Si/CuO Heterojunction-Based Photomemristor for Reconfigurable, Non-Volatile, and Self-Powered In-Sensor Computing.

In-sensor computing has attracted considerable interest as a solution for overcoming the energy efficiency and response time limitations of the traditional von Neumann architecture. Recently, emerging memristors based on transition-metal oxides (TMOs) have attracted attention as promising candidates for in-memory computing owing to their tunable conductance, high speed, and low operational energy. However, the poor photoresponse of TMOs presents challenges for integrating sensing and processing units into a single device. This integration is crucial for eliminating the need for a sensor/processor interface and achieving energy-efficient in-sensor computing systems. In this study, a Si/CuO heterojunction-based photomemristor is proposed that combines the reversible resistive switching behavior of CuO with the appropriate optical absorption bandgap of the Si substrate. The proposed photomemristor demonstrates a simultaneous reconfigurable, non-volatile, and self-powered photoresponse, producing a microampere-level photocurrent at zero bias. The controlled migration of oxygen vacancies in CuO result in distinct energy-band bending at the interface, enabling multiple levels of photoresponsivity. Additionally, the device exhibits high stability and ultrafast response speed to the built-in electric field. Furthermore, the prototype photomemristor can be trained to emulate the attention-driven nature of the human visual system, indicating the tremendous potential of TMO-based photomemristors as hardware foundations for in-sensor computing.

PbS/CsPbBr3 Heterojunction for Broadband Neuromorphic Vision Sensing.

Neuromorphic light sensors with analogue-domain image processing capability hold promise for overcoming the energy efficiency limitations and latency of von Neumann architecture-based vision chips. Recently, metal halide perovskites, with strong light-matter interaction, long carrier diffusion length, and exceptional photoelectric conversion efficiencies, exhibit reconfigurable photoresponsivity due to their intrinsic ion migration effect, which is expected to advance the development of visual sensors. However, suffering from a large bandgap, it is challenging to achieve highly tunable responsivity simultaneously with a wide-spectrum response in perovskites, which will significantly enhance the image recognition accuracy through the machine learning algorithm. Herein, we demonstrate a broadband neuromorphic visual sensor from visible (Vis) to near-infrared (NIR) by coupling all-inorganic metal halide perovskites (CsPbBr3) with narrow-bandgap lead sulfide (PbS). The PbS/CsPbBr3 heterostructure is composed of high-quality single crystals of PbS and CsPbBr3. Interestingly, the ion migration of CsPbBr3 with the implementation of an electric field induces the energy band dynamic bending at the interface of the PbS/CsPbBr3 heterojunction, leading to reversible, multilevel, and linearly tunable photoresponsivity. Furthermore, the reconfigurable and broadband photoresponse in the PbS/CsPbBr3 heterojunction allows convolutional neuronal network processing for pattern recognition and edge enhancements from the Vis to the NIR waveband, suggesting the great potential of the PbS/CsPbBr3 heterostructure in artificial intelligent vision sensing.

Artificial Synapse Consisted of TiSbTe/SiCx:H Memristor with Ultra-high Uniformity for Neuromorphic Computing.

To enable a-SiCx:H-based memristors to be integrated into brain-inspired chips, and to efficiently deal with the massive and diverse data, high switching uniformity of the a-SiC0.11:H memristor is urgently needed. In this study, we introduced a TiSbTe layer into an a-SiC0.11:H memristor, and successfully observed the ultra-high uniformity of the TiSbTe/a-SiC0.11:H memristor device. Compared with the a-SiC0.11:H memristor, the cycle-to-cycle coefficient of variation in the high resistance state and the low resistance state of TiSbTe/a-SiC0.11:H memristors was reduced by 92.5% and 66.4%, respectively. Moreover, the device-to-device coefficient of variation in the high resistance state and the low resistance state of TiSbTe/a-SiC0.11:H memristors decreased by 93.6% and 86.3%, respectively. A high-resolution transmission electron microscope revealed that a permanent TiSbTe nanocrystalline conductive nanofilament was formed in the TiSbTe layer during the DC sweeping process. The localized electric field of the TiSbTe nanocrystalline was beneficial for confining the position of the conductive filaments in the a-SiC0.11:H film, which contributed to improving the uniformity of the device. The temperature-dependent I-V characteristic further confirmed that the bridge and rupture of the Si dangling bond nanopathway was responsible for the resistive switching of the TiSbTe/a-SiC0.11:H device. The ultra-high uniformity of the TiSbTe/a-SiC0.11:H device ensured the successful implementation of biosynaptic functions such as spike-duration-dependent plasticity, long-term potentiation, long-term depression, and spike-timing-dependent plasticity. Furthermore, visual learning capability could be simulated through changing the conductance of the TiSbTe/a-SiC0.11:H device. Our discovery of the ultra-high uniformity of TiSbTe/a-SiC0.11:H memristor devices provides an avenue for their integration into the next generation of AI chips.

Artificial Neurons and Synapses Based on Al/a-SiNxOy:H/P+-Si Device with Tunable Resistive Switching from Threshold to Memory.

As the building block of brain-inspired computing, resistive switching memory devices have recently attracted great interest due to their biological function to mimic synapses and neurons, which displays the memory switching or threshold switching characteristic. To make it possible for the Si-based artificial neurons and synapse to be integrated with the neuromorphic chip, the tunable threshold and memory switching characteristic is highly in demand for their perfect compatibility with the mature CMOS technology. We first report artificial neurons and synapses based on the Al/a-SiNxOy:H/P+-Si device with the tunable switching from threshold to memory can be realized by controlling the compliance current. It is found that volatile TS from Al/a-SiNxOy:H/P+-Si device under the lower compliance current is induced by the weak Si dangling bond conductive pathway, which originates from the broken Si-H bonds. While stable nonvolatile MS under the higher compliance current is attributed to the strong Si dangling bond conductive pathway, which is formed by the broken Si-H and Si-O bonds. Theoretical calculation reveals that the conduction mechanism of TS and MS agree with P-F model, space charge limited current model and Ohm's law, respectively. The tunable TS and MS characteristic of Al/a-SiNxOy:H/P+-Si device can be successfully employed to mimic the biological behavior of neurons and synapse including the integrate-and-fire function, paired-pulse facilitation, long-term potentiation and long-term depression as well as spike-timing-dependent plasticity. Our discovery supplies an effective way to construct the neuromorphic devices for brain-inspired computing in the AI period.

Tracing the Si Dangling Bond Nanopathway Evolution ina-SiNx:H Resistive Switching Memory by the Transient Current.

With the big data and artificial intelligence era coming, SiNx-based resistive random-access memories (RRAM) with controllable conductive nanopathways have a significant application in neuromorphic computing, which is similar to the tunable weight of biological synapses. However, an effective way to detect the components of conductive tunable nanopathways in a-SiNx:H RRAM has been a challenge with the thickness down-scaling to nanoscale during resistive switching. For the first time, we report the evolution of a Si dangling bond nanopathway in a-SiNx:H resistive switching memory can be traced by the transient current at different resistance states. The number of Si dangling bonds in the conducting nanopathway for all resistive switching states can be estimated through the transient current based on the tunneling front model. Our discovery of transient current induced by the Si dangling bonds in the a-SiNx:H resistive switching device provides a new way to gain insight into the resistive switching mechanism of the a-SiNx:H RRAM in nanoscale.

Nonintrusive Monitoring of Mental Fatigue Status Using Epidermal Electronic Systems and Machine-Learning Algorithms.

Mental fatigue, characterized by subjective feelings of "tiredness" and "lack of energy", can degrade individual performance in a variety of situations, for example, in motor vehicle driving or while performing surgery. Thus, a method for nonintrusive monitoring of mental fatigue status is urgently needed. Recent research shows that physiological signal-based fatigue-classification methods using wearable electronics can be sufficiently accurate; by contrast, rigid, bulky devices constrain the behavior of those wearing them, potentially interfering with test signals. Recently, wearable electronics, such as epidermal electronics systems (EES) and electronic tattoos (E-tattoos), have been developed to meet the requirements for the comfortable measurement of various physiological signals. However, comfortable, effective, and nonintrusive monitoring of mental fatigue levels remains to be fulfilled. In this work, an EES is established to simultaneously detect multiple physiological signals in a comfortable and nonintrusive way. Machine-learning algorithms are employed to determine the mental fatigue levels and a predictive accuracy of up to 89% is achieved based on six different kinds of physiological features using decision tree algorithms. Furthermore, EES with the trained predictive model are applied to monitor in situ human mental fatigue levels when doing several routine research jobs, as well as the effect of relaxation methods in relieving fatigue.

High Precision Thermoforming 3D-Conformable Electronics with a Phase-Changing Adhesion Interlayer.

Modern design-conscious products have raised the development of advanced electronic fabricating technologies. These widely used industrial technologies show high compatibility for inorganic materials and capacity for mass production. However, the morphology accuracy is hard to ensure and cracks happen easily, which could cause the degradation of device performance and life span. In order to make high precision 3D conformable electronics, a thermal phase-changing adhesion interlayer and modified fabricating processes are used in self-developed equipment. The working principles and influencing factors such as heating time and geometry parameters are studied quantitatively. The accuracy of fabricated patterns is enhanced by this new technology and serpentine designed structures. The delamination or detachment are significantly alleviated. Due to the operation convenience and compatibility with existing materials, the presented fabrication method has great potential for mass production of 3D curved conformable electronics.

Tunnel Encapsulation Technology for Durability Improvement in Stretchable Electronics Fabrication.

Great diversity of process technologies and materials have been developed around stretchable electronics. A subset of them, which are made up of zigzag metal foil and soft silicon polymers, show advantages of being easy to manufacture and low cost. However, most of the circuits lack durability due to stress concentration of interconnects entirely embedded in elastic polymer silicone such as polydimethylsiloxane (PDMS). In our demonstration, tunnel encapsulation technology was introduced to relieve stress of these conductors when they were stretched to deform in and out of plane. It was realized by dissolving the medium of Polyvinyl Alcohol (PVA), previous cured together with circuits in polymer, to form the micro-tunnel which not only guarantee the stretchability of interconnect, but also help to improve the durability. With the protection of tunnel, the serpentine could stably maintain the designed shape and electrical performance after 50% strain cycling over 20,000 times. Finally, different materials for encapsulation were employed to provide promising options for applications in portable biomedical devices which demand duplicate distortion.