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The memristors offer significant advantages as a key element in non-volatile and brain-inspired neuromorphic systems because of their salient features such as remarkable endurance, ability to store multiple bits, fast operation speed, and extremely low energy usage. This work reports the resistive switching (RS) characteristics of the hydrothermally synthesized iron tungstate (FeWO 4 ) based thin film memristive device. The detailed physicochemical analysis was investigated using Rietveld's refinement, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM) techniques. The fabricated Ag/FWO/FTO memristive device exhibits bipolar resistive switching (BRS) behavior. In addition, the devices exhibit negative differential resistance (NDR) at both positive and negative bias. The charge-flux relation portrayed the non-ideal or memristive nature of the devices. The reliability in the RS process was analyzed in detail using Weibull distribution and time series analysis techniques. The device exhibits stable and multilevel endurance and retention characteristics which demonstrates the suitability of the device for the high-density non-volatile memory application. The current conduction of the device was dominated by Ohmic and trap controlled-space charge limited current (TC-SCLC) mechanisms and filamentary RS process responsible for the BRS in the device. In a nutshell, the present investigations reveal the potential use of the iron tungstate for the fabrication of memristive devices for the non-volatile memory application., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Here, resistive switching (RS) devices are fabricated using naturally abundant, nontoxic, biocompatible, and biodegradable biomaterials. For this purpose, 1D chitosan nanofibers (NFs), collagen NFs, and chitosan-collagen NFs are synthesized by using an electrospinning technique. Among different NFs, the collagen-NFs-based device shows promising RS characteristics. In particular, the optimized Ag/collagen NFs/fluorine-doped tin oxide RS device shows a voltage-tunable analog memory behavior and good nonvolatile memory properties. Moreover, it can also mimic various biological synaptic learning properties and can be used for pattern classification applications with the help of the spiking neural network. The time series analysis technique is employed to model and predict the switching variations of the RS device. Moreover, the collagen NFs have shown good cytotoxicity and anticancer properties, suggesting excellent biocompatibility as a switching layer. The biocompatibility of collagen NFs is explored with the help of NRK-52E (Normal Rat Kidney cell line) and MCF-7 (Michigan Cancer Foundation-7 cancer cell line). Additionally, the biodegradability of the device is evaluated through a physical transient test. This work provides a vital step toward developing a biocompatible and biodegradable switching material for sustainable nonvolatile memory and neuromorphic computing applications., (© 2024 Wiley‐VCH GmbH.)

In recent years, many metal oxides have been rigorously studied to be employed as solid electrolytes for resistive switching (RS) devices. Among these solid electrolytes, lanthanum oxide (La 2 O 3 ) is comparatively less explored for RS applications. Given this, the present work focuses on the electrodeposition of La 2 O 3 switching layers and the investigation of their RS properties for memory and neuromorphic computing applications. Initially, the electrodeposited La 2 O 3 switching layers are thoroughly characterized by various analytical techniques. The electrochemical impedance spectroscopy (EIS) and Mott-Schottky techniques are probed to understand the in situ electrodeposition, RS mechanism, and n-type semiconducting nature of the fabricated La 2 O 3 switching layers. All the fabricated devices exhibit bipolar RS characteristics with excellent endurance and stable retention. Moreover, the device mimics the various bio-synaptic properties such as potentiation-depression, excitatory post-synaptic currents, and paired-pulse facilitation. It is demonstrated that the fabricated devices are non-ideal memristors based on double-valued charge-flux characteristics. The switching variation of the device is studied using the Weibull distribution technique and modeled and predicted by the time series analysis technique. Based on electrical and EIS results, a possible filamentary-based RS mechanism is suggested. The present results assert that La 2 O 3 is a promising solid electrolyte for memory and brain-inspired applications., (© 2023 Wiley-VCH GmbH.)

In this study, we used the one-pot solvothermal method to synthesize the TiO 2 nanospheres (NSs) and used them for non-volatile memory and neuromorphic computing applications. Several analytical tools were used to understand the structural, optical, morphological, and compositional characteristics of synthesized TiO 2 NSs. The tetragonal crystal structure of anatase TiO 2 was formed, according to the Rietveld refined x-ray diffraction results. The NS morphology was confirmed by field emission scanning electron microscopy and transmission electron microscopy images. X-ray photoelectron spectroscopy was probed to understand the elemental composition and electronic states of the TiO 2 NSs. We specifically looked at the impact of reaction time on the structural, optical, morphological, compositional, and resistive switching (RS) properties of TiO 2 NSs. The fabricated devices (Ag/TiO 2 NSs/FTO) exhibit bipolar RS behavior. The optimized RS device shows good endurance (5000 cycles) and memory retention (5000 s) properties. Moreover, fabricated devices showed double-valued charge-flux characteristics, whereas charge transport was caused by the Ohmic and space charge-limited current mechanisms. Additionally, the optimized device can mimic various synaptic characteristics including potentiation-depression, excitatory post-synaptic current, and paired-pulse facilitation., (© 2023 IOP Publishing Ltd.)

Resistive switching (RS) memories have attracted great attention as promising solutions to next-generation non-volatile memories and computing technologies because of their simple device configuration, high on/off ratio, low power consumption, fast switching, long retention, and significant cyclic stability. In this work, uniform and adherent iron tungstate (FeWO 4 ) thin films were synthesized by the spray pyrolysis method with various precursor solution volumes, and these were tested as a switching layer for the fabrication of Ag/FWO/FTO memristive devices. The detailed structural investigation was done through various analytical and physio-chemical characterizations viz. X-ray diffraction (XRD) and its Rietveld refinement, Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) techniques. The results reveal the pure and single-phase FeWO 4 compound thin film formation. Surface morphological study shows the spherical particle formation having a diameter in the range of 20 to 40 nm. The RS characteristics of the Ag/FWO/FTO memristive device demonstrate non-volatile memory characteristics with significant endurance and retention properties. Interestingly, the memory devices show stable and reproducible negative differential resistance (NDR) effects. The in-depth statistical analysis suggests the good operational uniformity of the device. Moreover, the switching voltages of the Ag/FWO/FTO memristive device were modeled using the time series analysis technique by utilizing Holt's Winter Exponential Smoothing (HWES) approach. Additionally, the device mimics bio-synaptic properties such as potentiation/depression, excitatory post-synaptic current (EPSC), and spike-timing-dependent plasticity (STDP) learning rules. For the present device, the space-charge-limited current (SCLC) and trap-controlled-SCLC effects dominated during positive and negative bias I-V characteristics, respectively. The RS mechanism dominated in the low resistance state (LRS), and the high resistance state (HRS) was explained based on the formation and rupture of conductive filament composed of Ag ions and oxygen vacancies. This work demonstrates the RS in the metal tungstate-based memristive devices and demonstrates a low-cost approach for fabricating memristive devices., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Resistive-switching-based memory devices meet most of the requirements for use in next-generation information and communication technology applications, including standalone memory devices, neuromorphic hardware, and embedded sensing devices with on-chip storage, due to their low cost, excellent memory retention, compatibility with 3D integration, in-memory computing capabilities, and ease of fabrication. Electrochemical synthesis is the most widespread technique for the fabrication of state-of-the-art memory devices. The present review article summarizes the electrochemical approaches that have been proposed for the fabrication of switching, memristor, and memristive devices for memory storage, neuromorphic computing, and sensing applications, highlighting their various advantages and performance metrics. We also present the challenges and future research directions for this field in the concluding section.

Since the discovery of graphene, two-dimensional (2D) materials have gained widespread attention, owing to their appealing properties for various technological applications. Etched from their parent MAX phases, MXene is a newly emerged 2D material that was first reported in 2011. Since then, a lot of theoretical and experimental work has been done on more than 30 MXene structures for various applications. Given this, in the present review, we have tried to cover the multidisciplinary aspects of MXene including its structures, synthesis methods, and electronic, mechanical, optoelectronic, and magnetic properties. From an application point of view, we explore MXene-based supercapacitors, gas sensors, strain sensors, biosensors, electromagnetic interference shielding, microwave absorption, memristors, and artificial synaptic devices. Also, the impact of MXene-based materials on the characteristics of respective applications is systematically explored. This review provides the current status of MXene nanomaterials for various applications and possible future developments in this field.

In the present study, various statistical and machine learning (ML) techniques were used to understand how device fabrication parameters affect the performance of copper oxide-based resistive switching (RS) devices. In the present case, the data was collected from copper oxide RS devices-based research articles, published between 2008 to 2022. Initially, different patterns present in the data were analyzed by statistical techniques. Then, the classification and regression tree algorithm (CART) and decision tree (DT) ML algorithms were implemented to get the device fabrication guidelines for the continuous and categorical features of copper oxide-based RS devices, respectively. In the next step, the random forest algorithm was found to be suitable for the prediction of continuous-type features as compared to a linear model and artificial neural network (ANN). Moreover, the DT algorithm predicts the performance of categorical-type features very well. The feature importance score was calculated for each continuous and categorical feature by the gradient boosting (GB) algorithm. Finally, the suggested ML guidelines were employed to fabricate the copper oxide-based RS device and demonstrated its non-volatile memory properties. The results of ML algorithms and experimental devices are in good agreement with each other, suggesting the importance of ML techniques for understanding and optimizing memory devices., (© 2023. The Author(s).)

Corona Virus is spreading at an alarming rate in community causing respiratory diseases like SARS and MERS, which has laid down Government agencies and healthcare organizations to adopt and recommend various strategies in order to cease the spread of corona virus. Till the dawn of Vaccine, only available cost-effective preventive aid is the use of face mask. Since the outbreak of covid-19, demand for the face mask has been increased tremendously which has led to the shortage of face mask. Various masks are available in the market, but reuse and decontamination of reusable face mask has become the topic of concern. Commonly available masks in market are N-95, Medical/Surgical Mask and cloth masks. N-95 and Respirators should be reserved for frontline primary Healthcare professionals which are involved in High-risk aerosol generating procedures, while Surgical and medical mask should be used by secondary healthcare professionals and cloth masks by General public., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Advances in Materials Science.)

Dye-sensitized solar cells (DSSCs) are one of the most versatile and low-cost solar cells. However, DSSCs are prone to low power conversion efficiency (PCE) compared to their counterparts, owing to their different synthesis parameters and process conditions. Therefore, designing efficient DSSCs and identifying the parameters that control the PCE of DSSCs are a critical tasks. We have collected data from hydrothermally synthesized DSSCs in the present work, published from 2005 to 2020. In line with publishing trends in the said period, we evaluate ZnO as a popular photoactive material for DSSC applications. We further analyzed the performance of hydrothermally synthesized ZnO DSSCs using different statistical techniques and provided some significant insights. We further applied the machine-learning technique with a decision tree algorithm to understand and discover the possible set of rules and heuristics that govern the morphology of the hydrothermally grown ZnO. In addition, we also employed supervised and unsupervised machine-learning models using conventional decision trees and classification and regression trees, respectively, to identify the dependence of the PCE of ZnO DSSCs on the different synthesis parameters. The reported work also evidences the PCE predictions of the ZnO DSSCs by using random forest and artificial neural network algorithms. The results substantiate that the random forest and artificial neural network algorithms successfully predict the PCE of the ZnO DSSCs with reasonable accuracy. Thus, we present a novel approach of applying statistical analysis and machine-learning algorithms to understand, discover, and predict the performance of DSSCs. We recommend extending the said know-how to other solar cells to identify rules and heuristics and experimentally realize highly efficient solar cells in shrinking manufacturing windows with a cost-effective approach., Competing Interests: The authors declare no competing financial interest., (© 2021 The Authors. Published by American Chemical Society.)

In this study, the in situ sol-gel method has been deployed to prepare the titanium dioxide/multiwalled carbon nanotubes (TiO 2 /MWCNTs) nanocomposite (NCs) powders with varying content of MWCNTs (0.01-1.0 wt %), to construct the dye-sensitized solar cells (DSSCs). First, binder-free NCs were deposited on a transparent-conducting F:SnO 2 (FTO) glass substrate by a doctor-blade technique and then anchored with Ru(II)-based dyes to either N719 or ruthenium phthalocyanine (RuPc). The structural and optical properties and interconnectivity of the materials within the composite are investigated thoroughly by various spectral techniques (XRD, XPS, Raman, FT-IR, and UV-vis), electron microscopy (HRTEM), and BET analysis. The experimental results suggest that the ratio of MWCNTs and TiO 2 in NCs, morphology, and their interconnectivity influenced their structural, optical, and photovoltaic properties significantly. Finally, the photovoltaic performances of the assembled DSSCs with different content of MWCNTs to TiO 2 films anchored with two different dyes were tested under one sun irradiation (100 mW/cm 2 ). The measured current-voltage ( IV ) curve and incident photon-to-current conversion efficiency (IPCE) spectra of TiO 2 /0.1 wt % MWCNTs (T@0.1 C) for N719 dye show three times more power conversion efficiency (η = 6.21%) which is opposed to an efficiency (η = 2.07%) of T@0.1 C for RuPc dye under the same operating conditions., Competing Interests: The authors declare no competing financial interest.

In the present investigation, we have fabricated copper oxide (CuO) thin film memristor by employing a hydrothermal method for neuromorphic application. The X-ray diffraction pattern confirms the films are polycrystalline in nature with the monoclinic crystal structure. The developed devices show analog memory and synaptic property similar to biological neuron. The size dependent synaptic behavior is investigated for as-prepared and annealed CuO memristor. The results suggested that the magnitude of synaptic weights and resistive switching voltages are dependent on the thickness of the active layer. Synaptic weights are improved in the case of the as-prepared device whereas they are inferior for annealed CuO memristor. The rectifying property similar to a biological neuron is observed only for the as-prepared device, which suggested that as-prepared devices have better computational and learning capabilities than annealed CuO memristor. Moreover, the retention loss of the CuO memristor is in good agreement with the forgetting curve of human memory. The results suggested that hydrothermally grown CuO thin film memristor is a potential candidate for the neuromorphic device development.

Polycatalytic enzyme complexes made by immobilization of industrial enzymes on polymer- or nanoparticle-based scaffolds are technologically attractive due to their recyclability and their improved substrate binding and catalytic activities. Herein, we report the synthesis of polycatalytic complexes by the immobilization of nonprocessive cellulases on the surface of colloidal polymers with a magnetic nanoparticle core and the study of their binding and catalytic activities. These polycatalytic cellulase complexes have increased binding affinity for the substrate. But due to their larger size, these complexes were unable to access to the internal surfaces of cellulose and have significantly lower binding capacity when compared to those of the corresponding free enzymes. Analysis of released soluble sugars indicated that the formation of complexes may promote the prospect of having consistent, multiple attacks on cellulose substrate. Once bound to the substrate, polycatalytic complexes tend to remain on the surface with very limited mobility due to their strong, multivalent binding to cellulose. Hence, the overall performance of polycatalytic complexes is limited by its substrate accessibility as well as mobility on the substrate surface.

We report simulation of nanostructured memristor device using piecewise linear and nonlinear window functions for RRAM and neuromorphic applications. The linear drift model of memristor has been exploited for the simulation purpose with the linear and non-linear window function as the mathematical and scripting basis. The results evidences that the piecewise linear window function can aptly simulate the memristor characteristics pertaining to RRAM application. However, the nonlinear window function could exhibit the nonlinear phenomenon in simulation only at the lower magnitude of control parameter. This has motivated us to propose a new nonlinear window function for emulating the simulation model of the memristor. Interestingly, the proposed window function is scalable up to f ( x ) = 1 and exhibits the nonlinear behavior at higher magnitude of control parameter. Moreover, the simulation results of proposed nonlinear window function are encouraging and reveals the smooth nonlinear change from LRS to HRS and vice versa and therefore useful for the neuromorphic applications.

The acidic ionic liquid (IL) functionalized polymer (PDVB-SO3H-[C3vim][SO3CF3]) possesses abundant nanoporous structures, strong acid strength and unique capability for deconstruction of crystalline cellulose into sugars in ILs. The polymer shows much improved catalytic activities in comparison with mineral acids, homogeneous acidic ionic liquids and the acidic resins such as Amberlyst 15. The enhanced catalytic activity found in the polymer is attributed to synergistic effects between the strongly acidic group and the ILs grafted onto the polymer, which by itself is capable of breaking down the crystalline structures of cellulose. This study may help develop cost-effective and green routes for conversion of biomass to fuels.

The formation of polycatalytic enzyme complexes may enhance the effectiveness of enzymes due to improved substrate interaction and synergistic actions of multiple enzymes in proximity. Much effort has been made to develop highly efficient polycatalytic cellulase complexes by immobilizing cellulases on low-cost polymer or nanoparticle scaffolds, aiming at their potential applications in biomass conversion to fuels. However, some key cellulases carry out the hydrolytic reaction on crystalline cellulose in a directional, processive manner. A large, artificial polycatalytic complex is unlikely to undergo a highly coordinated motion to slide on the cellulose surface as a whole unit. The mechanism underlying the activity enhancements observed in some artificial cellulase complexes and the limit of this approach remain elusive. Herein, we report the synthesis of polycatalytic cellulase complexes bound to colloidal polymer nanoparticles with a magnetic core and describe their unique adsorption, hydrolytic activities, and motions on cellulose. The polycatalytic clusters of cellulases on colloidal polymers show an increased rate of hydrolytic reactions on cellulose, but this was observed mainly at relatively low cellulase-to-cellulose ratios. Enhanced efficiency is mainly attributed to increased local concentrations of cellulases on the scaffolds and their polyvalent interactions with cellulose. However, once bound, the polycatalytic complexes can only carry out reactions locally and are not capable of relocating to new sites rapidly due to their lack of long-range surface mobility and their extremely tight binding. The development of highly optimized polycatalytic complexes may arise by developing novel nanoscaffolds that induce concerted motion of the complex as a whole.