Control of Halogen Atom in Inorganic Metal-Halide Perovskites Enables Large Piezoelectricity for Electromechanical Energy Generation.

Regulating the strain of inorganic perovskites has emerged as a critical approach to control their electronic and optical properties. Here, an alternative strategy to further control the piezoelectric properties by substituting the halogen atom (I/Br) in the CsPbX3 perovskite (X = Cl, Br) structure is adopted. A series of piezoelectric materials with excellent piezoelectric coefficients (d33 ) are unveiled. Iodine-incorporated CsPbBr2 I demonstrates the record intrinsic piezoelectric response (d33 ≈47 pC N-1 ) among all inorganic metal halide perovskites. This leads to an excellent electrical output power of ≈ 0.375 mW (24.8 µW cm-2 N-1 ) in the piezoelectric energy generator (PEG) which is higher than those of the pristine/mixed perovskite references with CsPbX3 (X = I, Br, Cl). With its structural phase remaining unchanged, the strained CsPbBr2 I retains its superior piezoelectricity in both thin film and nanocrystal powder forms, further demonstrating its repeatability and versatility of applications. The origin of high piezoelectricity is found to be due to halogen-induced anisotropic lattice strain in the unit-cell along the c-axis, and octahedral distortion. This study reveals an avenue to design new piezoelectric materials by modifying their halide constituents and paves the way to design efficient PEGs for improved electromechanical energy conversion.

Engineering the defect distribution in ZnO nanorods through laser irradiation.

In recent years, defect engineering has shown great potential to improve the properties of metal oxide nanomaterials for various applications thus received extensive investigations. While traditional techniques mostly focus on controlling the defects during the synthesis of the material, laser irradiation has emerged as a promising post-deposition technique to further modulate the properties of defects yet there is still limited information. In this article, defects such as oxygen vacancies are tailored in ZnO nanorods through nanosecond (ns) laser irradiation. The relation between laser parameters and the temperature rise in the ZnO due to laser heating was established based on the observation in the SEM and the simulation. Raman spectra indicated that the concentration of the oxygen vacancies in the ZnO is temperature-dependent and can be controlled by changing the laser fluence and exposure time. This is also supported by the absorption spectra and the photoluminescence spectra of ZnO NRs irradiated under these conditions. On the other hand, the distribution of the oxygen vacancies was studied by XPS depth profiling, and it was confirmed that the surface-to-bulk ratio of the oxygen vacancies can be modulated by varying the laser fluence and exposure time. Based on these results, four distinctive regimes containing different ratios of surface-to-bulk oxygen vacancies have been identified. Laser-processed ZnO nanorods were also used as the catalyst for the photocatalytic degradation of rhodamine B (RhB) dye to demonstrate the efficacy of this laser engineering technique.

High-Performance Mid-IR to Deep-UV van der Waals Photodetectors Capable of Local Spectroscopy at Room Temperature.

The ability to perform broadband optical spectroscopy with subdiffraction-limit resolution is highly sought-after for a wide range of critical applications. However, sophisticated near-field techniques are currently required to achieve this goal. We bypass this challenge by demonstrating an extremely broadband photodetector based on a two-dimensional (2D) van der Waals heterostructure that is sensitive to light across over a decade in energy from the mid-infrared (MIR) to deep-ultraviolet (DUV) at room temperature. The devices feature high detectivity (>109 cm Hz1/2 W-1) together with high bandwidth (2.1 MHz). The active area can be further miniaturized to submicron dimensions, far below the diffraction limit for the longest detectable wavelength of 4.1 µm, enabling such devices for facile measurements of local optical properties on atomic-layer-thickness samples placed in close proximity. This work can lead to the development of low-cost and high-throughput photosensors for hyperspectral imaging at the nanoscale.

Heterogeneous stimuli induced nonassociative learning behavior in ZnO nanowire memristor.

Nonassociative learning is a biologically essential and evolutionarily adaptive behavior in organisms. The bionic simulation of nonassociative learning based on electronic devices is essential to the neuromorphic computing. In this work, nonassociative learning is mimicked by a ZnO nanowire memristor without any other peripheral control circuit. The memristor demonstrates habituation and sensitization behaviors at the electrical and optical stimuli. Typical network-level parametric characteristics of habituation in neuroscience are realized in the memristor. When the heterogeneous stimuli are applied coincidentally, sensitization pulse could be identified by the exceptional response current. The results show that the natural selection rules could be simulated by the current single memristor. A possible mechanism based on the trapping states and adsorption of oxygen at the interface of Au/ZnO is proposed. The implementation of nonassociative learning in a single memristor device paves the way for building neuromorphic systems by simple electronic devices.

A Unified Capacitive-Coupled Memristive Model for the Nonpinched Current-Voltage Hysteresis Loop.

The concept of the memristor, a resistor with memory, was proposed by Chua in 1971 as the fourth basic element of electric circuitry. Despite a significant amount of effort devoted to the understanding of memristor theory, our understanding of the nonpinched current-voltage (I-V) hysteresis loop in memristors remains incomplete. Here we propose a physical model of a memristor, with a capacitor connected in parallel, which explains how the nonpinched I-V hysteresis behavior originates from the capacitive-coupled memristive effect. Our model replicates eight types of characteristic nonlinear I-V behavior, which explains all observed nonpinched I-V curves seen in experiments. Furthermore, a reversible transition from a nonpinched I-V hysteresis loop to an ideal pinched I-V hysteresis loop is found, which explains the experimental data obtained in C15H11O6-based devices when subjected to an external stimulus (e.g., voltage, moisture, or temperature). Our results provide the vital physics models and materials insights for elucidating the origins of nonpinched I-V hysteresis loops ascribed to capacitive-coupled memristive behavior.

Synaptic learning behavior of a TiO2 nanowire memristor.

TiO2 nanowire memristors were fabricated by dielectrophoresis. The responding current of the memristor continuously increases and decreases with the consecutive positive and negative sweep voltage, which is similar to the nonlinear transmission characteristics of biological synapses. Spike-rate-dependent plasticity and learning behaviors of TiO2 memristor were studied by applying programmed pulses. The pulses with higher amplitude, bigger width and smaller interval cause a larger excitatory postsynaptic current. The number of relearning pulses is decreased with the learning experience, and a deepening memory will be consolidated by the repeated learning process. A mechanism based on the oxygen vacancy migration is proposed for the learning behavior. Excess oxygen vacancies are generated during the learning process and the conducting pathways are formed by the vacancy drift under the applied voltage. After removing the voltage at the forgetting process, back diffusion and electron trapping of the oxygen vacancies dominate the relaxation time, and the metastable atoms are formed with the involvement of the oxygen atoms. However, weak chemical bonding among the metastable atoms leads to the migration of the regenerated oxygen vacancies again, contributing to the enhanced current in the relearning process.

Self-powered, flexible and remote-controlled breath monitor based on TiO2 nanowire networks.

Smart breath monitor devices with high stretchability, fast response/recovery times and self-powered characteristic are essential in the wearable medical and life science applications. In this work, we report on the development of a versatile high-performance humidity sensor based on TiO2 nanowire networks for self-powered sensing application of human breath monitoring. These sensors, with typical response times of ∼3.6 s and recovery times of ∼14 s, exhibit high sensitivity to water vapor and can yield an output voltage that is directly proportional to the humidity level of ambient environment. The structure of nanowire networks is highly flexible and maintains the output voltage even after 10 000 times bending. By combining this type of sensor with a commercial signal transmission and processing system, it shows the good basis for real-time/remote-controlled monitoring and analysis of human breath under a variety of respiratory conditions. Our results suggest a new class of humidity sensing for self-powered biomedical devices and open to new technologies in energy, electronics, and sensor applications.

Investigation of impact and spreading of molten nanosized gold droplets on solid surfaces.

Understanding the impact dynamics and spreading of molten nanosized droplets on a solid surface is a crucial step towards the design and control of nano-fabrication in many novel applications of nanotechnology. In this context, molecular dynamic (MD) simulations have been conducted to compute temperature and dynamic contact angles of nano-droplets during impact. The evolution of the morphology of a molten metallic nano-droplet impacting on a substrate has been studied using a combination of experimental and simulation techniques. Femtosecond lasers have been used to transfer nanosized gold droplets. Droplet morphology calculated in MD simulations is found to be in good agreement with that seen in scanning electron microscopy (SEM) images. It is found that the spreading of nanoscale molten gold droplets upon impact is enhanced by increasing the droplet impact energy. As observed in experimental data, MD simulation results show that a high droplet-substrate heat transfer rate together with increased wettability of the substrate facilitates spreading and results in a thinner metal deposit after solidification.

Improving the electrical contact at a Pt/TiO2 nanowire interface by selective application of focused femtosecond laser irradiation.

In this paper, we show that tightly focused femtosecond laser irradiation is effective in improving nanojoining of an oxide nanowire (NW) (TiO2) to a metal electrode (Pt), and how this process can be used to modify contact states. Enhanced chemical bondings are created due to localized plasmonically enhanced optical absorption at the Pt/TiO2 interface as confirmed by finite element simulations of the localized field distribution during irradiation. Nano Auger electron spectroscopy shows that the resulting heterojunction is depleted in oxygen, suggesting that a TiO2-x layer is formed between the Pt electrode and the TiO2 NW. The presence of this redox layer at the metal/oxide interface plays an important role in decreasing the Schottky barrier height and in facilitating chemical bonding. After laser irradiation at the cathode for 10 s at a fluence of 5.02 mJ cm-2, the Pt/TiO2 NW/Pt structure displays different electrical properties under forward and reverse bias voltage, respectively. The creation of this asymmetric electrical characteristic shows the way in which modification of the electronic interface by laser engineering can replace the electroforming process in resistive switching devices and how it can be used to control contact states in a metal/oxide interface.

Highly-stable silver nanobelts joined via diffusion-free attachment.

Silver nanobelts are demonstrated here to undergo inter-particle joining at relatively low temperatures of less than 180 °C. For surface-coated networks of nanobelts this joining reduced the network sheet resistance by 95%. The joining mechanism appears to be non-diffusional oriented attachment, caused by the thermal reactivation of the halted oriented attachment mechanism that occurred originally at room temperature during the rapid nanobelt synthesis. This self-assembly mechanism was explored by in situ electrical and calorimetric experiments, and supported by electron microscopy. Unlike pentagonal silver nanowires, silver nanobelts do not rely on diffusional instability to achieve workably low joining temperatures. The oriented attachment displayed by nanobelts represents a new approach to achieving valuable reductions in network resistance, disentangled from the instability and diffusion-driven failure by nanoparticle degradation displayed by competing silver nanoparticles.

In situ nanojoining of Y- and T-shaped silver nanowires structures using femtosecond laser radiation.

We report the in situ joining of spatially separated silver nanowires without additional filler material by controlled irradiation with femtosecond laser pulses. Nanojoining under these conditions arises from highly localized heat generation in the vicinity of the gap between adjacent silver nanowires. Melting, followed by the flow of silver into the gap, is optimized by adjusting the direction of laser polarization relative to gap geometry. Our results show that melting of silver occurs on both nanowires in the vicinity of the gap between the two components. Successful formation of a joint is found to be a function of the angle between the long axis of the nanowires and the gap distance. Finite element simulations show that the strong localized electric field generated by optical excitation determines the location and the morphology of the resulting bond. Light coupling and the resulting emission properties of these Y-shaped nanowire structures have been simulated and are compared to similar structures where the gap remains open. It is suggested that joined Y-shaped couplers will have a higher switching ratio between emitted nanowire ends than those occurring in open-gap structures. Nanojoining induced by localized heating under strong field excitation may enable the production of robust branched metal nanowire structures for optical applications.

Measure for optical robustness of directly bonded glass-to-glass joint using its interaction with damage induced by fs laser.

To produce more powerful compact ultrafast lasers, research aims at improving the quality of bonds between components inside the laser cavity. Increasing bond robustness under optical irradiation helps the bonds to survive the high energy pulses that these lasers are designed to produce. A measure for such robustness is reported here to support work toward improved bonding processes for such lasers. We produced bonds between pairs of optical grade fused silica glass cylinders using a wet direct bonding procedure. We evaluated these bonds using conventional microscopy, including scanning electron microscopy (SEM) and optical microscopy, without quantifiable results. The bond interface was not discernible through conventional SEM imaging, even after cross sectioning and polishing. The majority of the interface was also undetectable in optical micrographs, except for some limited areas of interfacial disturbance. To obtain quantifiable results for optical robustness, we used an 800 nm femtosecond laser to produce filament-shaped damage from a focal spot moving across the interface. Microscopy of the damage showed its interaction with the interface, the presence of which caused a ≈0.130 to ≈0.230 mm long interruption in the damage line. The exact value depended not only on laser power but also interface quality, and thereby quantified the optical robustness. The reported method proved more sensitive in detecting bonds of fused silica samples compared to other visualization techniques used. Our results suggest a nuanced understanding of bonded glass joints-mechanically sound, yet with limited optical robustness under specific laser conditions.

Gate-Tunable Multiband van der Waals Photodetector and Polarization Sensor.

A single photodetector with tunable detection wavelengths and polarization sensitivity can potentially be harnessed for diverse optical applications ranging from imaging and sensing to telecommunications. Such a device will require the combination of multiple material systems with different structures, band gaps, and photoelectrical responses, which is extremely difficult to engineer using traditional epitaxial films. Here, we develop a multifunctional and high-performance photosensor using all van der Waals materials. The device features a gate-tunable spectral response that is switchable between near-infrared/visible and short-/midwave infrared, as well as broad-band operation, at room temperature. The linear polarization sensitivity in the telecommunication O-band can also be directly modulated between horizontal, vertical, and nonpolarizing modes. These effects originate from the balance of photocurrent generation in two of the active layers that can be manipulated by an electric field. The photodetector features high detectivity (>109 cmHz1/2W-1) together with fast operation speed (∼1 MHz) and can be further exploited for dual visible and infrared imaging.

Intelligent matter endows reconfigurable temperature and humidity sensations for in-sensor computing.

Data-centric tactics with in-sensor computing go beyond the conventional computing-centric tactic that is suffering from processing latency and excessive energy consumption. The multifunctional intelligent matter with dynamic smart responses to environmental variations paves the way to implement data-centric tactics with high computing efficiency. However, intelligent matter with humidity and temperature sensitivity has not been reported. In this work, a design is demonstrated based on a single memristive device to achieve reconfigurable temperature and humidity sensations. Opposite temperature sensations at the low resistance state (LRS) and high resistance state (HRS) were observed for low-level sensory data processing. Integrated devices mimicking intelligent electronic skin (e-skin) can work in three modes to adapt to different scenarios. Additionally, the device acts as a humidity-sensory artificial synapse that can implement high-level cognitive in-sensor computing. The intelligent matter with reconfigurable temperature and humidity sensations is promising for energy-efficient artificial intelligence (AI) systems.

Versatile memristor for memory and neuromorphic computing.

The memristor is a promising candidate to implement high-density memory and neuromorphic computing. Based on the characteristic retention time, memristors are classified into volatile and non-volatile types. However, a single memristor generally provides a specific function based on electronic performances, which poses roadblocks for further developing novel circuits. Versatile memristors exhibiting both volatile and non-volatile properties can provide multiple functions covering non-volatile memory and neuromorphic computing. In this work, a versatile memristor with volatile/non-volatile bifunctional properties was developed. Non-volatile functionality with a storage window of 4.0 × 105 was obtained. Meanwhile, the device can provide threshold volatile functionalities with a storage window of 7.0 × 104 and a rectification ratio of 4.0 × 104. The leaky integrate-and-fire (LIF) neuron model and artificial synapse based on the device have been studied. Such a versatile memristor enables non-volatile memory, selectors, artificial neurons, and artificial synapses, which will provide advantages regarding circuit simplification, fabrication processes, and manufacturing costs.

Multifunctional Self-Powered Electronics Based on a Reusable Low-Cost Polypropylene Fabric Triboelectric Nanogenerator.

We report the development of low-cost triboelectric nanogenerators (TENGs) based on polypropylene (PP) fabrics formulated via an inexpensive melt-blowing process with an output voltage as high as 50 V. By disinfection methods such as exposure to steam, ethanol, and dry heat at 75 °C, the commercial medical masks and N95 filtering facepiece respirators (FFRs) can be reused to fabricate PP fiber based TENGs, which provide a novel regime for energy-harvesting devices based on reusable materials. As a power source, the output of one TENG can drive 15 serially connected light-emitting diodes (LEDs) or a commercial electric calculator. PP fabric TENGs can also work as self-powered sensors for the high-sensitivity detection of mechanical impact. We provide examples where the TENG is used to detect biomechanical motion such as that associated with the extension of an elbow, the touch of a finger, the impact of footsteps, and the bending of a knee without an external power supply. Most importantly, these PP fabrics for TENGs can be obtained from decontaminated medical masks that are generated as tremendous wastes every day, which provide a great potential as sustainable energy. These properties suggest that PP fabric based TENGs are promising for harvesting energy from biological systems and that they may facilitate the large-scale production of a new range of inexpensive self-powered multifunctional wearable sensors for applications in healthcare, security, and information networks.

A Simple High Power, Fast Response Streaming Potential/Current-Based Electric Nanogenerator Using a Layer of Al2O3 Nanoparticles.

Harvesting energy from ambient moisture and natural water sources is currently of great interest due to the need for standalone self-powered nano/micro-systems. In this work, we report on the development of a cost-effective nanogenerator based on a carbon paper-Al2O3 nanoparticle layer-carbon paper (CAC) sandwich structure, where the 3D Al2O3 layer is deposited via vacuum filtration. This type of device can produce an open-circuit voltage (UOC) of up to 4 V and a short-circuit current (ISC) of ∼18 µA with only an 8 µL water droplet applied. To our knowledge, this is the highest voltage yet reported from a single moisture/water-induced electricity nanogenerator using solid oxides and carbon-based materials. A remarkable output power of 14.8 µW can be reached with an optimized resistive load. An LED with a working voltage of 3-3.2 V can operate for a short time with the power from a single CAC device exposed to one 8 µL water droplet. Furthermore, a CAC generator adsorbing as little as 2 µL water droplets every 3 min can also give a UOC of 3.63 V. We show that CAC devices provide a robust electrical output over more than 200 wet-dry cycles without any deterioration in performance. These units demonstrate much promise as cost-effective electricity generators for harvesting energy from natural sources like rainwater, tap water, snow runoff, and dew. The response time of CAC devices can be as fast as 10-100 ms, making them ideal for applications as self-powered water detectors. The generation of power in this device arises from the streaming current. To assist in the optimization of these devices, we have analyzed how their response is related to such factors as layer thickness, time interval between application of water droplets, and the volume of each water droplet.

A Battery-Like Self-Selecting Biomemristor from Earth-Abundant Natural Biomaterials.

Using the earth-abundant natural biomaterials to manufacture functional electronic devices meets the sustainable requirement of green electronics, especially for the practical application of memristors in data storage and neuromorphic computing. However, the sneak currents flowing though the unselected cells in a large-scale cross-bar memristor array is one of the major problems which need to be tackled. The self-selecting memristors can solve the problem to develop compact and concise integrated circuits. Here, a sustainable natural biomaterial (anthocyanin, C15H11O6) extracted from plant tissue is demonstrated for ions and electron transport. The capacitive-coupled memristive behavior of as-prepared bioelectronic device can be significantly modulated by diethylmethyl(2-methoxyethyl)ammoium bis(trifluoromethylsulfonyl)imide (DEME-TFSI) ionic liquid (IL). Furthermore, graphene was inserted into biomaterial matrix to manipulate the memristive effects by graphene protonation. This results in a battery-like self-selective memristive effect. This phenomenon is explained by a physical model and density functional theory (DFT) based first-principles calculations. Finally, the self-selective behavior was applied in 0T-1R array configuration, which indicates the battery-like self-selecting biomemristor has potential applications in the brain-inspired computing, data storage systems, and high-density device integration.

Moisture-Enabled Electricity Generation: From Physics and Materials to Self-Powered Applications.

The exploration of the utilization of sustainable, green energy represents one way in which it is possible to ameliorate the growing threat of the global environmental issues and the crisis in energy. Moisture, which is ubiquitous on Earth, contains a vast reservoir of low-grade energy in the form of gaseous water molecules and water droplets. It has now been found that a number of functionalized materials can generate electricity directly from their interaction with moisture. This suggests that electrical energy can be harvested from atmospheric moisture and enables the creation of a new range of self-powered devices. Herein, the basic mechanisms of moisture-induced electricity generation are discussed, the recent advances in materials (including carbon nanoparticles, graphene materials, metal oxide nanomaterials, biofibers, and polymers) for harvesting electrical energy from moisture are summarized, and some strategies for improving energy conversion efficiency and output power in these devices are provided. The potential applications of moisture electrical generators in self-powered electronics, healthcare, security, information storage, artificial intelligence, and Internet-of-things are also discussed. Some remaining challenges are also considered, together with a number of suggestions for potential new developments of this emerging technology.

From Memristive Materials to Neural Networks.

The information technologies have been increasing exponentially following Moore's law over the past decades. This has fundamentally changed the ways of work and life. However, further improving data process efficiency is facing great challenges because of physical and architectural limitations. More powerful computational methodologies are crucial to fulfill the technology gap in the post-Moore's law period. The memristor exhibits promising prospects in information storage, high-performance computing, and artificial intelligence. Since the memristor was theoretically predicted by L. O. Chua in 1971 and experimentally confirmed by HP Laboratories in 2008, it has attracted great attention from worldwide researchers. The intrinsic properties of memristors, such as simple structure, low power consumption, compatibility with the complementary metal oxide-semiconductor (CMOS) process, and dual functionalities of the data storage and computation, demonstrate great prospects in many applications. In this review, we cover the memristor-relevant computing technologies, from basic materials to in-memory computing and future prospects. First, the materials and mechanisms in the memristor are discussed. Then, we present the development of the memristor in the domains of the synapse simulating, in-memory logic computing, deep neural networks (DNNs) and spiking neural networks (SNNs). Finally, the existent technology challenges and outlook of the state-of-art applications are proposed.