A new group contribution method for predicting viscosity of organic liquids

Sastri, S. R. S.; Rao, K. K.

doi:10.1016/0300-9467(92)80002-r

Cited by 78 publications

(52 citation statements)

References 32 publications

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“…volatile (Goldstein and Galbally, 2007), more dense (Kuwata et al, 2012), more viscous (Sastri and Rao, 1992), and more CCN active (Suda et al, 2014).…”

Section: D Petters Et Al: Prediction Of Cloud Condensation Nuclementioning

confidence: 99%

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

2016

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Abstract.A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köh-ler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquidliquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

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“…volatile (Goldstein and Galbally, 2007), more dense (Kuwata et al, 2012), more viscous (Sastri and Rao, 1992), and more CCN active (Suda et al, 2014).…”

Section: D Petters Et Al: Prediction Of Cloud Condensation Nuclementioning

confidence: 99%

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

2016

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“…Quasi-equilibrium versus kinetically limited or non-equilibrium SOA growth remains an open issue and warrants further investigations. Group contribution methods have been used to predict the viscosities of pure compounds when the functionality and molecular structure are known (Sastri and Rao, 1992;Rothfuss and Petters, 2017a). Song et al (2016b) showed that estimations from group contribution approaches combined with either non-ideal or ideal mixing reproduced the RH-dependent trends particularly well for the alcohol, dicarboxylic, and tricarboxylic acid systems with viscosities of up to 10 4 Pa s. In contrast, model calculations overestimated the viscosity of more viscous compounds including monosaccharides, disaccharides, and trisaccharides by many orders of magnitude (Song et al, 2016b).…”

Section: Introductionmentioning

confidence: 99%

Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

et al. 2018

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Abstract. Secondary organic aerosol (SOA) accounts for a large fraction of submicron particles in the atmosphere. SOA can occur in amorphous solid or semi-solid phase states depending on chemical composition, relative humidity (RH), and temperature. The phase transition between amorphous solid and semi-solid states occurs at the glass transition temperature (T g ). We have recently developed a method to estimate T g of pure compounds containing carbon, hydrogen, and oxygen atoms (CHO compounds) with molar mass less than 450 g mol −1 based on their molar mass and atomic O : C ratio. In this study, we refine and extend this method for CH and CHO compounds with molar mass up to ∼ 1100 g mol −1 using the number of carbon, hydrogen, and oxygen atoms. We predict viscosity from the T g -scaled Arrhenius plot of fragility (viscosity vs. T g /T ) as a function of the fragility parameter D. We compiled D values of organic compounds from the literature and found that D approaches a lower limit of ∼ 10 (±1.7) as the molar mass increases. We estimated the viscosity of α-pinene and isoprene SOA as a function of RH by accounting for the hygroscopic growth of SOA and applying the Gordon-Taylor mixing rule, reproducing previously published experimental measurements very well. Sensitivity studies were conducted to evaluate impacts of T g , D, the hygroscopicity parameter (κ), and the Gordon-Taylor constant on viscosity predictions. The viscosity of toluene SOA was predicted using the elemental composition obtained by high-resolution mass spectrometry (HRMS), resulting in a good agreement with the measured viscosity. We also estimated the viscosity of biomass burning particles using the chemical composition measured by HRMS with two different ionization techniques: electrospray ionization (ESI) and atmospheric pressure photoionization (APPI). Due to differences in detected organic compounds and signal intensity, predicted viscosities at low RH based on ESI and APPI measurements differ by 2-5 orders of magnitude. Complementary measurements of viscosity and chemical composition are desired to further constrain RH-dependent viscosity in future studies.

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“…The constraints

g' (z, y) \leq 0

are defined according to the description of the case study

μ (T) - 100 \leq 0

0.97 - x_{{CH}_{4}}^{(3)} \leq 0

where μ is the solvent's viscosity (in cP) and

x_{{CH}_{4}}^{(3)}

is the mole fraction of methane in Stream (3). The viscosity is estimated by the method of Sastri and Rao . Further, there is a constraint on the normal melting point

T^{melt}

of the solvent (in K) for which two cases are considered:

Case 1 : T^{melt} - T + 10 \leq 0

Case 2 : T^{melt} - T + 30 \leq 0

…”

Section: Hierarchical Solvent and Process Design For Co2 Absorptionmentioning

confidence: 99%

A hierarchical method to integrated solvent and process design of physical CO₂ absorption using the SAFT‐γ Mie approach

et al. 2015

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in Wiley Online Library (wileyonlinelibrary.com) Molecular-level decisions are increasingly recognized as an integral part of process design. Finding the optimal process performance requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed-integer nonlinear programming (MINLP) problem. The formulation of such problems when using a group contribution version of the statistical associating fluid theory, SAFT-c Mie, to predict the physical properties of the relevant mixtures reliably over process conditions is presented. To solve the challenging MINLP, a novel hierarchical methodology for integrated process and solvent design (hierarchical optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the MINLP solution. The methodology is applied to the design of a physical absorption process to separate carbon dioxide from methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers.

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A new group contribution method for predicting viscosity of organic liquids

Cited by 78 publications

References 32 publications

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

A hierarchical method to integrated solvent and process design of physical CO₂ absorption using the SAFT‐γ Mie approach

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A new group contribution method for predicting viscosity of organic liquids

Cited by 78 publications

References 32 publications

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

Predicting the glass transition temperature and viscosity of secondary organic material using molecular composition

A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT‐γ Mie approach

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A hierarchical method to integrated solvent and process design of physical CO₂ absorption using the SAFT‐γ Mie approach