Development of unconventional computing architectures, including neuromorphic computing, relies heavily on novel devices with properly engineered properties. This requires exploration of new ...functional materials and their designed interfaces. Ferroelectric memories including two‐terminal ferroelectric tunnel junctions and three‐terminal ferroelectric field‐effect transistors have shown promising performances in recent years as analog, multibit memory components with ultralow power consumption. However, for ferroelectric memory technology to become a mainstream technology, CMOS integration of these components is of major importance. For further diversifying their application to edge computing and smart sensing industry, a vast unchartered territory of low‐temperature processable and CMOS back‐end‐of‐line (BEOL) compatible materials needs to be researched. In recent years, doped HfO2‐based memory devices and in‐memory computing architectures have gathered huge momentum as one of the “beyond von Neumann” computing alternatives. In comparison, molecular ferroelectric‐based systems are still in their early exploratory phase. This review discusses the potential for doped HfO2 and molecular ferroelectrics as CMOS BEOL and flexible and wearable platform compatible neuromorphic devices and circuits and the challenges that need to be overcome for turning the opportunities to a technological reality.
Ferroelectric devices are promising as analog memories with ultralow power consumption. For maturity of ferroelectric memory technology, complementary metal oxide semiconductor integration is necessary. For wearable smart sensing, low‐temperature processable materials are vital. This review discusses the potential of ferroelectric based memory and neuromorphic systems and challenges that need further research for turning the opportunities to a technological reality.
The future computing beyond von Neumann era relies heavily on emerging devices that can extensively harness material and device physics to bring novel functionalities and can perform power-efficient ...and real time computing for artificial intelligence (AI) tasks. Additionally, brain-like computing demands large scale integration of synapses and neurons in practical circuits that requires the nanotechnology to support this hardware development, and all these should come at an affordable process complexity and cost to bring the solutions close to market rather soon. For bringing AI closer to quantum computing and space technologies, additional requirements are operation at cryogenic temperatures and radiation hardening. Considering all these requirements, nanoelectronic devices utilizing ferroic ordering has emerged as one promising alternative. The current review discusses the basic architectures of spintronic and ferroelectric devices for their integration in neuromorphic and analog memory applications, ferromagnetic and ferroelectric domain structures and control of their dynamics for reliable multibit memory operation, synaptic and neuronal leaky-integrate-and-fire (LIF) functions, concluding with their large-scale integration possibilities, challenges and future research directions.
The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Inspired by biological ...somatosensory systems, we report an optoelectronic spiking afferent nerve with neural coding, perceptual learning and memorizing capabilities to mimic tactile sensing and processing. Our system senses pressure by MXene-based sensors, converts pressure information to light pulses by coupling light-emitting diodes to analog-to-digital circuits, then integrates light pulses using a synaptic photomemristor. With neural coding, our spiking nerve is capable of not only detecting simultaneous pressure inputs, but also recognizing Morse code, braille, and object movement. Furthermore, with dimensionality-reduced feature extraction and learning, our system can recognize and memorize handwritten alphabets and words, providing a promising approach towards e-skin, neurorobotics and human-machine interaction technologies.
Materials engineering on the nanoscale by precise control of growth parameters can lead to many unusual and fascinating physical properties. The development of pulsed laser deposition (PLD) 25 years ...ago has enabled atomistic control of thin films and interfaces and as such it has contributed significantly to advances in fundamental material science. One application area is the research field of spintronics, which requires optimized nanomaterials for the generation and transport of spin-polarized carriers. The mixed-valence manganite La1−xSrxMnO3 (LSMO) is an interesting material for spintronics due to its intrinsic magnetoresistance properties, electric-field tunable metal-insulator transitions, and half-metallic band structure. Studies on LSMO thin-film growth by PLD show that the deposition temperature, oxygen pressure, laser fluence, strain due to substrate-film lattice mismatch and post-deposition annealing conditions significantly influence the magnetic and electrical transport properties of LSMO. For spintronic structures, robust ferromagnetic exchange interactions and metallic conductivity are desirable properties. In this paper, we review the physics of LSMO thin films and the important role that PLD played in advancing the field of LSMO-based spintronics. Some specific application areas including magnetic tunnel junctions, multiferroic tunnel junctions and organic spintronic devices are highlighted, and the advantages, drawbacks and opportunities of PLD-grown LSMO for next-generation spintronic devices are discussed.
Energy efficiency, parallel information processing, and unsupervised learning make the human brain a model computing system for unstructured data handling. Different types of oxide memristors can ...emulate synaptic functions in artificial neuromorphic circuits. However, their cycle‐to‐cycle variability or strict epitaxy requirements remain a challenge for applications in large‐scale neural networks. Here, solution‐processable ferroelectric tunnel junctions (FTJs) with P(VDF‐TrFE) copolymer barriers are reported showing analog memristive behavior with a broad range of accessible conductance states and low energy dissipation of 100 fJ for the onset of depression and 1 pJ for the onset of potentiation by resetting small tunneling currents on nanosecond timescales. Key synaptic functions like programmable synaptic weight, long‐ and short‐term potentiation and depression, paired‐pulse facilitation and depression, and Hebbian and anti‐Hebbian learning through spike shape and timing‐dependent plasticity are demonstrated. In combination with good switching endurance and reproducibility, these results offer a promising outlook on the use of organic FTJ memristors as building blocks in artificial neural networks.
A solution‐processable ferroelectric tunnel junction with P(VDF‐TrFE) barrier is investigated as electronic synapse for neuromorphic computing. Key synaptic functions like long‐ and short‐term potentiation, Hebbian and anti‐Hebbian learning, good switching endurance, and reproducibility are demonstrated. Broad range of accessible conductance states, nanosecond operating timescales, and ultra‐low energy dissipation offer promises for these devices as building blocks in artificial neural networks.
Online training of deep neural networks (DNN) can be significantly accelerated by performing in situ vector‐matrix multiplication in a crossbar array of analog memories. However, training accuracies ...often suffer due to nonideal properties of synapses such as nonlinearity, asymmetry, limited bit precision, and dynamic weight update range within a constrained power budget. Herein, a fully scalable process is reported for digital and analog ferroelectric memory transistors with possibilities for both volatile and nonvolatile data retention and <4 V operation that would be suitable as programmable synaptic weight elements. Ferroelectric copolymer P(VDF‐TrFE) gate insulator and 2D semiconductor MoS2 as the n‐type semiconducting channel material make them suitable for flexible and wearable substrate integration. The ferroelectric‐only devices show excellent performance as digital nonvolatile memory operating at <±5 V while the hybrid ferroelectric–dielectric devices show quasi‐continuous resistive switching resulting from gradual ferroelectric domain rotation. Analog conductance states of the hybrid devices allow good linearity and symmetry of weight updates and produce a dynamic conductance range of 104 with >16 reproducible conducting states. Network training experiments with these ferroelectric field‐effect transistors show >96% classification accuracy with Modified National Institute of Standards and Technology (MNIST) handwritten datasets highlighting their potential for implementation in scaled DNN architectures.
Herein, ferroelectric field‐effect transistors are reported which are compatible with the complementary metal–oxide–semiconductor back‐end‐of‐line operate at <4 V, and can work efficiently as digital and analog memory or synaptic weight element with nonvolatile or volatile data retention capability based on their gate stack composition. Ferroelectric copolymer P(VDF‐TrFE) gate ferroelectric and 2D semiconductor MoS2 n‐type channel material make the devices suitable for flexible and wearable substrate integration.
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Over the last few decades several vegetation indices were used to map Mangrove forest using satellite images. Difficulty still persists in discrimination of mangroves from ...non-mangrove vegetation, especially in areas where mangrove species are mixed with other vegetation types.
In the present study we have attempted to develop an improved index, which utilizes the information from the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) of Bhitarkanika mangrove forest of Odisha, India. These indices are negatively correlated (r = –0.988; p?<?0.01). Further, the NDWI values were subtracted from the NDVI values at the pixel level. As the outputs are negatively related, subtraction increases the upper and lower range of the overall output, also increasing the distinct values of two classes with near-similar spectral signatures. Same algorithm was applied on mangroves of Sundarbans (r = -0.987) and Andaman (r = -0.989).
A comparison between four established indices NDVI, NDWI, Soil Adjusted Vegetation Index (SAVI), Simple Ratio (SR) and the newly developed index namely Combined Mangrove Recognition Index (CMRI) were performed. Accuracy assessment using Kappa statistics, revealing that CMRI produces better accuracy (73.43%) compared to other indices, followed by NDVI (56.29%) and SR (48.79%).
Neuromorphic computing architectures demand the development of analog, non-volatile memory components operating at femto-Joule/bit operation energy. Electronic components working in this energy range ...require devices operating at ultrafast timescales. Among different non-volatile, analog memories, ferroelectric tunnel junctions (FTJs) have emerged as an important contender due to their voltage-driven operation leading to extreme energy-efficiency. Here, we report a study on the switching timescale and linear conductance modulation of organic FTJs comprising a metal/ferroelectric/semiconductor (MFS) stack with different morphologies of ferroelectric copolymer P(VDF-TrFE) ultrathin films. The results show that due to different annealing temperatures and protocols, the spin-coated copolymer films are modified significantly, which can have a large effect on the switching timescales and threshold fields of the FTJs with the best quality devices having a projected switching timescale of sub-nanosecond range. An improvement in switching speed by 7 orders of magnitude can be obtained with an increase of the programming voltage by less than a factor of 2 in these devices. This ultrafast switching of ferroelectric domains in our FTJs leads to pico to femto joule range of operation energy per bit opening the pathways for energy efficient and fast operating non-volatile memories while devices with higher domain pinning sites show a route for tuning analog conductivity for bio-realistic neuromorphic architectures.
Structural phase transitions driven by oxygen‐vacancy ordering can drastically affect the properties of transition metal oxides. The focused electron beam of a transmission electron microscope (TEM) ...can be used to control structural phase transitions in epitaxial La2/3Sr1/3MnO3. The ability to induce and characterize oxygen‐deficient structural phases simultaneously in a continuous and controllable manner opens up new pathways for atomic‐scale studies of transition metal oxides and other complex materials.
Neuromorphic computing architectures demand the development of analog, non-volatile memory components operating at femto-Joule/bit operation energy. Electronic components working in this energy range ...require devices operating at ultrafast timescales. Among different non-volatile, analog memories, ferroelectric tunnel junctions (FTJs) have emerged as an important contender due to their voltage-driven operation leading to extreme energy-efficiency. Here, we report a study on the switching timescale and linear conductance modulation of organic FTJs comprising a metal/ferroelectric/semiconductor (MFS) stack with different morphologies of ferroelectric copolymer P(VDF-TrFE) ultrathin films. The results show that due to different annealing temperatures and protocols, the spin-coated copolymer films are modified significantly, which can have a large effect on the switching timescales and threshold fields of the FTJs with the best quality devices having a projected switching timescale of sub-nanosecond range. An improvement in switching speed by 7 orders of magnitude can be obtained with an increase of the programming voltage by less than a factor of 2 in these devices. This ultrafast switching of ferroelectric domains in our FTJs leads to pico to femto joule range of operation energy per bit opening the pathways for energy efficient and fast operating non-volatile memories while devices with higher domain pinning sites show a route for tuning analog conductivity for bio-realistic neuromorphic architectures.
Ferroelectric copolymer morphology dependent resistive switching in tunneling devices shows operation down to nanosecond timescales and emulation of synaptic functions with good conductance linearity.
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