Pure and Pt-loaded gamma iron oxide as sensor for detection of sub ppm level of acetone

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Abstract

In this study, pure and Pt-loaded nanocrystalline γ-Fe2O3 have been prepared by precipitation using ultrasonic irradiation. The synthesized powders were characterized by X-ray diffraction (XRD), thermo-gravimetric analysis (TGA), differential thermal analysis (DTA), transmission electron micrograph (TEM), selected area electron diffraction (SAED), scanning electron microscope (SEM) and energy dispersive X-ray (EDX). Pure nanocrystallline γ-Fe2O3 sensors were found to show good response towards sub ppm level of acetone at 250 °C, and improves significantly on Pt loading. As an example, 1 wt% Pt loading of nanocrystallline γ-Fe2O3 increased its response towards acetone by 55%. The high response of γ-Fe2O3 holds it as a potentially promising candidate for acetone detection which may lead for the non-invasive testing of diabetics.

Introduction

Metal oxide semiconductor gas sensors have found increasing application in domestic, commercial and industrial gas sensing systems through environmental pollution monitoring, detection of harmful gases in mines, grading of food and agro-products, home safety to hand held breath analysers etc. [1], [2], [3]. The metal oxide gas sensors have several unique advantages such as low cost, small size, measurement simplicity, durability, ease to fabricate and ability to detect low concentration of reducing gases. Various metal oxides mixed with different dopants, catalysts, adhesives, binders, volatile fillers and electrodes have been studied to enhance sensing characteristics of gas sensors [2], [3], [4], [5], [7]. A promising candidate in this category of materials is γ-Fe2O3, which is also widely used for magnetic storage, magnetic refrigeration, catalysts, in addition to gas sensor applications. The advantages of γ-Fe2O3 gas sensors are its high response and low cost [4], [5], [6]. It has also been recognised that doping of γ-Fe2O3 with suitable doping agents can significantly enhance its response as well as selectivity towards the targeted gases [3], [4], [5], [7].

On the other hand, gas analysis of human expiration provides some important information on the state and functioning of different organs and hence acts as the biomarker of diseases. As an example, sensors with ability to detect sub-ppm level of acetone is important in monitoring the health conditions of diabetic patients. Detection of traces of acetone vapor in human expiration implies exacerbation of diabetes [1]. Acetone concentration in human breath depends on the nature and amount of food taken, percentage of moisture in the breath, sample collection before/after smoking etc. The maximum concentration of acetone in a healthy individual should be below 0.9 ppm [8], [9], [10]. Acetone concentration of >0.9 ppm suggests that the individual has diabetes. Some researchers have suggested that measuring acetone concentration in breath may be more effective than in urine samples for monitoring ketosis in insulin-dependent diabetic patients with high ketone levels [8], [11], [12], [13]. Different materials have been studied for acetone detection. Jing used undoped and Zn doped γ-Fe2O3 for detection of 500 ppm acetone [4], whereas Ryabtsev et al. [1] used Fe2O3 and SnO2 based sensors for detecting 10 ppm of acetone. However sub-ppm acetone detection is necessary for non-invasive testing of diabetics. In this work we have attempted to detect sub-ppm acetone by using γ-Fe2O3 semiconductor as gas sensor.

Section snippets

Powder synthesis

First, 100 mL ferric nitrate solution was prepared in a 500 mL beaker by dissolving the 1.616 g of Fe(NO3)3·9H2O (99% purity Merck Ltd., Mumbai) in distilled water. PtCl4 solution of x wt% (x = 0.25, 0.5, 1 or 2 wt% on metal basis) was prepared separately in another beaker. A small amount of hydrochloric acid was added at 60–80 °C under constant stirring for 1 h to dissolve it completely. Both the solutions were then mixed and made up to 200 mL by diluting with distilled water. The solution was then

Material characterization

Fig. 1 represents the XRD pattern of pure and 1 wt% Pt loaded γ-Fe2O3. The only phase detected on all pure and loaded films was well-crystallized γ-Fe2O3 as compared with standard data (JCPDS 39-1346). No peaks of PtO were observed because of its small loading amount (1 wt%). The average crystallite size estimated from line broadening analysis of the diffraction peaks by using the Scherrer equation is found to be 12–26 nm.

TEM image of γ-Fe2O3 as shown in Fig. 2(a) and (b) shows the formation of

Conclusion

Pure and Pt-loaded nanocrystalline γ-Fe2O3 have been prepared by a precipitation method using ultrasonics irradiation. γ-Fe2O3 when loaded with Pt, shows higher phase transformation temperature which is favorable for the stability of the γ-Fe2O3 based gas sensor. Dot mapping of the sensor coating shows the uniform distribution of constituent elements. Response of 1 wt% Pt-loaded γ-Fe2O3 based gas sensors towards acetone was enhanced to 55% than the value of pure γ-Fe2O3 based sensor. To make

Acknowledgements

Heartfelt thanks to Dr. Amarnath Sen, Sensor and Actuator Division, Central Glass and ceramic Research Institute, Kolkata, for guiding me in various ways during my research work. The author also would like to express thanks to Dr. Laxmidhar Besra and Dr. Sarama Bhattacharjee, colloids and Materials Chemistry Department, Institute of Minerals and Materials Technology, Bhubaneswar and Prof. Kousik Biswas, Indian Institute of Technology, Kharagpur, for their valuable suggestion, constant

Ramesh Chandra Biswal was born in India on 1983. He received his MSc degree in physics from Utkal University on 2006 and MTech degree in Materials Engineering from Jadavpur University, Kolkata on 2010 where he had started working on semiconducting metal oxide gas sensor in sensor and actuator division, Central Glass and Ceramic Research Institute. Since January 2010, he has joined as a research fellow in colloids and materials chemistry department, Institute of Minerals and Materials Technology

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