Toward Neuromorphic Diagnostics: Memristors in Noncommunicable Disease Detection and Sensory Emulation Debashis Panda, Arpan Acharya, Subhrakali Swain, Cheng‐Yao Lo Chemnanomat, 2026 Emerging materials‐based devices are revolutionizing healthcare by advancing diagnostics, monitoring, and therapeutic strategies. Among them, memristor devices capable of storing and processing information are attracting and receiving significant attention for their biomedical potential. Their tunable resistance enables sensitive, low‐power detection of major noncommunicable diseases such as diabetes and cancer. Devices fabricated with AlO x , SiO x , and GeO x have demonstrated effective glucose monitoring and biomarker detection, including sarcosine for prostate cancer and LOXL2 for breast cancer, offering pathways toward cost‐effective and early diagnosis. Beyond disease detection, memristor exhibit nociceptive properties such as threshold sensing, synaptic plasticity, and adaptive learning, enabling multifunctional applications in neurological and sensory systems. Artificial nociceptors emulate pain perception for prosthetics and robotics, photoreceptors integrate light sensing with memory for artificial vision, and memristors neuromodulatory platforms provide energy‐efficient seizure control and adaptive deep brain stimulation for Parkinson's disease. Collectively, these developments position memristors as versatile, compact, and biomimetic devices with the potential to unify diagnostics, therapy, and sensory replication in next‐generation biomedical technologies.
SCAPS-1D Modeling and Optimization of Perovskite Solar Cells With Inorganic Cu2O Hole-Transport Layers for Enhanced Performance Sham Datto, Anik Halder, Md. Zubair Hossain, Santi M. Mandal, Debashis Panda Chemnanomat, 2026 This study presents a detailed simulation model of a perovskite solar cell (PSC) developed using the SCAPS (Solar Cell Capacitance Simulator) software, aiming to enhance photovoltaic technology performance. In this work, the model incorporates CH 3 NH 3 PbI 3 as the perovskite absorber layer, PCBM (phenyl‐C 61 ‐butyric acid methyl ester) as the electron‐transport material, and Cu 2 O as the hole‐transport material. This combination was selected based on its suitability for achieving efficient charge transport in CH 3 NH 3 PbI 3 ‐based PSCs. The optimization process investigated how changes in layer thickness, defect density, and doping concentration influence carrier recombination and device output parameters, providing a deeper understanding of performance‐limiting factors. The simulated device achieves impressive performance metrics, including an open‐circuit voltage of 1.4807 V, a short‐circuit current density of 25.13 mA/cm 2 , a fill factor of 86.95%, and a maximum power conversion efficiency of 32.36%. This work addresses a key challenge in PSCs by improving charge transport and enabling better stability by using robust inorganic Cu 2 O as the hole‐transport layer (HTL). Cu 2 O is chosen here as an alternative to conventional organic HTLs due to its low cost and excellent thermal stability. Notably, the efficiency of the PSC has been significantly improved compared to previous models, mainly through the optimization of key material properties. This simulation study serves as a valuable tool for guiding the development of PSCs, offering both design strategies and a deeper understanding of the factors governing high energy conversion efficiency.
Nanoscale Electronic Nociceptor using ZnO/TiOx Bilayer Memristor on a Flexible Substrate Debashis Panda, Arpan Acharya Chemnanomat, 2025 Nociceptive behaviors of binary zinc oxide and titanium oxide sandwiched memristor are observed on a flexible transparent substrate. The ITO/ZnO/TiOx/ITO/PEN device probes threshold behavior by applying beyond 0.9 V pulse amplitude along with an 1 ms pulse width. However, the nociceptor crossed the tolerance by applying a higher pulse width than 1 ms by maintaining the same 0.9 V pulse amplitude. The relaxation properties of the memristor‐based nociceptor are also confirmed by measuring the device after a prolonged time of more than 10 ms prior to the noxious stimulation. The allodynia and hyperalgesia behavior of the nociceptor is validated from the resistance response with different injury voltages. The low‐cost binary oxide sandwiched memristor‐based flexible nociceptor can be the best alternative for humanoid robotic applications.
Metal free all oxide SnOx/HfOx bilayer transristor synapse for neuromorphic computing Asutosh Patnaik, Debashis Panda, Ping-Xing Chen, Narayan Sahoo, Tseung-Yuen Tseng Journal of Applied Physics, 2025 Developing flexible and transparent memristors for emulating biological activities aligns with the growing demand for sustainable technologies in electronics. This paper presents the development and characterization of transparent memristors (transristors) on a flexible substrate, utilizing a structure of ITO/SnOx/HfOx/ITO/PEN. Hafnium oxide (HfOx) and tin oxide (SnOx) films are sequentially RF sputtered onto an indium doped tin oxide (ITO) bottom electrode, with polyethylene naphthalate serving as the flexible substrate. Then, an ITO top electrode is sputtered onto the SnOx layer using a shadow mask. Samples with varying thicknesses of HfOx and SnOx were prepared to optimize the device configuration. Electrical switching and synaptic characteristics of these samples were measured at room temperature, with a positive voltage applied to the top electrode and a negative voltage to the bottom electrode. This study identifies a configuration with 35 nm SnOx and 6 nm HfOx as the most effective, exhibiting excellent bipolar switching properties. Notably, it demonstrates low set/reset voltages of 1.3 and −1.6 V, with a compliance current of 100 μA. X-ray photoelectron spectroscopy was employed to assess the concentration of oxygen vacancies in the films. The device also shows the highest endurance up to 104 cycles, long-term potentiation/depression characteristics over 350 cycles, a good nonlinearity value of 1.53 (potentiation)/1.46 (depression), and 100% pattern recognition accuracy at just 14 iterations. Multi-state resistive switching characteristics were also explored. Obtained characteristics reveal that the optimized device could serve as a flexible component in making artificial synapses.
Diffusive Memristor with CuS Nanoparticles Embedded in Polymeric Film as Artificial Nociceptor Rajesh Deb, Debashis Panda, Manjula G. Nair, Farhana Yasmin, Yamineekanta Mishra, et al. ACS Applied Materials and Interfaces, 2024 The threshold behavior and the ion diffusion dynamics in diffusive volatile memristors have a very uncanny resemblance to the transduction process of biological nociceptors. Hence, the diffusive memristors are considered the most suited for making artificial nociceptive systems. To facilitate their widespread adoption, it is imperative to develop polymeric or organic-inorganic hybrid material-based diffusive memristors that are economical, biocompatible, and easily processable. In this study, we present a cluster-type polymeric diffusive memristor where copper is used as the active top electrode. The switching medium comprises copper(II) sulfide (CuS) nanoparticles embedded in poly(ethylene oxide) (PEO). The devices show electrochemical metalization (ECM)-type and bidirectional diffusive volatile memory with high nonlinearity (104) and turn-on slope (5.6 mV/dec). They reliably remain diffusive volatile with up to 10 wt % CuS in PEO and for a wide range of compliance (10-6 to 10-2 A) without transitioning to the bipolar nonvolatile type. The low reduction potential of CuS and optimal segmental dynamics of PEO work synergistically to ensure stable and reproducible diffusive memory. The CuS nanoparticles act as bipolar electrodes, undergoing local oxidation and reduction under the influence of the bias. The switching of resistance states in the CuS-PEO memristors is attributed to the formation of cluster-type filaments between CuS nanoparticles within the PEO matrix supported by the participation of copper ions from the top Cu electrode. The observation of low filament temperature and the independence of on-state resistance with respect to the device area and temperature further corroborate the cluster-type filament in CuS-PEO memristors. Using a 5 wt % CuS-based device, an artificial nociceptor is realized, which successfully mimics most of the nociceptive plasticities such as threshold, relaxation, no adaptation, and sensitization.
Synaptic plasticity in zinc oxide-based flexible invisible transparent memristor by modulating oxygen concentration Asutosh Patnaik, Arpan Acharya, Kabin Tiwari, Priyanka Saha, Narayan Sahoo, et al. Journal of Applied Physics, 2024 Artificial synapses based on memristors are used in emulating the synaptic plasticity behavior of a human brain. Here, we have proposed a transparent memristor based on aluminum zinc oxide (AZO) on a flexible substrate—polyethylene naphthalate. We have analyzed the elemental composition of the gadget subjected to the optimized flow rate of Ar/O2 = 2/1 by x-ray photoelectron spectroscopy. The prepared AZO/ZnO/indium-doped tin oxide memristor exhibits a bipolar switching behavior with Vset/Vreset of 1.4/−2.0 V. The results reflect an acceptable endurance of >500 cycles and retention of 104 s. The optimized device shows an improvement in the non-linearity of potentiation—2.31/depression—3.05 and has more than 25 cycles of stability. The transparency is checked using a UV-visible spectrophotometer showing 90% transparency in the visible region making the device suitable for applications in invisible electronics. Our results reflect that the proposed device can be used as a transparent electrode in making artificial synapses for neuromorphic applications.
All oxide based flexible multi-folded invisible synapse as vision photo-receptor Ping-Xing Chen, Debashis Panda, Tseung-Yuen Tseng Scientific Reports, 2023 All oxide-based transparent flexible memristor is prioritized for the potential application in artificially simulated biological optoelectronic synaptic devices. SnOx memristor with HfOx layer is found to enable a significant effect on synaptic properties. The memristor exhibits good reliability with long retention, 104 s, and high endurance, 104 cycles. The optimized 6 nm thick HfOx layer in SnOx-based memristor possesses the excellent synaptic properties of stable 350 epochs training, multi-level conductance (MLC) behaviour, and the nonlinearity of 1.53 and 1.46 for long-term potentiation and depression, respectively, and faster image recognition accuracy of 100% after 23 iterations. The maximum weight changes of -73.12 and 79.91% for the potentiation and depression of the synaptic device, respectively, are observed from the spike-timing-dependent plasticity (STDP) characteristics making it suitable for biological applications. The flexibility of the device on the PEN substrate is confirmed by the acceptable change of nonlinearities up to 4 mm bending. Such a synaptic device is expected to be used as a vision photo-receptor.
