The continuous development of electron devices towards the trend of “More than Moore” requires functional diversification that can collect data (sensors) and store (memories) and process (computing ...units) information. Considering the large occupation proportion of image data in both data center and edge devices, a device integration with optical sensing and data storage and processing is highly demanded for future energy-efficient and miniaturized electronic system. Two-dimensional (2D) materials and their heterostructures have exhibited broadband photoresponse and high photoresponsivity in the configuration of optical sensors and showed fast switching speed, multi-bit data storage, and large ON/OFF ratio in memory devices. In addition, its ultrathin body thickness and transfer process at low temperature allow 2D materials to be heterogeneously integrated with other existing materials system. In this paper, we overview the state-of-the-art optoelectronic random-access memories (ORAMs) based on 2D materials, as well as ORAM synaptic devices and their applications in neural network and image processing. The ORAM devices potentially enable direct storage/processing of sensory data from external environment. We also provide perspectives on possible directions of other neuromorphic sensor design (
e.g
., auditory and olfactory) based on 2D materials towards the future smart electronic systems for artificial intelligence.
In-sensor and near-sensor computing are becoming the next-generation computing paradigm for high-density and low-power sensory processing. To fulfil a high-density and efficient neuromorphic visual ...system with fully hierarchical emulation of the retina and visual cortex, emerging multimodal neuromorphic devices for multi-stage processing and a fully hardware-implemented system with versatile image processing functions are still lacking and highly desirable. Here we demonstrate an emerging multimodal-multifunctional resistive random-access memory (RRAM) device array based on modified silk fibroin protein (MSFP), exhibiting both optoelectronic RRAM (ORRAM) mode featured by unique negative and positive photoconductance memory and electrical RRAM (ERRAM) mode featured by analogue resistive switching. A full hardware implementation of the artificial visual system with versatile image processing functions is realised for the first time, including ORRAM mode array for the in-sensor image pre-processing (contrast enhancement, background denoising, feature extraction) and ERRAM mode array for near-sensor high-level image recognition, which hugely improves the integration density, and simply the circuit design and the fabrication and integration complexity.
To alleviate photoinduced charge recombination in semiconducting nanomaterials represents an important endeavor toward high‐efficiency photocatalysis. Here a judicious integration of piezoelectric ...and photocatalytic properties of organolead halide perovskite CH3NH3PbI3 (MAPbI3) to enable a piezophotocatalytic activity under simultaneous ultrasonication and visible light illumination for markedly enhanced photocatalytic hydrogen generation of MAPbI3 is reported. The conduction band minimum of MAPbI3 is higher than hydrogen generation potential (0.046 V vs normal hydrogen electrode), thereby rendering efficient hydrogen evolution. In addition, the noncentrosymmetric crystal structure of MAPbI3 enables its piezoelectric properties. Thus, MAPbI3 readily responds to external mechanical force, creating a built‐in electric field for collective piezophotocatalysis as a result of effective separation of photogenerated charge carriers. The experimental results show that MAPbI3 powders exhibit superior piezophotocatalytic hydrogen generation rate (23.30 µmol h−1) in hydroiodic acid (HI) solution upon concurrent light and mechanical stimulations, much higher than that of piezocatalytic (i.e., 2.21 µmol h−1) and photocatalytic (i.e., 3.42 µmol h−1) hydrogen evolution rate as well as their sum (i.e., 5.63 µmol h−1). The piezophotocatalytic strategy provides a new way to control the recombination of photoinduced charge carriers by cooperatively capitalizing on piezocatalysis and photocatalysis of organolead halide perovskites to yield highly efficient piezophotocatalysis.
CH3NH3PbI3 exhibits a superior piezophotocatalytic hydrogen generation rate upon concurrent light and mechanical stimulations, much higher than that of piezocatalytic and photocatalytic hydrogen evolution rate as well as their sum. Combining piezocatalysis and photocatalysis of semiconductor photocatalysts to attain a collective piezophotocatalysis may represent an appealing strategy for efficient solar energy conversion, including water splitting, organic fuel production, etc.
•A climate-adaptive transfer learning framework for soil moisture estimation is proposed.•The framework mainly uses ERA5-Land data, ISMN data, and global Köppen climate classification data.•The ...framework is designed for data-scarce region and performed well on the Qinghai-Tibet Plateau.•The framework can contribute to historical soil moisture data reconstruction.•A long-term (1960–2019) soil moisture dataset with accuracy improvement is produced.
Soil moisture (SM) plays essential roles in revealing complex interaction mechanisms among air–soil-water-plant processes. In the Qinghai-Tibet Plateau (QTP), the in-situ SM data is sparse and limited, satellite-based SM data has short period, while reanalysis SM data has advantages on long-term and high spatiotemporal resolution but has relatively high error. In this study, to improve soil moisture estimation in the QTP, we aim to propose a Climate-Adaptive Transfer Learning (CATL) framework for data scarce region based on reanalysis data (ERA5-LAND dataset) and the in-situ data (International Soil Moisture Network (ISMN) data). Specifically, regarding the QTP as the target region, selecting the areas with similar climate types with QTP as the source region, we train the CNN-LSTM fusion model in the source region and then transfer it to the target region via fine-tuning strategy. Results indicate that the produced soil moisture data based on CATL framework achieves CC of 0.755 and ubRMSE of 0.042, which has better quality than SMAPL3 during 2015–2019. Additionally, the CATL framework also produced the historical SM data reconstruction during 1960–2010, with CC increased by 11.3 % and ubRMSE reduced by 1.5 % compared with the original ERA5-Land reanalysis data. Furthermore, compared to the direct fine-tuning strategy (without climate adaptive), the CATL framework showed an increase of CC with 2.6 %, and decreases in RMSE, MAE, and ubRMSE of 5.3 %, 4.2 %, and 7.5 %, respectively. Finally, an improved soil moisture dataset (daily, 0.05°) ranging from 1960 to 2019 is produced for the QTP. This study provides a new tool for soil moisture estimation improvement in data-scarce region which will also benefit basin hydrology and water resources management.
Abstract
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
FE
/
µ
o
) of 85/140 cm
2
/V·s is presented here. The ZnO TFT was integrated with HfO
2
RRAM in a 1 kbit (32 × 32) 1T1R array, demonstrating functionalities in RRAM switching. In order to co-design for future technology requiring high performance BEOL circuitries implementation, a spice-compatible model of the ZnO TFTs was developed. We then present designs of various ZnO TFT-based inverters, and 5-stage ring oscillators through simulations and experiments with working frequency exceeding 10’s of MHz.
Physically unclonable crypto primitives have potential applications for anti-counterfeiting, identification, and authentication, which are clone proof and resistant to variously physical attack. ...Conventional physical unclonable function (PUF) based on Si complementary metal-oxide-semiconductor (CMOS) technologies greatly suffers from entropy loss and bit instability due to noise sensitivity. Here we grow atomically thick MoS
2
thin film and fabricate field-effect transistors (FETs). The inherently physical randomness of MoS
2
transistors from materials growth and device fabrication process makes it appropriate for the application of PUF device. We perform electrical characterizations of MoS
2
FETs, collect the data from 448 devices, and generate PUF keys by splitting drain current at specific levels to evaluate the response performance. Proper selection of splitting threshold enables to generate binary, ternary, and double binary keys. The generated PUF keys exhibit good randomness and uniqueness, providing a possibility for harvesting highly secured PUF devices with two-dimensional materials.
Photovoltachromic cells (PVCCs) are of great interest for the self-powered smart windows of architectures and vehicles, which require widely tunable transmittance and automatic color change under ...photostimuli. Organolead halide perovskite possesses high light absorption coefficient and enables thin and semitransparent photovoltaic device. In this work, we demonstrate co-anode and co-cathode photovoltachromic supercapacitors (PVCSs) by vertically integrating a perovskite solar cell (PSC) with MoO3/Au/MoO3 transparent electrode and electrochromic supercapacitor. The PVCSs provide a seamless integration of energy harvesting/storage device, automatic and wide color tunability, and enhanced photostability of PSCs. Compared with conventional PVCC, the counter electrodes of our PVCSs provide sufficient balancing charge, eliminate the necessity of reverse bias voltage for bleaching the device, and realize reasonable in situ energy storage. The color states of PVCSs not only indicate the amount of energy stored and energy consumed in real time, but also enhance the photostability of photovoltaic component by preventing its long-time photoexposure under fully charged state of PVCSs. This work designs PVCS devices for multifunctional smart window applications commonly made of glass.
As a zero-carbon fuel, hydrogen is considered a promising alternative fuel. Hydrogen flames can be greatly affected by intrinsic instabilities including the diffusional-thermal instability (DTI) and ...Darrieus-Landau instability (DLI). Therefore, it is important to understand their properties, especially for cryogenic flames that are related to the safe utilization of liquid hydrogen. In this work, we conduct two-dimensional simulations of unsteady hydrogen/air conical flames to assess the effects of intrinsic instabilities, DTI and DLI, on the response of premixed hydrogen/air conical flames to inlet flow perturbations. The equivalence ratio and initial temperature are changed to respectively achieve different Lewis numbers (related to DTI) and expansion ratios (related to DLI). It is found that under certain conditions flame pinch-off occurs, during which a separated flame pocket is formed by the strong amplification of flame wrinkles generated by the inlet flow perturbations. The underlying mechanism of flame pinch-off enhancement due to DTI and DLI is different. For fuel-lean hydrogen/air at normal temperature, the flame front wrinkling is enhanced by strong DTI and it is the stretch-chemistry interaction that leads to flame pinch-off. However, for stoichiometric hydrogen/air at cryogenic temperature, there is a strong effect of DLI and flame pinch-off is mainly induced by flame-flow interaction. Moreover, downstream flow and flame speed near the separated flame pocket for flames exhibiting strong DTI and DLI are compared and the difference is analyzed. The findings indicate that intrinsic flame instability can amplify flame wrinkling and fluctuations in heat release rate, thereby contributing to flame pinch-off.
Ion migration as well as electron transfer and coupling in resistive switching materials endow memristors with a physically tunable conductance to resemble synapses, neurons, and their networks. Four ...different types of volatile memristors and another four types of nonvolatile memristors are systemically surveyed in terms of the switching mechanisms and electrical properties that are the basis of different computing applications. The volatile memristor features spontaneous conductance decay after the cease of electrical/optical stimulations, which are closely related to the surface atom diffusion, metal–insulator–transition (including charge–density–wave), thermal spontaneous emission, and charge polarization. Such unique dynamic state evolution at the edge of chaos has enabled them to emulate certain synaptic and neural dynamics, leading to various applications ranging from spiking neural networks to combinatorial optimizations. Nonvolatile resistive switching behavior originated from the electron spins, ferroelectric polarization, crystalline‐amorphous transitions or interplay between ions and electrons enables the memristor array to implement the vector–matrix multiplication, which is the key convolutional operation in artificial neural networks. The progress, challenges, and opportunities for both volatile and nonvolatile memristor in the level of materials, integration technology, algorithm, and system are highlighted in this review.
Four volatile memristors and four nonvolatile memristors in terms of the switching dynamics, application in neuromorphic computing, and architectures of memristor arrays are systemically summarized. The motivation of this review is to refine the conception of volatile and nonvolatile memristor, summarizes the important progress in hardware technology, and proposes the possible solutions in different level for memristor‐based neuromorphic computing.
Accurate quantification of heat release rate (HRR) profiles is useful for identifying important combustion processes in practical engines. This study aims to show whether the conventional HRR markers ...can still be used for highly stretched premixed methane/air flames with and without hydrogen addition. The correlation of formaldehyde-based molar concentrations, HCH2O and OHCH2O, with HRR is numerically studied for highly stretched premixed CH4/air and CH4/H2/air flames. Two types of premixed flames are considered: the spherically expanding flame (SEF) starting from a highly positively stretched ignition kernel and the Bunsen flame with a high negative stretch rate at the flame tip. It is found that both HCH2O and OHCH2O can qualitatively describe the spatial distribution of HRR profiles in these two types of flames. In comparison to HCH2O, OHCH2O is slightly better because it has a higher correlation coefficient and weaker sensitivity to the stoichiometry. However, during the ignition-influenced regime of SEFs, the magnitude of HRR cannot be accurately correlated by the concentrations of CH2O, OH, and H. Besides, hydrogen addition does not change the good spatial reconstruction qualities of these two HRR markers when its volume fraction in methane/hydrogen binary fuel blends is below 70%. The present results demonstrate that the conventional HRR markers, OHCH2O and HCH2O, can be used to quantify the shape of HRR profiles even for highly stretched premixed flames with a small amount of hydrogen addition. Nevertheless, the magnitude of HRR cannot be accurately correlated by these two HRR markers for a highly stretched ignition kernel and hydrogen-dominated binary fuel blends.
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