose/graphene/PDMS prepolymer film. Further, based on the skin-like PDMS film with a graphene conductive layer, a new skin-like flexible piezoresistive sensor is obtained. Due to the stress concentration caused by the surface protrusions and the low stiffness caused by the porous structures, the flexible piezoresistive sensor realizes an ultrahigh sensitivity of 1348 kPa-1 at 0-2 kPa, a wide range of 200 kPa, a fast response/recovery time of 52 ms/35 ms, and good stability over 5000 cycles. The application of the sensor to the detection of human pulses and robot clamping force indicates its potential for health monitoring and soft robots. Furthermore, in combination with the neural network (CNN) algorithm in artificial intelligence technology, the sensor achieves 95% accuracy in speech recognition, which demonstrates its great potential for intelligent wearable electronics. Especially, the laser-induced forming process is expected to facilitate the efficient, large-scale preparation of flexible devices with multilevel structures.

The Roadmap of 2D Materials and Devices Toward Chips.

Due to the constraints imposed by physical effects and performance degradation, silicon-based chip technology is facing certain limitations in sustaining the advancement of Moore's law. Two-dimensional (2D) materials have emerged as highly promising candidates for the post-Moore era, offering significant potential in domains such as integrated circuits and next-generation computing. Here, in this review, the progress of 2D semiconductors in process engineering and various electronic applications are summarized. A careful introduction of material synthesis, transistor engineering focused on device configuration, dielectric engineering, contact engineering, and material integration are given first. Then 2D transistors for certain electronic applications including digital and analog circuits, heterogeneous integration chips, and sensing circuits are discussed. Moreover, several promising applications (artificial intelligence chips and quantum chips) based on specific mechanism devices are introduced. Finally, the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed, and potential development pathways or roadmaps are further speculated and outlooked.

Programmable Ferroelectricity in Hf0.5Zr0.5O2 Enabled by Oxygen Defect Engineering.

Ferroelectricity, especially the Si-compatible type recently observed in hafnia-based materials, is technologically useful for modern memory and logic applications, but it is challenging to differentiate intrinsic ferroelectric polarization from the polar phase and oxygen vacancy. Here, we report electrically controllable ferroelectricity in a Hf0.5Zr0.5O2-based heterostructure with Sr-doped LaMnO3, a mixed ionic-electronic conductor, as an electrode. Electrically reversible extraction and insertion of an oxygen vacancy into Hf0.5Zr0.5O2 are macroscopically characterized and atomically imaged in situ. Utilizing this reversible process, we achieved multilevel polarization states modulated by the electric field. Our study demonstrates the usefulness of the mixed conductor to repair, create, manipulate, and utilize advanced ferroelectric functionality. Furthermore, the programmed ferroelectric heterostructures with Si-compatible doped hafnia are desirable for the development of future ferroelectric electronics.

Polarized Tunneling Transistor for Ultralow-Energy-Consumption Artificial Synapse toward Neuromorphic Computing.

Neural networks based on low-power artificial synapses can significantly reduce energy consumption, which is of great importance in today's era of artificial intelligence. Two-dimensional (2D) material-based floating-gate transistors (FGTs) have emerged as compelling candidates for simulating artificial synapses owing to their multilevel and nonvolatile data storage capabilities. However, the low erasing/programming speed of FGTs renders them unsuitable for low-energy-consumption artificial synapses, thereby limiting their potential in high-energy-efficient neuromorphic computing. Here, we introduce a FGT-inspired MoS2/Trap/PZT heterostructure-based polarized tunneling transistor (PTT) with a simple fabrication process and significantly enhanced erasing/programming speed. Distinct from the FGT, the PTT lacks a tunnel layer, leading to a marked improvement in its erasing/programming speed. The PTT's highest erasing/programming (operation) speed can reach ∼20 ns, which outperforms the performance of most FGTs based on 2D heterostructures. Furthermore, the PTT has been utilized as an artificial synapse, and its weight-update energy consumption can be as low as 0.0002 femtojoule (fJ), which benefits from the PTT's ultrahigh operation speed. Additionally, PTT-based artificial synapses have been employed in constructing artificial neural network simulations, achieving facial-recognition accuracy (95%). This groundbreaking work makes it possible for fabricating future high-energy-efficient neuromorphic transistors utilizing 2D materials.

Graphene-based Two-Stage Enhancement Pressure Sensor for Subtle Mechanical Force Monitoring.

The development of pressure sensors with high sensitivity and a low detection limit for subtle mechanical force monitoring and the understanding of the sensing mechanism behind subtle mechanical force monitoring are of great significance for intelligent technology. Here, we proposed a graphene-based two-stage enhancement pressure sensor (GTEPS), and we analyzed the difference between subtle mechanical force monitoring and conventional mechanical force monitoring. The GTEPS exhibited a high sensitivity of 62.2 kPa-1 and a low detection limit of 0.1 Pa. Leveraging its excellent performance, the GTEPS was successfully applied in various subtle mechanical force monitoring applications, including acoustic wave detection, voice-print recognition, and pulse wave monitoring. In acoustic wave detection, the GTEPS achieved a 100% recognition accuracy for six words. In voiceprint recognition, the sensor exhibited accurate identification of distinct voiceprints among individuals. Furthermore, in pulse wave monitoring, GTEPS demonstrated effective detection of pulse waves. By combination of the pulse wave signals with electrocardiogram (ECG) signals, it enabled the assessment of blood pressure. These results demonstrate the excellent performance of GTEPS and highlight its great potential for subtle mechanical force monitoring and its various applications. The current results indicate that GTEPS shows great potential for applications in subtle mechanical force monitoring.

Probing the Strain Direction-Dependent Nonmonotonic Optical Bandgap Modulation of Layered Violet Phosphorus.

Recent theoretical investigations have well-predicted strain-induced nonmonotonic optical band gap variations in low-dimensional materials. However, few two-dimensional (2D) materials are experimentally confirmed to exhibit nonmonotonic optical band gap variation under varying strain. Here, a strain-induced nonmonotonic optical bandgap variation in violet phosphorus (VP) nanosheets is observed, as evidenced by photoluminescence spectroscopy, which is reported in a few other 2D materials in knowledge. The optical bandgap variations are characterized to show the modulation rates of 41 and -24 meV/% with compression and tensile strains, respectively. Remarkably, first-principle calculations predict and clarify the nonmonotonic modulation accurately, highlighting its relationship with the strain direction-dependent asymmetric distribution of conduction band minimum wavefunctions, demonstrating that this unique nonmonotonic optical bandgap modulation is determined by the distinctive crystal structure of VP. This work provides a deep insight into the design of 2D materials toward optoelectronic and photoelectrochemical applications via strain engineering.

PZT-Enabled MoS2 Floating Gate Transistors: Overcoming Boltzmann Tyranny and Achieving Ultralow Energy Consumption for High-Accuracy Neuromorphic Computing.

Low-power electronic devices play a pivotal role in the burgeoning artificial intelligence era. The study of such devices encompasses low-subthreshold swing (SS) transistors and neuromorphic devices. However, conventional field-effect transistors (FETs) face the inherent limitation of the "Boltzmann tyranny", which restricts SS to 60 mV decade-1 at room temperature. Additionally, FET-based neuromorphic devices lack sufficient conductance states for highly accurate neuromorphic computing due to a narrow memory window. In this study, we propose a pioneering PZT-enabled MoS2 floating gate transistor (PFGT) configuration, demonstrating a low SS of 46 mV decade-1 and a wide memory window of 7.2 V in the dual-sweeping gate voltage range from -7 to 7 V. The wide memory window provides 112 distinct conductance states for PFGT. Moreover, the PFGT-based artificial neural network achieves an outstanding facial-recognition accuracy of 97.3%. This study lays the groundwork for the development of low-SS transistors and highly energy efficient artificial synapses utilizing two-dimensional materials.

Landauer-QFLPS Model for Mixed Schottky-Ohmic Contact Two-Dimensional Transistors.

Two-dimensional material-based field-effect transistors (2DM-FETs) are playing a revolutionary role in electronic devices. However, before electronic design automation (EDA) for 2DM-FETs can be achieved, it remains necessary to determine how to incorporate contact transports into model. Reported methods compromise between physical intelligibility and model compactness due to the heterojunction nature. To address this, quasi-Fermi-level phase space theory (QFLPS) is generalized to incorporate contact transports using the Landauer formula. It turns out that the Landauer-QFLPS model effectively overcomes the issue of concern. The proposed new formula can describe 2DM-FETs with Schottky or Ohmic contacts with superior accuracy and efficiency over previous methods, especially when describing non-monotonic drain conductance characteristics. A three-bit threshold inverter quantizer (TIQ) circuit is fabricated using ambipolar black phosphorus and it is demonstrated that the model accurately predicts circuit performance. The model could be very effective and valuable in the development of 2DM-FET-based integrated circuits.

Wearable Temperature Sensors Based on Reduced Graphene Oxide Films.

With the development of medical technology and increasing demands of healthcare monitoring, wearable temperature sensors have gained widespread attention because of their portability, flexibility, and capability of conducting real-time and continuous signal detection. To achieve excellent thermal sensitivity, high linearity, and a fast response time, the materials of sensors should be chosen carefully. Thus, reduced graphene oxide (rGO) has become one of the most popular materials for temperature sensors due to its exceptional thermal conductivity and sensitive resistance changes in response to different temperatures. Moreover, by using the corresponding preparation methods, rGO can be easily combined with various substrates, which has led to it being extensively applied in the wearable field. This paper reviews the state-of-the-art advances in wearable temperature sensors based on rGO films and summarizes their sensing mechanisms, structure designs, functional material additions, manufacturing processes, and performances. Finally, the possible challenges and prospects of rGO-based wearable temperature sensors are briefly discussed.

Macroscopic negative differential thermal resistance in the overlapping graphene homojunction structure.

As one of the most potential ways to manipulate heat, thermal functional devices have achieved several breakthroughs in recent years, but are still limited to theoretical simulations. One of its theoretical bases is the existence of the negative differential thermal resistance (NDTR). However, most of the existing systems where the phenomenon of NDTR is found are atomic-level systems. In order to realize the macroscopic NDTR and provide effective theoretical guidance and support for the practical realization of thermal functional devices, we construct the overlapping graphene homojunction model, using the negative thermal expansion property of graphene to modify the overlapping area, and thus regulating the heat flow. The COMSOL-MATLAB co-simulation is used to perform calculations through negative feedback loops. It is found that the NDTR phenomenon exists under certain parameter conditions, which can provide new ideas and bring more opportunities for the experimental realization of nonlinear thermal functional devices.

Diverse long-term potentiation and depression based on multilevel LiSiOxmemristor for neuromorphic computing.

Memristor-based neuromorphic computing is expected to overcome the bottleneck of von Neumann architecture. An artificial synaptic device with continuous conductance variation is essential for implementing bioinspired neuromorphic systems. In this work, a memristor based on Pt/LiSiOx/TiN structure is developed to emulate an artificial synapse, which shows non-volatile multilevel resistance state memory behavior. Moreover, the high nonlinearity caused by abrupt changes in the set process is optimized by adjusting the initial resistance. 100 levels of continuously modulated conductance states are achieved and the nonlinearity factors are reduced to 1.31. The significant improvement is attributed to the decrease in the Schottky barrier height and the evolution of the conductive filaments. Finally, due to the improved linearity of the long-term potentiation/long-term depression behaviors in LiSiOxmemristor, a robust recognition rate (∼94.58%) is achieved for pattern recognition with the modified National Institute of Standards and Technology handwriting database. The Pt/LiSiOx/TiN memristor shows significant potential in high-performance multilevel data storage and neuromorphic computing systems.