Effect of Temperature on Density and Refractive Index

Kurtz, S. S.; Amon, Senta; Sankin, Albert

doi:10.1021/ie50481a045

Cited by 24 publications

(12 citation statements)

References 8 publications

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“…Overall, the superiority of the EKFP method over the simple Fano fit and projection methods is demonstrated, especially for the case of low- Q resonant biosensors. The remaining limitations are the restriction of the camera resolution (the number of pixels), temperature fluctuations, and mechanical noise during the experiment; for example, a thermal noise of 0.1 °C can easily occur, which may result in a Δ n = 1.0 × 10 –5 RIU variation. − Although the system has a reference channel to minimize the impact of such variations, differences between the signal and reference channel cannot be totally avoided.…”

Section: Resultsmentioning

confidence: 99%

Extended Kalman Filtering Projection Method to Reduce the 3σ Noise Value of Optical Biosensors

Gupta

Drayton

et al. 2020

ACS Sens.

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Optical biosensors have experienced a rapid growth over the past decade because of their high sensitivity and the fact that they are label-free. Many optical biosensors rely on tracking the change in a resonance signal or an interference pattern caused by the change in refractive index that occurs upon binding to a target biomarker. The most commonly used method for tracking such a signal is based on fitting the data with an appropriate mathematical function, such as a harmonic function or a Fano, Gaussian, or Lorentz function. However, these functions have limited fitting efficiency because of the deformation of data from noise. Here, we introduce an extended Kalman filter projection (EKFP) method to address the problem of resonance tracking and demonstrate that it improves the tolerance to noise, reduces the 3σ noise value, and lowers the limit of detection (LOD). We utilize the method to process the data of experiments for detecting the binding of C-reactive protein in a urine matrix with a chirped guided mode resonance sensor and are able to improve the LOD from 10 to 1 pg/mL. Our method reduces the 3σ noise value of this measurement compared to a simple Fano fit from 1.303 to 0.015 pixels. These results demonstrate the significant advantage of the EKFP method to resolving noisy data of optical biosensors.

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Section: Resultsmentioning

confidence: 99%

Extended Kalman Filtering Projection Method to Reduce the 3σ Noise Value of Optical Biosensors

Gupta

Drayton

et al. 2020

ACS Sens.

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“…The Eykman equation, as recommended by Kurtz, Amon, and Sankin (6), gave excellent checks for 20°and 25°C…”

Section: Refractive Index Measurementsmentioning

confidence: 95%

Densities and Refractive Indices of Glycol Ether-Water Solutions.

Chu¹,

Thompson²

1960

J. Chem. Eng. Data

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“…As before, Px equals 4.455 x 109 N m-2, R equals 8.314 J mol-1 K-1 and T is the temperature (K). It will be seen from (27) that when x= 1, log y is zero and the liquids are completely miscible: under other conditions logy is negative, For a variety of liquids, the swelling of a given crosslinked polymeric liquid would at equilibrium be expected to be a maximum when ( p~-p g ) / p~ equalled ( p~' -p~' ) / p , ' and to decrease as the difference between these two fractions, and Vx, increased. It is worthy of note that for a given value of x , log y is proportional to Vx.…”

Section: 4 X 10-7mentioning

confidence: 99%

“…It has been suggested that unassociated liquids would be completely miscible if they had the same isothermal compressibility and that the work required to bring the liquids to the same isothermal compressibility is a measure of the work required to transfer the liquid from its liquid phase to the saturated solution. The following equation (27) was given.s2 where y is the volume fraction for a standard solution of the liquid, having characteristic molecular volume V,, characteristic density px= M/Vx, density p~ and saturated vapour density pg, in a liquid of characteristic density px', density PL' and saturated vapour density pg'. As before, Px equals 4.455 x 109 N m-2, R equals 8.314 J mol-1 K-1 and T is the temperature (K).…”

Section: 4 X 10-7mentioning

confidence: 99%

Estimates of the Properties of Liquids

McGowan¹

1978

J. Chem. Technol. Biotechnol.

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An equation which relates the volume term ( V = M / (~L -p g ) ) of unassociated liquids to pressure P and temperature T has been obtained by the combination of (a) 0 . 3 V ( a l / a V )~, , = T,-T for the effect of temperature on V at low (atmospheric) pressure and (b) -V(aP/a V ) T = P, Vx6/ V"P+O + 9( P -p ) for the effect of pressure on volume at constant temperature. In the equations, p is the vapour pressure; p~ the density of the liquid and pe the vapour density. Often pg can be neglected compared with PL a n d p is small compared with the large pressures required to affect the densities of liquids appreciably. There are three constants: T,, P,, which equals 4.455 x 10" N m-2, and V, which can be calculated by rhe addition of atomic values for all the atoms in the molecule and subtraction of a value (6.56 x m3 mol-1) for each bond. When V approximates to Ilt/pL, the molar volume, the equation can be integrated to give the work and heat of isothermal compression. The viscosity of a liquid is related to the work of compression and solubilities in a liquid to the work required to bring the solute to the compressibility of the liquid. Many relationships can be derived and can be used to estimate properties of unassociated liquids.

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Effect of Temperature on Density and Refractive Index

Cited by 24 publications

References 8 publications

Extended Kalman Filtering Projection Method to Reduce the 3σ Noise Value of Optical Biosensors

Extended Kalman Filtering Projection Method to Reduce the 3σ Noise Value of Optical Biosensors

Densities and Refractive Indices of Glycol Ether-Water Solutions.

Estimates of the Properties of Liquids

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