scholarly journals The Establishment of Thermodynamic Model for Ti Bearing Steel-Slag Reaction and Discuss

2022 ◽  
Vol 8 ◽  
Author(s):  
Mao-Guo Zhao ◽  
Xu-Feng Wang ◽  
Gu-Jun Chen ◽  
Sheng-Ping He
Keyword(s):  
Gibbs Energy ◽  
Thermodynamic Model ◽  
Steel Slag ◽  
Influence Factors ◽  
Bearing Steel ◽  
Molar Gibbs Energy ◽  
Energy Change ◽  
Gibbs Energy Change ◽  
Mass Ratio ◽  
Coexistence Theory

A thermodynamic model for seven CaO-MgO-BaO-CaF2-SiO2-Al2O3-TiO2 ladle slags based on the Ion and Molecule Coexistence theory (IMCT) is establishment and validated by the experiment results at 1873K. The calculated activity of SiO2, Al2O3 and TiO2 in the slag can be approved by the experiment results and the IMCT model used in this study is reasonable. Then the influence factors such as the mass ratio of CaO to SiO2 (C/S ratio) ranging from 1 to 10, the mass ratio of CaO to Al2O3 (C/A ratio) ranging from 1 to 2.5, TiO2 content (wt pct) ranging from 0 to 30, BaO content (wt pct) ranging from 0 to 30 are investigated based on the thermodynamic calculating results. The raise of C/S ratio, TiO2 content and BaO content in the slag can increase the molar Gibbs energy change (ΔG) of Ti reacted with SiO2 and Al2O3 or Al reacted with SiO2. The effect of C/A ratio on the molar Gibbs energy change (ΔG) of Ti reacted with SiO2 and Al2O3 or Al reacted with SiO2 was less. Finally, the slag with higher C/S ratio and TiO2 content and appropriate BaO content can weaken the reaction between Ti and SiO2 or Al2O3 in the slag.

A description of effect of composition of mixed binary solvents on processes in solutions

1988 ◽  
Vol 53 (4) ◽  
pp. 671-685 ◽  
Author(s):  
Oldřich Pytela ◽  
Miroslav Ludwig
Keyword(s):  
Gibbs Energy ◽  
Mixed Solvents ◽  
Theoretical Description ◽  
Energy Change ◽  
Binary Solvents ◽  
Gibbs Energy Change ◽  
Order Model ◽  
Significant Difference

A theoretical description of the effect of changed composition of mixed solvents on processes in solutions has been suggested on the basis of the proportionality between the Gibbs energy change of the process and that of the solvent due to the transition from pure components to the mixture. The additional Gibbs energy has been expressed by means of the so-called classical functions by Margules, van Laar-Wohl, and van Laar-Null. The application to 115 various processes (pK, IR, UV-VIS, NMR, log k, and others) has confirmed that the theoretical presumptions are justified, the most suitable being Margules' 4th order model which shows a statistically significant difference from the models of lower orders.

Correlation Between Reduced Mass and Gibbs Energy Change of Reaction

2021 ◽  
Author(s):  
Masatoshi Kawashima
Keyword(s):  
Gibbs Energy ◽  
Bond Formation ◽  
Energy Change ◽  
Gibbs Energy Change ◽  
Positive Direction ◽  
Dissociation Equilibrium ◽  
Equilibrium Reactions ◽  
The Relationship ◽  
Good Agreement ◽  
Bond Formation Reactions

<p>The correlation between the Gibbs free energy change of reaction and the reduced mass was clarified. In the case of bond formation reactions, the computed Gibbs energy change of reaction increased in the positive direction as the reduced mass increased. In the case of dissociation equilibrium reactions, such as the dissociation of tetrahedral carbonyl addition compound, the computed Gibbs energy change of reaction also increased in the positive direction as the reducing mass increased, but the extent of the change was smaller than in the case of bond formation reactions. The results were in good agreement with those derived from the relationship between yield and reduced mass, indicating that was originated from the correlation between the Gibbs energy change and the reduced mass.</p>

Gibbs Energy Change of Reactions

1996 ◽  
pp. 203-246 ◽  
Author(s):  
N. A. Gokcen ◽  
R. G. Reddy
Keyword(s):  
Gibbs Energy ◽  
Energy Change ◽  
Gibbs Energy Change

Novel Formulation of the Gibbs–Energy Change in Terms of Stoichiometrically Unique Response Reactions

1996 ◽  
Vol 51 (10-11) ◽  
pp. 1079-1083 ◽  
Author(s):  
Ilie Fishtik ◽  
István Nagypál ◽  
Ivan Gutman
Keyword(s):  
Gibbs Energy ◽  
Energy Change ◽  
Gibbs Energy Change ◽  
Chemical Thermodynamics ◽  
Present Formulation ◽  
Remarkable Property ◽  
Complex Chemical ◽  
Chemical Systems ◽  
Sensitivity Coefficients ◽  
Basic Concepts

Abstract The equation for the change of Gibbs energy in complex chemical systems is reformulated in terms of the newly conceived response reactions (RERs). The present formulation has the remarkable property of being unique: the composition of the species unequivocally determines the response reactions and via them the change of the Gibbs energy of the system. Furthermore, it enables one to reinterpret and rationalize some basic concepts of chemical thermodynamics, as coupling between reactions, sensitivity coefficients, etc.

scholarly journals dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

2021 ◽  
Vol 17 (9) ◽  
pp. e1009448
Author(s):  
Lin Wang ◽  
Vikas Upadhyay ◽  
Costas D. Maranas
Keyword(s):  
Gibbs Energy ◽  
De Novo ◽  
Standard Gibbs Energy ◽  
Energy Change ◽  
Gibbs Energy Change ◽  
Easy Access ◽  
Metabolic Reaction ◽  
Enzymatic Reactions ◽  
Seamless Integration ◽  
Standard Gibbs Energy Change

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change (ΔrG′o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).

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