Memristive Biosensors for Cancer Biomarkers Detection: A Review

Homsi, Rami; Al‐Azzam, Nosayba; Mohammad, Baker; Alazzam, Anas

doi:10.1109/access.2023.3248683

Cited by 6 publications

(4 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They can be utilized in biosensors and diagnostic technologies, interacting with biomolecules to enable highsensitivity early cancer detection and rapid virus diagnosis. 11 Additionally, memristors show great potential in the domain of neural computing and brain-machine interfaces, facilitating the construction of neuromorphic computing systems to simulate brain information processing and learning mechanisms. 12 A memristor is a non-linear two-terminal device, and its resistance varies as the input current or voltage accumulates.…”

Section: Chuan Yangmentioning

confidence: 99%

Memristor based electronic devices towards biomedical applications

Zhang,

Du,

Yang

et al. 2024

J. Mater. Chem. C

View full text Add to dashboard Cite

show abstract

Section: Chuan Yangmentioning

confidence: 99%

Memristor based electronic devices towards biomedical applications

Zhang,

Du,

Yang

et al. 2024

J. Mater. Chem. C

View full text Add to dashboard Cite

show abstract

“…For our device, the linearity of synaptic plasticity for Y8.03 is close to perfect linearity, and the nonlinearity value is calculated to be 0.949 for potentiation and 0.984 for depression, as shown in Figure S8 (Supporting Information), while Y1.74 exhibited a much higher nonlinearity of 5.964/0.829 for potentiation/depression, respectively. [42,43] Perfect linearity represents a nonlinearity value of 1. Furthermore, low power consumption, which is essential for neuromorphic computing, is accomplished using outstanding synaptic characteristics.…”

Section: Application To Artificial Synapse Device Of Ysh-based Egfetmentioning

confidence: 99%

First Demonstration of Yttria‐Stabilized Hafnia‐Based Long‐Retention Solid‐State Electrolyte‐Gated Transistor for Human‐Like Neuromorphic Computing

Jin,

2023

Small

View full text Add to dashboard Cite

Electrolyte‐gated transistors have strong potential for high‐performance artificial synapses in neuromorphic bio‐interfaces owing to their outstanding synaptic characteristics, low power consumption, and human‐like mechanisms. However, the short retention time is a hurdle to overcome owing to the natural diffusion of protons. Here, a novel modulation technique of ionic conductivity is proposed with yttria‐stabilized hafnia for the first time to enhance the retention characteristic of a solid‐state electrolyte‐gated transistor‐based artificial synapse. With the optimization of the ionic conductivity in yttria‐stabilized hafnia, a high retention time of over 300 s and remarkable synaptic characteristics are accomplished by regulating channel conductance with precise modulation of the strength of the proton‐electron coupling intensity along the input signals. Furthermore, pattern recognition simulation is conducted based on the measured synaptic characteristics, exhibiting 94.41% of operation accuracy, which implies a promising solution for neuromorphic in‐memory computing systems with a high operation accuracy and low power consumption.

show abstract

“…In all cases the time derivative of the charge gradient is a function with the parameters of the memristor [120]. Memristors can be applied in the synaptic contacts [129] [130], and other memory applications like neuronal calculations [131], perspiration processes [132] and biosensors [133]. Microtubules composed of tubulin dimers are show also memristor effects [134].…”

Section: A Szasz Open Journal Of Biophysicsmentioning

confidence: 99%

Memristor Hypothesis in Malignant Charge Distribution

Szasz

2023

OJBIPHY

View full text Add to dashboard Cite

Tissues in biological objects from the point of view of electromagnetic effects must be modeled not only for their conductivity. The ionic double layer induced by the electric field, built by electrolytic diffusion, must be counted. The micro (frequency dispersion phenomena) and macro (interfacial polarization), as well as more generalized by Nernst-Planck cells describe the biophysical aspects of this phenomena. The charge distribution depends on the processes and produces charge gradients in space. The dynamic feasibility of the-charge transition layer has memory and adaptability, working like a memristor in cancerous development. The memristor processes may complete the adaptation mechanisms of cancer cells to extremely stressful conditions. Our objective is to show the distribution and redistribution of space charges that generate memristors and internal currents like injury current (IC) in the development of cancer. We show some connected aspects of the modulated electrohyperthermia (mEHT) limiting the proliferation process in the micro-range like the macro-range electrochemotherapy (ECT) processes do. The internal polarization effects form space-charge, which characteristically differ in malignant and healthy environments. The electrical resistivity of the electrolytes depends on the distribution of the charges and concentrations of ions in the electrolytes, consequently the space-charge differences appear in the conductivity parameters too. The polarization heterogeneities caused by the irregularities of the healthy tissue induce a current (called injury current), which appears in the cancerous tumor as well. Due to the nonlinearity of the space-charge production and the differences of the relaxation time of the processes in various subunits. The tumor develops the space-charge which appears as an inductive component in the otherwise capacitive setting and forms a memristive behavior of the tumorous tissue. This continuously developing space-charge accommodates the tumor to the permanently changing conditions and helps the adopting the malignant cells in the new environment.

show abstract

Memristive Biosensors for Cancer Biomarkers Detection: A Review

Cited by 6 publications

References 103 publications

Memristor based electronic devices towards biomedical applications

Memristor based electronic devices towards biomedical applications

First Demonstration of Yttria‐Stabilized Hafnia‐Based Long‐Retention Solid‐State Electrolyte‐Gated Transistor for Human‐Like Neuromorphic Computing

Memristor Hypothesis in Malignant Charge Distribution

Contact Info

Product

Resources

About