This work demonstrates the high-performance hydrogen peroxide (H2O2) sensing field-effect transistor (FET) using reduced graphene oxide - polypyrrole (rGO/PPy) nanocomposites. The SiO2 trench type FET is fabricated using lithography and etching techniques. The fabricated SiO2 trench structure was used not only for holding H2O2 but also for sensing purpose. The morphology and structure of the rGO/PPy nanocomposites were analyzed and confirmed their bonding. The output electrical signal changes as the concentration of H2O2 increases. The device shows a fast response of 5 s and is highly stable with excellent sensitivity. The detection limit obtained is 10 pM at appropriate signal-to-noise ratio (S/N) of the sensing electrical signal. The device is high selectivity towards H2O2. The device structure may be employed for other liquid sensing applications.

Detection of Hydrogen Peroxide Using rGO/PPy Nanocomposites in Silicon Dioxide Trench Embedded Field Effect Transistor

This study demonstrates the application of graphene oxide-silver (GO/Ag) nanocomposite to develop a non-enzymatic high-performance glucose-sensing field-effect transistor (FET). Lithography and etching processes are used to fabricate the SiO2 trench embedded FET. The fabricated device structure was used not only for glucose storage but also for glucose sensing. The bonding of the GO/Ag nanocomposite was validated by analysing their shape and structure. As the concentration of glucose rises (<inline-formula> <tex-math notation="LaTeX">$1~\mu \text{M}$ </tex-math></inline-formula> to 10 mM range), the output electrical signal changes. With a <inline-formula> <tex-math notation="LaTeX">$1~\mu \text{M}$ </tex-math></inline-formula> limit of detection (Signal to Noise ratio, S/N >3), the sensor has a response time of fewer than 5 seconds. It also demonstrated great long-term stability, outstanding reproducibility, and excellent glucose selectivity. This sensor has notable characteristics such as ease of production, simplicity of usage, and small size. It has the potential to fabricate portable glucose sensors for point-of-care sensing in the future. Additional liquid sensing applications could benefit from the sensor structure.

Non-Enzymatic Glucose Detection Based on GO/Ag Nanocomposite in SiO2 Trench Embedded Field Effect Transistor

This work illustrates a high-performance Urea sensor using Cys-GO (L-Cysteine functionalized GO) as a sensing material. The device is fabricated using the standard lithography process. The device has an additional feature of liquid holding, which increases sensing performance. The morphological and structural characterization of Cys-GO is investigated to ensure the bonding between L-Cysteine and GO. The electrical analysis shows excellent sensitivity (<inline-formula> <tex-math notation="LaTeX">$0.1423~\boldsymbol \mu \text{A}$ </tex-math></inline-formula>/dec) over the 1 nM-<inline-formula> <tex-math notation="LaTeX">$10~\boldsymbol \mu \text{M}$ </tex-math></inline-formula> range of Urea concentration with high linearity (<inline-formula> <tex-math notation="LaTeX">$\text {R}^{{2}}={0.99082}$ </tex-math></inline-formula>). The sensor is highly selective towards Urea, is reusable, and has a faster response time (10-20 s). The proposed sensor can be used in point-of-care applications for Urea sensing.

Non-Enzymatic Urea Sensing With Cys-GO Using Device With Silicon Dioxide Trench

A low-cost biosensor with multifunctionality, wide detection range, and enhanced sensitivity was highly desirable. In this work, we demonstrated the desirable application of Cu2O@Au in nitrite, glucose, and formaldehyde detection. The surfactant-free synthesis of Cu2O@Au nanocrystals with a hexapod morphology and controllable Au loading rates has been achieved. The surfactant-free surface maximized the active sites and the decoration by Au accelerated electron transfer, resulting in an enhanced biosensor performance. The correlation between the atomic rate and biosensor performance for obtained Cu2O@Au nanocrystals has been investigated systematically. It is indicated that an optimal Au loading rate would not only enhance the sensitivity but also rationalize the sensor cost. In the detection of nitrite, the sensitivity of the sensor constructed by Cu2O@Au-20% was $368.77 ~\mu \text{A}$ /mM $\cdot $ cm2, which exhibited 6.8 folds higher than that by pure Cu2O. The superior biosensor sensitivity of Cu2O@Au could also be extended to the glucose and formaldehyde detection, the enhanced factors could reach 1.26 and 1.88, respectively. Meanwhile, the surface decoration by Au elevated enabled Cu2O an effective photocatalyst. This work optimized the performances of Cu2O by a green approach, which opened up new avenues for designing a nontoxic biosensor with multifunctionality and enhanced performance.

Surfactant-free synthesis of hexapod Cu2O@Au nanocrystals and their enhanced performances in biosensor and photo-catalysis

Amine neurotransmitters (NTs) are crucial in the central nervous system, and dysregulation in their levels is implicated in a spectrum of neurological disorders. Thus, a precise and timely assessment of their concentrations is critical for early diagnosis and treatment efficacy monitoring. Graphene-based field effect transistors (GFETs) have become a ground-breaking instrument in the detection of these NTs because of their exceptional electrical characteristics and adaptability. This paper summarises the significant advancements in GFET biosensors in amine NT detection and highlights developments in the selectivity, sensitivity, and limit of detection (LOD) attained by selecting various graphene materials and functionalisation approaches. 

Advances in Graphene Field Effect Transistors (FETs) for Amine Neurotransmitter Sensing

This work explores the fabrication and characterization of an ionic liquid channel field effect transistor (FET) incorporated within the trench structure on SiO2. The trench structure allows any liquid to be accommodated, thereby eliminating the mold creation on the device or the requirement for an intricate architecture to store liquid. For the fabrication of the trench, we followed a standard photolithography process with the help of selective etching of aluminum and SiO2. The fabricated trench surface is characterized using atomic force microscopy (AFM) and contact angle analysis. The electrical characterization of the proposed FET structure is also performed with 0.01-mM potassium chloride (KCl) solution as an ionic channel. We tested both the n-FET and p-FET type characteristics which can be controlled by the back gate biasing condition. The dc characterization shows a high ${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ ratio of 105 for both the n-FET and p-FET. The device further shows an improvement in K+ mobility and Cl− mobility of $2.24 \times 10^{-4} {\mathrm {m}}^{2}/{\mathrm {Vs}}$ and $4.96 \times 10^{-4} {\mathrm {m}}^{2}/{\mathrm {Vs}}$ , respectively. We also carried out the FET structure modeling to estimate the effective ${C}_{{\mathrm {ox}}}$ for the trench SiO2 structure. It is observed that the total capacitance after the inclusion of Debye length is $1.29 \times 10^{-4} {\mathrm {F/m}}^{2}$ . Furthermore, the number of ions is also calculated from the electrical characteristics, and it is almost comparable with the number of ions in the molar solution. Overall, the proposed fabricated structure, although simple, enables to accommodate any liquid as a channel and provides an easy way to develop electrolyte-based sensors.

Ionic Liquid Channel Field Effect Transistor Fabricated Using Silicon Dioxide Trench

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of {limit} columns in the table. Remove at least 1 column to add or create another one.

Monica Naorem

Author Tools

Chat about Author

Papers

Detection of Hydrogen Peroxide Using rGO/PPy Nanocomposites in Silicon Dioxide Trench Embedded Field Effect Transistor

Non-Enzymatic Glucose Detection Based on GO/Ag Nanocomposite in SiO2 Trench Embedded Field Effect Transistor

Non-Enzymatic Urea Sensing With Cys-GO Using Device With Silicon Dioxide Trench

Ionic Liquid Channel Field Effect Transistor Fabricated Using Silicon Dioxide Trench