Progress in the Development of Flexible Devices Utilizing Protein Nanomaterials

Flexible devices are soft, lightweight, and portable, making them suitable for large-area applications. These features significantly expand the scope of electronic devices and demonstrate their unique value in various fields, including smart wearable devices, medical and health monitoring, human-computer interaction, and brain-computer interfaces. Protein materials, due to their unique molecular structure, biological properties, sustainability, self-assembly ability, and good biocompatibility, can be applied in electronic devices to significantly enhance the sensitivity, stability, mechanical strength, energy density, and conductivity of the devices. Protein-based flexible devices have become an important research direction in the fields of bioelectronics and smart wearables, providing new material support for the development of more environmentally friendly and reliable flexible electronics. Currently, many proteins, such as silk fibroin, collagen, ferritin, and so on, have been used in biosensors, memristors, energy storage devices, and power generation devices. Therefore, in this paper, we provide an overview of related research in the field of protein-based flexible devices, including the concept and characteristics of protein-based flexible devices, fabrication materials, fabrication processes, characterization, and evaluation, and we point out the future development direction of protein-based flexible devices.

Unique Coexistence of Two Resistive Switching Modes in a Memristor Device Enables Multifunctional Neuromorphic Computing Properties

We report on hybrid memristor devices consisting of germanium dioxide nanoparticles (GeO2 NP) embedded within a poly(methyl methacrylate) (PMMA) thin film. Besides exhibiting forming-free resistive switching and an uncommon "ON" state in pristine conditions, the hybrid (nanocomposite) devices demonstrate a unique form of mixed-mode switching. The observed stopping voltage-dependent switching enables state-of-the-art bifunctional synaptic behavior with short-term (volatile/temporal) and long-term (nonvolatile/nontemporal) modes that are switchable depending on the stopping voltage applied. The short-term memory mode device is demonstrated to further emulate important synaptic functions such as short-term potentiation (STP), short-term depression (STD), paired-pulse facilitation (PPF), post-tetanic potentiation (PTP), spike-voltage-dependent plasticity (SVDP), spike-duration-dependent plasticity (SDDP), and, more importantly, the "learning-forgetting-rehearsal" behavior. The long-term memory mode gives additional long-term potentiation (LTP) and long-term depression (LTD) characteristics for long-term plasticity applications. The work shows a unique coexistence of the two resistive switching modes, providing greater flexibility in device design for future adaptive and reconfigurable neuromorphic computing systems at the hardware level.

One-Dimensional Covalent Organic Framework-Based Multilevel Memristors for Neuromorphic Computing

Memristors are essential components of neuromorphic systems that mimic the synaptic plasticity observed in biological neurons. In this study, a novel approach employing one-dimensional covalent organic framework (1D COF) films was explored to enhance the performance of memristors. The unique structural and electronic properties of two 1D COF films (COF-4,4'-methylenedianiline (MDA) and COF-4,4'-oxydianiline (ODA)) offer advantages for multilevel resistive switching, which is a key feature in neuromorphic computing applications. By further introducing a TiO2 layer on the COF-ODA film, a built-in electric field between the COF-TiO2 interfaces could be generated, demonstrating the feasibility of utilizing COFs as a platform for constructing memristors with tunable resistive states. The 1D nanochannels of these COF structures contributed to the efficient modulation of electrical conductance, enabling precise control over synaptic weights in neuromorphic circuits. This study also investigated the potential of these COF-based memristors to achieve energy-efficient and high-density memory devices.

Flexible multilevel nonvolatile biocompatible memristor with high durability

Current protein or glucose based biomemristors have low resistance-switching performance and require complex structural designs, significantly hindering the development of implantable memristor devices. It is imperative to discover novel candidate materials for biomemristor with high durability and excellent biosafety for implantable health monitoring. Herein, we initially demonstrate the resistance switching characteristics of a nonvolatile memristor in a configuration of Pt/AlOOH/ITO consisting of biocompatible AlOOH nanosheets sandwiched between a Indium Tin Oxides (ITO) electrode and a platinum (Pt) counter-electrode. The hydrothermally synthesized AlOOH nanosheets have excellent biocompatibility as confirmed through the Cell Counting Kit-8 (CCK-8) tests. Four discrete resistance levels are achieved in this assembled device in responsible to different compliance currents (ICC) for the set process, where the emerging multilevel states show high durability over 103 cycles, outperforming the protein-based biomemristors under similar conditions. The excellent performance of the Pt/AlOOH/ITO memristor is attributed to the significant role of hydrogen proton with pipe effect, as confirmed by both experimental results and density functional theory (DFT) analyses. The present results indicate the nonvolatile memristors with great potential as the next generation implantable multilevel resistive memories for long-term human health monitoring.

Realization of Artificial Nerve Synapses Based on Biological Threshold Resistive Random Access Memory

A one-selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high-density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10-7  A), a high ON/OFF current ratio (106 ), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA-based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein-based 1S1R array to achieve high-density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.).

Flexible Transient Resistive Memory Based on Biodegradable Composites

Physical transient electronics have attracted more attention as the basis for building green electronics and biomedical devices. However, there are difficulties in selecting materials for the fabricated devices to take into account both biodegradability and high performance. In this paper, a physically transient resistive random-access memory (RRAM) device was fabricated by using egg protein and graphene quantum dot composites as active layers. The sandwich structure composed of Al/EA:GQD/ITO shows a good write-once-multiple-read memory characteristic, and the introduced GQD improves the switching current ratio of the device. By using the sensitivity of GQDs to ultraviolet light, the logic operation of the "OR gate" is completed. Furthermore, the device exhibits a physical transient behavior and good biodegradability due to the dissolution behavior in deionized water. These results suggest that the device is a favorable candidate for the construction of memory elements for transient electronic systems.

Biopolymer based artificial synapses enable linear conductance tuning and low-power for neuromorphic computing

Neuromorphic computing is considered a promising method for resolving the traditional von Neumann bottleneck. Natural biomaterial-based artificial synapses are popular units for constructing neuromorphic computing systems while suffering from poor linearity and limited conduction states. In this work, a AgNO₃ doped iota-carrageenan (ι-car) based memristor is proposed to resolve the non-linear limitation. The memristor presents linear conductance tuning with a higher endurance (∼10⁴), more enriched conduction states (>2000), and much lower power consumption (∼3.6 μW) than previously reported biomaterial-based analog memristors. AgNO₃ is doped to ι-car to suppress the formation of Ag filaments, thereby eliminating uneven Joule heating. Using deep learning of hand-written digits as an application, a doping-enhanced recognition accuracy (93.8%) is achieved, close to that of an ideal synaptic device (95.7%). This work verifies the feasibility of using biopolymers for future high-performance computational and wearable/implantable electronic applications.

Physically Transient, Flexible, and Resistive Random Access Memory Based on Silver Ions and Egg Albumen Composites

Organic-resistance random access memory has high application potential in the field of next-generation green nonvolatile memory. Because of their biocompatibility and environmental friendliness, natural biomaterials are suitable for the fabrication of biodegradable and physically transient resistive switching memory devices. A flexible memory device with physically transient properties was fabricated with silver ions and egg albumen composites as active layers, which exhibited characteristics of write-once-read-many-times (WORM), and the incorporation of silver ions improved the ON/OFF current ratio of the device. The device can not only complete the logical operations of "AND gate" and "OR gate", but its active layer film can also be dissolved in deionized water, indicating that it has the characteristics of physical transients. This biocompatible memory device is a strong candidate for a memory element for the construction of transient electronic systems.

Applications of biomemristors in next generation wearable electronics

With the rapid development of mobile internet and artificial intelligence, wearable electronic devices have a great market prospect. In particular, information storage and processing of real-time collected data are an indispensable part of wearable electronic devices. Biomaterial-based memristive systems are suitable for storage and processing of the obtained information in wearable electronics due to the accompanying merits, i.e. sustainability, lightweight, degradability, low power consumption, flexibility and biocompatibility. So far, many biomaterial-based flexible and wearable memristive devices were prepared by spin coating or other technologies on a flexible substrate at room temperature. However, mechanical deformation caused by mechanical mismatch between devices and soft tissues leads to the instability of device performance. From the current research and practical application, the device will face great challenges when adapting to different working environments. In fact, some interesting studies have been performed to address the above issues while they were not intensively highlighted and overviewed. Herein, the progress in wearable biomemristive devices is reviewed, and the outlook and perspectives are provided in consideration of the existing challenges during the development of wearable biomemristive systems.

Ferritin-Based Single-Electron Devices

We report on the fabrication of single-electron devices based on horse-spleen ferritin particles. At low temperatures the current vs. voltage characteristics are stable, enabling the acquisition of reproducible data that establishes the Coulomb blockade as the main transport mechanism through them. Excellent agreement between the experimental data and the Coulomb blockade theory is demonstrated. Single-electron charge transport in ferritin, thus, establishes a route for further characterization of their, e.g., magnetic, properties down to the single-particle level, with prospects for electronic and medical applications.

'Stateful' threshold switching for neuromorphic learning

Memristors have promising prospects in developing neuromorphic chips that parallel the brain-level power efficiency and brain-like computational functions. However, the limited available ON/OFF states and high switching voltage in conventional resistive switching (RS) constrain its practical and flexible implementations to emulate biological synaptic functions with low power consumption. We present 'stateful' threshold switching (TS) within the millivoltage range depending on the resistive states of RS, which originates from the charging/discharging parasitic elements of a memristive circuit. Fundamental neuromorphic learning can be facilely implemented based on a single memristor by utilizing four resistive states in 'stateful' TS. Besides the metaplasticity of synaptic learning-forgetting behaviors, multifunctional associative learning, involving acquisition, extinction, recovery, generalization and protective inhibition, was realized with nonpolar operation and power consumption of 5.71 pW. The featured 'stateful' TS with flexible tunability, enriched states, and ultralow operating voltage will provide new directions toward a massive storage unit and bio-inspired neuromorphic system.

New Silk Road: From Mesoscopic Reconstruction/Functionalization to Flexible Meso-Electronics/Photonics Based on Cocoon Silk Materials

Two of the key questions to be addressed are whether and how one can turn cocoon silk into fascinating materials with different electronic and optical functions so as to fabricate the flexible devices. In this review, a comprehensive overview of the unique strategy of mesoscopic functionalization starting from silk fibroin (SF) materials to the fabrication of various meso flexible SF devices is presented. Notably, SF materials with novel and enhanced properties can be achieved by mesoscopically reconstructing the hierarchical structures of SF materials. This is based on rerouting the refolding process of SF molecules by meso-nucleation templating. As-acquired functionalized SF materials can be applied to fabricate bio-compatible/degradable flexible/implantable meso-optical/electronic devices of various types. Consequently, functionalized SF can be fabricated into optical elements, that is, nonlinear photonic and fluorescent components, and make it possible to construct silk meso-electronics with high-performance. These advances enable the applications of SF-material based devices in the areas of physical and biochemical sensing, meso-memristors, transistors, brain electrodes, and energy generation/storage, applicable to on-skin long-term monitoring of human physiological conditions, and in-body sensing, information processing, and storage.

Optoelectronic Artificial Synapses Based on Two-Dimensional Transitional-Metal Trichalcogenide

The memristor is a foundational device for an artificial synapse, which is essential to realize next-generation neuromorphic computing. Herein, an optoelectronic memristor based on a two-dimensional (2D) transitional-metal trichalcogenide (TMTC) is designed and demonstrated. Owing to the excellent optical and electrical characteristics of titanium trisulfide (TiS₃), the memristor exhibits stable bipolar resistance switching (RS) as a result of the controllable formation and rupturing of the conductive aluminum filaments. Multilevel storage is realized with light of multiple wavelengths between 400 and 808 nm, and the synaptic properties such as conduction modulation and spiking timing-dependent plasticity (STDP) are achieved. On the basis of the photonic potentiation and electrical habitual ability, Pavlovian-associative learning is successfully established on this TiS₃-based artificial synapse. All these results reveal the large potential of 2D TMTCs in artificial neuromorphic chips.

Fabrication and investigation of quaternary Ag-In-Zn-S quantum dots-based memristors with ultralow power and multiple resistive switching behaviors

Quaternary Ag-In-Zn-S (AIZS) quantum dots (QDs) play critical roles in various applications since they have advantages of combining superior optical and electrical features, such as tunable fluorescence emission and high carrier mobilities. However, the application of semiconductor AIZS QDs in brain-inspired devices (e.g. memristor) has been rarely reported. In this work, the tunable volatile threshold switching (TS) and non-volatile memory switching (MS) behaviors have been obtained in a memristor composed of AIZS QDs by regulating the magnitude of compliance current. Additionally, the innovative Ag/AIZS structure devices without traditional oxide layer exhibit low operation voltage (∼0.25 V) and programming current (100 nA) under the TS mode. Moreover, the devices achieve reproducible bipolar resistive switching (RS) behaviors with large ON/OFF ratio of ∼10⁵, ultralow power consumption of ∼10^-10 W, and good device-to-device uniformity under the MS mode. Furthermore, the charge transport mechanisms of the high- and low-resistance states under the positive and negative bias have been analyzed with space-charge-limited-current and filament conduction models, respectively. This work not only validates the potential of AIZS QDs acting as dielectric layer in RS devices but also provides a new guideline for designing ultralow power and multiple RS characteristics devices.

90% yield production of polymer nano-memristor for in-memory computing

Polymer memristors with light weight and mechanical flexibility are preeminent candidates for low-power edge computing paradigms. However, the structural inhomogeneity of most polymers usually leads to random resistive switching characteristics, which lowers the production yield and reliability of nanoscale devices. In this contribution, we report that by adopting the two-dimensional conjugation strategy, a record high 90% production yield of polymer memristors has been achieved with miniaturization and low power potentials. By constructing coplanar macromolecules with 2D conjugated thiophene derivatives to enhance the π–π stacking and crystallinity of the thin film, homogeneous switching takes place across the entire polymer layer, with fast responses in 32 ns, D2D variation down to 3.16% ~ 8.29%, production yield approaching 90%, and scalability into 100 nm scale with tiny power consumption of ~ 10⁻¹⁵ J/bit. The polymer memristor array is capable of acting as both the arithmetic-logic element and multiply-accumulate accelerator for neuromorphic computing tasks.

Though polymer memristors are promising for low‐power flexible edge computing applications, realizing efficient nanometer‐scale arrays remains a challenge. Here, the authors report a record high 90% production yield in nm‐scale 2D conjugated polymer memristors with homogeneous resistive switching.

Building memory devices from biocomposite electronic materials

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.

Analog Memristive Characteristics of Mesoporous Silica-Titania Nanocomposite Device Concurrent with Selection Diode Property

A threshold resistive switching (RS) device concurrently demonstrating analog memristive property with mesoporous silica-titania (m-ST) nanocomposites is introduced in this study. The nanostructured m-ST layer in an Al/m-ST/Pt device was constructed by facile soft templating of evaporation-induced self-assembly (EISA) method to demonstrate nonlinear threshold RS behaviors accompanying with discrete synaptic characteristics along with adaptive motions. The EISA layer was composed of well-ordered mesopores (∼10 nm), where paths of electrical currents could be controllably guided and sequentially activated by repeated voltage sweeps. The combinational memristive behavior accompanying the shift of threshold voltage (V_th) could implicate concurrent performances of threshold RS and selection diode devices. In addition, synaptic functionalities of long-term potentiation and depression were characterized by variations of pulse timing width (7-100 ms). Physical and chemical features of the m-ST were analyzed with Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, field emission scanning electron microscopy, high-resolution transmission electron microscopy, and optical microscopy to investigate the unique origin of dual operation modes of the device. The m-ST synaptic device could have potential for further development of a hybrid selection diode having both a low sneaky current loss and memristive characteristics accomplishing low level of cross-talk between RS devices.

Solid-State Electrochemical Process and Performance Optimization of Memristive Materials and Devices

As an emerging technology, memristors are nanoionic-based electrochemical systems that retains their resistance state based on the history of the applied voltage/current. They can be used for on-chip memory and storage, biologically inspired computing, and in-memory computing. However, the underlying physicochemical processes of memristors still need deeper understanding for the optimization of the device properties to meet the practical application requirements. Herein, we review recent progress in understanding the memristive mechanisms and influential factors for the optimization of memristive switching performances. We first describe the working mechanisms of memristors, including the dynamic processes of active metal ions, native oxygen ions and other active ions in ECM cells, VCM devices and ion gel-based devices, and the switching mechanisms in organic devices, along with discussions on the influential factors of the device performances. The optimization of device properties by electrode/interface engineering, types/configurations of dielectric materials and bias scheme is then illustrated. Finally, we discuss the current challenges and the future development of the memristor.

Organic and hybrid resistive switching materials and devices

This review presents a timely and comprehensive summary of organic and hybrid materials for nonvolatile resistive switching memory applications in the “More than Moore” era, with particular attention on their designing principles for electronic property tuning and flexible memory performance.

Ultralow Power Consumption Flexible Biomemristors

Low power consumption is the important requirement in memory devices for saving energy. In particular, improved energy efficiency is essential in implantable electronic devices for operation under a limited power supply. Here, we demonstrate the use of κ-carrageenan (κ-car) as the resistive switching layer to achieve memory that has low power consumption. A carboxymethyl (CM) group is introduced to the κ-car to increase its ionic conductivity. Ag was doped in CM:κ-car to improve the resistive switching properties of the devices. Memory devices based on Ag-doped CM:κ-car showed electroforming-free resistive switching. This device exhibited low reset voltage (∼0.05 V), fast switching speed (50 ns), and high on/off ratio (>10³) under low compliance current (10^-5 A). Its power consumption (∼0.35 μW) is much lower than those of the previously reported biomemristors. The resistive switching may be a result of an electrochemical redox process and Ag filament formation in the CM:κ-car under an electric field. This biopolymer memory can also be fabricated on flexible substrate. This study verifies the feasibility of using biopolymers for applications to future implantable and biocompatible nanoelectronics.

Highly Uniform Resistive Switching Properties of Solution-Processed Silver-Embedded Gelatin Thin Film

The silver-embedded gelatin (AgG) thin film produced by the solution method of metal salts dissolved in gelatin is presented. Its simple fabrication method ensures the uniform distribution of Ag dots. Memory devices based on AgG exhibit good device performance, such as the ON/OFF ratio in excess of 10⁵ and the coefficient of variation in less of 50%. To further investigate the position of filament formation and the role of each element, current sensing atomic force microscopy (CSAFM) analysis as well as elemental line profiles across the two different conditions in the LRS and HRS are analyzed. The conductive and nonconductive regions in the current map of the CSAFM image show that the conductive filaments occur in the AgG layer around Ag dots. The migration of oxygen ions and the redox reaction of carbon are demonstrated to be the driving mechanism for the resistive switching of AgG memory devices. The results show that dissolving metal salts in gelatin is an effective way to achieve high-performance organic-electronic applications.

Short-Term Plasticity and Long-Term Potentiation in Artificial Biosynapses with Diffusive Dynamics

The development of electronic devices possessing the functionality of biological synapses is a crucial step toward replicating the capabilities of the human brain. Of the various materials that have been used to realize artificial synapses, renewable natural materials have the advantages of being abundant, inexpensive, biodegradable, and ecologically benign. In this study, we report a biocompatible artificial synapse based on a matrix of the biopolymer ι-carrageenan (ι-car), which exploits Ag dynamics. This artificial synapse emulates the short-term plasticity (STP), paired-pulse facilitation (PPF), and transition from STP to long-term potentiation (LTP) of a biological synapse. The above-mentioned characteristics are realized by exploiting the similarities between the Ag dynamics in the ι-car matrix and the Ca²⁺ dynamics in a biological synapse. By demonstrating a method that uses biomaterials and Ag dynamics to emulate synaptic functions, this study confirms that ι-car has the potential for constructing neuromorphic systems that use biocompatible artificial synapses.

Nonvolatile Bio-Memristor Based on Silkworm Hemolymph Proteins

This paper reports the first successful fabrication of an ITO/silkworm hemolymph/Al bio-memristor using silkworm hemolymph as the active layer. Experiments demonstrate that the silkworm hemolymph bio-memristor is a nonvolatile rewritable bipolar memory device with a current switching ratio exceeding 10³. The state of the bio-memristor can be retained for more than 10⁴ seconds and remains stable for at least 500 cycles. Tests of 1/f noise have shown that the resistance switching characteristics of the silkworm hemolymph bio-memristor are related to the formation and breaking of conductive filaments, which result from the migration of oxygen ions and the oxidation and reduction of metal cations in the silkworm hemolymph film. The naturally non-toxic silkworm hemolymph offers advantages for human health, environmental protection, and biocompatibility. The proposed nonvolatile rewritable bio-memristor based on silkworm hemolymph possesses great application potential.