Absolute Hydration Free Energy of Small Anions and the Aqueous p of Simple Acids.

J Phys Chem A

Department of Chemistry and Biochemistry, The University of Alabama, Tuscaloosa, Alabama 35487, United States.

Published: December 2022

Heats of formation and gas phase acidities for the simple acids and their deprotonated anions (A = F, Cl, Br, I, OH, SH, SeH, TeH, OCl, OBr, and OI) were calculated using the Feller-Peterson-Dixon (FPD) method with large basis sets including Douglass-Kroll scalar relativistic corrections. Hydration of the neutral and anionic species was predicted using the supermolecule-continuum approach, resulting in absolute hydration free energies that, when combined with calculated gas phase acidities, produce aqueous acidities and p values for these simple acids that are, in general, in excellent agreement with experimental literature values. Absolute hydration free energy values converged quickly in terms of the experimental values for neutral species, requiring only four explicit HO molecules. HI is anomalous in that it fully dissociates ionically in a water tetramer and was treated without explicit water molecules. The hydration energies of anionic species converged more slowly and were modeled with up to 16 explicit HO molecules. Calculated values for Δ and Δ agree with experimental values within . 1.2 kcal/mol, and Δ and ΔΔ agree with experimental values within 2 kcal/mol in most cases.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.jpca.2c06205DOI Listing

Publication Analysis

Top Keywords

absolute hydration
12
hydration free
12
simple acids
12
experimental values
12
free energy
8
gas phase
8
phase acidities
8
anionic species
8
explicit molecules
8
agree experimental
8

Similar Publications

The development and modification of grouting materials constitute crucial factors influencing the effectiveness of grouting. Given the pivotal role of water in the hydration of cement-based composite materials and construction processes, this study proposes an exploratory approach using green, economical magnetized water technology to enhance the performance of cement grouts. The research systematically investigates the effects of magnetized water on the fundamental grouting properties (stability, rheological behavior, and stone body strength) of cement grouts, prepared under varying magnetization conditions (including magnetic intensity, water flow speed, and cycle times).

View Article and Find Full Text PDF

In treating type 2 diabetes, avoiding glucose reabsorption (glucotoxicity) and managing hyperglycemia are also important. A metabolic condition known as diabetes (type-2) is characterized by high blood sugar levels in comparison to normal Bilosomes (BLs) containing Dapagliflozin (Dapa) were formulated, optimized, and tested for oral therapeutic efficacy in the current investigation. Used the Box Behnken design to optimize the Dapa-BLs, formulated via a thin-film hydration technique.

View Article and Find Full Text PDF
Article Synopsis
  • Heart failure and renal dysfunction often occur together, creating complex interactions that negatively affect patient outcomes.
  • The drug sacubitril/valsartan shows promise in improving heart and kidney health in heart failure patients with reduced ejection fraction, potentially slowing kidney function decline.
  • However, more evidence is needed to confirm its safety in preventing hyperkalemia and worsening kidney function, emphasizing the need for personalized treatment strategies and further research into heart-kidney interactions.
View Article and Find Full Text PDF

In this work, artificial neural network coupled with multi-objective genetic algorithm (ANN-NSGA-II) has been used to develop a model and optimize the conditions for the extracting of the Mentha longifolia (L.) L. plant.

View Article and Find Full Text PDF

Predicting solvation free energies with an implicit solvent machine learning potential.

J Chem Phys

December 2024

Multiscale Modeling of Fluid Materials, Department of Engineering Physics and Computation, TUM School of Engineering and Design, Technical University of Munich, Munich, Germany.

Machine learning (ML) potentials are a powerful tool in molecular modeling, enabling ab initio accuracy for comparably small computational costs. Nevertheless, all-atom simulations employing best-performing graph neural network architectures are still too expensive for applications requiring extensive sampling, such as free energy computations. Implicit solvent models could provide the necessary speed-up due to reduced degrees of freedom and faster dynamics.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!