scholarly journals A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3978
Author(s):  
Rocco Peter Fornari ◽  
Piotr de Silva
Keyword(s):  
Organic Molecules ◽  
Ph Value ◽  
Computational Cost ◽  
Legendre Transform ◽  
Good Prediction ◽  
Redox Potentials ◽  
Free Energies ◽  
Hybrid Functional ◽  
Data Set ◽  
State Changes

Discovering new materials for energy storage requires reliable and efficient protocols for predicting key properties of unknown compounds. In the context of the search for new organic electrolytes for redox flow batteries, we present and validate a robust procedure to calculate the redox potentials of organic molecules at any pH value, using widely available quantum chemistry and cheminformatics methods. Using a consistent experimental data set for validation, we explore and compare a few different methods for calculating reaction free energies, the treatment of solvation, and the effect of pH on redox potentials. We find that the B3LYP hybrid functional with the COSMO solvation method, in conjunction with thermal contributions evaluated from BLYP gas-phase harmonic frequencies, yields a good prediction of pH = 0 redox potentials at a moderate computational cost. To predict how the potentials are affected by pH, we propose an improved version of the Alberty-Legendre transform that allows the construction of a more realistic Pourbaix diagram by taking into account how the protonation state changes with pH.

scholarly journals A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials

2021 ◽  
Author(s):  
Rocco Peter Fornari ◽  
Piotr de Silva
Keyword(s):  
Organic Molecules ◽  
Ph Value ◽  
Computational Cost ◽  
Legendre Transform ◽  
Good Prediction ◽  
Redox Potentials ◽  
Free Energies ◽  
Hybrid Functional ◽  
Data Set ◽  
State Changes

<p>We present and validate a robust procedure to calculate the redox potentials of organic molecules at any pH value, using widely available quantum chemistry and cheminformatics methods. Using a consistent experimental data set for validation, we explore and compare a few different methods for calculating reaction free energies, the treatment of solvation, and the effect of pH on redox potentials. We find that the B3LYP hybrid functional with COSMO solvation method, in conjunction with thermal contributions evaluated from BLYP gas-phase harmonic frequencies, yields a good prediction of pH=0 redox potentials at a moderate computational cost. To predict how the potentials are affected by pH, we propose an improved version of the Alberty-Legendre transform that allows the construction of a more realistic Pourbaix diagram by taking into account how the protonation state changes with pH.</p>

scholarly journals A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials

2021 ◽  
Author(s):  
Rocco Peter Fornari ◽  
Piotr de Silva
Keyword(s):  
Organic Molecules ◽  
Ph Value ◽  
Computational Cost ◽  
Legendre Transform ◽  
Good Prediction ◽  
Redox Potentials ◽  
Free Energies ◽  
Hybrid Functional ◽  
Data Set ◽  
State Changes

<p>We present and validate a robust procedure to calculate the redox potentials of organic molecules at any pH value, using widely available quantum chemistry and cheminformatics methods. Using a consistent experimental data set for validation, we explore and compare a few different methods for calculating reaction free energies, the treatment of solvation, and the effect of pH on redox potentials. We find that the B3LYP hybrid functional with COSMO solvation method, in conjunction with thermal contributions evaluated from BLYP gas-phase harmonic frequencies, yields a good prediction of pH=0 redox potentials at a moderate computational cost. To predict how the potentials are affected by pH, we propose an improved version of the Alberty-Legendre transform that allows the construction of a more realistic Pourbaix diagram by taking into account how the protonation state changes with pH.</p>

scholarly journals Calculating free energies of organic molecules on insulating substrates

2017 ◽  
Vol 8 ◽  
pp. 667-674
Author(s):  
Julian Gaberle ◽  
David Z Gao ◽  
Alexander L Shluger
Keyword(s):  
Free Energy ◽  
Organic Molecules ◽  
Computational Cost ◽  
Potential Of Mean Force ◽  
Free Energies ◽  
Energy Profiles ◽  
Integration Techniques ◽  
Ring Structures ◽  
Anchoring Groups ◽  
Insulating Substrates

The challenges and limitations in calculating free energies and entropies of adsorption and interaction of organic molecules on an insulating substrate are discussed. The adhesion of 1,3,5-tri(4'-cyano-[1,1'-biphenyl]-4-yl)benzene (TCB) and 1,4-bis(4-cyanophenyl)-2,5-bis(decyloxy)benzene (CDB) molecules to step edges on the KCl(001) surface and the formation of molecular dimers were studied using classical molecular dynamics. Both molecules contain the same anchoring groups and benzene ring structures, yet differ in their flexibility. Therefore, the entropic contributions to their free energy differ, which affects surface processes. Using potential of mean force and thermodynamic integration techniques, free energy profiles and entropy changes were calculated for step adhesion and dimer formation of these molecules. However, converging these calculations is nontrivial and comes at large computational cost. We illustrate the difficulties as well as the possibilities of applying these methods towards understanding dynamic processes of organic molecules on insulating substrates.

scholarly journals ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

2017 ◽  
Vol 8 (4) ◽  
pp. 3192-3203 ◽  
Author(s):  
J. S. Smith ◽  
O. Isayev ◽  
A. E. Roitberg
Keyword(s):  
Neural Network ◽  
Force Field ◽  
Deep Neural Network ◽  
Organic Molecules ◽  
Computational Cost ◽  
Quantum Mechanical ◽  
Data Set

We demonstrate how a deep neural network (NN) trained on a data set of quantum mechanical (QM) DFT calculated energies can learn an accurate and transferable atomistic potential for organic molecules containing H, C, N, and O atoms.

Hydration Free Energies of Organic Molecules in the FreeSolv Database Calculated with Polarized Atom In Molecules Atomic Charges and the GAFF Force Field.

2018 ◽  
Author(s):  
Maximiliano Riquelme ◽  
Alejandro Lara ◽  
David L. Mobley ◽  
Toon Vestraelen ◽  
Adelio R Matamala ◽  
...  
Keyword(s):  
Force Field ◽  
Functional Groups ◽  
Electrostatic Interactions ◽  
Organic Molecules ◽  
Force Fields ◽  
Chemical Elements ◽  
Atomic Charges ◽  
Free Energies ◽  
Molecular Systems ◽  
Solvent Model

<div>Computer simulations of bio-molecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in bio-molecular systems and are therein described by atomic point charges.</div><div>In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the MBIS atomic charge method, including the solvent polarization, with a root mean square error of 2.0 kcal mol<sup>-1</sup> for the 613 organic molecules studied. The largest deviation was observed for phosphor-containing molecules and the molecules with amide, ester and amine functional groups.</div>

scholarly journals A quantitative evaluation of computational methods to accelerate the study of alloxazine-derived electroactive compounds for energy storage

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi Zhang ◽  
Abhishek Khetan ◽  
Süleyman Er
Keyword(s):  
Energy Storage ◽  
Density Functional ◽  
Tight Binding ◽  
Computational Cost ◽  
Redox Potentials ◽  
Storage Compounds ◽  
Computational Screening ◽  
Chemical Descriptor ◽  
Lowest Unoccupied Molecular Orbital ◽  
Semi Empirical

AbstractAlloxazines are a promising class of organic electroactive compounds for application in aqueous redox flow batteries (ARFBs), whose redox properties need to be tuned further for higher performance. High-throughput computational screening (HTCS) enables rational and time-efficient study of energy storage compounds. We compared the performance of computational chemistry methods, including the force field based molecular mechanics, semi-empirical quantum mechanics, density functional tight binding, and density functional theory, on the basis of their accuracy and computational cost in predicting the redox potentials of alloxazines. Various energy-based descriptors, including the redox reaction energies and the frontier orbital energies of the reactant and product molecules, were considered. We found that the lowest unoccupied molecular orbital (LUMO) energy of the reactant molecules is the best performing chemical descriptor for alloxazines, which is in contrast to other classes of energy storage compounds, such as quinones that we reported earlier. Notably, we present a flexible in silico approach to accelerate both the singly and the HTCS studies, therewithal considering the level of accuracy versus measured electrochemical data, which is readily applicable for the discovery of alloxazine-derived organic compounds for energy storage in ARFBs.

Adaptive sampling of potential-field data: A direct approach to compressive inversion

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. IM1-IM9 ◽  
Author(s):  
Nathan Leon Foks ◽  
Richard Krahenbuhl ◽  
Yaoguo Li
Keyword(s):  
Potential Field ◽  
Adaptive Sampling ◽  
Field Data ◽  
Computational Cost ◽  
Large Field ◽  
Magnetic Data ◽  
Data Sampling ◽  
Data Types ◽  
Data Set ◽  
Potential Field Data

Compressive inversion uses computational algorithms that decrease the time and storage needs of a traditional inverse problem. Most compression approaches focus on the model domain, and very few, other than traditional downsampling focus on the data domain for potential-field applications. To further the compression in the data domain, a direct and practical approach to the adaptive downsampling of potential-field data for large inversion problems has been developed. The approach is formulated to significantly reduce the quantity of data in relatively smooth or quiet regions of the data set, while preserving the signal anomalies that contain the relevant target information. Two major benefits arise from this form of compressive inversion. First, because the approach compresses the problem in the data domain, it can be applied immediately without the addition of, or modification to, existing inversion software. Second, as most industry software use some form of model or sensitivity compression, the addition of this adaptive data sampling creates a complete compressive inversion methodology whereby the reduction of computational cost is achieved simultaneously in the model and data domains. We applied the method to a synthetic magnetic data set and two large field magnetic data sets; however, the method is also applicable to other data types. Our results showed that the relevant model information is maintained after inversion despite using 1%–5% of the data.

A combined local and global structure module for human pose estimation

2021 ◽  
pp. 1-11
Author(s):  
Zhihui Yang ◽  
Xiangyu Tang ◽  
Lijuan Zhang ◽  
Zhiling Yang
Keyword(s):  
Pose Estimation ◽  
Computational Cost ◽  
Hybrid Structure ◽  
Estimation Accuracy ◽  
Structure Model ◽  
Data Set ◽  
Human Pose ◽  
Human Joints ◽  
Residual Block ◽  
Keypoints Detection

Human pose estimate can be used in action recognition, video surveillance and other fields, which has received a lot of attentions. Since the flexibility of human joints and environmental factors greatly influence pose estimation accuracy, related research is confronted with many challenges. In this paper, we incorporate the pyramid convolution and attention mechanism into the residual block, and introduce a hybrid structure model which synthetically applies the local and global information of the image for the analysis of keypoints detection. In addition, our improved structure model adopts grouped convolution, and the attention module used is lightweight, which will reduce the computational cost of the network. Simulation experiments based on the MS COCO human body keypoints detection data set show that, compared with the Simple Baseline model, our model is similar in parameters and GFLOPs (giga floating-point operations per second), but the performance is better on the detection of accuracy under the multi-person scenes.

scholarly journals Penyisihan Limbah Organik Air Lindi TPA Jatibarang Menggunakan Koagulasi-Flokulasi Kimia

Teknik ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 78 ◽  
Author(s):  
Arya Rezagama ◽  
Mochtar Hadiwidodo ◽  
Purwono Purwono ◽  
Nurul Fajri Ramadhani ◽  
Mia Yustika
Keyword(s):  
Landfill Leachate ◽  
Organic Molecules ◽  
Ph Value ◽  
Optimal Dose ◽  
Organic Load ◽  
Leachate Treatment ◽  
Negative Effect ◽  
Value Changes ◽  
Positive Effect ◽  
Age Process

Air lindi yang meresap ke dalam tanah yang berpotensi bercampur dengan air tanah sehingga menimbulkan pencemaran tanah, air tanah dan air permukaan. Komposisi limbah lindi dari berbagai TPA berbeda-beda bergantung pada musim, jenis limbah, umur TPA. Proses dalam TPA menghasilkan molekul organik recalcitrant yang ditunjukkan dengan rendahnya rasio BOD/COD dan tingginya nilai NH3-N. Belum optimalnya pengolahan air lindi di Jatibarang membutuhkan pretreatment sebagai bentuk upaya alternatif dalam proses pengolahan air lindi sebelum masuk ke dalam proses aerated lagun. Penelitian ini bertujuan untuk menganalisa pengaruh koagulan kimia pada penyisihan bahan organik air lindi TPA Jatibarang. Penelitian dilakukan pada bulan April- Agustus 2016. Karaktersitik air lindi TPA Jatibarang termasuk dalam kategori "moderately stable" dan lindi muda. Penyisihan bahan organik dengan menggunakan kuagulan kimia FeCl3 dan Al2SO4 menunjukkan nilai yang cukup signifikan untuk parameter COD, BOD, TSS. Penggunaan dosis optimal terjadi pada 16 g/L FeCl3 serta 16 g/L Al2SO4 dapat menurunkan nilai COD sebesar 51% dan 65%, BOD sebesar 50% dan 56%, dan TSS sebesar 24% dan 21%. Perubahan nilai pH akibat penambahan koagulan berpengaruh positif terhadap tingkat penyisihan, namun memberikan dampak negatif yaitu buih yang cukup banyak. Penurunan beban organik menguntungkan bagi sistem pengolahan lindi eksisting TPA Jatibarang. [Title: Removal of Lindi Water Organic Waste of TPA Jatibarang using Chemical Coagulation- Floculation] Leachate grounding into the soil that potentially could mix with the groundwater caused contamination of soil, groundwater and surface water. The composition of waste landfill leachate from the various location is depending on the season, the type of waste, and landfill age. Process in the TPA produces recalcitrant organic molecules as indicated by the low ratio of BOD/COD and NH3-N high value. The ineffective treatment of leachate at Jatibarang require a pretreatment as a form of alternative effort in the processing of leachate prior to entry into the aerated lagoon process. This study aims to analyze the influence of chemical coagulants on grounding organic material Jatibarang landfill leachate. The study was conducted in April-August 2016. Jatibarang landfill leachate characteristics were categorized as "moderately stable" and young leachate. Allowance for organic materials using chemical coagulants of FeCl3 and Al2SO4 showed significant values for the parameters of COD, BOD, and TSS. The use of optimal dose occurs at 16 g/L FeCl3 and 16 g/L Al2SO4 which can reduce the COD value by 51% and 65%, BOD by 50% and 56%, and TSS at 24% and 21%. PH value changes due to the addition of coagulant positive effect on the level of the allowance, but a negative effect that is quite a lot of froth. The decline in organic load favorable for existing landfill leachate treatment systems Jatibarang. 

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