Monte Carlo simulation combined with experimental measurements based on gamma transmission technique for determining the density of liquid

Chương, Huỳnh Đình; Sang, Truong Thanh; Tâm, Hoàng Đức

doi:10.1016/j.radphyschem.2020.109216

Cited by 8 publications

(3 citation statements)

References 18 publications

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“…Physicochemical properties of compounds play crucial roles for their applications. 1 Among them, density is an important characteristic of substances which can monitor product quality 2 and is also essential in the calculation of chemical processes. 3,4 Vapor pressure, a fundamental physicochemical property of substances, is also indispensable in plenty of significant applications, such as the distillation process and two-phase reactions.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Physicochemical properties of compounds play crucial roles for their applications . Among them, density is an important characteristic of substances which can monitor product quality and is also essential in the calculation of chemical processes. , Vapor pressure, a fundamental physicochemical property of substances, is also indispensable in plenty of significant applications, such as the distillation process and two-phase reactions. − Furthermore, the vaporization enthalpy, being able to obtain from vapor pressure data, is one of the important thermodynamic data required for the calculation, analysis, and design of chemical processes . Heat capacity values are characteristic data related to the structure of substances, and can be widely applied to chemical engineering, energy, and material engineering .…”

Section: Introductionmentioning

confidence: 99%

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Heat Capacity, Density, Vapor Pressure, and Enthalpy of Vaporization of Propyl Cinnamate

et al. 2021

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The density and liquid heat capacity of propyl cinnamate were measured in the temperature range from 290.15 to 503.15 K by a pycnometer and automatic adiabatic calorimeter and correlated with temperature by the linear equation and quadratic polynomial, respectively. Vapor pressure data of propyl cinnamate were determined by the ebulliometric method at 419.15–559.15 K, and they are in accordance with the Antoine equation. The vaporization enthalpy Δvap H (T b) of propyl cinnamate at normal boiling point was attained based on the Clausius–Clapeyron equation. The standard enthalpy of vaporization Δvap H (298.15 K) was calculated by the Othmer method and verified by the Watson relation.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heat Capacity, Density, Vapor Pressure, and Enthalpy of Vaporization of Propyl Cinnamate

et al. 2021

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“…Nu mer ous stud ies have been con ducted to de termine the den sity of un known liq uids by us ing gamma trans mis sion tech niques (GTT) or gamma scat ter ing tech niques (GST) [2,3]. In these stud ies, GTT and GST can be used to de ter mine the liq uid den sity which yields the rel a tive er ror be tween the mea sured den sity and the ref er ence den sity (cer ti fied by the man u facturer) in the range from 5 % to 8 %.…”

Section: Introductionmentioning

confidence: 99%

Estimation of liquid density using artificial neural network in gamma-ray scattering measurement

et al. 2022

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The feasibility of an artificial neural network for the estimation of the liquid density, in gamma scattering measurement, has been investigated in this paper. The liquid density was estimated using a well-trained artificial neural network model with only two input parameters: the scattering angle and the ratio of the area under a single scattering peak for a liquid relative to that for water. It is worth noting that the whole training data was generated by carrying out the Monte Carlo simulation using Monte Carlo N-Particle code. The results indicated that the artificial neural network model exhibits a good correlation between the estimated and reference densities, at all the investigated scattering angles, with a relative error below 5.5 %. Next, the trained model is used to predict the liquid density with the input data of being the experimatal data, which yield the relative deviation between the predicted density and the reference one, mostly less than 5 % (only three cases with deviation in the range from 5-8.1 %). The obtained results demonstrated that the model developed in this work gives more accurate results within the defined conditions.

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Combining Monte Carlo simulation and experimental data for determining the density of polymer materials in gamma scattering and gamma transmission measurements

Linh

Trang

Sang

et al. 2023

J Radioanal Nucl Chem

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Monte Carlo simulation combined with experimental measurements based on gamma transmission technique for determining the density of liquid

Cited by 8 publications

References 18 publications

Heat Capacity, Density, Vapor Pressure, and Enthalpy of Vaporization of Propyl Cinnamate

Heat Capacity, Density, Vapor Pressure, and Enthalpy of Vaporization of Propyl Cinnamate

Estimation of liquid density using artificial neural network in gamma-ray scattering measurement

Combining Monte Carlo simulation and experimental data for determining the density of polymer materials in gamma scattering and gamma transmission measurements

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