基于气体浓度定量的嗅觉刺激器优化设计

现有的基于磁共振测量的嗅觉刺激器，通过调节嗅剂液体浓度的方法可以实现不同浓度的嗅觉刺激，但随着实验进行，受到嗅剂挥发以及实验环境（温度、湿度、气流量）变化的影响，很难确保输送至鼻腔的嗅剂气体浓度的稳定性，进而影响实验结果的准确性．本研究对本实验室前期开发的嗅觉刺激装置进行改进，实现了气体浓度精确定量．改进后的嗅觉刺激器主要分为三个部分：控制系统、反馈系统和气路系统．控制系统主要实现气路系统的送气控制和嗅剂气体浓度调节；反馈系统则负责对气体浓度进行测量；气路系统则在原有基础上添加活性炭装置，降低无关因素干扰．装置改进之后，不同气路切换时间为75.2 ms，比原装置减少了1 s，有效提高刺激精度．实验结果显示，气体浓度调节前，300 s内乙醇、吡啶、乙酸戊酯嗅剂气体浓度分别下降6.7%、71.4%、79.2%，嗅剂气体浓度短时间内发生较大改变．加入气体浓度调节功能后，当气体浓度下降至目标浓度的90%时，可通过调节气泵电压改变嗅剂气流与空气气流比例，从而调节嗅剂气体浓度至目标值，其中吡啶、乙酸戊酯用时13 s．     

Novel synthesis of sensor for selective detection of Fe+3 ions under various solvents

Naked-eye colored chemo dosimeter based on vanilline based conjugated sensor was synthesized and characterized. The main point of this paper is that the solvent also affects on selectivity of metals. Vanilline based conjugate sensor exhibited high selectivity and sensitivity for detection of Ferric ions (Fe⁺³) in all (both polar and nonpolar) solvents according to absorbance which can be observed by naked eye. The selectivity was more prominent in nonpolar or less polar solvent due to solubility factor of ions and sensor but not for polar. The detection of limit of the synthesized probes was shown up to 0.84 ppm. The dielectric constant of solvents affected on the complex formation of ligand with transition metal ions. A filter paper strip system was used for rapid monitoring of detection by color variation.     

高居里温度铁电单晶PIN-PT的机电性能

弛豫铁电单晶Pb(In_1/2Nb_1/2)O₃-PbTiO₃(PIN-PT)相较于常用的Pb(Mg_1/3Nb_2/3)O₃-PbTiO₃(PMN-PT)具有更高的居里温度,在高稳定性、高性能的传感器、换能器方面具有应用前景。本工作采用谐振法研究了[001]方向极化的0.66PIN-0.34PT铁电单晶的全矩阵机电性能参数。0.66PIN-0.34PT 单晶的三方-四方相变温度(T_RT)约为160 ℃,居里温度(T_C)约为260 ℃,室温压电系数d₃₃、d₃₁、d₁₅分别为1 340 pC/N、-780 pC/N、321 pC/N,介电常数ε^T₃₃、ε^S₃₃、ε^T₁₁、ε^S₁₁分别为2 700、905、2 210、1 927,机电耦合系数 k₃₃、k₃₁、k₁₅、k_t分别为 87%、58%、38%、61%。其纵向压电常数(d₃₃)和纵向机电耦合系数(k₃₃)小于 PMN-PT 单晶,但是横向压电性能(d₃₁)和剪切压电性能(d₁₅)都略高于PMN-PT单晶。另外,研究了机电耦合性能随温度的变化趋势,发现0.66PIN-0.34PT单晶在150 ℃以下有较好的温度稳定性。     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Sensitivity improvement of aluminum-based far-ultraviolet nearly guided-wave surface plasmon resonance sensor

An aluminum (Al) based nearly guided-wave surface plasmon resonance (NGWSPR) sensor is investigated in the far-ultraviolet (FUV) region. By simultaneously optimizing the thickness of Al and dielectric films, the sensitivity of the optimized Al-based FUV-NGWSPR sensor increases from 183°/RIU to 309°/RIU, and its figure of merit rises from 26.47 RIU^-1 to 32.59 RIU^-1 when the refractive index of dielectric increases from 2 to 5. Compared with a traditional FUV-SPR sensor without dielectric, the optimized FUV-NGWSPR sensor can realize simultaneous improvement of sensitivity and figure of merit. In addition, the FUV-NGWSPR sensor with realistic materials (diamond, Ta₂O₅, and GaN) is also investigated, and 137.84%, 52.70%, and 41.89% sensitivity improvements are achieved respectively. This work proposes a method for performance improvement of FUV-SPR sensors by exciting nearly guided-wave, and could be helpful for the high-performance SPR sensor in the short-wavelength region.     

Fluorescent macrocyclic chemosensor for Zn(II) detection at alkaline pH values

ABSTRACT

The new macrocyclic ligand L (28,29-dimethoxy-27-oxa-8,11,14,17,25,26-hexaazatetracyclo[22.2.1.1(2,6).1(19,23)]nonacosa-2,4,6(28),19,21,23(29),24,26(1)-octaene) has been synthesised. It contains a tetramine chain and the 2,5-bis(2-methoxy-3-metyl-phenyl)-1,3,4-oxadiazole (PPD-OMe) chromophore, acting as coordinating and sensing units, respectively.

The fluorescent emission of L depends on the pH being highly fluorescent at pH = 2 and not emitting from pH >10. The studies highlighted that L is a PET mediated emitting chemosensor, being the PET effect regulated by the degree of the tetraamine protonation.

L coordinates metal ions (Cu(II), Zn(II) and Cd(II)) in water giving rise to an OFF-ON fluorescent response for the presence of Zn(II) ion thus signalling its presence in the medium. This response is particularly notable at pH = 9 allowing to extend the Zn(II) sensing also in the alkaline pH field.     

Free radical oxidation reaction for selectively solvatochromic sensors with dynamic sensing ability

A novel BODIPY (boradiazaindacene) dye denoted as BODIPY-DT containing terpyridine unit has been designed and characterized. The dye is found to be selective and visual solvatochromic sensor toward DMF among test organic solvents. The sensing process displays time-controllable, dynamic signal outputs in the emission colors including red, purple, yellow and even white emission colors. It is presented that selective free radical oxidation reaction happens during the recognition process.     

光寻址电位传感器的正交相位检波检测方法

光寻址电位传感器的幅度检测方法易受噪声干扰,灵敏度差,信噪比和精度低,且受调制光源的影响较大,影响检测结果的准确性.为此提出了一种基于正交相位检波的光寻址电位传感器检测方法.该方法是将光寻址电位传感器的输出光电流信号分别与两路正交信号相乘,通过低通滤波提取直流分量并相除,即可得到光寻址电位传感器的输出信号相位信息.与已有的光寻址电位传感器相位检测方法相比,该方法具有算法复杂度低、实时性高的优点.实验研究了调制光源光强对光寻址电位传感器幅度检测和相位检测的影响,对比分析了光寻址电位传感器的传统幅度检测方法与正交相位检波检测方法对pH检测的灵敏度、线性度及信噪比.结果表明,相比于幅度检测方法,调制光源光强对光寻址电位传感器的相位检测影响更小,在频率为10 kHz,pH的范围为1.68~10.01的情况下,相位检测方法比幅度检测方法测得的灵敏度增加了7 mV/pH,精度提高了14.9 mpH,非线性误差减小了0.003%,均方差减少了0.1051×10^-5,信噪比增加了8.2827 dB.该方法特别适用于弱光下的光寻址电位传感器检测.