Cellulose Nanocrystal Based Bio‐Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications See discussions, stats, and author profiles for this publication at https www researchgate netpublication355430751 Cellulose Nanocrystal Based Bio‐Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications Article in Advanced Materials Technologies October 2021 DOI 10 1002admt 202100744 CITATIONS 4 READS 153 11 authors, including Some of the au.
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/355430751 Cellulose Nanocrystal Based Bio‐Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications Article in Advanced Materials Technologies · October 2021 DOI: 10.1002/admt.202100744 CITATIONS READS 153 11 authors, including: Tassawar Hussain Haider Abbas KU Leuven & IMEC.be Nanyang Technological University 14 PUBLICATIONS 95 CITATIONS 31 PUBLICATIONS 378 CITATIONS SEE PROFILE SEE PROFILE Turgun Boynazarov Boncheol Ku Sejong University Hanyang University PUBLICATIONS 6 CITATIONS 16 PUBLICATIONS 389 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Development of Resistive Random Access Memory (RRAM) Devices View project corrosion, metallurgy, surface coating View project All content following this page was uploaded by Turgun Boynazarov on 21 October 2021 The user has requested enhancement of the downloaded file SEE PROFILE Research Article www.advmattechnol.de Cellulose Nanocrystal Based Bio-Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications Tassawar Hussain, Haider Abbas, Chulmin Youn, Hojin Lee, Turgun Boynazarov, Boncheol Ku, Yu-Rim Jeon, Hoonhee Han, Jong Hyeon Lee, Changhwan Choi,* and Taekjib Choi* sustainable materials and green electronics.[1,2] In particular, eco-friendly, renewable, bio-compatible, and bio-degradable natural biomaterials are potential alternatives to emerging green electronics that can reduce harmful electronic waste The use of natural biomaterials greatly aids the sustainable development of the electronics industry.[2–5] In fact, natural biomaterials such as (e.g., silk fibroin, spider silk, cellulose, chitosan, etc.) have been widely employed in a variety of green-electronic systems, such as energy storage devices, biosensors, and bio-memristor, benefiting from unique biological structure, biocompatibility, biodegradability, transparency, and flexibility.[6–8] However, biomaterials often exhibit degradable and unstable performance due to their weak electrical function Therefore, recent investigations into biocomposites containing one or more naturally-derived content combined with other functional materials have shown the improved performance of bioelectronic elements.[2,9–11] In addition, increasing demand for green information storage and computation technology has accelerated the rapid development of nonvolatile memory devices based on biocomposite materials Among the emerging nonvolatile memory technologies, resistive switching random access memory (RRAM), in which the resistance states can be switched between the high resistance state (HRS) and the low resistance state (LRS) by applying an electric field, has Nanocomposites based on biomaterials are promising candidates for emerging green- electronics benefiting from environment-friendly, renewable, biocompatible, and biodegradable resources for sustainable research and development Especially, the application of biocomposites-based memristor for simulating artificial synapses called bio-memristor has further facilitated the progress of ecologically benign bioelectronics In this study, the authors present that the environment-friendly nanocomposites films, consisting of Ag nanoparticles and cellulose nanocrystal (CNC)-based bio-memristor with excellent bipolar resistive switching behavior can perform the artificial bio-synaptic emulation with continuous resistance modulation for memory storage and neuromorphic computing applications The bio-memristor exhibits a large resistive switching (ION/OFF as high as ≈104 and ultralow SET/RESET voltage of ≈0.2 V) and reliable switching characteristics through the electrochemical formation/ rupture of Ag metallic filaments within the nanocomposite layer The device presents coexistence of digital and analog switching properties favorable for both nonvolatile digital memory and neuromorphic computing applications By applying appropriate pulse stimulations to the device, the authors demonstrate biological synaptic functions, including long-term potentiation/depression, spike-rate-dependent plasticity, excitatory post-synaptic current, paired-pulse facilitation, and paired-pulse depression Thus, this CNC-based bio-memristor as an effective artificial synaptic device is beneficial towards the realization of green-electronics and bio-inspired neuromorphic systems Introduction Global concerns over environmental issues from growing electronic waste along with a tremendous production of silicon-based electronics have stimulated extensive research into T Hussain, C Youn,[+] H Lee, T Boynazarov, T Choi Hybrid Materials Research Center and Department of Nanotechnology and Advanced Materials Engineering Sejong University Seoul 143-747, South Korea E-mail: tjchoi@sejong.ac.kr The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/admt.202100744 [+]Present address: Advanced Textile R&D Department, Korea Institute of Industrial Technology, Ansan-si, 15588, South Korea H Abbas, B Ku, Y.-R Jeon, H Han, C Choi Division of Materials Science and Engineering Hanyang University Seoul 04763, South Korea E-mail: cchoi@hanyang.ac.kr J H Lee Department of Chemistry Catholic University of Korea Bucheon, Gyeonggi 420-743, South Korea DOI: 10.1002/admt.202100744 Adv Mater Technol 2021, 2100744 2100744 (1 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de gained intensive research interest due to its simple structure with an insulating layer sandwiched between two conducting electrodes.[12–15] This simple capacitor-like structure can provide large-scale integration and high-density storage through the fabrication of a 3D stacked crossbar array. It is worth noting that as a suitable material for implementing green nonvolatile memory devices, biocomposites have proven resistive switching devices with excellent performance Celano et al represented biodegradable RRAM devices consisting of a nanocellulosebased resistive switching layer and a nano-paper substrate, which exhibit bipolar resistive switching as well as multilevel storage.[16] By using egg albumen as a switching layer, the water-soluble and flexible RRAMs were reported with long retention time and fast switching speed, in which the switching performance was improved by the hybridization of metal nanoparticles (NPs).[17] On the other hand, besides RRAM based on biocomposites, biomaterials such as lignin, carrageenan, and collagen have been designed as bio-memristor for simulating biological synaptic functions via analog resistive switching behaviors.[18,19] Moreover, biocomposites-based RRAM is one of the promising candidates for next-generation bio-memristor with advantages of low power consumption, compatibility, reliability, high switching ratio, and high storage density.[20] In particular, bio-memristor composed of bio-nanocomposites with both digital and analog switching characteristics is highly desirable to realize biorealistic synaptic devices for neuromorphic computing that can overcome the limitations of von Neumann computing.[21] However, there are very limited reports on the co-existence of digital and analog switching bio-memristors comprising biodegradable, eco-friendly, and green dielectric materials as a primary element A number of artificial synaptic devices have been proposed, where the main switching layer is based on inorganic materials.[13,22–25] For example, Ohno et al.[26] reported synaptic behavior of Ag/Ag2S/nanogap/Pt device controlled by adjusting repetition time of input pulses Serb et al.[27] reported synapses with gradual, intrinsic, and multilevel resistive switching in TiO2-based memristor Similarly, Wang et al.[28] investigated synaptic behavior of FeOx based memristor by manipulating different analog characteristics via controlling compliance current during the electroforming process However, these inorganic metal oxide-based devices are not environment-friendly, and new low-cost biodegradable organic materials should be replaced with conventional materials in electronic synaptic devices for implantable and wearable biomedical applications.[18,29–31] In this regard, Park et al.[18] reported artificial synapses in lignin-based bio-memristor devices, lignin is biodegradable and the abundant renewable material extracted from plants Li et al.[32] reported a bio-memristor based synaptic device with a hybrid structure of Ag/HfO2/BSA:Au/Pt They used hybrid biomaterial of bovine serum doped with nano-gold (BSA:Au) and HfO2 double layers as insulating switching layer materials Similarly, Li et al.[33] reported synaptic plasticity in a biodegradable organic conducting polymer of PEDOT:PSS with Ag/PEDOT:PSS/Ta device structure Here, we report cellulose nanocrystal (CNC)-based nanocomposite as a bio-memristor for both memory storage and synaptic application Cellulose nanofiber (CNF), one of the abundant and emerging green materials derived from plant cells, is the focus Adv Mater Technol 2021, 2100744 of modern research on a variety of novel high-tech material applications.[34–36] CNF, having a nanometric diameter below 50 nm and micrometric length with alternating crystalline and amorphous structure, provide excellent mechanical properties, including high stiffness, good tensile strength, and high surface area The surfaces of CNFs with the abundant hydroxyl (-OH) functional groups also provide greater flexibility for modification and incorporation of various other functional groups for the desired applications.[34,37,38] We have successfully utilized CNCs into fabricating a bio-memristor for both memory storage (bio-RRAM), and neuromorphic computing application as an artificial synaptic device.[16] CNFs were modified by TEMPO oxidation and periodate oxidation processes for the hybridization of silver (Ag+) ions along its 1D CNC structure Our bio-memristor showed the coexistence of both digital and analog switching characteristics Besides a stable and reliable bipolar switching behavior, the features of bio-synaptic functioning such as longterm potentiation (LTP), long-term depression (LTD), spike rate-dependent plasticity (SRDP), specifically paired-pulse facilitation (PPF), paired-pulse depression (PPD), and post-tetanic potentiation (PTP) are demonstrated using analog-voltage bias to consecutive conductance modulation Ionic excitatory postsynaptic current (EPSC) is performed with the decay function of silver conducting filament Through the ultralow operation voltages for both digital and analog switching, our bio-memristors are beneficial for highly efficient synaptic devices Results and Discussion CNF insulating material was used as a precursor in our memristor device which was modified for growing in situ AgNPs along with its chemical structure CNF was subjected to successive TEMPO-mediated oxidation and Periodate oxidation after which AgNPs were in situ-grown on it by tollen’s reaction Figure 1a schematically illustrates the chemical reactions, modification steps and NPs of silver grown on CNCs and the detailed method is explained in the synthesis section CNFs are fiber bundles with alternative crystalline and amorphous regions, by TEMPO oxidation we only get individual TCNC with carbonyl and aldehyde functional groups, and by periodate oxidation, we tend to increase the dialdehyde functional groups in the obtained CNCs.[39–42] The thin rod-like structure of nanocrystals can be observed by the TEM image of our prepared Tempo-oxidized CNCs as shown in Figure 1b To confirm the uniform attachment of AgNPs on CNCs a small amount of the final solution is drop-casted on FTO and dried at room temperature, after which it was analyzed with EDX for its elemental mapping, which confirms the uniform distribution of AgNPs along the coating as shown in Figure 1c To investigate the chemical properties of CNF, surface analysis of pristine CNF, TCNC, and dialdehyde-TCNC (DAC) was performed using FTIR-ATR analysis as shown in Figure 2a The FTIR results of pristine CNF can be clearly distinguished from TCNC and DAC, where the infrared spectra of both TCNC and DAC have the negative functional groups stretching such as (CH, CC, COC, CO, CH, and OCH) in addition to (OH) functional group of pristine CNF.[43–45] In all samples, the broad bands around 3100–3600 cm−1 region are assigned 2100744 (2 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 1. a) Schematic illustration of chemical modification reactions, and attachment of Ag-NPs along CNC structure, b) The TEM image of prepared Tempo-oxidized CNCs from CNF, and c) EDS elemental mapping analysis of the deposited Ag-TCNC thin film on FTO showing uniform distribution of Ag-NPs on nanocrystals to OH stretching vibrations, and in the final DAC sample, the band around 2970 cm−1 refers to CH stretching vibrations, around 1635 cm−1 it can refer to the offset of absorbed water OH band or a CC aromatic band, at 1450 cm−1 it can attribute to HCH and OCH in-plane bending vibrations, and around 1380 cm−1 it is the C-H deformation vibration.[43,46] The stretching at 1085 cm−1 refers to the COC stretching of glucose and at 1045 cm−1 it reflects to the CO stretching of pyranose ring vibrations All these functional groups belong to TCNC and DAC crystals confirming successive TEMPO-oxidation and Periodate oxidation The increased peak intensity of hemiacetal at 881 cm−1 and CH stretching in the FTIR results of final DAC demonstrates that the TCNC is oxidized to DAC having a higher amount of aldehyde functional groups.[47,48] These functional groups were introduced by the discussed oxidation reactions so that the AgNPs can be easily and successfully attached along the length of CNCs at the aldehyde sites.[46,49,50] Free silver (Ag+) cations of the tollen’s reagent [Ag(NH3)2]+OH− reacts with an aldehyde (CHO) and carbonyl (CO) functional groups and is precipitated at these sites as NPs which later facilitates the formation of conducting filaments.[51,52] The particles zeta-potential (ζ) of parent material and after each modification steps were measured and a noticeable expected trend in electro-negativity shift is observed as shown in Figure 2b The mean value of zeta-potential is shifted towards a more electronegative value from CNF ≈ (−33.2 ± 5.27 mV) to TCNC ≈ (−71.3 ± 4.80 mV) when CNF is transformed because of the evident reason of replacing some of the (OH) functional groups with more electronegative functional groups Adv Mater Technol 2021, 2100744 of carboxylate by tempo-oxidation along nanocrystals After the periodate oxidation the mean value of zeta-potential (ζ) is shifted to DAC ≈ (−63.8 ± 5.28 mV) which is because of the increase in the introduction of aldehyde group so, the replacement of carboxylate group with a less electronegative aldehyde functional group along TCNC length And at the final stage as a result of tollen’s reaction, the free silver-ions (Ag+) precipitation at the aldehyde sites along the nanocrystals, which further shifts the zeta-potential towards a less electronegative value of AgNPs-TCNC ≈ (−44.1 ± 5.56 mV) This shift in zeta-potential (ζ) value after tollen’s reaction also indicates the successful attachment of free silver ions along the nanocrystals The schematic presentation of the complete memristor devices and the XRD characteristics of the switching layer is presented in Figure Figure 3a shows the schematic structures of the biological synapse and the memristor device with Ag and FTO top and bottom electrodes and AgNPs-TCNC (nanopaper) as a sandwiched switching layer of MIM configuration The structure of our bio-memristor correlates with that of the biological synapse The crystallinity of the coated AgNPs-TCNC insulating layer on the FTO substrate prior to the deposition of the top electrode was observed by XRD analysis The XRD graph of AgNPs-TCNC film is indexed with standard JCPDS patterns of Ag (JCPDS: 04-0783), and cellulose Iβ as shown in Figure 3b The sample had shown cellulose Iβ patterns with the diffraction peaks of 2θ at 15.3⁰ (110), 19.3⁰ (110), and 22.8⁰ (200).[46,53,54] The crystallographic planes of cubic Ag in the Ag-TCNC nanocomposite were identified by the observed diffraction peaks of 2θ at 38.1⁰ (111), and 44.5⁰ (200), further 2100744 (3 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 2. a) FTIR-ATR spectra of CNF, TCNC, and DAC materials, and b) Zeta-Potential behavior of particles of CNF, TCNC, DAC, and AgNPs-TCNC confirming the crystalline nature of attached metallic silver on the CNC surfaces.[46,55] As discussed in the introduction section, our bio-memristor device showed a repeatable dual switching behavior of digital switching and analog switching with the coexistence of both types of switching The switching behavior could be controlled by controlling the switching voltages The digital switching and analog switching characteristics could be achieved by tuning the switching voltages above ±0.15 and below ±0.10 V, respectively The digital switching characteristics are utilized for digital memory applications Whereas, the analog switching behavior is exploited to emulate the important biological synaptic functions of the brain for neuromorphic computing 2.1 Digital Switching for Memory Applications The fabricated memristor device with 4.37 µm thickness of the insulating layer and 100 µm2 size silver top electrode of ≈150 nm thickness was subjected to measurement at room temperature and atmospheric pressure The FTO bottom electrode was grounded, whereas the silver top electrode was connected with the tungsten probe tip to control the applied bias voltage during the current–voltage (I–V) measurements We applied alternative positive and negative voltage sweeps from to ±0.5 V for the digital switching A high-voltage electroforming process was needed to initiate the switching The electroforming Adv Mater Technol 2021, 2100744 process is a phenomenon of resistive memories where the initial conductive filaments begin to grow by the progression of oxidized metal ions migration within the insulating medium by the application of applied voltage.[56] As a result of the continuous growth of these filaments, the top and bottom conducting electrodes connect together by virtue of which the insulating high resistance (OFF) state changes to conductive low resistance (ON) state It is usually a preparatory step in most of the memristors before the actual switching cycles and voltages for SET (ON) and RESET (OFF) are observed SET voltage (VSET) is the value of the voltage at which the current level abruptly changes from a high resistance value to a low resistance value transforming the device from OFF state to ON state, and the sandwiched insulating medium between the top and bottom conducting electrode can now conduct current by the growth of these conductive filaments within the medium While the RESET voltage (VRESET) represents the value of voltage at which the opposite phenomenon occurs and the conducting filaments break down and no more high level of current can pass through the insulating medium and its resistance state abruptly changes from lower resistance values to high resistance value which means the device is again transformed to OFF state The digital switching characteristics of the device and its repeatability and reliability for nonvolatile memory applications are presented in Figure The device needed an initial electroforming process to initiate the resistive switching The I–V curve for the forming process is shown in Figure S1, Supporting Information The forming voltage was found to be ≈−1.6 V Figure 4a illustrates switching cycles after the initial forming process The change of HRS to LRS after the completion of forming was reversed by applying the positive bias voltage sweep (RESET) Subsequently, after the reversal of forming, the device was SET to LRS by negative voltage sweep (0 to −0.5 V) and RESET back again to HRS by positive voltage sweep (0 to +0.5 V), while this time lower VSET than the first forming voltage was observed By applying the alternative positive and negative voltage sweeps from V to ±0.5 V, a sharp digital SET/RESET can be seen To check the effect of compliance current, the compliance current was increased from 10−3 to 10−2 A after 100 switching cycles for the same device and a compliance-free digital switching behavior was observed for the subsequent 150 continuous cycles (Figure S2, Supporting Information) The switching stability and cycle-to-cycle variability of our memristor device were evaluated by the data endurance characteristics, as shown in Figure 4b,c The DC endurance characteristics were evaluated up to 200 continuous switching cycles, as shown in Figure 4b The device showed good endurance properties, maintaining a decent ON/OFF resistance ratio of ≈104 at a readout voltage of 0.04 V Moreover, the pulse endurance characteristics were tested to evaluate the endurance characteristics of the device for a higher number of cycles The device presented repeatable bipolar switching without any failure for 104 cycles, as presented in Figure 4c The LRS was relatively stable, whereas variations in HRS were observed The variation in HRS is attributed to the stochastic behavior of the conducting filament rupture during the RESET process.[13] For pulse endurance measurement, the SET and RESET pulses with pulse amplitudes of −1 and +1 V were applied, followed by a small read pulse of 0.05 V The pulse widths of both SET and 2100744 (4 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 3. a) Schematic diagrams of the device structure and biological synapse presenting a correlation between the memristor and biological synapse b) XRD pattern of final AgNPs-TCNC film on FTO RESET pulses were ms and that of the read pulse was 0.3 ms Moreover, the study of the device-to-device variability is a prerequisite for mass production and is essential for the practical applications of the devices The digital switching characteristics of different devices were tested to evaluate the device-todevice variability for the basic digital switching properties of the devices The typical I–V characteristics of five different devices showing the device-to-device switching variability for the digital switching are presented in Figure S3, Supporting Information It is noted that all of the devices exhibited digital switching with negligible variations in the switching voltages and the HRS and LRS levels This shows that the CNF-based devices exhibit better device-to-device repeatability for digital switching confirming the suitability of the devices for nonvolatile memory applications Furthermore, the nonvolatile switching behavior was evaluated with the retention time measurements The data retention characteristics of the device are presented in Figure 4d It is noted that both ON and OFF states of the device were maintained for more than 104 s confirming the nonvolatile nature of our memristor device The device maintained an ON/ OFF ratio of ≈104 over the time The average VSET and VRESET values calculated from continuous switching cycles were −0.187 and +0.211 V, respectively For VSET and VRESET the standard deviation was measured to be 0.0187 and 0.0859, respectively, Adv Mater Technol 2021, 2100744 which indicates a minimal and acceptable variation of switching voltages during switching cycles The statistical distributions of operational VSET and VRESET and resistance levels during HRS and LRS are also plotted in Figure 4e,f as the form of a cumulative probability to show the distribution of VSET and VRESET values and HRS and LRS levels recorded during these switching cycles If we see the distribution of the SET and RESET voltages over the repeated DC sweep cycles we can see that the average RESET voltage during the repeated DC sweeps is higher than the SET voltage For the repeated DC sweep cycles, the RESET voltages are distributed from about −0.17–−0.28 V, whereas the SET voltages are distributed as about 0.16–0.42 V The cycleto-cycle variability in the RESET voltage is higher than that of the SET voltage This higher variation in the RESET voltage is attributed to the stochastic behavior of the conductive filament rupture during the RESET process The small variation in VSET can be understood from Figure 4a, displaying that after the initial forming voltage of −1.6 V the VSET of the first cycle was (−0.26 V), which gradually reduced with the increasing cycles to a certain point The VSET observed for the 1st, 20th, 50th, and 100th cycle was −0.26, −0.23, −0.23, and −0.19 V, respectively, but a random trend was observed during the RESET process A similar trend is observed for cycles measured at a higher compliance current of 10−2 A (Figure S2, Supporting Information) 2100744 (5 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 4. Digital switching characteristics of the bio-memristor for nonvolatile memory storage applications a) Digital switching I–V characteristics of AgNPs-TCNC bio-memristor under current compliance of 10−3 A b) The endurance characteristics of the device presenting good repeatability in the ON and OFF states for 200 DC sweep cycles c) Pulse endurance characteristics of the device for 104 pulse cycles d) Data retention characteristics of the device maintaining a memory window of ≈104 for more than ≈104 s e) Statistical distribution data of operating voltages for SET and RESET processes and f) HRS and LRS resistance distributions for 200 continuous switching cycles The VSET showed a slightly decreasing trend as the number of cycles increases The reason for this behavior we believe is the formation of multiple filaments as a result of continuous reduction of Ag+ ions as Ag+ + e− → Ag (reduction) and therefore, the SET voltage for the later repeated cycles is slightly lower than that of the initial cycles While upon RESET the filaments rapture at bottom electrode side by the effect of redox reaction, thus Ag oxidizes again into Ag+ ions as Ag → Ag+ + e− (oxidation) The device was further evaluated to see if the device will turn on when there are enough switching cycles For this, we first tested the pulse endurance of the device by repeating the switching for 104 cycles The device showed a stable endurance without any larger degradation in the device switching After that, the DC I–V characteristics were measured immediately after 104 repeated cycles The I–V curve following the 104 repeated pulse switching cycles is added in Figure 4a This shows that the device can still turn on, although the SET voltage has reduced compared to the initial cycles A slight increase in the HRS current is also observed Hence, all the above-mentioned results satisfy the reliability of our device for nonvolatile memory application with good endurance and data retention characteristics, high ON/OFF ratio, and acceptable variation of operating voltages for digital SET and RESET Adv Mater Technol 2021, 2100744 2.2 Analog Switching for Biorealistic Synaptic Emulation The analog switching characteristics of the device were utilized to mimic the plasticity functions of the biological synapses, which is essential for the realization of neuromorphic computing systems The analog switching behaviors were tested under DC voltage sweeps and pulse measurements for the emulation of synaptic functions as shown in Figure The DC voltage was applied to the Ag top electrode and controlled carefully to prevent it from direct digital switching, and the sweeping voltage was kept below ±0.10 V As shown in Figure 5a the I–V curve response can be seen when the consecutive negative voltage sweeps and consecutive positive voltage sweeps of ±0.07 V were applied In the response of consecutive negative voltage sweeps, the absolute value of the current level after each sweep increases stepwise from curve to 6, in an analog fashion which is similar to synaptic potentiation of biological synapses Whereas, the current level similarly decreases upon the application of consecutive positive voltage sweeps, from curve to 12, in an analog stepwise fashion, which is considered as a counterpart of synaptic depression in biological synapses This gradual increase and decrease of conductance level at readout voltage of ±0.04 V during these 12 2100744 (6 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 5. Analog switching characteristics of bio-memristor a) I–V characteristics of the device during consecutive negative and positive sweeps b) Changes of conductance levels during consecutive sweeps c) Current-time responses with applied bias pulses of opposite polarity (±0.10 V, 30 ms) d) Potentiation and depression of conductance levels after 30 consecutive negative and 30 positive pulses of (−0.10 V, ms) and (+0.10 V, ms), respectively consecutive voltage sweeps are shown in Figure 5b This shows the potentiation and depression behavior of the device due to the consecutive voltage sweeps acting as the action potential The retention characteristics of the four highest conductance states were evaluated for 10 min, as shown in Figure S4, Supporting Information For each conductance state, the device current was read at a reading voltage of 0.04 V for 600 s with an interval of 50 s between each reading measurement event The higher states could maintain the conductance state however, the lowest state could not maintain for a longer time This is attributed to the formation of very small conductive filaments which cannot sustain for a longer time Moreover, the analog switching characteristics were investigated in different devices to evaluate the device-to-device variability which is critical for practical applications of the devices Figure S5, Supporting Information, shows the incremental current modulation in five different devices depicting the device-to-device variations during the analog switching It can be seen that the CNF-based devices exhibit good device-to-device repeatability for analog switching Realizing the continuous and gradual change in the current level upon the applied DC sweeps, we tried to understand more clearly by further exploring the transient electrical characteristics upon applying input pulses to the device The 10 consecutive pulses (±0.10 V, 30 ms) with opposite polarities are applied to measure the current response with time as shown in Figure 5c The increase of current values upon successive negative bias pulses as well as decrease of current values upon successive positive bias pulses with time demonstrate the resultant potentiation and depression of conductance of the Adv Mater Technol 2021, 2100744 device This potentiation/depression behavior is the imitation of successive variable synaptic weight and connection strength in biological synapses Usually, the human brain experiences an enormous number of synapses (≈1015) between presynaptic neurons and postsynaptic neurons of connected neural networks, which serve all the computations, and facilitates our entire memory blocks This fundamental phenomenon of our brain is known as synaptic plasticity Synaptic plasticity is an activity-dependent process where synaptic weight is modulated by the input stimuli within the synaptic cleft between synaptic connections of the neural network.[57–59] When the presynaptic neurons receive an action potential (electrical stimuli) Ca2+ ions influx are transported to presynaptic vesicles through voltagegated Ca2+ ion channels, and neurotransmitters are released by the presynaptic-neurons Upon reaching the postsynaptic neurons, the receptors receive these neuro-transmitters, and the electrical signal is transferred forward The weak stimulus lasts only hundreds of milliseconds, and this state is termed as short term plasticity (STP), but by the repetition of receiving action potentials (electrical stimulus), the Ca2+ ion influx is prolonged and the synaptic conduction through neurotransmitters is enhanced, which causes structural changes in the synaptic connection known as long term plasticity (LTP).[60] Our biomemristor as an artificial synaptic device mimics the above mechanism utilizing attached AgNPs AgNPs oxidize into Ag+ ions as a counterpart of Ca2+ ions influx, activated by voltage pulses, which is equivalent to action potential (presynaptic spiking) of biological synapses To check the long-term potentiation and depression, two pulse trains with successive negative 2100744 (7 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 6. The synaptic function characteristics of Ag/AgNPs-TCNC/FTO bio-memristor device a) Pulse train scheme of 10 pulses with different intervals b) Measured current levels for 10 consecutive pulses with different pulse intervals c) The difference in current levels (∆I) after each consecutive pulse for each mentioned pulse train d) The demonstration of the PPF behavior of the device showing the dependence of the PPF index on the interspike interval e) The demonstration of the PPD behavior of the device f) EPSC characteristics with a single voltage pulse stimulation (−0.1 V, 10 ms) and positive pulses (-0.10 V, ms) and (0.10 V, ms) were applied and as a result of which the potentiation and depression in the current levels can be observed in Figure 5d By the response of each negative voltage pulse, the silver ions attached to nanocrystals are oxidized and accumulate to grow the conductive filaments incrementally, reducing the disconnection gap between the filaments and the bottom electrode due to which the conductance level increases with each passing pulse The opposite phenomenon of filament dissolution occurs with each pulse of positive polarity In the biological system, synaptic plasticity is considered as the basis for learning and memory functions where synaptic weight is adjusted according to the presynaptic and postsynaptic stimulations The emulation of such synaptic plasticity characteristics is desirable in artificial electronic synapses to build neuromorphic systems Our bio-memristor synaptic device, as shown in Figure 6, successfully emulated some of the important synaptic functions One of the important synaptic plasticity functions is the SRDP For the emulation of SRDP functions with our electronic synaptic device, sets of 10 pulse trains with different intervals but the same pulse height (−0.10 V) and width (30 ms) were applied to check the corresponding responses The pulse scheme diagram and the device corresponding response in terms of conductance with each pulse number are shown Adv Mater Technol 2021, 2100744 in Figures 6a,b, respectively The pulse stimulations with pulse intervals of and s showed no increment in the current level, while the pulse stimulation train with intervals of 500 ms showed the least increment in the current level The stimulation with pulse intervals of 100 and 50 ms showed the highest increment in current levels In biological synapses, the presynaptic stimulation causes the influx of Ca+ ions, resulting in the release of neurotransmitters temporarily, after which it is recovered But if the second or third identical stimulation is received before the Ca+ ions recovery, the response of the post-synapse will be larger than the response it showed to the first one In our case, by the reduction of pulse interval during measurements, we can see a similar effect in terms of increased current conduction, and this effect is known as PPF By continuation of these identical stimulations (pulses) in the form of a pulse train with suitable intervals, it will cause a gradual increase in conduction (synaptic transmission), and this effect is called PTP To make this behavior of PPF and PTP prominently visible, we plotted the increased current in the form of change in current (∆I) in Figure 6c, which is calculated by subtracting the current (IN, N = 1, 2, 3, 4…10) from I1 Both PPF and PTP behaviors for each pulse train with different intervals are highlighted Moreover, the characteristics of the PPF index and PPD index were further studied by applying a pair of pulses with a varying interval 2100744 (8 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 7. The schematic diagram of the switching mechanism to explain the proposed mechanisms of filament formation and rupture during the process of a) digital switching and b) analog switching between both pulse spikes The PPF index and PPD index were calculated as a ratio of the current response of the device due to the second pulse to that of the first pulse (I2/I1) The PPF index characteristics of the device are presented in Figure 6d The paired-pulse stimulations with smaller pulse intervals showed the largest PPF index whereas the dual pulse stimuli with significantly larger intervals depicted no or little current facilitation showing a smaller PPF index The device also showed similar behavior for the PPD The PPD index showed a clear dependence on the inter-spiking interval, as shown in Figure 6e This confirms that our device can faithfully mimic the short-term plasticity behaviors of the biological synapses The change in the conductance of the device as a result of successive pulses is because of the temporal interaction between applied stimulations and its ionic EPSC, which also gives us information about the decay function of the conducting filament For measuring an EPSC, a single electrical pulse of (−0.1 V, 10 ms) was applied as a stimulus source and a readout pulse of 0.04 V was continuously applied after a single stimulation to observe the resultant behavior as a postsynaptic current The postsynaptic current decayed gradually over time after an abrupt increase with input spike as shown in Figure 6f Moreover, the EPSC characteristics of the device were further evaluated by varying the amplitudes of the applied stimuli The EPSC characteristics for the pulses with different pulse amplitudes are presented in Figure S6, Supporting Information With the interpretation of the above results and discussion, our bio-memristor can successfully work as an artificial synaptic device Adv Mater Technol 2021, 2100744 Since the device is prepared with the silver top electrode, it is expected that the electroforming and the SET phenomenon could occur by applying positive voltage bias on the silver top electrode because of the ionization of silver near the positive bias electrode and the subsequent Ag+ ions migration under electric field but the opposite case was observed The device showed the electroforming and SET phenomenon with the application of negative voltage bias on the top electrode We propose that this phenomenon is due to the high Ag+ ions concentration precipitated on nanocrystals The schematic presentation of the proposed digital and analog switching mechanisms is presented in Figure The switching mechanism is realized by the effect of redox reactions at the electrode interfaces causing oxidation of Ag atoms and reduction of Ag+ ions in the switching process The attached silver of AgNPs-TCNC dielectric layer near the FTO bottom electrode is oxidized into Ag+ ions as the FTO acts as an opposite positive electrode in this case The ionized silver ions near the positive FTO bottom electrode start migrating under the effect of the electric field, and by reaching the negative top electrode the Ag+ ions reduce to Ag by receiving the electrons from the top electrode illustrated as Ag+ + e− → Ag (reduction) With the successive metallization of silver ions and the accumulation process of metallic silver, stable conductive filaments are formed connecting top and bottom electrodes The thickness of these formed conducting multi-filaments grows with increasing voltage during voltage sweep With the reversal of the applied voltage polarity, the silver filament metal starts oxidizing into Ag+ ions dissolving in the dielectric layer near the negative bottom electrode (FTO) 2100744 (9 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Figure 8. Study of the current conduction mechanisms for a) digital switching and b) analog switching as Ag → Ag+ + e− (oxidation) thus disconnecting the top and bottom electrodes This disconnected gap can be bridged again by reversing polarity and is SET again because the disconnected filament can now donate electrons for Ag+ ion reduction and metallization To confirm our proposed mechanism of silver ions migration from ionization of AgNPs-TCNC (nanocrystals) rather than the silver top electrode, devices with gold top electrodes were fabricated The device with a 3.63 µm thickness of the insulating layer showed similar behavior to the one with the silver top electrode device The bipolar switching cycles of the device with the gold top electrode are shown in Figure S7a, Supporting Information Similar polarity dependent SET (negative sweep) and RESET (positive sweep) results from the device with gold top electrode confirm our proposed mechanism that the silver attached to the nanocrystals (AgNPs-TCNC) are responsible for the filament formation which is ionized near the positive bottom electrode when negative voltage bias is applied on the top electrode of both devices fabricated with silver and gold top electrodes Figures S7b,c, Supporting Information, show the endurance and data retention characteristics of the Au/AgNPs-TCNC/FTO device, respectively Figures S7d,e, Supporting Information, represent the corresponding cumulative distribution of the switching voltages and distribution of HRS and LRS currents, respectively For the measurement of synaptic properties; however, the applied bias was controlled below (−0.1 V) to avoid binary resistive switching behavior and to avoid abrupt resistance change Figure 7b represents the stepwise decrease of disconnection gap in case of potentiation and stepwise increase of disconnection gap in case of depression by adjusting the electrical bias This progressive development of conductive filaments and adjustment of disconnection gap as a result of redox reactions alter the HRS current level in memristor as shown in Figures 5 and 6 The current level within HRS increases with a decrease of the disconnection gap and it decreases with an increase of the disconnection gap However, the sweeping voltage below (−0.10 V) is not enough to form a conductive filament fully connecting the top electrode with the bottom electrode Similarly, when we applied a single pulse or pulses with long interval gaps an EPSC behavior occurs because of the successive metallization and ionization processes as a result of redox reactions However, by the repetition of voltage pulses the Ag+ ion Adv Mater Technol 2021, 2100744 ionization and precipitation is facilitated to grow filaments by which the disconnection gap continuously reduces and hence the conductance increases (potentiation) At the same time, the device is prevented from abrupt binary switching by the use of controlled voltage pulses When the device polarity is reversed or when positive pulses are applied, the disconnection gap starts increasing again in a stepwise fashion with each sweep or pulse Rather than direct RESET, this stepwise depression is attained by the virtue of the controlled lower value of applied voltage Similarly, the disconnection gap is again reduced in a stepwise fashion with each sweep or pulse when polarity is reversed thus the device shows the potentiation behavior To further confirm our proposed mechanism of formation and rupture of conductive filaments during the digital and analog switching, the current conduction mechanisms of the device in different resistance states were investigated, as shown in Figure The typical I–V curves of the digital and analog switching characteristics were replotted as logI–logV plots The study of the current conduction mechanism reveals that the Ohmic conduction is dominant in LRS during digital switching, confirming the formation of conductive filaments as shown in Figure 8a In HRS, Ohmic conduction is dominant at lower voltages, followed by space charge limited conduction (SCLC) at higher voltages For analog switching, the slope values of the 1st, 2nd, and 6th sweeps of the gradual SET process were analyzed in Figure 8b It can be seen that at lower voltages, the slopes are equal to for all sweeps, whereas for higher voltages the slopes are 5.8, 1.3, and for 1st, 2nd, and 6th sweeps, respectively For the 1st negative sweep, the highest slope value indicates that the conductive filament is not fully formed and confirms a trap-filled SCLC With the successive voltage sweeping, the slope value decreases and finally becomes for the sweep confirming the formation of the conductive filaments incrementally For the 6th sweep, the slope at all voltage range is equal to indicating Ohmic conduction A comparison of our cellulose-based memristor device with other bio-memristors is carried out with respect to the essential resistive switching properties and emulation of synaptic functions Table shows the resistive switching characteristics of the memristive devices based on various biomaterials The memristive devices based on various bio-composite materials exhibited resistive switching characteristics with 2100744 (10 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de Table 1. Memristor devices with the main switching layers based on various biomaterials Biomaterial Anthocyanin (C15H11O6) DNA Device structure Mo/C15H11O6-graphene/Mo Battery-like switching Pectin Lignin Cellulose nanocrystal (CNC) SET/ RESET voltages [V] Endurance Retention ON/ OFF [Cycles] time [s] ratio Synaptic emulation Ref – 100 – 28 – [61] Au/CuO-DNA-Al/Au/Si Bipolar switching 2.25/−2.25 100 103 50 – [62] Ag/Lotus/ITO Bipolar switching 5/−3 100 103 40 – [63] Ag/Ag-doped chitosan/Pt Digital switching ≈0.5/−0.3 100 104 105 – [64] 500 >10 ≈10 – [65] LTP/LTD, STP/LTP, EPSC, SRDP [18] Lotus leaves Chitosan Switching type Ag/pectin/ITO Multilevel digital switching 1.1/−0.5 Au/lignin/ITO/PET Analog switching −0.7/0.7 – – – Ag/AgNPs-TCNC/FTO Digital and analog switching Digital switching: ≈−0.2/0.2 Analog switching: −0.07/0.07 104 >104 104 different types of switching in each device including batterylike switching, multilevel switching, digital switching, and analog switching The digital switching is useful for nonvolatile memory applications whereas analog switching is more favorable for the emulation of biological synaptic functions for the realization of neuromorphic computing systems Our cellulose-based bio-memristor exhibited repeatable digital switching, with a high ON/OFF ratio and better endurance and memory retention properties, as well as reliable analog switching which was utilized for synaptic emulation It can be seen that our CNF-based device is comparable and suitable for nonvolatile memory and biorealistic synaptic emulation for neuromorphic computing applications Conclusions A bio-memristor of cellulose-based renewable material is developed with a simple room-temperature fabrication technique that showed both digital and analog bipolar switching characteristics by the formation of a redox-controlled Ag-filament and fracture process Its digital switching behavior was utilized for nonvolatile data storage and memory application, while its stepwise analog switching behavior is exploited to mimic important neuromorphic features such as LTP, LTD, EPSC, SRDP, PPF, PPD, and PTP Our results suggest that cellulosebio-memristor can effectively be implemented as an artificial synaptic device in neuromorphic computing systems and for data storage applications in the future Experimental section Tempo-Oxidization of CNFs: The CNFs hydrogel (10 g) was first dispersed in DI water (300 mL) by magnetic stirring at 500 rpm and room temperature TEMPO (0.06 g) and NaBr (0.6 g) are added to the CNF suspension each after 30 respectively until it gets dissolved completely and gives an ivory color NaClO solution (35 wt%, 15 mL) is then slowly added mL by mL, and after 24 h of stirring, the color of suspension changes to yellow color After this 0.5 M NaOH is added drop by drop to maintain the pH at 10.5 and by which the suspension becomes transparent and is allowed for stirring for up to 30 The high pH of the suspension is then neutralized up to a pH level of 7.0 by adding Adv Mater Technol 2021, 2100744 LTP/LTD,EPSC, SRDP, PPF, PPD This work 0.1 M HCL drop by drop The last step of obtaining the TEMPO-oxidized CNCs (CNC) from the CNF suspension is by adding a 70/30 ratio of ethanol/water solution to the reacted suspension CNC as a final product in the form of hydrogel is obtained finally using centrifugation at 12000 rpm for Synthesis and Characterization of AgNPs-Decorated CNFs: CNF hydrogel supplied from Maine University was used as a precursor material for further processing steps In the first step, 3.2 wt.% of CNF hydrogel was subjected to TEMPO-mediated oxidation using 2,2,6,6-tetramethylpiperidine-1-oxyl catalyst from Sigma-Aldrich 0.06 g of TEMPO catalyst is used per 10 g of CNF hydrogel to obtain TEMPOoxidized-cellulose-nanocrystals (TCNC) with a reaction time of 40 h In the second step, the aldehyde groups were introduced on the surfaces of CNCs using sodium-periodate (NaIO4) 1.5 g of NaIO4 dissolved in 50 mL of D.I water was mixed with the 50 mL aqueous dispersion of g of 7.44 wt.% TCNC hydrogel and the mixture were left on stirring at 300 rpm at room temperature for 30 h The reaction was quenched with ethanol the first time to obtain TCNC with dialdehyde functional groups from the mixture and later washed four times with a 100 mL aqueous mixture of ethanol/water with 70/30 (v/v) ratios using a centrifuge The ethanol was removed after washing by solvent exchange step with DI water and by stirring the obtained solution at 80 °C for a few minutes In the third step, the silver NPs were in situ grown on the CNCs by tollen’s reaction Tollen’s reagent was prepared by adding mL of (35%) ammonia aqueous solution in (0.47 M, 10 mL) of the AgNO3 solution In the final step, 10 mL of tollen’s reagent [Ag(NH3)2]+OH− was mixed with 30 mL of prepared CNC and the mixture was stirred at room temperature for 1.5 h to in situ grow silver NPs (AgNPs) on CNCs To prevent interference of remaining byproduct chemicals, the mixture was recovered by centrifugation at 8000 rpm, redispersed in DI water, and centrifuged three times to remove any residual [Ag(NH3)2]+ and unbound Ag+ Note that the AgNPs-CNCs suspension exhibited no aggregation and remained stable after month Fabrication and Characterization of Ag-Decorated CNF Devices: The device was fabricated by dropping a few mL of solution mixture on the cleaned fluorine-doped tin oxide (FTO) coated glass substrate and was left for drying for 24 h at room temperature FTO glass was cleaned by sonication process for in acetone, ethanol, and isopropanol each and after which it was dried with nitrogen gas purge The thickness and area of the substrate to be coated were controlled by considering the amount of used solution during device fabrication The silver and gold top electrodes of 100 µm2 size with 150 nm thickness were deposited on our insulative nano-paper coated FTO glass with the help of a metal mask The electrical characterization of the device was performed using semiconductor parameter analyzers Keithley 4200 SCS and KeySight B1500-A, equipped with tungsten probe tips All measurements described in this paper were performed at room temperature and atmospheric conditions Infrared spectra of pristine CNF, TCNC, and 2100744 (11 of 13) © 2021 Wiley-VCH GmbH www.advancedsciencenews.com www.advmattechnol.de DAC were recorded with FTIR-ATR spectroscopy (PerkinElmer Spectrum 100) from a wave-number range of 500–4000 cm−1 for surface analysis to examine the success of the reaction and the introduction of functional groups X-ray diffraction of the coated film was performed by (XRD; RIGAKU, D-MAX 2500) Zeta-potentials (ζ) were measured with a Zetasizer nano ZS instrument (Malvern Instruments) TEM (JEM3010, JEOL instrument) was used for the structural analysis of TCNC synthesized from CNF suspension in water Supporting Information Supporting Information is available from the Wiley Online Library or from the author Acknowledgements H.A., T.H and C.Y contributed equally to this work This research was supported by the MOTIE (Ministry of Trade, Industry & Energy (#10080643) and KSRC (Korea Semiconductor Research Consortium) support program for the development of future semiconductor devices and partially supported by the Next Generation Engineering Researcher Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (NRF-2019H1D8A2106002, NRF-2021R1A2C2010781) This research was also supported by the Nano Material Technology Development Programs and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of science, ICT & Future Planning (NRF2019R1F1A1057243, NRF-2020M3F3A2A02082449) Conflict of Interest The authors declare no conflict of interest Data Availability Statement Research data are not shared Keywords cellulose nanocrystals, nanocomposites, bio-memristor, synaptic devices, green-electronics, neuromorphic computing artificial Received: June 18, 2021 Revised: September 7, 2021 Published online: [1] K. 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(FTO) coated glass substrate and was left for drying for 24 h at room temperature FTO glass was cleaned by sonication process for in acetone, ethanol, and isopropanol each and after which it was dried... biodegradable, eco-friendly, and green dielectric materials as a primary element A number of artificial synaptic devices have been proposed, where the main switching layer is based on inorganic materials.[13,22–25]