Classical Density Functional Theory for Molecular Systems

Wu, Jianzhong

doi:10.1007/978-981-10-2502-0_3

Cited by 20 publications

(19 citation statements)

References 61 publications

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“…in conjunction with mean field approaches like Poisson-Boltzmann (PB) or modified Poisson-Boltzmann (MPB) theory[51,52,53]. An alternative to continuum theories is the rigorous classical density functional theory of liquids[54]; it calculates thermodynamic functions by variational free energy minimization, rendering it computationally more efficient than molecular dynamics simulations.As for the latter, there are currently no reports on explicit simulations of electrochemical interfaces based on QM/MM, as are widely popular in other fields[55].Combination of electronic structure calculations for the electrode region with different treatment of the solvent region results in three main classes of FPEC approaches, which are (i) the computational hydrogen electrode (CHE) of Nørskov, Rossmeisl and others [56, 57, 58], (ii) a standard approach (DFT-CSM/MPB) that combines electronic DFT with mean field theories for the electrolyte region, pioneered by Otani and Sugino [59] and developed further by Jinnouchi and Anderson [49] as well as Dabo, Bonnet and Marzari [60], and (iii) joint density functional theory (JDFT) that combines electronic and classical DFT for the respective regions [35, 61]. All of these approaches and their numerous derivatives (too many to cite) are heavily preoccupied with two crucial questions: how to fix a potential scale and how to maintain electroneutrality in the system?…”

mentioning

confidence: 99%

Approaching the self-consistency challenge of electrocatalysis with theory and computation

Eslamibidgoli

Eikerling

2018

Current Opinion in Electrochemistry

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This is a PDF file of an unedited manuscript that has been accepted for publication. Highlights • In electrocatalysis, complex nonlinear and non-monotonic coupling arises in the boundary region between metal and electrolyte • A recent theoretical framework demonstrates how to handle this coupling • Approaches in first-principles electrochemical modeling need to be modified to consistently treat nonlinear and non-monotonic charging effects

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mentioning

confidence: 99%

Approaching the self-consistency challenge of electrocatalysis with theory and computation

Eslamibidgoli

Eikerling

2018

Current Opinion in Electrochemistry

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“…The study of new systems, as soon as they become technologically and scientifically relevant, requires continual development of new methods to improve Systems involving liquids, such as electrochemical interfaces or solvated biomolecules, are particularly challenging for DFT calculations, requiring thermodynamic sampling of several thousands of atomic configurations in ab initio molecular dynamics (AIMD) simulations [8]. Joint density-functional theory (JDFT) was proposed as a theoretical framework to address this issue by combining electronic DFT with classical DFT of liquids [9] to directly compute equilibrium properties of quantum-mechanically described solutes in diverse solvent environments [10]. Bringing this method to fruition required the simultaneous development of physical models (free energy functionals) of liquids and their interaction with electrons, algorithms to perform variational free-energy minimization and code that tightly and efficiently coupled these new models with electronic DFT.…”

Section: Motivation and Significancementioning

confidence: 99%

JDFTx: Software for joint density-functional theory

et al. 2017

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Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) that combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.

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“…Moving down the scale of accuracy and cost, we can consider solvent density without the need for simulations of explicit water molecules by utilising an integral equation theory model with a suitable free energy functional, e.g. 3D-RISM with the UC, PC, or PC+ functional (Misin et al 2015;Misin et al 2016;Sergiievskyi et al, 2015;Palmer et al 2010), or classical molecular density functional theory (Wu, 2017), which describes the density of molecules in a fluid rather than the more familiar use of DFT to describe the density of electrons in a molecule. This can provide an excellent compromise between cost and precision.…”

Section: Computing Hydration Energiesmentioning

confidence: 99%

3. In Silico methods to predict solubility

McDonagh¹,

Mitchell²,

Palmer³

et al. 2019

Solubility in Pharmaceutical Chemistry

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A solution is a homogenous mixture of solute(s) and solvent(s) in any physical state, solid, liquid or gas, where the solute is the substance dissolved in the solvent. A substance's solubility describes the extent to which the substance can be dissolved in a given solvent, resulting in a solution. Solubility is a thermodynamic property, related to the equilibrium between the solute and solvent. From these general ideas, we can begin to discuss the finer details of solubility and the process of solvation. Solubility Data and Experimental DeterminationsSolubility data, particularly in the pharmaceutical industry, tend to be of two distinct types: equilibrium solubility measurements, also called thermodynamic solubility, and kinetic solubility measurements. In the following paragraphs we provide a short overview of how solubility data can be measured. A more in-depth discussion of this topic is provided in the chapter "The role of solubility to optimize drug substances -a Medicinal Chemistry perspective" of this book. Equilibrium solubilityEquilibrium solubility is the concentration of solute in equilibrium with its saturated solution. These measurements are often made at the later stages of pharmaceutical development, such as during formulation (Narasimham & Barhate, 2011;Saal & Petereit, 2012).The classical method for determining this is the shake flask method (Jouyban & Fakhree, 2012), which involves mixing a sample of a solute with a buffer solution until saturation. The saturated solution is then shaken until equilibrium is achieved and a final solubility determined by the dissolved concentrations. This is often achieved using high-pressure liquid chromatography. This method relies upon long shaking times, as it is difficult to determine when the solution has reached equilibrium.A more modern approach is the CheqSol (chasing equilibrium solubility) method (Stuart &

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Classical Density Functional Theory for Molecular Systems

Cited by 20 publications

References 61 publications

Approaching the self-consistency challenge of electrocatalysis with theory and computation

Approaching the self-consistency challenge of electrocatalysis with theory and computation

JDFTx: Software for joint density-functional theory

3. In Silico methods to predict solubility

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