scholarly journals Analysis of interaction between mechanical force and chemical effect in cleaning phenomenon by probability density functional method

2021 ◽  
Author(s):  
Miyako Oya‐Hasegawa ◽  
Yuya Sato ◽  
Masaru Oya
Keyword(s):  
Probability Density ◽  
Density Functional ◽  
Density Functional Method ◽  
Functional Method ◽  
Mechanical Force ◽  
Chemical Effect ◽  
Probability Density Functional

Relation between mechanism of soil removal from fabrics and a parameter derived from probability density functional method for washing force analysis

2018 ◽  
Vol 89 (11) ◽  
pp. 2236-2246 ◽  
Author(s):  
Masaru Oya
Keyword(s):  
Probability Density ◽  
Density Functional ◽  
Soil Removal ◽  
Density Functional Method ◽  
Functional Method ◽  
Water Soluble ◽  
Oily Soil ◽  
Force Analysis ◽  
Removal Mechanisms ◽  
Probability Density Functional

The probability density functional method is one of the washing force analysis methods that combines the classical kinetic analysis of detergency method and risk calculation method using probability density function. This paper discusses the relation between soil removal mechanisms and the value of σ rl, which is one of the two parameters used in the probability density functional method. Four repetitive washing tests were conducted using test fabrics soiled with iron(III) oxide, carbon black, four kinds of water-soluble dyes and three kinds of oily dyes, and the removal (%) was analyzed with the probability density functional method. The results show that the range of σ rl varied with removal mechanisms; mechanical removal of particle soil (0.01–0.6), dissolution into water of water-soluble soil (0.3–1.4), solubilization of oily soil into surfactant micelle (1.0–2.0) and emulsification or dispersion of oily soil (≥3.0). This tendency can be used for estimating the removal mechanism of any washing system where the soil type is unknown.

scholarly journals Kinetic analysis of hemoglobin detergency by probability density functional method

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0237255
Author(s):  
Miyako Oya ◽  
Yosuke Taniguchi ◽  
Naoaki Fujimura ◽  
Karen Miyamoto ◽  
Masaru Oya
Keyword(s):  
Kinetic Analysis ◽  
Probability Density ◽  
Density Functional ◽  
Density Functional Method ◽  
Functional Method ◽  
Probability Density Functional

Computer Simulation of an Synthetic Ultraviolet Absorbent in the Interface of DMB and DMF

2010 ◽  
Vol 146-147 ◽  
pp. 966-971
Author(s):  
Qi Hua Jiang ◽  
Hai Dong Zhang ◽  
Bin Xiang ◽  
Hai Yun He ◽  
Ping Deng
Keyword(s):  
Computer Simulation ◽  
Computer Simulations ◽  
Density Functional ◽  
Density Functional Method ◽  
Mean Field ◽  
Functional Method ◽  
Dynamic Density ◽  
Interface Phase ◽  
Simulation Results

This work studies the aggregation of an synthetic ultraviolet absorbent, named 2-hydroxy-4-perfluoroheptanoate-benzophenone (HPFHBP), in the interface between two solvents which can not completely dissolve each other. The aggregation is studied by computer simulations based on a dynamic density functional method and mean-field interactions, which are implemented in the MesoDyn module and Blend module of Material Studios. The simulation results show that the synthetic ultraviolet absorbent diffuse to the interface phase and the concentration in the interface phase is greater than it in the solvents phase.

A New Approach for Calculating the Band Gap of Semiconductors within the Density Functional Method

2015 ◽  
Vol 242 ◽  
pp. 434-439 ◽  
Author(s):  
Vasilii E. Gusakov
Keyword(s):  
Density Functional Theory ◽  
Band Gap ◽  
Density Functional ◽  
Density Functional Method ◽  
Functional Method ◽  
Localized States ◽  
Experimental Accuracy ◽  
Functional Theory ◽  
New Approach ◽  
The Density Functional Theory

Within the framework of the density functional theory, the method was developed to calculate the band gap of semiconductors. We have evaluated the band gap for a number of monoatomic and diatomic semiconductors (Sn, Ge, Si, SiC, GaN, C, BN, AlN). The method gives the band gap of almost experimental accuracy. An important point is the fact that the developed method can be used to calculate both localized states (energy deep levels of defects in crystal), and electronic properties of nanostructures.

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