Roya Maboudian (Advisor)

Research Advised by Professor Roya Maboudian

Maboudian Group:  List of Projects | List of Researchers

Arthur Montazeri

Alumni
Professor Roya Maboudian (Advisor)
PostDoc 2018

Sinem Ortaboy

Alumni
Professor Roya Maboudian (Advisor)
PostDoc 2017

Chuan-Pei Lee

Alumni
Professor Roya Maboudian (Advisor)
PostDoc 2017

Raphael Brechbuehler

Alumni
Chemical and Biomolecular Engineering
Professor Roya Maboudian (Advisor)
M.S. 2016

Won Seok (Lucas) Chi

Alumni
Professor Roya Maboudian (Advisor)
PostDoc 2017

BPN933: Ag@MIL-53 Core-Shell Nanostructures for SERS-Based Chemical Analysis

Aifei Pan
Yong Xia
Adrian K. Davey
2021

A large number of poisonous chemicals, such as PFOA, PFOS, and mercury ions, are mandated to be controlled in drinking water with their permissible concentrations below parts-per-billion (ppb). In this context, an increase in the concentration is a necessary step preceding detection. Apart from their selective absorption ability, metal-organic frameworks (MOFs) have an extraordinarily large internal surface area, which can be used for extraction. In terms of detection methods, Raman spectroscopy is a powerful non-invasive chemical detection technology characterized by portability,...

BPN964: Metal Oxide Heterostructure Nanowires for Gas Sensing Applications

Sikai Zhao
2021

Metal oxide semiconducting gas sensors are one of the most widely used gas sensing devices due to their low cost, high reliability, solid-state, and high response. While they have been employed for the detection of various gases and in many applications, several issues remain including their limited selectivity and humidity interference. As the core part of a semiconducting gas sensor, sensing materials play the key role in determining the sensing performance of the device, with the materials’ microstructure and surface properties being the dominant factors. Thus the primary...

Improved Hydrogen Sensitivity and Selectivity in PdO with Metal-Organic Framework Membrane

David Gardner
Xiang Gao
Hossain M. Fahad
Ali Javey
Carlo Carraro
Roya Maboudian
2020

Metal-organic frameworks (MOFs) are highly designable porous materials and are recognized for their exceptional selectivity as chemical sensors. However, they are not always suitable for incorporation with existing sensing platforms, especially sensing modes that rely on electronic changes in the sensing material (e.g., work-function response or conductometric response). One way that MOFs can be utilized is by growing them as a porous membrane on a sensing layer and using the MOF to affect the electronic structure of the sensing layer. In this paper, a proof-of-concept for...

Transistor‐Based Work Function Measurement of Metal‐Organic Frameworks for Ultra‐Low‐Power, Rationally Designed Chemical Sensors

David Gardner
Xiang Gao
Hossain M. Fahad
An-Ting Yang
Sam He
Ali Javey
Carlo Carraro
Roya Maboudian
2019

A classic challenge in chemical sensing is selectivity. Metal-organic frameworks (MOFs) are an exciting class of materials because they can be tuned for selective chemical adsorption. Adsorption events trigger work-function shifts, which can be detected with a chemical-sensitive field-effect transistor (power ≈microwatts). In this work, several case studies were used towards generalizing the sensing mechanism, ultimately towards our metal-centric hypothesis. HKUST-1 was used as a proof-of-principle humidity sensor. The response is thickness independent, meaning the response is...

Scalable Ultra Low-Power Chemical Sensing with Metal-Organic Frameworks

David Gardner
Xiang Gao
Hossain M. Fahad
An-Ting Yang
Sam He
Ali Javey
Carlo Carraro
Roya Maboudian
2019

This paper reports the innovative use of a highly tunable material, metal-organic frameworks (MOFs), for chemical sensing on an ultra-low-power platform based on a field-effect transistor. We demonstrate proof-of-principle devices functionalized with two MOFs: "HKUST-1" for humidity sensing and "ZIF-8" for reversible NO 2 detection. These devices show minimal drift, yield highly reproducible responses, recover rapidly, and have excellent selectivity. Through this approach, devices with minimal power draw and high selectivity could be widely distributed for continuous environmental and...