Sorption Kinetics of Poly(ethyleneimine)–Poly(ethylene Oxide) Blends and the Implication for Low-Cost, Small-Scale CO2 Sensors

吸附 环氧乙烷 氧化物 化学工程 材料科学 纳米技术 化学 聚合物 共聚物 有机化学 复合材料 吸附 工程类 冶金
作者
Zachary A. Siefker,John N. Hodul,Bryan W. Boudouris,George T.‐C. Chiu,James E. Braun,Jeffrey F. Rhoads,Bryan W. Boudouris
出处
期刊:ACS applied polymer materials [American Chemical Society]
卷期号:4 (6): 4389-4397 被引量:2
标识
DOI:10.1021/acsapm.2c00361
摘要

Public health depends on reliable, low-cost methods of measuring indoor air quality (IAQ), and carbon dioxide (CO2) is often used as a surrogate measure for IAQ. Thus, there is an increasing interest in developing inexpensive CO2 sensors that can be seamlessly integrated into existing ventilation systems for smart and connected healthy buildings. To this aim, microelectromechanical system-based (MEMS-based) resonant mass sensors functionalized with specific surface chemistries are a promising sensing platform because of their compact size, low cost, and fast response times. Furthermore, poly(ethyleneimine)-based (PEI-based) materials capture CO2 selectively and reversibly. Here, we report the temperature dependencies of a polymer blend composed of PEI and poly(ethylene oxide) (PEO), as this synergetically blended material platform is useful as a CO2 sensing system when coated atop a MEMS-based resonant mass sensor. Importantly, we report how temperature can impact polymer characteristics, which ultimately dictate sensor performance. To achieve this aim, adsorption rate constants and thermodynamic parameters were calculated using a Langmuir model for a series of polymer blends with different compositions. Throughout a range of temperatures relevant to indoor sensing systems, these polymer blends adsorbed less and desorbed more CO2 with increasing temperature. This was due, in part, to the melting of the polymer materials and a decrease in the availability of PEI amines to capture CO2. Ultimately, these data provide a deeper understanding of the selection criteria and boundaries to consider when using polymer-based selective recognition layers in indoor environments and inform the development of low-cost and small-scale IAQ sensors.

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