Fabrication and Optimization of Bilayered Nanoporous Anodic Alumina Structures as Multi-Point Interferometric Sensing Platform.

Sensors (Basel)

School of Chemical Engineering, The University of Adelaide, Engineering North Building, Adelaide 5005, Australia.

Published: February 2018

AI Article Synopsis

  • The text discusses a novel method to improve the optical sensing capabilities of nanoporous anodic alumina (NAA) for detecting multiple substances simultaneously through carefully controlled fabrication processes.
  • This technique involves creating bilayered NAA structures with varying pore sizes, allowing for unique optical interference signals that can help identify and analyze different analytes, such as quercetin.
  • The paper details experiments that demonstrate this method's effectiveness by tracking binding interactions between human serum albumin and quercetin, showcasing the potential of these structures for real-time, multi-analyte sensing applications.

Article Abstract

Herein, we present an innovative strategy for optimizing hierarchical structures of nanoporous anodic alumina (NAA) to advance their optical sensing performance toward multi-analyte biosensing. This approach is based on the fabrication of multilayered NAA and the formation of differential effective medium of their structure by controlling three fabrication parameters (i.e., anodization steps, anodization time, and pore widening time). The rationale of the proposed concept is that interferometric bilayered NAA (BL-NAA), which features two layers of different pore diameters, can provide distinct reflectometric interference spectroscopy (RIfS) signatures for each layer within the NAA structure and can therefore potentially be used for multi-point biosensing. This paper presents the structural fabrication of layered NAA structures, and the optimization and evaluation of their RIfS optical sensing performance through changes in the effective optical thickness (EOT) using quercetin as a model molecule. The bilayered or funnel-like NAA structures were designed with the aim of characterizing the sensitivity of both layers of quercetin molecules using RIfS and exploring the potential of these photonic structures, featuring different pore diameters, for simultaneous size-exclusion and multi-analyte optical biosensing. The sensing performance of the prepared NAA platforms was examined by real-time screening of binding reactions between human serum albumin (HSA)-modified NAA (i.e., sensing element) and quercetin (i.e., analyte). BL-NAAs display a complex optical interference spectrum, which can be resolved by fast Fourier transform (FFT) to monitor the EOT changes, where three distinctive peaks were revealed corresponding to the top, bottom, and total layer within the BL-NAA structures. The spectral shifts of these three characteristic peaks were used as sensing signals to monitor the binding events in each NAA pore in real-time upon exposure to different concentrations of quercetin. The multi-point sensing performance of BL-NAAs was determined for each pore layer, with an average sensitivity and low limit of detection of 600 nm (mg mL) and 0.14 mg mL, respectively. BL-NAAs photonic structures have the capability to be used as platforms for multi-point RIfS sensing of biomolecules that can be further extended for simultaneous size-exclusion separation and multi-analyte sensing using these bilayered nanostructures.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855889PMC
http://dx.doi.org/10.3390/s18020470DOI Listing

Publication Analysis

Top Keywords

sensing performance
16
sensing
9
naa
9
nanoporous anodic
8
anodic alumina
8
optical sensing
8
pore diameters
8
naa structures
8
photonic structures
8
simultaneous size-exclusion
8

Similar Publications

Unlabelled: LCN2 has an osteokine important for appetite regulation; in type 2 diabetes (T2D) it is not known whether appetite regulation mediated by LCN2 in the brain is altered. In this work, we focus on exploring the role of blocking LCN2 in metabolic health and appetite regulation within the central nervous system of mice with T2D.

Material And Methods: 4-week-old male C57BL/6 mice were used, divided into four experimental groups: intact, T2D, TD2/anti-LCN2, and T2D/IgG as isotype control.

View Article and Find Full Text PDF

Construction of an electrochemical sensor for the detection of methyl parathion with three-dimensional graphdiyne-carbon nanotubes.

Mikrochim Acta

January 2025

CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, 100049, China.

To enhance the application performance of graphdiyne (GDY) in electrochemical sensing, carbon nanotubes (CNTs) were grown in situ to construct three-dimensional nanoarchitectures of GDY-CNTs composites. GDY-CNTs showed superior electrochemical properties and detection response to MP when compared with GDY, as the in situ growth of CNTs significantly increased the electrode surface area and enhanced the electron transfer process. GDY-CNTs were successfully used to construct electrochemical sensors for methyl parathion (MP).

View Article and Find Full Text PDF

Recent advances in electrochemical sensing and remediation technologies for ciprofloxacin.

Environ Sci Pollut Res Int

January 2025

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India.

Ciprofloxacin (CIP) is an extensively used broad-spectrum, fluoroquinolone antibiotic used for treating diverse bacterial infections. Effluent treatment plants (ETPs) worldwide lack technologies to detect or remediate antibiotics. CIP reaches the aquatic phase primarily due to inappropriate disposal practices, lack of point-of-use sensing, and preloaded activated charcoal filter at ETPs.

View Article and Find Full Text PDF

Utilizing convolutional neural network (CNN) for orchard irrigation decision-making.

Environ Monit Assess

January 2025

Department of Environmental Management, Graduate School of Agriculture, Kindai University, Nara, Japan.

Efficient agricultural management often relies on farmers' experiential knowledge and demands considerable labor, particularly in regions with challenging terrains. To reduce these burdens, the adoption of smart technologies has garnered increasing attention. This study proposes a convolutional neural network (CNN)-based model as a decision-support tool for smart irrigation in orchard systems, focusing on persimmon cultivation in mountainous regions.

View Article and Find Full Text PDF

Introduction: Eating disorders can be irreversible and, in many cases, fatal. However, the symptoms full recovery is possible, and early diagnosis is one, of many, important factors for the success of treatment. In this sense, the screening of risk behaviours arises as a relevant alternative to improve the prognosis of patients.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!