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Although remarkable improvement has been achieved in stretchable strain sensors, challenges still exist in aspects including intelligent sensing, simultaneous data processing, and scalable fabrication techniques. In this work, a strain-sensitive device is presented by fabricating a CsPbBr3 quantum dots (QDs) floating-gate field-effect transistor (FET) sensing array on thin polyimide (PI) films. The FET exhibits an excellent on/off ratio (>103) and a large memory window (>2 V). With the introduction of CsPbBr3 QDs as the trapping layer, an additional UV response is obtained because of the photogenerated charge carriers that significantly enhance the source-drain current (IDS) of the device. At each electrical state, the IDS varies with the strains and the sensing range is from compressive +12.5% to tensile -10.8%. Excellent data retainability and mechanical durability demonstrate the high quality and reliability of the fabricated sensors. Furthermore, synapse functions including long-term potentiation (LTP), long-term depression (LTD), etc., are emulated at the device level. Linearity factor changes of LTP/LTD in different sensing scenarios demonstrate the reliability of the device and further confirm the different sensing mechanisms with/without UV illumination. Our results exhibit the potential of transistor-based devices for multifunctional intelligent sensing.

It is of great significance to develop multifunction-integrated photoelectric synaptic devices with the simple structure to imitate the functions of eyes. In this work, we reported the multimodal photoelectric neuromorphic thin film transistors (TFTs) with single gate and two input terminals using sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) mixed with lead-free perovskite (CsBi3I10) and lightly n-doped silicon as active layers and gate electrodes. The results showed that optical and electrical responses of SWCNT TFTs could increase 26 and 23 times after addition of CsBi3I10 under the same pulse sequence stimulation, respectively. Apart from emulating a series of typical synaptic functionalities, an artificial neural network based on SWCNT phototransistors was simulated to be trained for the recognition of handwritten digits in the Modified National Institute of Standards and Technology with the maximum accuracy of about 85.46%. Moreover, our synaptic devices can imitate traditional Pavlovian conditioning, and show NOR logic, reproducible flash memory functions under the optical and electrical programming stimulations. It is noted that the erasing voltage (3 V, 0.2 s) is one of the best value among the reported phototransistor memory. Furthermore, our synaptic devices can work well after more than 150 programming/erasing operation cycles and over 40 days testing.

Cellulose nanocrystals (CNCs) are the most commonly used natural polymers for biomaterial synthesis. However, their low dispersibility, conductivity, and poor compatibility with the hydrophobic matrix hinder their potential applications. Therefore, we grafted sulfate half-ester and carboxylic functional groups onto CNC surfaces (S-CNC and C-CNC) to overcome these shortcomings. The effect of the dopants, surfactant ratios, and properties of CNCs on the thermal stability, conductivity, and surface morphology of polyaniline (PANI)-doped CNC nanocomposites were investigated through emulsion and in situ polymerization. The higher electrical conductivity and well-dispersed morphology of SCNC–PANI30 (1.1 × 10−2 S cm−1) but lower thermal stability than that of CCNC–PANI30 (T0: 189 °C) nanocomposites are highly related to dispersibility of S-CNCs. However, after 4-dodecylbenzenesulfonic acid (DBSA) was added, the conductivity and thermal stability of SCNC/PANI increased up to 2.5 × 10−1 S cm−1 and 192 °C with almost no particle aggregation because of the increase in charge dispersion. The proposed biodegradable, renewable, and surface-modified S-CNC and C-CNC can be used in high-thermal-stability applications such as food packaging, optical films, reinforcement fillers, flexible semiconductors, and electromagnetic materials.

With the miniaturization of silicon-based electronic components, power consumption is becoming a fundamental issue for micro-nano electronic circuits. The main reason for this is that the scaling of the supply voltage in the ultra-large-scale integrated circuit cannot keep up with the shrinking of the characteristic size of conventional transistors due to the physical limit termed "Boltzmann Tyranny", in which a gate voltage of at least 60 mV is required to modulate the drain current by one order of magnitude. Accordingly, to solve this problem, several new transistor architectures have been designed to reduce the subthreshold swing (SS) to lower than the fundamental limitation, thus lowering the supply voltage and reducing the power consumption. In this review, we first analytically formulate the SS, summarize the methods for reducing the SS, and propose four new transistor concepts, including tunnelling field-effect transistor, negative capacitance field-effect transistor, impact ionization field-effect transistor, and cold source field-effect transistor. Then, we review their physical mechanisms and optimization methods and consider the potential and drawbacks of these four new transistors. Finally, we discuss the challenges encountered in the investigation of these steep-slope transistors and present the future outlook.

As the power density of the electronics is on increasing, improving the heat dissipation performance of electronic packaging materials will play a positive role in promoting the performance of modern electronics. In this work, the three-dimensional carbon fiber (CF)-MXenes foam, in which the vertically aligned CF constructed the heat transport paths, were prepared by simple freeze-drying method. As a result, the thermal conductivity (TC) of CF-M/epoxy composites was improved to an ultra-high level (9.68 W/mK) at 30.2 wt% hybrid fillers, increasing by 4509% enhancement compared with that of neat epoxy. In addition, the thermal properties of composites, such as glass transition temperature (Tg), coefficient of thermal expansion (CTE) were investigated. All the results indicated that the CF-MXenes/epoxy composite was supposed to be a promising heat dissipation material and will be used in the field of electronic packaging.

The continued growth in the demand of data storage and processing has spurred the development of high-performance storage technologies and brain-inspired neuromorphic hardware. Semiconductor quantum dots (QDs) offer an appealing option for these applications since they combine excellent electronic/optical properties and structural stability and can address the requirements of low-cost, large-area, and solution-based manufactured technologies. Here, we focus on the development of nonvolatile memories and neuromorphic computing systems based on QD thin-film solids. We introduce recent advances of QDs and highlight their unique electrical and optical features for designing future electronic devices. We also discuss the advantageous traits of QDs for novel and optimized memory techniques in both conventional flash memories and emerging memristors. Then, we review recent advances in QD-based neuromorphic devices from artificial synapses to light-sensory synaptic platforms. Finally, we highlight major challenges for commercial translation and consider future directions for the postsilicon era.

With the rapid application of artificial intelligence in daily life and work, the traditional von Neumann architecture device faces the limitation of scalability and high energy consumption. These limitations can be overcome by in-memory computing based on analog resistance switch devices, but the resistive switching behavior depends on the formation and rupture of filaments with spatial and temporal variation. According to the filamentary switching mechanisms, conductive filaments play an irreplaceable role in the resistive switching process, and the stochastic filaments are the main cause of nonuniform performances and variation. Therefore, an efficient way to solve these problems is by controlling the filaments. In recent years, researchers have made many efforts to control the filaments, resulting in numerous feasible methods being invented. Herein, departing from the filamentary mechanisms, the strategies of filament control are discussed from the aspects of electrode optimization, switching layer optimization and channel design. Meanwhile, the challenges of promotion in device performance and application in neuromorphic computing and outlook for future research directions are also discussed.

Natural biomaterials are potential candidates for the next generation of green electronics due to their biocompatibility and biodegradability. On the other hand, the application of biocomposite systems in information storage, photoelectrochemical sensing, and biomedicine has further promoted the progress of environmentally benign bioelectronics. Here, we mainly review recent progress in the development of biocomposites in data storage, focusing on the application of biocomposites in resistive random-access memory (RRAM) and field effect transistors (FET) with their device structure, working mechanism, flexibility, transient characteristics. Specifically, we discuss the application of biocomposite-based non-volatile memories for simulating biological synapse. Finally, the application prospect and development potential of biocomposites are presented., Graphical abstract

Inspired by the parallel performing of storage and processing information in biological synapse, artificial synapse that can control ionic and protonic currents are ideal means for attracted tremendous attention as a promising option to break the von Neumann bottleneck. Here we demonstrate an artificial synapse with tunable synaptic behavior based on solution-processed two-dimensional (2D) C3N/polyvinylpyrrolidone (PVPy). The proton modulated memristive characteristics of synaptic device are verified by ambient pressure X-ray photoelectron spectroscopy under different H2O gas atmosphere. The highly proton conducting of C3N/PVPy matrix stems from the hydrogen bonding network between C3N and PVPy, as well as the large amount of ordered nitrogen atoms in C3N. The artificial synapse ensure a direct imitation of short-term and long-term plasticity in biological synapses including excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), paired-pulse depression (PPD), PPF following PPD and post-tetanic potentiation (PTP). The C3N/PVPy matrix-based memristor which can mimic the synapse cleft based on proton conducting mechanism may find further applications in artificial intelligence.

The coherent developments of high performance broadband photodetection and a discrimination technique are highly essential for multiscene imaging and optical communication applications. The integration of traditional bandpass filters or stacking other spectral absorber in photodetectors often complicates the device design and leads to asymmetric photogain for each waveband. Herein, we report on ultraviolet–visible (UV-vis) multispectral photodetection based on a single ZnO nanowire (NW) phototransistor, where defect reconstructions can be reliably induced by a two-step annealing that leads to the observed broadband photodetection. Electron paramagnetic resonance and photoluminescence spectra reveal the reconstructions of zinc-atom-related defects (i.e., zinc interstitials and vacancies). Combined microdifferential reflectance and multimode scanning probe microscope (SPM) technique confirm the presence of a unique visible-sensitive Zn-rich ZnO shell layer and a trap-free UV-sensitive ZnO core. We achieve n...

MXenes have drawn considerable attention in both academia and industry due to their attractive properties, such as a combination of metallic conductivity and surface hydrophilicity. However, to the best of our knowledge, the potential use of MXenes in non-volatile resistive random access memories (RRAMs) has rarely been reported. In this paper, we first demonstrated a RRAM device with MXene (Ti3C2) as the active component. The Ti3C2-based RRAM exhibited typical bipolar switching behavior, long retention characteristics, low SET voltage, good mechanical stability and excellent reliability. By adjusting different compliance currents in the SET process, multi-state information storage was achieved. The charge trapping assisting hopping process is considered to be the main mechanism of resistive switching for this fabricated Ti3C2-based RRAM, which was verified by conductive atomic force microscopy (C-AFM) and Kelvin probe force microscopy (KPFM). Moreover, this flexible Ti3C2-based RRAM, with good mechanical stability and long retention properties, was successfully fabricated on a plastic substrate. Ti3C2-based RRAMs may open the door to additional applications and functionalities, with high potential for application in flexible electronics.

The amorphous/nanocrystal hybrid TiO2 based butterfly wing structure (ANH-TiO2-BW) is successfully fabricated via an easily controlled self-deposition sintering method. The hybrid configuration greatly enhances the structural toughness and maintains the original morphology throughout the experiment. The ANH-TiO2-BW configuration is very conductive to gas diffusion, and the calculated value of the diffusion coefficient (Dk) is 0.37 cm2 s−1 at room temperature (27 °C). As the completely reserved structure provides sufficient effective gas diffusion channels and gas molecule reaction sites, the ANH-TiO2-BW based gas sensor demonstrates a remarkable sensitivity to acetone, up to 1.88 at a detection limit of 5 ppm at room temperature and 180.08 for 200 ppm at an optimal operating temperature of 65 °C. Meanwhile, the device exhibits long-term stability, good cycle-to-cycle repeatability and selectivity to trace acetone at room temperature. Moreover, benefiting from the 3D penetrating porous structure, the average response time of the device is only about 1.8 s. This work may open up a new way for the design and application of toxic and harmful gas detection at room temperature.

Understanding the mobility and electrochemical process of ion species at the nanoscale is the key step to obtain high performance non-volatile data storage devices. Here, we present a systematic study on the resistive switching mechanism of an assembled metal–oxo cluster [Bi6O4(OH)4](NO3)6 (BiON) to build reliable non-volatile memory devices. The bipolar resistive-switching with low operation voltage is observed and is attributed to the migration of ion species (mainly OH−) with low activation energy (∼0.20 eV) along the polar electric field and simultaneous valence change of the bismuth of the [Bi6O4(OH)4] clusters in the BiON film. The X-ray photoelectron spectroscopy (XPS), conductive atomic force microscopy (CAFM) and Kelvin probe force microscopy (KPFM) characterization confirms that OH− with low activation energy is expected to facilitate the formation and rupture of anion vacancy filaments. Moreover, intermediate oxide layers formed at the Al/BiON interfaces could help to stabilize and assist the resistive switching. The control of the clusters and counter-ion species in the metal–oxo cluster-assembled materials represents a step toward next generation multi-level, high-speed and low energy consumption non-volatile memory devices for in-memory computing and artificial intelligence.

Resistive random-access memory (RRAM) is the most promising research direction of the next generation non-volatile memory (NVM) devices, and seeking novel materials as the active layer can facilitate RRAM device development. Two-dimensional graphitic carbon nitride (g-C3N4) nanosheets with a mass of carrier trapping sites are employed as the active layer of RRAM devices. Solution processed memory devices show good stability and reliability, and the fabricated g-C3N4-based RRAM devices show a non-volatile behavior and a bipolar switching characteristic with an ON/OFF ratio of 103, a low operation voltage and good retention capability. In addition, by means of controlling the compliance current precisely, multi-level data storage can be realized. The mechanism of the RRAM devices is thought to be carrier trapping assisted hopping, which is verified by atomic force microscopy in the electrical mode. This work demonstrates that g-C3N4 nanosheet based RRAM devices provide a novel direction for low energy and high density data storage devices.

Neuromorphic computing could tackle the inherent limitations of traditional von Neumann architecture in devoted machine learning applications. Nevertheless, implementation of a transistor-based artificial synapse which is the fundamental building block for mimicking the functions of biological synapses remains challenging owing to the nonlinear and asymmetric weight update protocol and fast saturation within the initial few pulses. Here, a three-terminal photoactive synapse is proposed based on black phosphorus (BP)–ZnO hybrid nanoparticles (NPs) with a combination of an electronic mode and a photoactive mode. By the electronic mode, the channel conductance can be manipulated by charge trapping inside the thin BP–ZnO NPs which ensures an enlarged variation margin and the realization of 4 synaptic weight levels, while optical modulation of the excitatory and inhibitory synaptic weights with symmetry and linearity variation was realized, since an extended energy threshold of photon absorption and accelerated dissipation of excitons can be achieved in the BP–ZnO hybrid NPs. Crucially, we can modulate the synaptic weight simply by varying the wavelength of the light source (365, 520, and 660 nm) and achieve an extended synaptic weight change of 400% within 10 optical pulses. This study proposes an extremely simple and powerful system with multiple forms of synaptic plasticity resembling an analogue of a natural biological synapse due to the broadband response of the BP–ZnO hybrid NPs.

MOFs have a highly ordered self-assembled nanostructure, high surface area, nanoporosity with tunable size and shape, reliable host-guest interactions, and responsiveness to physical and chemical stimuli which can be exploited to address critical issues in sensor applications. On the one hand, the nanoscale pore size of MOFs ranging from less than 1 nm to ≈ 10 nm not only allows the diffusion of small molecules into the pores or through the MOF layer, but also excludes other larger molecules depending on the size, shape, and conformation of MOFs. On the other hand, MOFs with flexible structure exhibit a dynamic response to external stimuli, including guest molecules, temperature, pressure, pH, and light. Due to the unsaturated coordination metal sites and active functional groups, the interaction between certain analytes and active sites results in high selectivity. In this review, we summarize the latest studies on MOF-based electronic sensors in terms of the function of MOFs, discuss challenges, and suggest perspectives.

To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl}(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.

In recent years, halide perovskite quantum dots (HP-QDs) based composites have been widely developed and used in various applications owing to their unique photonic, electronic and mechanical properties, as well as high stability to water, oxygen, heat and illumination. Remarkable efforts have been made in the synthesis and applications of these materials in photonics, electronics, sensors and other fields. Besides these topics, we also cover enhancement of optoelectronic properties as well as chemical, thermal and photostability of HP-QDs-based composites. We hope this review will promote both the development and applications of perovskite-based materials., GRAPHICAL ABSTRACT 10.1080/14686996.2020.1752115-UF0001

Artificial limbs have been widely investigated in the past several decades, and multifuncional bionic limbs have already been constructed. However, due the lack of nociceptive systems, amputees still cannot feel ubiquitous noxious stimuli through bionic limbs. The construction of artificial nociceptors can bring bionic limbs closer to real flesh and bone. In daily life, UV irradiation is an invisible potential noxious stimulus to human skin and eyes. Furthermore, it is well known that the synthetic polymers widely used in bionic limbs can be degraded by UV radiation, accelerating their aging. Based on the above, UV damage-sensing nociceptors could be a feasible strategy to solve these existing problems. Here, azobenzene-functionalized gold nanoparticles (Azo-Au NPs) are embedded in insulating poly(methyl methacrylate) (PMMA) to construct a two-terminal memristor. With UV irradiation as a light damage medium, major nociceptive behaviors such as "threshold", "relaxation" and "sensitization" are successfully emulated, demonstrating its potential application as a nociceptive system.

Natural biomaterials are capable of producing biodegradable and/or biocompatible electronic devices for vast applications such as next-generation green data storage. Here, we demonstrate an environment-friendly alkali lignin as a favourable candidate for resistive switching memory storage applications. The resistive memory devices based on gold nanoparticles embedded alkali lignin (Au NPs:lignin) exhibits a typical write-once-read-many-times memory (WORM) resistive switching behaviour with a large on-off ratio (>104), and long data retention characteristics (>103 s) under low power operation (4.7 V). Au NPs acting as trapping sites in the active layer are responsible for the resistive switching mechanism. The active layer is fabricated on organic substrates through facile solution-processed methods under normal ambient conditions. The skin-inspired polylactide (PLA) film is utilized as an ultrathin substrate endowing the memory devices with good mechanical support and biodegradability. This work opens up new avenues towards renewable and environmentally benign lignin-based materials for biodegradable electronic devices.

Interface engineering has been recognized to be substantially critical for achieving efficient charge separation, charge carrier transport, and enhanced device performance in emerging optoelectronics. Nevertheless, precise control of the interface structure using current techniques remains a formidable challenge. Herein, we demonstrate a facile and versatile protocol wherein in situ thiol–ene click photopolymerization-induced phase separation is implemented for constructing heterojunction semiconductor interfaces. This approach generates continuous mountainlike heterojunction interfaces that favor efficient exciton dissociation at the interface while providing a continuous conductive area for hole transport above the interface. This facile low-temperature paradigm presents good adaptability to both rigid and flexible substrates, offering high-performance UV-responsive phototransistors with a normalized detectivity up to 6.3 × 1014 cm Hz1/2 W–1 (also called jones). Control experiments based on ex situ phot...

Molecular non-volatile memory devices are deemed to offer remarkable features such as low-cost, high retention times and low power consumption that could possibly catapult their implementation over the contemporary silicon-based devices. Although scattered examples of small molecules, particularly transition metal complexes with rich electrochemical behavior, have been demonstrated to show promising performance in memory device application, systematic study on the molecular design and the structure–property relationship is lacking. Moreover, studies on memory applications of transition metal complexes have been mainly confined to those of precious metals. These have hindered the development and the practical applications of molecular non-volatile memory devices. To improve the practical applicability of transition metal complex-based molecular memory devices, herein, we report the study of memory applications of various solution-processable and earth-abundant polypyridyl Cr(III) complexes. Some of the fabricated resistive random-access memory (RRAM) devices exhibit reversible bipolar switching, high ON/OFF ratio and long retention time. It is anticipated that this study will provide important insights on the molecular design of transition metal complexes for memory device applications and would lead to a new generation of economically accessible and sustainable non-volatile memory devices.

Motivated by the biological neuromorphic system with a high degree of connectivity to process huge amounts of information, light-triggered electronic synapses are expected to pave the way for overcoming the von Neumann bottleneck for non-conventional computing. Here, a light-triggered electronic synapse based on solution-processed ZnO–phosphorene nanoparticles (ZP NPs) with an in situ fabricated heterojunction is demonstrated. In situ Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (CAFM) have been employed to investigate the operation principle of the memristor. The essential synaptic functions of learning and memory of the bio-synapse have been emulated, including potentiation and depression under positive and negative pulse trains, paired-pulse facilitation (PPF), spike-rate-dependent plasticity (SRDP), spike-timing-dependent plasticity (STDP) and short-term potentiation (STP) to long-term potentiation transition (LTP). The well-arranged pn junction inside the ZP NPs arouses the multiple wavelength response and fast separation of photogenerated excitons, which serves as the basis for broadband optically-mediated plasticity. The experimental results confirm that ZP nanoparticles could be promising key components for mimicking biological synaptic behaviors with light stimulation, which is of great importance for the further development of artificial light triggered neural systems.

Digital technology is one of the greatest modern breakthroughs, allowing sounds, words and images to be stored in binary form. However, there is a huge gap between the amount of data created daily and the capacities of existing storage media. Developing multibit memory in which 2n levels, typically represented by distinguishable current levels, can be achieved in a single cell is a critical specification for achieving high-density memory devices. Compared with electrically operated memory, photonic memory—in which electrical read-out is orthogonal to the photo-programming operation—promises high differentiation among different data levels. From another aspect, benefiting from its high density, multifunctionality, low power consumption, and multilevel data storage, photonic memory devices hold future promise for built-in, non-volatile memory and reconstructed logic operation and are expected to bridge this capacity gap. Thus, we present a review on the development of photonic memory, with a view towards inspiring more intriguing ideas on the elegant selection of materials and design of novel device structures that may finally induce major progress in the manufacture and application of photonic memory.

Since the discovery of perovskite materials with the general chemical formula ABX3 in 1839, research on perovskite materials has drawn exponentially greater attention, owing to their flexible properties, including their ferroelectric, piezoelectric, and dielectric, as well as resistive switching, properties. Perovskite materials have high potential for developing nonvolatile high-density data storage devices. In this review, we summarized the current development of the application of perovskites in nonvolatile memories with an emphasis on the resistive switching properties. The unique advances of perovskite materials are introduced, followed by an assortment of the characterisations of their compositions and crystal structures. The insight into perovskite materials in artificial synapses has also concluded with predictable opportunities and challenges in this promising field.

In the past several years, two-dimensional black phosphorus (BP) has captured the research community's interest because of its unique electronic, photonic, and mechanical properties. Remarkable efforts have been made regarding the synthesis, fundamental understanding, and applications of BP in the fields of nanoelectronics, nanophotonics, and optoelectronics. In this review, we summarize the recent developments in the study of BP, which covers the state-of-the-art synthesis methods for preparing single-layer or few-layer BP, the recent advances in characterizing its electronic, optical and mechanical properties, and the reported functional devices utilizing such properties. Finally we discuss the existing challenges in developing BP-based nanoelectronics and optoelectronics, and describe the prospects for future BP-related research.

Multi-functional devices have become progressively attractive in integrated complex systems. Real-time storage of thermal signals in organic memory has been achieved with micro-contact printed core–shell nanoparticles floating on plastic substrates. Herein, a micro-contact printed Au core Pd shell (Au@Pd) bimetal nanoparticle monolayer is designed as the charge trapping layer in a self-encapsulated top-gated memory device. The thermal memory device exhibits a low working voltage of 105 s, stable endurance characteristics over more than 103 repeated program/erase cycles and good mechanical properties during bending cycling tests. The memory properties under various thermal signals are carefully analyzed, and it is found that the devices also show reliable retention capability of pulse thermal signals. Our findings not only demonstrate top-gated flexible organic transistor based devices to sense various environmental thermal signals, but also confirm their applications for the real-time storage of temperature sensing signals as well as more complex thermal related integrated circuits.

Depending on the mobile species involved in the resistive switching process, redox random access memories and conductive bridge random access memories are widely studied with distinct switching mechanisms. Although the two resistance switching types have faithfully proved to be electrochemically linked in metal oxide‐based memristive devices, the corresponding photo‐induced transition has not yet been realized. Here, a photo‐induced transition through the integration of a graphene layer into a titanium oxide‐based memory device is demonstrated. Coupled with Raman mapping and an electron energy loss spectroscopy technique, the photo‐induced interaction at the heterostructure of graphene/titanium oxide are considered to dominate the transition process. Moreover, a negative differential resistance effect is observed by controlling the applied voltage, which can be credited to the saturation of trap centers (oxygen vacancies) and the increase of interfacial barrier at the graphene/titanium oxide heterojunction.

Increasing environmental crises caused by exploring and using fossil fuels have compelled human being to develop innovative technologies to utilize renewable and sustainable energy sources. For this purpose, photovoltaic conversion of solar energy into electricity with solar cells is a promising and attracting way in that solar energy is clean and inexhaustible. Nowadays, the bottleneck in the application of solar cells on a large scale to sustainable energy generation still lies in lacking an efficient, stable and low-cost materials system for photon-to-electricity conversion. Perovskite materials are a class of materials widely applied in solar cells. Many evidences showed that the perovskite materials have both ferroelectric and photovoltaic properties, offering a special system called photoferroelectric materials. A built-in electric field established in these materials due to the ferroelectric property is more helpful for the separation of e-h pairs and enhancing the power conversion efficiency during photovoltaic process in solar cells. Here, we review the recent photoferroelectric perovskite solar cells (PPSCs). After giving a brief description of the structure and property of photoferroelectric perovskite materials, the device structures, working principles and characterization of PPSCs are introduced, followed by the state-of-the-art advances and the insights for the PPSCs based on oxide and halide perovskite materials. Finally, the main challenges in developing efficient PPSCs are discussed.

One of the most effective approaches to solving the current problem arising from the von Neumann bottleneck in this period of data proliferation is the development of intelligent devices that mimic the human learning process. Information sensing and processing/storage are considered to be the essential processes of learning. Therefore, high-performance sensors, memory/synaptic devices, and relevant intelligent artificial tactile perception systems are urgently needed. In this regard, innovative device concepts and emerging two-dimensional materials have recently received considerable attention. Herein, we discuss the development of MXenes for applications in tactile sensors, memristors, and artificial tactile perception systems. First, we summarize the structures, common properties, and synthesis and assembly techniques of MXenes. We then discuss the applications of MXenes in tactile sensors, memristors, and relevant neuromorphic-based artificial tactile perception systems along with the related working mechanisms. Finally, we present the challenges and prospects related to MXene synthesis, assembly, and application.

Electronic synapses implementing in-memory computing system could overcome the developing limitation on the energy efficiency of traditional von Neumann architecture. Compared with the high sensitivity of biological synapses, lower responsivity of the memristive synapses was found via the electrical stimulations. Here, poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6- tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)-dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl} (PDPPBTT)/zinc oxide (ZnO) based heterojunction is found to exhibit stable memristive switching behavior, which originates from the confined formation/rupture of filament in the two-layer interface region as the ions migrate with different transport rates in two layers. The implementing synaptic functions in the sensitive memristive device can realize the short-term plasticity and long-term plasticity when stimulated by the applied electrical signals with different stimulating rate. Similar to the biological synapse, the memory loss, memory transition, and the critical role of stimulation rate on the transition process, can be achieved in the as-prepared memristor device. The systematic demonstrations on the synaptic emulation may facilitate building bio-inspired device-level neuromorphic systems.

Previous investigations on rare-earth oxides (REOs) reveal their high possibility as dielectric films in electronic devices, while complicated physical methods impede their developments and applications. Herein, we report a facile route to fabricate 16 REOs thin insulating films through a general solution process and their applications in low-voltage thin-film transistors as dielectrics. The formation and properties of REOs thin films are analyzed by atomic force microscopy (AFM), X-ray diffraction (XRD), spectroscopic ellipsometry, water contact angle measurement, X-ray photoemission spectroscopy (XPS), and electrical characterizations, respectively. Ultrasmooth, amorphous, and hydrophilic REO films with thickness around 10 nm have been obtained through a combined spin-coating and postannealing method. The compositional analysis results reveal the formation of RE hydrocarbonates on the surface and silicates at the interface of REOs films annealed on Si substrate. The dielectric properties of REO films are investigated by characterizing capacitors with a Si/Ln

Field-effect transistors (FETs) employing the solution-processed metal oxides as dielectrics have shown excellent performance on rigid silicon substrate. However, there have been very limited reports on FETs with solution-processed, thermal-annealed metal oxide dielectrics on low-cost flexible substrates. To date, to our knowledge there is almost no report on flexible FETs having the similar or better performance than the FETs on Si substrate with solution-processed, thermal-annealed metal oxides as dielectrics. Herein, flexible pentacene-based organic FETs have been demonstrated with polystyrene (PS)-modified, solution-processed yttrium oxide (Y2O3), hafnium oxide (HfO2), or aluminum oxide (Al2O3) as dielectrics on commercially available aluminum (Al) foil substrates. The transistors exhibit a good carrier mobility (µ), a large on/off current ratio (Ion/off), a low threshold voltage (VT), and a small subthreshold swing (SS) at a low-operation voltage (−4 V), which is comparable with the device performance on rigid Si substrate. Therefore, the excellent electrical performance of the FETs on commercially available Al foil substrate, together with the virtue of light-weight, makes the devices possess the promising potential for various electronic system applications.

Artificial retina perception system is significant to pattern recognition and visual function emulation. However, the recent artificial retina system is mainly reported on the integration of three-terminal transistors, whose structural limitations may result in low processing speeds and high energy consumption due to a low array density and complex line design. Furthermore, the external power source is required to drive devices so that the power consumption of the system would increase. Here we present a self-powered artificial retina perception system by utilizing two-terminal solar cells as artificial neurons and perovskite-based memristors as artificial synapses, ensuring the bio-inspired retina system with extendable crossbar array structure for high-density and low power consumption neural networks. By a light stimulation with various wavelengths and intensities, the electrical pre-synaptic signal is generated in the solar cell and subsequently transferred to the perovskite-based memristor to perform further information preprocessing. Especially, the applicability of the artificial retina system to neuromorphic computing is demonstrated for contrast enhancement and noise reduction. The retina perception system is capable of feature extraction by to implement partial functions of convolutional neural networks (CNNs) on the hardware level with improved recognition rate, boosted recognition speed, and reduced energy consumption.

The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike-based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain-like computing.

Coupling integration devices have been widely investigated in order to realize advanced artificial intelligence. In particular, by varying the mechanical energy of the sensory memory, the external force causes the alteration of internal energy and exerts an effect on its electrical properties. The goal of converting artificial touch into electronic implementation is to achieve perceptual intelligence, and it would profoundly advance a wide range of applications, such as robotic grasping tools, prosthetics, and human-computer interaction. Here, we focus on the recent progresses in electromechanical coupling memory and their applications in tactile sensory memory and artificial synapses. Also, electromechanical sensory memories are analyzed in terms of deformation-involved physical mechanisms, including the piezoelectric effect, piezoresistive effect, and triboelectric effect. Deformation-involved functional sensors integrated with memristors are also discussed for the artificial tactile memory applications. In addition, pressure-tunable synaptic functions and artificial memory skin emulated by electromechanical memories are discussed in details. At last, the application prospect is shown and challenges are also exist in aspects such as multilevel storage, energy consumption, and sensitive degree, which would further disclosure the merit and demerit of electromechanical integrated devices.

Artificial neuron is an important part of constructing neuromorphic network in which information can be computed with high parallelism and efficiency like in the human brain. However, owing to the poor biological plausibility, artificial neurons based on traditional complementary metal-oxide-semiconductor (CMOS) platform fail to reveal the rich ion dynamics of the biological counterparts. Organic–inorganic halide perovskites (OHPs) are prospective for imitating the ion dynamics on the membranes of biological neurons because of its intrinsic ion migration. Herein, a diffusive CH3NH3PbI3(MAPbI3)-based memristor with superior amplitude-frequency characteristics and highly linear conductivity modulation for more than 1000 states have been fabricated for the construction of a leaky integrate-and-fire (LIF) bio-inspired neuron. The as-designed LIF model can successfully emulate the leakage, spatiotemporal integration and firing functions in a biological neuron. Moreover, by connecting LIF neurons with a 2*2 non-volatile Al2O3-based synaptic array, a simple spiking neural network (SNN) which is called the 3rd generation of neural network has been implemented at the hardware level to study the cognitive performance of the network. The SNN exhibits outstanding selective sensitivity to particular input sequence, indicating the excellent adaptability and versatility of the network for future applications of neuromorphic computing by utilizing novel ionotropic device.

Lead-free halide perovskites are emerging as promising candidate for practical application of optoelectronic devices due to their nontoxicity. Unfortunately, previously-reported lead-free halide perovskites-based resistive switching devices suffer from high leakage and operating current stemmed from the intrinsic nature of polycrystalline film with a great amount of grain boundaries and pin-holes. Here, we report for the first time a monocrystalline lead-free Cs3Sb2Br9 perovskite nanoflake based lateral-structured device capable of combining nonvolatile bipolar switching and threshold switching with record-low switching electric field of 2.2 × 105 V m−1. Confirmed by elemental analysis and theoretical calculation, migration of highly mobile Br vacancy with low activation energy in defects-free monocrystalline Cs3Sb2Br9 is believed to be responsible for resistive switching. Short-term Ca2+ dynamics of biological synapses were then imitated by Cs3Sb2Br9 resistive switching devices which were further implemented as an effective reservoir element. The construction of neural network-based reservoir computing system to efficiently process temporal information can be realized since its conductance states are determined by the history of external simulation.

Developing new-style non-volatile memory is an important part to solve von Neumann bottleneck. Among numerous studies of memory device, resistive random-access memory (RRAM) is widely researched for their simple geometrical structure and high integration density. In recent decades, organic RRAM catches many researchers’ attention for their superiorities such as outstanding flexibility, simple solution processability, low-cost fabrication and tunable functionalities by changing the chemical groups. Herein, a series of organic small molecules 2,7-di(9H-carbazol-9-yl)-9H-fluoren-9-one (FLOCZ) and 2,7-bis(3,6-di-tert-butyl-9H-carbazol-9-yl)-9H-fluoren-9-one (FLOBCZ) are synthesized and their band structures and electronic states are systematically studied with the assistance of density function theory (DFT). Then, using simple solution-processing approach, FLOCZ/FLOBCZ based RRAMs are fabricated and their memory characteristics are studied. The as-fabricated Ag/FLOBCZ/ITO RRAM exhibits non-volatile memory effect with a memory window up to 7 × 103 and data retention time of more than 2 × 104 s, which can meet the requirement of data storage. Meanwhile, by controlling compliance current on the RRAM precisely, multi-level data storage can be implemented experimentally. Our work extends the applications of organic small molecule and promotes the evolution of organic RRAM.

Near infrared (NIR) synaptic devices offer a remote-control approach to implement neuromorphic computing for data safety and artificial retinal system applications. In upconverting nanoparticles (UCNPs)-mediated optogenetics biosystems, NIR regulation of membrane ion channels allows remote and selective control of the Ca2+ flux to modulate synaptic plasticity behaviors. Inspired by the upconversion optogenetics, we proposed a NIR artificial synapse based on a UCNPs-MoS2 floating gate phototransistor in which MoS2 acts as light-sensitive ion channels to reabsorb the visible light emitted from UCNPs under NIR illumination. As a result, the synaptic device exhibits stable persistent photocurrent (PPC) effect up to 353 K and ultrahigh photogain (~108 electrons per photon), ensuring the long-term potentiation (LTP) behavior. Simulations using the handwritten digit data sets indicate good recognition accuracy of the light-controlled artificial neuron network. Overall, this design concept combining biology, optics and electronics opens up a new avenue for developing optogenetics-inspired neuromorphic technology in the future.

High-performance photonic nonvolatile memory combining photosensing and data storage with low power consumption ensures the energy efficiency of computer systems. This study first reports in situ derived phosphorene/ZnO hybrid heterojunction nanoparticles and their application in broadband-response photonic nonvolatile memory. The photonic nonvolatile memory consistently exhibits broadband response from ultraviolet (380 nm) to near infrared (785 nm), with controllable shifts of the SET voltage. The broadband resistive switching is attributed to the enhanced photon harvesting, a fast exciton separation, as well as the formation of an oxygen vacancy filament in the nano-heterojunction. In addition, the device exhibits an excellent stability under air exposure compared with reported pristine phosphorene-based nonvolatile memory. The superior antioxidation capacity is believed to originate from the fast transfer of lone-pair electrons of phosphorene. The unique assembly of phosphorene/ZnO nano-heterojunctions paves the way toward multifunctional broadband-response data-storage techniques.

Piezoresistive microsensors are considered to be essential components of the future wearable electronic devices. However, the expensive cost, complex fabrication technology, poor stability, and low yield have limited their developments for practical applications. Here, we present a cost-effective, relatively simple, and high-yield fabrication approach to construct highly sensitive and ultrastable piezoresistive sensors using a bioinspired hierarchically structured graphite/polydimethylsiloxane composite as the active layer. In this fabrication, a commercially available sandpaper is employed as the mold to develop the hierarchical structure. Our devices exhibit fascinating performance including an ultrahigh sensitivity (64.3 kPa–1), fast response time (100 000 cycles), and high ambient stability (>1 year). The applications of these devices in sensing radial artery pulses, acoustic vibrations, and human body motion are demonstrated, exhibiting their enormous potential use in real-time healthcare monitoring and robotic tactile sensing.

The in-depth understanding of ions' generation and movement inside all-inorganic perovskite quantum dots (CsPbBr3 QDs), which may lead to a paradigm to break through the conventional von Neumann bottleneck, is strictly limited. Here, it is shown that formation and annihilation of metal conductive filaments and Br- ion vacancy filaments driven by an external electric field and light irradiation can lead to pronounced resistive-switching effects. Verified by field-emission scanning electron microscopy as well as energy-dispersive X-ray spectroscopy analysis, the resistive switching behavior of CsPbBr3 QD-based photonic resistive random-access memory (RRAM) is initiated by the electrochemical metallization and valance change. By coupling CsPbBr3 QD-based RRAM with a p-channel transistor, the novel application of an RRAM-gate field-effect transistor presenting analogous functions of flash memory is further demonstrated. These results may accelerate the technological deployment of all-inorganic perovskite QD-based photonic resistive memory for successful logic application.

Here, a single-device demonstration of novel hybrid architecture is reported to achieve programmable transistor nodes which have analogies to flash memory by incorporating a resistive switching random access memory (RRAM) device as a resistive switch gate for field effect transistor (FET) on a flexible substrate. A high performance flexible RRAM with a three-layered structure is fabricated by utilizing solution-processed MoS2 nanosheets sandwiched between poly(methyl methacrylate) polymer layers. Gate coupling with the pentacene-based transistor can be controlled by the RRAM memory state to produce a nonprogrammed state (inactive) and a programmed state (active) with a well-defined memory window. Compared to the reference flash memory device based on the MoS2 floating gate, the hybrid device presents robust access speed and retention ability. Furthermore, the hybrid RRAM-gated FET is used to build an integrated logic circuit and a wide logic window in inverter logic is achieved. The controllable, well-defined memory window, long retention time, and fast access speed of this novel hybrid device may open up new possibilities of realizing fully functional nonvolatile memory for high-performance flexible electronics.

One of the important problems in organic thin film transistors (OTFTs) is the existence of traps on oxide gate dielectrics which degrades the device performance and stability. By modifying the dielectric oxide surface, we obtained devices with bilayer dielectrics that show high mobility and good operational stability compared with the devices based on bare silicon dioxide dielectric layer. The average carrier mobility increases from 0.19 (without surface modification) to 0.35, 0.51, and 0.97 cm2 V−1 s−1 after employing a thin layer of hexamethyldisilazane (HMDS), polymethylmethacrylate (PMMA), and polystyrene (PS), respectively. The PS-modified device exhibits the superior mobility, operational, and air stability in comparison with other devices. We ascribe these results to fewer traps caused by the OH group or OH-induced water at the interface of semiconductor and the dielectric layer. In our study, the morphology of the semiconductor layer seems to have limited influence on the mobility and operational stability.

Following the trend of miniaturization as per Moore's law, and facing the strong demand of next-generation electronic devices that should be highly portable, wearable, transplantable, and lightweight, growing endeavors have been made to develop novel flexible data storage devices possessing nonvolatile ability, high-density storage, high-switching speed, and reliable endurance properties. Nonvolatile organic data storage devices including memory devices on the basis of floating-gate, charge-trapping, and ferroelectric architectures, as well as organic resistive memory are believed to be favorable candidates for future data storage applications. In this Review, typical information on device structure, memory characteristics, device operation mechanisms, mechanical properties, challenges, and recent progress of the above categories of flexible data storage devices based on organic nanoscaled materials is summarized.

We report a low-voltage organic field-effect transistor consisting of an extended gate sensory area to detect various ions in a solution. The device distinguishes various ions by the shift in threshold voltage and is sensitive to multiple ions with various concentrations. X-ray photoelectron spectroscopy measurements and the resistance changes at the sensor area prove that the ions are doped into the sensitive film at the sensor area. Because of the effect of doping, the conductivity of the semiconductor polymer film changes thus causing a threshold voltage shift.