Journal articles: 'Computational Chemistry Method'

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Zhou, Lei, Wanhui Zhao, and Haiqiao Wei. "Effect of improved accelerating method on efficient chemistry calculations in diesel engine." International Journal of Engine Research 19, no. 8 (September 18, 2017): 839–53. http://dx.doi.org/10.1177/1468087417731438.

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With detailed chemical kinetics being employed in combustion simulations, its major computational challenge is the time-intensive nature of chemical kinetics integration due to the large number of chemical species and wide range of chemical timescales involved. In this work, an extended tabulated dynamic chemistry approach with dynamic pruning method is carried out to simulate complex spray combustion for non-premixed combustion process. The thought of extended tabulated dynamic chemistry approach with dynamic pruning is achieved by selecting the optimum acceleration method as well as its error tolerances at different combustion stages depending on combustion characteristics involving the low-temperature combustion. The present method is applied to realistically complex combustion systems involving spray flame of n-heptane fuel and non-premixed combustion engine. Computation efficiency of the proposed method is compared with the results using different accelerating methods, including dynamical adaptive chemistry, in situ adaptive tabulation, and coupled method of tabulated dynamical adaptive chemistry. The results show that transient computational cost will decrease for low-temperature combustion by reducing ambient oxygen concentration clearly in spray flame. Meanwhile, very low computational efficiency is presented once the autoignition occurs, especially at the initial oxygen concentration of 21%. Based on the feature, extended tabulated dynamic chemistry approach with dynamic pruning with different dynamic adaptive chemistry error tolerances is proposed to improve computational efficiency. Extended tabulated dynamic chemistry approach with dynamic pruning with larger error tolerance [Formula: see text] improves around two times for decreased amplitude of transient computational cost at high-temperature combustion stage, and at the same time, the computational accuracy is also improved by comparing the important intermediate species obtained by direct integration. For applications in diesel engine, the results show that extended tabulated dynamic chemistry approach with dynamic pruning can accurately capture the first-stage ignition feature that determines the high-temperature combustion stage. In addition, extended tabulated dynamic chemistry approach with dynamic pruning with the smaller in situ adaptive tabulation error tolerance of 0.001 only used at the high-temperature combustion stage significantly improves the performance on diesel engine simulation with a larger chemistry mechanism. The present method further significantly improves computational efficiency with an overall speedup factor of 10 with high-accuracy compared with result using direct integration.

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Lam, S. H. "REDUCED CHEMISTRY MODELING IN REACTING FLOWS." International Journal of Modern Physics C 05, no. 02 (April 1994): 225–27. http://dx.doi.org/10.1142/s0129183194000209.

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This paper reviews the need for reduced chemistry modeling for hypersonic reactive flows, and describes the method of computational singular perturbation which can computationally derive reduced chemistry models for a massively complex reaction system.

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Aristoff, David. "An ergodic theorem for the weighted ensemble method." Journal of Applied Probability 59, no. 1 (January 18, 2022): 152–66. http://dx.doi.org/10.1017/jpr.2021.38.

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AbstractWe study weighted ensemble, an interacting particle method for sampling distributions of Markov chains that has been used in computational chemistry since the 1990s. Many important applications of weighted ensemble require the computation of long time averages. We establish the consistency of weighted ensemble in this setting by proving an ergodic theorem for time averages. As part of the proof, we derive explicit variance formulas that could be useful for optimizing the method.

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Khadka, Deba Bahadur. "Development of Computational Research Methods and Application in Chemistry." NUTA Journal 5, no. 1-2 (December 31, 2018): 72–78. http://dx.doi.org/10.3126/nutaj.v5i1-2.23460.

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The development of computational research methods and its application in chemistry has been described in this paper. Based on theoretical review on computational research, the study applied experimental research method. The discussion of findings showed that, the development of computational research methods have both advantages and disadvantages that have clearly highlighted in this study.

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Liang, Long, Song-Charng Kong, Chulhwa Jung, and Rolf D. Reitz. "Development of a Semi-implicit Solver for Detailed Chemistry in Internal Combustion Engine Simulations." Journal of Engineering for Gas Turbines and Power 129, no. 1 (February 28, 2006): 271–78. http://dx.doi.org/10.1115/1.2204979.

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An efficient semi-implicit numerical method is developed for solving the detailed chemical kinetic source terms in internal combustion (IC) engine simulations. The detailed chemistry system forms a group of coupled stiff ordinary differential equations (ODEs), which presents a very stringent time-step limitation when solved by standard explicit methods, and is computationally expensive when solved by iterative implicit methods. The present numerical solver uses a stiffly stable noniterative semi-implicit method. The formulation of numerical integration exploits the physical requirement that the species density and specific internal energy in the computational cells must be non-negative, so that the Lipschitz time-step constraint is not present and the computation time step can be orders of magnitude larger than that possible in standard explicit methods. The solver exploits the characteristics of the stiffness of the ODEs by using a sequential sort algorithm that ranks an approximation to the dominant eigenvalues of the system to achieve maximum accuracy. Subcycling within the chemistry solver routine is applied for each computational cell in engine simulations, where the subcycle time step is dynamically determined by monitoring the rate of change of concentration of key species, which have short characteristic time scales and are also important to the chemical heat release. The chemistry solver is applied in the KIVA-3V code to diesel engine simulations. Results are compared to those using the CHEMKIN package, which uses the VODE implicit solver. Good agreement was achieved for a wide range of engine operating conditions, and 40-70% CPU time savings were achieved by the present solver compared to the standard CHEMKIN.

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Purwiandono, Gani. "Development of Computational-based Visualization Method in Physical Chemistry Practical Course." International Journal of Science and Applied Science: Conference Series 2, no. 1 (December 10, 2017): 114. http://dx.doi.org/10.20961/ijsascs.v2i1.16692.

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<p class="Abstract">Study on the development of computational-based visualization method in Physical Chemistry practical course has been carried out. The study was carried out by combining the conventional method and the visualization using the software. This combination class then was compared to the conventional class of the practical course. The cognitive evaluation showed that the distribution of students’ understanding for the supporting theory of the practical course was not significantly different. The students had relatively the same level of understanding regarding the supporting theory. The evaluation of learning outcomes and the distribution of final grade showed that the class which combined the conventional and visualization method gave a positive result in the learning process</p>

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Zhang, Ruiqing. "Analysis of mathematical methods and principles of molecular dynamics and monte carlo method." Theoretical and Natural Science 5, no. 1 (May 25, 2023): 395–401. http://dx.doi.org/10.54254/2753-8818/5/20230252.

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In this era, molecular dynamics and Monte Carlo methods have become the primary simulation methods. With the emergence of computer simulation research methods, it has been possible to solve the sizeable computational volume and some other problems in the simulation process. At present, molecular dynamics simulations have taken an essential place in the substantial computational system and have a remarkable ability to solve multi-body problems. Therefore, researchers widely use it in many fields such as physics, chemistry, and materials science. Meanwhile, the Monte Carlo method is also a very effective statistical simulation method. This method can far surpass ordinary integration in efficiency with guaranteed computational accuracy. Furthermore, the derived kinetic Monte Carlo method can simulate and study dynamics problems. It can be seen that both simulation methods play an vital role in various disciplines. Therefore, it is very significant to understand the mathematical principles behind them and to know their advantages and disadvantages.

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Filho, Eloi Alves da Silva, Fabricio Uliana, Stêner Romanel Ambrozio, Cleverton Oliveira, Renan Martin, and Arlan da Silva Gonçalves. "COMPUTATIONAL STUDY OF ORGANIC COMPOUNDS – AN APPLICATION FOR LEARNING IN CHEMISTRY." Revista Ifes Ciência 5, no. 1 (November 22, 2019): 257–66. http://dx.doi.org/10.36524/ric.v5i1.293.

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Organic chemistry is a theme not so easy to understand by undergraduating students. The motivation of this work was carried out computational study of three different molecules by molecular modeling using classic and semi-empirical methods besides open-source softwares. The optimized structures were visualized through 3D representations which made the study more understanding. Physical chemistry properties were extracted from all molecules. For the molecule one there was good correlation between the calculation methods. For the molecule two and more complex structures like molecule three and four there was possible influence of steric effect showing that each method is applicable for each study system.

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Prakoso, Nurcahyo Iman, Lukman Hakim, and Nuri Hidayati. "Molecular Modeling of An Analog Of Curcumin Compounds Pentagamavunon-0 (PGV-0) And Pentagamavunon-1 (PGV-1) Through Computational Chemistry Methods Ab-Initio HF/4-31G." Chemical 3, no. 1 (December 31, 2017): 28–39. http://dx.doi.org/10.20885/ijcr.vol2.iss1.art4.

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Breast cancer is the second largest number of cancer cases in Indonesia, after cervical cancer. The growth of these cancer cells can be prevented with compounds Pentagamavunon-0 (PGV-0) and Pentagamavunon-1 (PGV-1). This compound is an analog of curcumin compounds that have anti breast cancer activity. Modeling the structure of compound PGV-0 and PGV-1 through computational chemistry methods Ab-initio HF/4-31G could be used to predict the geometry and structure elucidation spectra associated with pharmacological activity such as anticancer compounds theoretically.This research involves modeling the structures and spectra prediction calculation compounds PGV-0 and PGV-1 by computational chemistry methods Ab-initio HF/4-31G, using Gaussian03W. The result using Ab-initio HF/4-31G method then compared with data from experimental geometry and the results of calculations with AM1.The results showed that computational chemistry methods Ab-initio HF/4-31G calculations give better results for modeling the structure compared semiempirik method AM1.

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Aithal, S. M. "Charged Species Concentration in Combusting Mixtures Using Equilibrium Chemistry." Journal of Combustion 2018 (October 4, 2018): 1–11. http://dx.doi.org/10.1155/2018/9047698.

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Ionization in flames is of interest in the design and development of modern combustion devices. The identity and concentration of various charged species in reacting mixtures can play an important role in the diagnostics and control of such devices. Simplified chemistry computations that provide good estimates of ionic species in complex flow-fields can be used to model turbulent reacting flows in various combustion devices, greatly reducing the required computational resources for design and development studies. A critical assessment of the use of the equilibrium chemistry method to compute charged species concentration in combusting mixtures under various temperatures, pressures, and thermal disequilibrium conditions is presented. The use of equilibrium chemistry to compute charged species concentrations in propane-air mixtures performed by Calcote and King has been extended. A more accurate computational methodology that includes the effect of negative ions, chemi-ions (H3O+ and CHO+), and thermal nonequilibrium was investigated to evaluate the suitability of equilibrium computations for estimating charged species concentrations in reacting mixtures. The results show that equilibrium computations which include the effects of H3O+ and elevated electron temperatures can indeed explain the levels of ion concentrations observed in laboratory flame experiments under lean and near-stoichiometric conditions. Furthermore, under engine-like conditions at higher temperatures and pressures, equilibrium computations can be used to obtain useful estimates of charged species concentrations in modern combustion devices.

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Werstiuk, Nick Henry, and David Andrew. "A study of thermodynamic acidities of enols with the semiempirical computational method AM1." Canadian Journal of Chemistry 68, no. 8 (August 1, 1990): 1467–69. http://dx.doi.org/10.1139/v90-224.

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Using the semiempirical computational method AM1 we have computed the enthalpies of ionization of enols 1–21 and correlated these values with solution and estimated pKa's. From this initial study it appears that, in general, it is possible to predict the pK's of acyclic enols within ± 1 pKa unit. On the basis of this correlation we predict the pKa's of 1-hydroxy-1,3-butadiene (3-butenal enol) (9.7) and 1,1-difluoroacetone enol (9.6) and suggest that the previously estimated pKa of 1,1-dichloroacetone enol (6.2) is low by approximately 3 pK units. We find computationally (this has been established experimentally) that the Z-enol of phenylacetaldehyde is less acidic than the E-enol. Keywords: enols, acidities, computational studies, AM1.

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Zhang, Mingjie, Jiangang Yang, Wanfu Zhang, and Qianlei Gu. "Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals." Applied Sciences 11, no. 9 (May 7, 2021): 4237. http://dx.doi.org/10.3390/app11094237.

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The elliptical orbit whirl model is widely used to identify the frequency-dependent rotordynamic coefficients of annular seals. The existing solution technique of an elliptical orbit whirl model is the transient computational fluid dynamics (CFD) method. Its computational time is very long. For rapid computation, this paper proposes the orbit decomposition method. The elliptical whirl orbit is decomposed into the forward and backward circular whirl orbits. Under small perturbation circumstances, the fluid-induced forces of the elliptical orbit model can be obtained by the linear superposition of the fluid-induced forces arising from the two decomposed circular orbit models. Due to that the fluid-induced forces of circular orbit, the model can be calculated with the steady CFD method, and the transient computations can be replaced with steady ones when calculating the elliptical orbit whirl model. The computational time is significantly reduced. To validate the present method, its rotordynamic results are compared with those of the transient CFD method and experimental data. Comparisons show that the present method can accurately calculate the rotordynamic coefficients. Elliptical orbit parameter analysis reveals that the present method is valid when the whirl amplitude is less than 20% of seal clearance. The effect of ellipticity on rotordynamic coefficients can be ignored.

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Vigren, Erik. "Analytic model of comet ionosphere chemistry." Astronomy & Astrophysics 616 (August 2018): A59. http://dx.doi.org/10.1051/0004-6361/201832704.

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Context. We consider a weakly to moderately active comet and make the following simplifying assumptions: (i) The partial ionization frequencies are constant throughout the considered part of the coma. (ii) All species move radially outward with the same constant speed. (iii) Ion-neutral reactions affect the chemical composition of the ions, but ion removal through dissociative recombination with free electrons is negligible. Aims. We aim to derive an analytical model for the radial variation of the abundances of various cometary ions. Methods. We present two methods for retrieving the ion composition as a function of r. The first method, which has previously been used frequently, solves a series of coupled differential equations. The new method introduced here is based on probabilistic arguments and is analytical in nature. Results. For a pure H2O coma, the resulting closed-form expressions yield results that are identical to the standard method, but are computationally much less expensive. Conclusions. In addition to the computational simplicity, the analytical model provides insight into how the various abundances depend on parameters such as comet production rate, outflow speed, and reaction rate coefficients. It can also be used to investigate limiting cases. It cannot easily be extended to account for a radially varying flow speed or dissociative recombination in the way a code based on numerical integrations can.

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Malau, Nur Aisah, and Asep Wahyu Nugraha. "Study Of Energy And Structure On Intermolecular Interactions In Organic Solvents Using Computational Chemistry Method." Indonesian Journal of Chemical Science and Technology (IJCST) 4, no. 2 (August 23, 2021): 79. http://dx.doi.org/10.24114/ijcst.v4i2.27601.

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This study aims to determine the amount of energy, the difference in energy, the relationship between the amount of energy and the distance between compounds, and the interactions that occur in organic solvent molecules using computational chemistry methods. In determining the amount of energy and interactions that occur, computational chemistry calculations are used using NWChem software version 6.6 with the DFT method with the B3LYP hybrid function/basis set 6-31G, the calculation results are visualized using Jmol software. The results of calculations with large computations of energy for benzene are -230.62447487 KJ/mol, ethanol -154.01322923 KJ/mol, methanol -114.98816558 KJ/mol, hexane are -235.27001385 KJ/mol. Mixture of benzene and ethanol in a ratio of 1 : 1 -384.63823964 KJ/mol, 1 : 2 538.66009762 KJ/mol , and 2 : 1 - 615.26607558 KJ/mol. A mixture of benzene and methanol in a ratio of 1 : 1 -345.61255299 KJ/mol, 1 : 2 - 460.60826254 KJ/mol, and 2 : 1 -576.24044425 KJ/mol, a mixture of hexane and ethanol in a ratio of 1 : 1 - 389.28477268 KJ/mol, 1 : 2 -543.29869234 KJ/mol and 2 : 1 -624.55723290 KJ/mol. A mixture of hexane and methanol at a ratio of 1 : 1 -350.25984691 KJ/mol, 1 : 2 -465.26041654 KJ/mol and 2 : 1 -585.53373886 KJ/mole. The difference in energy is the most in a mixture of benzene and ethanol in a ratio of 1 : 2 -0.00916429 K /mol, in a mixture of benzene and methanol in a ratio of 1 : 2 - 0.00745651 KJ/mol, a mixture of hexane and ethanol in a ratio of 2 : 1 -0.00397597 KJ/mol, and a mixture of hexane and methanol in a ratio of 1 : 2 - 0.01407153 KJ/mol. and there is no relationship between the magnitude of the interaction energy of the mixture with the distance between the molecules.

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Pastorczak, Ewa, and Katarzyna Pernal. "ERPA–APSG: a computationally efficient geminal-based method for accurate description of chemical systems." Physical Chemistry Chemical Physics 17, no. 14 (2015): 8622–26. http://dx.doi.org/10.1039/c4cp05958a.

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Ling, Lixia, Maohong Fan, Baojun Wang, and Riguang Zhang. "Application of computational chemistry in understanding the mechanisms of mercury removal technologies: a review." Energy & Environmental Science 8, no. 11 (2015): 3109–33. http://dx.doi.org/10.1039/c5ee02255j.

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Huzinaga, Sigeru. "1994 Polanyi Award Lecture Concept of active electrons in chemistry." Canadian Journal of Chemistry 73, no. 5 (May 1, 1995): 619–28. http://dx.doi.org/10.1139/v95-080.

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The notion of division between active and dormant electrons has been well received and widely used in the chemists' way of thinking. The core–valence separation in atoms is the best-known example. This paper describes a theoretical and computational method called the model potential method, which deals only with active electrons in molecular and solid state calculations. The method is capable of reaching computational accuracy of testing the validity of the separation of active and dormant electrons in individual cases. Keywords: separability of electrons, model potential method, valence orbitals, relativistic effects.

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KODAMA, Koichi, Arwan SYAH, Kazutomo KAWAGUCHI, Toru MATSUI, Hidemi NAGAO, and Yasuteru SHIGETA. "The Study of the Octanol-Water Partition Coefficient by the Computational Chemistry Method." Journal of Computer Chemistry, Japan 18, no. 5 (2019): 241–43. http://dx.doi.org/10.2477/jccj.2019-0047.

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Nakamura, K., T. Nakamoto, and T. Moriizumi. "Prediction of quartz crystal microbalance gas sensor responses using a computational chemistry method." Sensors and Actuators B: Chemical 61, no. 1-3 (December 1999): 6–11. http://dx.doi.org/10.1016/s0925-4005(99)00071-4.

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Amirjani, Amirmostafa, and S. K. Sadrnezhaad. "Computational electromagnetics in plasmonic nanostructures." Journal of Materials Chemistry C 9, no. 31 (2021): 9791–819. http://dx.doi.org/10.1039/d1tc01742j.

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A comprehensive review on the ability of finite difference time domain (FDTD), finite element method (FEM), discrete dipole approximation (DDA), and boundary element method (BEM) for simulating the optical properties of plasmonic nanostructures.

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Stelz-Sullivan, Eleanor J., Barbara Marchetti, and Tolga Karsili. "Simulating Electronic Absorption Spectra of Atmospherically Relevant Molecules: A Systematic Assignment for Enhancing Undergraduate STEM Education." Education Sciences 12, no. 4 (April 1, 2022): 252. http://dx.doi.org/10.3390/educsci12040252.

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Computational and atmospheric chemistry are two important branches of contemporary chemistry. With the present topical nature of climate change and global warming, it is more crucial than ever that students are aware of and exposed to atmospheric chemistry, with an emphasis on how modeling may aid in understanding how atmospherically relevant chemical compounds interact with incoming solar radiation. Nonetheless, computational and atmospheric chemistry are under-represented in most undergraduate chemistry curricula. In this manuscript, we describe a simple and efficient method for simulating the electronic absorption spectral profiles of atmospherically relevant molecules that may be utilized in an undergraduate computer laboratory. The laboratory results give students hands-on experience in computational and atmospheric chemistry, as well as electronic absorption spectroscopy.

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Raji, Kochandra, and Choondal B. Sobhan. "Simulation and modeling of carbon nanotube synthesis: current trends and investigations." Nanotechnology Reviews 2, no. 1 (February 1, 2013): 73–105. http://dx.doi.org/10.1515/ntrev-2012-0038.

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AbstractA review of significant investigations reported on simulating the nucleation and growth processes of carbon nanotubes (CNTs) using different modeling techniques is presented here. Special emphasis is given to the chemical vapor deposition method, being the cheapest and most versatile of the fabrication methods. The modeling methods involve the conventional computational fluid dynamics approaches as well as discrete computation techniques. Some in-house investigations utilizing chemical kinetic modeling and discrete computations to predict the growth of CNTs using the chemical vapor deposition method are also discussed. The modeling and simulation techniques reviewed here are expected to assist in the design of chirality-specific single-walled CNT synthesis systems.

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Chong, Song‐Ho, and Sihyun Ham. "A New Computational Method for Protein–Ligand Binding Thermodynamics." Bulletin of the Korean Chemical Society 40, no. 2 (February 2019): 180–85. http://dx.doi.org/10.1002/bkcs.11681.

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Yonchev, Dimitar, Martin Vogt, and Jürgen Bajorath. "Compound optimization monitor (COMO) method for computational evaluation of progress in medicinal chemistry projects." Future Drug Discovery 1, no. 2 (October 1, 2019): FDD15. http://dx.doi.org/10.4155/fdd-2019-0016.

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Aim: Development of a new, practically applicable computational method to monitor progress in lead optimization. Computational approaches that aid in compound optimization are discussed and the Compound Optimization Monitor (COMO) method is introduced and put into scientific context. Methodology & calculations: The methodological concept and the COMO scoring scheme are described in detail. Results & discussions: Calculation parameters are evaluated, and profiling results reported for an ensemble of analog series. Future perspective: The dual role of virtual analogs as diagnostic tools for progress evaluation and as potential candidates for lead optimization is discussed. In light of this dual role, interfacing COMO with machine learning for compound activity prediction and prioritization of candidates is highlighted as a future research objective.

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Alluri, Venkata Sai Priyatham Varma, William (Hoang Chi Hieu) Nguyen, and Amr Henni. "Determination of the Dissociation Constants (pKa) of Eight Amines of Importance in Carbon Capture: Computational Chemistry Calculations, and Artificial Neural Network Models." Liquids 3, no. 2 (May 20, 2023): 214–45. http://dx.doi.org/10.3390/liquids3020016.

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This work focuses on determining the dissociation constants (pKa) of eight amines, namely, 3-(Diethylamino) propylamine, 1,3-Diaminopentane, 3-Butoxypropylamine, 2-(Methylamino) ethanol, Bis(2-methoxyethyl) amine, α-Methylbenzylamine, 2-Aminoheptane, and 3-Amino-1-phenylbutane, within temperatures ranging from 293.15 K to 323.15 K. The thermodynamic properties of the protonated reactions were regressed from the pKa work. In addition, the protonated order of both 3-(Diethylamino) propylamine and 1,3-Diaminopentane were determined using computational chemistry methods owing to their unsymmetrical structures. In addition to the experimental methods, the dissociation constants at the standard temperature (298.15 K) were also estimated using group functional models (paper–pencil) and computational methods. The computational methods include COSMO-RS and computational chemistry calculations. An artificial neural network (ANN) method was employed to model the data by collecting and combining the experimental properties to estimate the missing pKa values. Although the ANN models can provide acceptable results, they depend on the availability of the data. Instead of using the experimental properties, they were generated using software such as Aspen Plus or CosmothermX. The simulated ANN model can also provide very good fits to the experimental constant values.

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Wadi, Basil, Ayub Golmakani, Tohid N.Borhani, Vasilije Manovic, and Seyed Ali Nabavi. "Molecular Simulation Techniques as Applied to Silica and Carbon-Based Adsorbents for Carbon Capture." Energies 16, no. 13 (June 28, 2023): 5013. http://dx.doi.org/10.3390/en16135013.

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There has been ongoing interest in research to mitigate climate change through carbon capture (CC) by adsorption. This guideline is meant to introduce computational chemistry techniques in CC by applying them to mesoporous structures and disordered morphologies. The molecular simulation techniques presented here use examples of literature studies on silica and carbon-based adsorbents. An initial summary of molecular simulation techniques and concepts is first presented. This is followed by a section on molecular simulation applications in mesoporous amorphous silica, both functionalized and not. Novel strategies to validate and output useful results are discussed, specifically when modelling chemisorption. The use of computational chemistry to build upon experimental results is reviewed, and a similar summation is presented for carbon-based adsorbents. The final section provides a short review of computational chemistry methods in novel applications and highlights potential complications. Computational chemistry techniques provide a streamlined method of gathering data across a range of conditions. Alongside experimental studies, these techniques can provide valuable information on underlying molecular mechanisms. This paper aims to be a starting point for navigating these numerical methods by providing an initial understanding of how these techniques can be applied to carbon capture while clarifying the current and inherent limitations present.

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James, S., M. S. Anand, M. K. Razdan, and S. B. Pope. "In Situ Detailed Chemistry Calculations in Combustor Flow Analyses." Journal of Engineering for Gas Turbines and Power 123, no. 4 (March 1, 1999): 747–56. http://dx.doi.org/10.1115/1.1384878.

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In the numerical simulation of turbulent reacting flows, the high computational cost of integrating the reaction equations precludes the inclusion of detailed chemistry schemes, therefore reduced reaction mechanisms have been the more popular route for describing combustion chemistry, albeit at the loss of generality. The in situ adaptive tabulation scheme (ISAT) has significantly alleviated this problem by facilitating the efficient integration of the reaction equations via a unique combination of direct integration and dynamic creation of a look-up table, thus allowing for the implementation of detailed chemistry schemes in turbulent reacting flow calculations. In the present paper, the probability density function (PDF) method for turbulent combustion modeling is combined with the ISAT in a combustor design system, and calculations of a piloted jet diffusion flame and a low-emissions premixed gas turbine combustor are performed. It is demonstrated that the results are in good agreement with experimental data and computations of practical turbulent reacting flows with detailed chemistry schemes are affordable.

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Zhang, Yi, Yiduo Xiong, and Yi Xiao. "3dDNA: A Computational Method of Building DNA 3D Structures." Molecules 27, no. 18 (September 13, 2022): 5936. http://dx.doi.org/10.3390/molecules27185936.

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Considerable progress has been made in the prediction methods of 3D structures of RNAs. In contrast, no such methods are available for DNAs. The determination of 3D structures of the latter is also increasingly needed for understanding their functions and designing new DNA molecules. Since the number of experimental structures of DNA is limited at present, here, we propose a computational and template-based method, 3dDNA, which combines DNA and RNA template libraries to predict DNA 3D structures. It was benchmarked on three test sets with different numbers of chains, and the results show that 3dDNA can predict DNA 3D structures with a mean RMSD of about 2.36 Å for those with one or two chains and fewer than 4 Å with three or more chains.

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D’Alessio, Giuseppe, Alberto Cuoci, Gianmarco Aversano, Mauro Bracconi, Alessandro Stagni, and Alessandro Parente. "Impact of the Partitioning Method on Multidimensional Adaptive-Chemistry Simulations." Energies 13, no. 10 (May 18, 2020): 2567. http://dx.doi.org/10.3390/en13102567.

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The large number of species included in the detailed kinetic mechanisms represents a serious challenge for numerical simulations of reactive flows, as it can lead to large CPU times, even for relatively simple systems. One possible solution to mitigate the computational cost of detailed numerical simulations, without sacrificing their accuracy, is to adopt a Sample-Partitioning Adaptive Reduced Chemistry (SPARC) approach. The first step of the aforementioned approach is the thermochemical space partitioning for the generation of locally reduced mechanisms, but this task is often challenging because of the high-dimensionality, as well as the high non-linearity associated to reacting systems. Moreover, the importance of this step in the overall approach is not negligible, as it has effects on the mechanisms’ level of chemical reduction and, consequently, on the accuracy and the computational speed-up of the adaptive simulation. In this work, two different clustering algorithms for the partitioning of the thermochemical space were evaluated by means of an adaptive CFD simulation of a 2D unsteady laminar flame of a nitrogen-diluted methane stream in air. The first one is a hybrid approach based on the coupling between the Self-Organizing Maps with K-Means (SKM), and the second one is the Local Principal Component Analysis (LPCA). Comparable results in terms of mechanism reduction (i.e., the mean number of species in the reduced mechanisms) and simulation accuracy were obtained for both the tested methods, but LPCA showed superior performances in terms of reduced mechanisms uniformity and speed-up of the adaptive simulation. Moreover, the local algorithm showed a lower sensitivity to the training dataset size in terms of the required CPU-time for convergence, thus also being optimal, with respect to SKM, for massive dataset clustering tasks.

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Abaffy, József, and Szabina Fodor. "ABS-Based Direct Method for Solving Complex Systems of Linear Equations." Mathematics 9, no. 19 (October 8, 2021): 2527. http://dx.doi.org/10.3390/math9192527.

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Efficient solution of linear systems of equations is one of the central topics of numerical computation. Linear systems with complex coefficients arise from various physics and quantum chemistry problems. In this paper, we propose a novel ABS-based algorithm, which is able to solve complex systems of linear equations. Theoretical analysis is given to highlight the basic features of our new algorithm. Four variants of our algorithm were also implemented and intensively tested on randomly generated full and sparse matrices and real-life problems. The results of numerical experiments reveal that our ABS-based algorithm is able to compute the solution with high accuracy. The performance of our algorithm was compared with a commercially available software, Matlab’s mldivide (\) algorithm. Our algorithm outperformed the Matlab algorithm in most cases in terms of computational accuracy. These results expand the practical usefulness of our algorithm.

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Hori, Kenzi, Hirotaka Sadatomi, Katsuhiko Okano, Michinori Sumimoto, Atsuo Miyamoto, Saori Hayashi, and Hidetoshi Yamamoto. "An Attempt Method for Developing New Synthetic Routes by Fusing Computational Chemistry and Chemoinformatics:." Journal of Computer Aided Chemistry 8 (2007): 12–18. http://dx.doi.org/10.2751/jcac.8.12.

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Enisoğlu Atalay, Vildan, and İbrahim Barış Ölüç. "Antioxidant activity of the hazelnut plant determination by computational chemistry methods." Main Group Chemistry 19, no. 4 (January 23, 2021): 273–82. http://dx.doi.org/10.3233/mgc-200960.

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Nowadays, it is known that the species defined as free radicals in our body increase due to the change in our eating / drinking habits, physical activities and environmental conditions. Free radicals cause especially canser and diseases affecting many systems such as nervous system, cardiovascular system and digestive system. The formation of free radicals causes cell / tissue damage or cell deaths that occur as a result of oxidative balance disruption due to the insufficient antioxidants defined as oxidative stress. The purpose of this study is to determine the activity ranking of the compounds that give antioxidant properties to hazelnut plants by using quantum chemistry methods and to determine which hydroxyl groups cause the activity. In the antioxidant activity calculations, HAT, SET-PT and SPLET mechanisms are optimized with DFT//M062X/6-311++G(d,p) method, and single point energy as well as the EHOMO-ELUMO values were obtained with the Gaussian09 program in three different phases: gas, ethanol and water. According to the results, Riboflavin compound has been found to have the highest antioxidant potential and it was found that the antioxidant capacity of the compound originated from OH group at O4 position.

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Saudi, Azali, and A’qilah Ahmad Dahalan. "An Efficient Red–Black Skewed Modified Accelerated Arithmetic Mean Iterative Method for Solving Two-Dimensional Poisson Equation." Symmetry 14, no. 5 (May 12, 2022): 993. http://dx.doi.org/10.3390/sym14050993.

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This paper presents the extended variants to the established two-stage Arithmetic Mean (AM) method known as the Modified Accelerated Arithmetic Mean (MAAM) and Skewed Modified Accelerated Arithmetic Mean (SkMAAM) methods to solve the two-dimensional elliptic problem. The existing two-stage AM and its skewed variants apply one weighted parameter for the computation of nodes in Levels 1 and 2. The suggested MAAM and SkMAAM methods employ red–black ordering with two different weighted parameters and an additional two distinct accelerated parameters for red and black nodes, respectively. By carefully choosing optimum parameter values, the proposed MAAM and SkMAAM improve the computational execution of the algorithm. With red–black ordering, the computational molecules of red and black nodes are symmetrical, in which the computation of red nodes applies the updated values of their four neighbouring black nodes and vice versa. These symmetrical computational molecules of red and black nodes can be seen for the modified variants MAM and MAAM, and their corresponding skewed variants SkMAM and SkMAAM. The proposed MAAM and SkMAAM methods are compared to the existing AM and Modified AM (MAM) and their corresponding skewed variants, namely the Skewed AM (SkAM) and Skewed MAM (SkMAM) methods. The performance of the newly proposed MAAM and SkMAAM methods is compared against the existing methods in terms of computational complexity and actual execution time. It is shown in the simulation results that the skewed variants are superior to their corresponding regular variants, in which the SkMAAM method gives the best performance.

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Ahn, Jung Min, Hongtae Kim, Jae Gab Cho, Taegu Kang, Yong-seok Kim, and Jungwook Kim. "Parallelization of a 3-Dimensional Hydrodynamics Model Using a Hybrid Method with MPI and OpenMP." Processes 9, no. 9 (August 30, 2021): 1548. http://dx.doi.org/10.3390/pr9091548.

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Process-based numerical models developed to perform hydraulic/hydrologic/water quality analysis of watersheds and rivers have become highly sophisticated, with a corresponding increase in their computation time. However, for incidents such as water pollution, rapid analysis and decision-making are critical. This paper proposes an optimized parallelization scheme to reduce the computation time of the Environmental Fluid Dynamics Code-National Institute of Environmental Research (EFDC-NIER) model, which has been continuously developed for water pollution or algal bloom prediction in rivers. An existing source code and a parallel computational code with open multi-processing (OpenMP) and a message passing interface (MPI) were optimized, and their computation times compared. Subsequently, the simulation results for the existing EFDC model and the model with the parallel computation code were compared. Furthermore, the optimal parallel combination for hybrid parallel computation was evaluated by comparing the simulation time based on the number of cores and threads. When code parallelization was applied, the performance improved by a factor of approximately five compared to the existing source code. Thus, if the parallel computational source code applied in this study is used, urgent decision-making will be easier for events such as water pollution incidents.

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Shee, James, John L. Weber, David R. Reichman, Richard A. Friesner, and Shiwei Zhang. "On the potentially transformative role of auxiliary-field quantum Monte Carlo in quantum chemistry: A highly accurate method for transition metals and beyond." Journal of Chemical Physics 158, no. 14 (April 14, 2023): 140901. http://dx.doi.org/10.1063/5.0134009.

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Approximate solutions to the ab initio electronic structure problem have been a focus of theoretical and computational chemistry research for much of the past century, with the goal of predicting relevant energy differences to within “chemical accuracy” (1 kcal/mol). For small organic molecules, or in general, for weakly correlated main group chemistry, a hierarchy of single-reference wave function methods has been rigorously established, spanning perturbation theory and the coupled cluster (CC) formalism. For these systems, CC with singles, doubles, and perturbative triples is known to achieve chemical accuracy, albeit at [Formula: see text]( N7) computational cost. In addition, a hierarchy of density functional approximations of increasing formal sophistication, known as Jacob’s ladder, has been shown to systematically reduce average errors over large datasets representing weakly correlated chemistry. However, the accuracy of such computational models is less clear in the increasingly important frontiers of chemical space including transition metals and f-block compounds, in which strong correlation can play an important role in reactivity. A stochastic method, phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC), has been shown to be capable of producing chemically accurate predictions even for challenging molecular systems beyond the main group, with relatively low [Formula: see text]( N3 − N4) cost and near-perfect parallel efficiency. Herein, we present our perspectives on the past, present, and future of the ph-AFQMC method. We focus on its potential in transition metal quantum chemistry to be a highly accurate, systematically improvable method that can reliably probe strongly correlated systems in biology and chemical catalysis and provide reference thermochemical values (for future development of density functionals or interatomic potentials) when experiments are either noisy or absent. Finally, we discuss the present limitations of the method and where we expect near-term development to be most fruitful.

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Datta, B. P. "Polynomial method of molecular isotopic abundance calculations: a computational note." Rapid Communications in Mass Spectrometry 11, no. 16 (October 30, 1997): 1767–74. http://dx.doi.org/10.1002/(sici)1097-0231(19971030)11:16<1767::aid-rcm23>3.0.co;2-d.

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Canedo, M. M., and J. L. González-Hernández. "KINMODEL (AGDC): a multipurpose computational method for kinetic treatment." Journal of Mathematical Chemistry 49, no. 1 (September 26, 2010): 163–84. http://dx.doi.org/10.1007/s10910-010-9733-z.

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YUAN, Xigang, and Guocong YU. "Computational Mass Transfer Method for Chemical Process Simulation." Chinese Journal of Chemical Engineering 16, no. 4 (January 2008): 497–502. http://dx.doi.org/10.1016/s1004-9541(08)60113-5.

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Dührkop, Kai. "Computational methods for small molecule identification." it - Information Technology 61, no. 5-6 (October 25, 2019): 285–92. http://dx.doi.org/10.1515/itit-2019-0033.

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Abstract Identification of small molecules remains a central question in analytical chemistry, in particular for natural product research, metabolomics, environmental research, and biomarker discovery. Mass spectrometry is the predominant technique for high-throughput analysis of small molecules. But it reveals only information about the mass of molecules and, by using tandem mass spectrometry, about the mass of molecular fragments. Automated interpretation of mass spectra is often limited to searching in spectral libraries, such that we can only dereplicate molecules for which we have already recorded reference mass spectra. In my thesis “Computational methods for small molecule identification” we developed SIRIUS, a tool for the structural elucidation of small molecules with tandem mass spectrometry. The method first computes a hypothetical fragmentation tree using combinatorial optimization. By using a Bayesian statistical model, we can learn parameters and hyperparameters of the underlying scoring directly from data. We demonstrate that the statistical model, which was fitted on a small dataset, generalizes well across many different datasets and mass spectrometry instruments. In a second step the fragmentation tree is used to predict a molecular fingerprint using kernel support vector machines. The predicted fingerprint can be searched in a structure database to identify the molecular structure. We demonstrate that our machine learning model outperforms all other methods for this task, including its predecessor FingerID. SIRIUS is available as commandline tool and as user interface. The molecular fingerprint prediction is implemented as web service and receives over one million requests per month.

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Tolpadi, A. K., I. Z. Hu, S. M. Correa, and D. L. Burrus. "Coupled Lagrangian Monte Carlo PDF–CFD Computation of Gas Turbine Combustor Flowfields With Finite-Rate Chemistry." Journal of Engineering for Gas Turbines and Power 119, no. 3 (July 1, 1997): 519–26. http://dx.doi.org/10.1115/1.2817015.

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A coupled Lagrangian Monte Carlo Probability Density Function (PDF)-Eulerian Computational Fluid Dynamics (CFD) technique is presented for calculating steady three-dimensional turbulent reacting flow in a gas turbine combustor. PDF transport methods model turbulence-combustion interactions more accurately than conventional turbulence models with an assumed shape PDF. The PDF transport equation was solved using a Lagrangian particle tracking Monte Carlo (MC) method. The PDF modeled was over composition only. This MC module has been coupled with CONCERT, which is a fully elliptic three-dimensional body-fitted CFD code based on pressure correction techniques. In an earlier paper (Tolpadi et al., 1995), this computational approach was described, but only fast chemistry calculations were presented in a typical aircraft engine combustor. In the present paper, reduced chemistry schemes were incorporated into the MC module that enabled the modeling of finite rate effects in gas turbine flames and therefore the prediction of CO and NOx emissions. With the inclusion of these finite rate effects, the gas temperatures obtained were also more realistic. Initially, a two scalar scheme was implemented that allowed validation against Raman data taken in a recirculating bluff body stabilized CO/H2/N2-air flame. Good agreement of the temperature and major species were obtained. Next, finite rate computations were performed in a single annular aircraft engine combustor by incorporating a simple three scalar reduced chemistry scheme for Jet A fuel. This three scalar scheme was an extension of the two scalar scheme for CO/H2/N2 fuel. The solutions obtained using the present approach were compared with those obtained using the fast chemistry PDF transport approach (Tolpadi et al., 1995) as well as the presumed shape PDF method. The calculated exhaust gas temperature using the finite rate model showed the best agreement with measurements made by a thermocouple rake. In addition, the CO and NOx emission indices were also computed and compared with corresponding data.

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Devaurs, Didier, Dinler Antunes, and Lydia Kavraki. "Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data." International Journal of Molecular Sciences 19, no. 11 (October 31, 2018): 3406. http://dx.doi.org/10.3390/ijms19113406.

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Both experimental and computational methods are available to gather information about a protein’s conformational space and interpret changes in protein structure. However, experimentally observing and computationally modeling large proteins remain critical challenges for structural biology. Our work aims at addressing these challenges by combining computational and experimental techniques relying on each other to overcome their respective limitations. Indeed, despite its advantages, an experimental technique such as hydrogen-exchange monitoring cannot produce structural models because of its low resolution. Additionally, the computational methods that can generate such models suffer from the curse of dimensionality when applied to large proteins. Adopting a common solution to this issue, we have recently proposed a framework in which our computational method for protein conformational sampling is biased by experimental hydrogen-exchange data. In this paper, we present our latest application of this computational framework: generating an atomic-resolution structural model for an unknown protein state. For that, starting from an available protein structure, we explore the conformational space of this protein, using hydrogen-exchange data on this unknown state as a guide. We have successfully used our computational framework to generate models for three proteins of increasing size, the biggest one undergoing large-scale conformational changes.

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Kunimoto, Ryo, Tomoyuki Miyao, and Jürgen Bajorath. "Computational method for estimating progression saturation of analog series." RSC Advances 8, no. 10 (2018): 5484–92. http://dx.doi.org/10.1039/c7ra13748f.

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Chemical space view of an analog series. Shown are inactive (red) and active (blue) analogs together with virtual candidate compounds (green) available to expand the series. Chemical neighborhoods of analogs are depicted in gray.

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Dalla, Carlos Eduardo Rambalducci, Wellington Betencurte da Silva, Júlio Cesar Sampaio Dutra, and Marcelo José Colaço. "A comparative study of gradient-based and meta-heuristic optimization methods using Griewank benchmark function/ Um estudo comparativo de métodos de otimização baseados em gradientes e meta-heurísticos usando a função de benchmark do Griewank." Brazilian Journal of Development 7, no. 6 (June 7, 2021): 55341–50. http://dx.doi.org/10.34117/bjdv7n6-102.

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Optimization methods are frequently applied to solve real-world problems such, engineering design, computer science, and computational chemistry. This paper aims to compare gradient-based algorithms and the meta-heuristic particle swarm optimization to minimize the multidimensional benchmark Griewank function, a multimodal function with widespread local minima. Several approaches of gradient-based methods such as steepest descent, conjugate gradient with Fletcher-Reeves and Polak-Ribiere formulations, and quasi-Newton Davidon-Fletcher-Powell approach were compared. The results presented showed that the meta-heuristic method is recommended for function with this behavior because is no needed prior information of the search space. The performance comparison includes computation time and convergence of global and local optimum.

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Yu, Jianghong, Zhengbao Lei, Qishui Yao, and Fenglin Zhou. "A Sigmoidal and Distance Combined Transformation Method for Nearly Singular Integral on Asymmetric Patch." Symmetry 12, no. 6 (June 9, 2020): 983. http://dx.doi.org/10.3390/sym12060983.

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This paper is devoted to developing a new computational method for nearly singular integral computation in the application of the boundary element method for the analysis of thin-shell-like structures in mechanical engineering. Based on the traditional distance transformation method, a sigmoidal transformation method is introduced to further cluster the integral points around the source point with respect to the circumferential direction. The combined method provides accurate results without employing a large quantity of integral points. Numerical examples demonstrate that the computational accuracy and efficiency of the proposed method is significantly higher than that of the traditional single distance transformation method, especially in the case of the asymmetric integral patch.

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Suthanyawatchai, Narisara, and Usa Onthong. "Adsorption of Hydrogen Sulfide, Carbondioxide and Methane by Zeolite (Ferrierite; H-FER): Computational Chemistry Method." Advanced Materials Research 356-360 (October 2011): 707–11. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.707.

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The adsorption of hydrogen sulfide (H2S), carbondioxide (CO2) and methane (CH4) on H-FER zeolite was investigated under computational chemistry using ONIOM (HF/6-31G (d,p):UFF) and ONIOM (B3LYP/6-31G (d,p):UFF) method. Compared to the H-FER zeolite induces much stronger binding of H2S, CO2 and CH4 suggesting great enhancements in the adsorption selectivity. The order of binding energies of adsorbed molecules is H2S > CO2 > CH4. It was found that the extended zeolitic framework covering the nanocavity was essential for describing the confinement effect of the zeolite. The results of these calculations show that the zeolite can be used to adsorb H2S bester then CO2 and CH4. Carbondioxide and hydrogen sulfide are pollutant in biogas product from anaerobic digestion of biodegradable materials. There for, zeolite can be use to purified gas before using as fuel.

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Meyer, Ralf, Klemens S. Schmuck, and Andreas W. Hauser. "Machine Learning in Computational Chemistry: An Evaluation of Method Performance for Nudged Elastic Band Calculations." Journal of Chemical Theory and Computation 15, no. 11 (September 25, 2019): 6513–23. http://dx.doi.org/10.1021/acs.jctc.9b00708.

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Mahmmod, Basheera M., Sadiq H. Abdulhussain, Marwah Abdulrazzaq Naser, Muntadher Alsabah, Abir Hussain, and Dhiya Al-Jumeily. "3D Object Recognition Using Fast Overlapped Block Processing Technique." Sensors 22, no. 23 (November 26, 2022): 9209. http://dx.doi.org/10.3390/s22239209.

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Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essential. To this end, this paper presents an efficient method for 3D object recognition with low computational complexity. Specifically, the proposed method uses a fast overlapped technique, which deals with higher-order polynomials and high-dimensional objects. The fast overlapped block-processing algorithm reduces the computational complexity of feature extraction. This paper also exploits Charlier polynomials and their moments along with support vector machine (SVM). The evaluation of the presented method is carried out using a well-known dataset, the McGill benchmark dataset. Besides, comparisons are performed with existing 3D object recognition methods. The results show that the proposed 3D object recognition approach achieves high recognition rates under different noisy environments. Furthermore, the results show that the presented method has the potential to mitigate noise distortion and outperforms existing methods in terms of computation time under noise-free and different noisy environments.

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Zeng, Xiongzhi, Wei Hu, Xiao Zheng, Jin Zhao, Zhenyu Li, and Jinlong Yang. "Computational characterization of nanosystems." Chinese Journal of Chemical Physics 35, no. 1 (February 2022): 1–15. http://dx.doi.org/10.1063/1674-0068/cjcp2111233.

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Nanosystems play an important role in many applications. Due to their complexity, it is challenging to accurately characterize their structure and properties. An important means to reach such a goal is computational simulation, which is grounded on ab initio electronic structure calculations. Low scaling and accurate electronic-structure algorithms have been developed in recent years. Especially, the efficiency of hybrid density functional calculations for periodic systems has been significantly improved. With electronic structure information, simulation methods can be developed to directly obtain experimentally comparable data. For example, scanning tunneling microscopy images can be effectively simulated with advanced algorithms. When the system we are interested in is strongly coupled to environment, such as the Kondo effect, solving the hierarchical equations of motion turns out to be an effective way of computational characterization. Furthermore, the first principles simulation on the excited state dynamics rapidly emerges in recent years, and nonadiabatic molecular dynamics method plays an important role. For nanosystem involved chemical processes, such as graphene growth, multiscale simulation methods should be developed to characterize their atomic details. In this review, we review some recent progresses in methodology development for computational characterization of nanosystems. Advanced algorithms and software are essential for us to better understand of the nanoworld.

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Liu, Lei, Jan Gerit Brandenburg, and Stefan Grimme. "On the hydrogen activation by frustrated Lewis pairs in the solid state: benchmark studies and theoretical insights." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, no. 2101 (July 24, 2017): 20170006. http://dx.doi.org/10.1098/rsta.2017.0006.

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Recently, the concept of small molecule activation by frustrated Lewis pairs (FLPs) has been expanded to the solid state showing a variety of interesting reactivities. Therefore, there is a need to establish a computational protocol to investigate such systems theoretically. In the present study, we selected several FLPs and applied multiple levels of theory, ranging from a semi-empirical tight-binding Hamiltonian to dispersion corrected hybrid density functionals. Their performance is benchmarked for the computation of crystal geometries, thermostatistical contributions, and reaction energies. We show that the computationally efficient HF-3c method gives accurate crystal structures and is numerically stable and sufficiently fast for routine applications. This method also gives reliable values for the thermostatistical contributions to Gibbs free energies. The meta-generalized gradient approximated TPSS-D3 evaluated in a projector augmented plane wave basis set is able to produce sufficiently accurate reaction electronic energies. The established protocol is intended to support experimental studies and to predict new reactions in the emerging field of solid-state FLPs. This article is part of the themed issue ‘Frustrated Lewis pair chemistry’.

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Nardi, Alessandro Nicola, Alessio Olivieri, Andrea Amadei, Riccardo Salvio, and Marco D’Abramo. "Modelling Complex Bimolecular Reactions in a Condensed Phase: The Case of Phosphodiester Hydrolysis." Molecules 28, no. 5 (February 24, 2023): 2152. http://dx.doi.org/10.3390/molecules28052152.

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(1) Background: the theoretical modelling of reactions occurring in liquid phase is a research line of primary importance both in theoretical–computational chemistry and in the context of organic and biological chemistry. Here we present the modelling of the kinetics of the hydroxide-promoted hydrolysis of phosphoric diesters. (2) Method: the theoretical–computational procedure involves a hybrid quantum/classical approach based on the perturbed matrix method (PMM) in conjunction with molecular mechanics. (3) Results: the presented study reproduces the experimental data both in the rate constants and in the mechanistic aspects (C–O bond vs. O–P bond reactivity). The study suggests that the basic hydrolysis of phosphodiesters occurs through a concerted ANDN mechanism, with no formation of penta-coordinated species as reaction intermediates. (4) Conclusions: the presented approach, despite the approximations, is potentially applicable to a large number of bimolecular transformations in solution and therefore leads the way to a fast and general method to predict the rate constants and reactivities/selectivities in complex environments.

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Journal articles on the topic 'Computational Chemistry Method'

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