Xu Pengcheng, Yu Haitao, Guo Shuanbao, Li Xinxin
State Key Lab of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences , 865 Changning Road, Shanghai 200050, China.
Anal Chem. 2014 May 6;86(9):4178-87. doi: 10.1021/ac403498x. Epub 2014 Apr 9.
On the basis of microgravimetric sensing data, an analytical modeling method is proposed for comprehensive evaluation and optimization of gas sensing or adsorbing related functional materials. Resonant microcantilever is loaded with the material to be evaluated for a gravimetric sensing experiment. With sensing isotherm curves obtained at different temperatures, key thermodynamic and kinetic parameters of the material, such as enthalpy ΔH°, Gibbs free energy, adsorption rate constant Ka, and coverage θ, etc., can be quantitatively extracted for optimal selection and design. On the basis of the gravimetric experiment, the modeling method is used on three sorts of trimethylamine sensing nanomaterials of mesoporous silica nanoparticles (MSNs). The COOH-functionalized material is clearly identified as the best sensing material among the three similar ones, thereby validating high accuracy of the proposed model. Broad applicability of the modeling method to other sensing materials and/or target gases is also experimentally confirmed, where sensing properties of a functionalized hyper-branched polymer to organophorous simulant of dimethyl methylphosphonate (DMMP) are still evaluated well. In addition to sensing materials, the gravimetric experiment-based modeling method can be expanded to other functional materials like moisture absorbents or detoxification agents. Water adsorbing experiment on KIT-5 mesoporous-silica is modeled, with the low -ΔH° value (i.e., low adsorption heat) result, indicating that the KIT-5 is a good adsorbent to humidity. Alternatively, the modeled high -ΔH° value (i.e., high reaction heat) shows promising usage of SBA-15 mesoporous-silica as detoxification material to hazardous organophorous chemicals. Therefore, the analytical modeling technology can be used for developing and evaluating new adsorbing materials for gas sensing, fixing, and detoxification applications.
基于微重力传感数据，提出了一种用于气体传感或吸附相关功能材料综合评估与优化的分析建模方法。将待评估材料加载到共振微悬臂梁上进行重量传感实验。利用在不同温度下获得的传感等温线曲线，可以定量提取材料的关键热力学和动力学参数，如焓变ΔH°、吉布斯自由能、吸附速率常数Ka和覆盖率θ等，以进行优化选择和设计。在重量实验的基础上，将该建模方法应用于三种介孔二氧化硅纳米颗粒（MSN）的三甲胺传感纳米材料。在三种相似材料中，明确鉴定出COOH功能化材料是最佳传感材料，从而验证了所提出模型的高精度。实验还证实了该建模方法对其他传感材料和/或目标气体具有广泛的适用性，其中一种功能化超支化聚合物对甲基膦酸二甲酯（DMMP）有机磷模拟物的传感性能仍能得到很好的评估。除了传感材料外，基于重量实验的建模方法还可以扩展到其他功能材料，如吸湿剂或解毒剂。对KIT-5介孔二氧化硅进行了水吸附实验建模，其低ΔH°值（即低吸附热）结果表明KIT-5是一种良好的湿度吸附剂。相反，建模得到的高ΔH°值（即高反应热）表明SBA-15介孔二氧化硅有望用作危险有机磷化学品的解毒材料。因此，该分析建模技术可用于开发和评估用于气体传感、固定和解毒应用的新型吸附材料。
