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Semiempirical synonyms, semiempirical antonyms - FreeThesaurus. References in periodicals archive? It was observed that semiempirical methods failed to describe the double bond between sulfur and phosphorous from malathion and the resonance at the end of the methyl-parathion chain, due to a potential barrier in both cases.

The semiempirical method PM6 that we have used has given better results in both gas phase and aqueous phase than other methods, with especially a good R2 0. The goal of this work is the discussion and assessment of two novel semiempirical equations with several specific cases for quantitative description of shear viscosity curves of different non-Newtonian fluids.

The third approach to the efficiency calibration is the semiempirical approach. A number of semiempirical models can be used to take into account the decrease in proliferation that results from limitations of nutrient supply or mechanical constraints or metabolites accumulation.

Caption: Figure 5: Comparison of semiempirical correlation see 10 with calculated values for the area ratio of the meniscus to the cross-section of container. Later, a combined slip semiempirical tire model was developed. In our opinion, this optical and structural behaviour requires an analysis through the application of some theoretical models as mentioned before and differentiating interactions of L-tryptophan with PbS nanocrystals; this report only presents the experimental results and a semiempirical analysis.

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The law of non-Darcy seepage in smooth fractures can be deduced according to the semiempirical theory of Prandtl turbulence [22]. For the semiempirical GB simulations, the size of the simulation cells was increased due to the low computational cost.

Based on experiments, many scholars have established empirical or semiempirical formulas to evaluate the elastic modulus of ordinary SFRC. The current work addresses this issue by developing and testing a semiempirical method which combines environmental, meteorological, and SWC data for the operational estimation of [ET. A] in water-limited Mediterranean environments. A theoretical calculation for single point energy was conducted according to a semiempirical molecular orbital calculation method Parameterized Model 3 by using Spartan'14 software from Wavefunction, Inc.

Thesaurus browser? Full browser?There are a variety of semi-empirical methods available in Gaussian In addition to increased efficiency, this change also provides analytic gradients and frequencies. The remaining semi-empirical methods use the modified version of MOPAC in Linkand they are discussed on their individual pages.

Standard parameters for supported atoms are generated automatically by the program unless the NoGenerate option is specified. Read-in parameters take precedence over internal ones when both are used. For some systems containing these elements, instabilities can exists in the PM7 wavefunction. There may be difficulties getting the wavefunction to converge. This is less common for lighter elements and is most likely to occur for transition metal complexes.

In such cases, the first option is to try an alternate SCF algorithm: e. If this fails, other options are to use a different initial guess or read in the density from a calculation using a different method see the Guess keyword.

This too is most common for transition metals and so caution is advised when performing calculations on transition metals.

Semi-empirical mass formula

A straightforward way of testing the wavefunction is to use the Stable keyword. Generate the standard parameters for the specified method.

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This is the default. NoGenerate says not to generate any standard parameters; all parameters must be read in. Any parameter can be specified or overridden. The input section must be terminated by a blank line. Cards is a synonym for Input. Most but not all parameters can be changed. Both input sections must be terminated by a blank line. Read parameters from the checkpoint file.

Chk and Read are synonymous with Checkpoint. This is the default if parameters are read from the input file. NoPrint says not to print parameters, and it is the default if standard parameters are used. Print all parameters including the ones that are zero. The default is NonZerowhich says to print only non-zero parameters.

Second derivatives are done numerically. Applies only to AM1 and PM3. The default is Newwhich says to use the new implementation described above. We begin with the native Gaussian semi-empirical parameter format, which is very general. Atomic units are used throughout the input. Parameter sections are separated by lines containing four asterisks.One of the main problems in quantitative gamma-ray spectroscopy is the determination of detection efficiency, for different energies, source-detector geometries, and composition of samples or sources.

There are, in principle, three approaches to this issue: experimental, numerical, and semiempirical. Semiempirical approach is based on the calculation of the efficiency for the measured sample on the basis of an experimental efficiency measured on the same detector, but with a calibration source that can be of different size, geometry, density, or composition—the so-called efficiency transfer.

The results were compared to the experimentally obtained efficiency, and further validation is performed by measuring reference materials issued within the framework of several interlaboratory intercomparisons. The analysis of the results showed that the efficiency transfer produces good results with the discrepancies within the limits of the measurement uncertainty. Also, for intercomparison measurement, u test criterion for the trueness of the result was applied showing that the majority of the obtained results were acceptable.

Some difficulties were identified, and the ways to overcome them were discussed. Gamma spectrometry is a widely used method for the measurement of gamma-ray emitting radionuclide content in various materials. It is a method of choice for the measurement of environmental samples conducted, for example, during radiological monitoring of the environment and contamination control. This method is based on the interaction of gamma rays emitted from the source and the active volume of the detector.

Semiconductor detectors and among them, high-purity germanium HPGe detectors, are proven to be very sensitive and have good energy and time resolution. That is why this type of detector is commonly used for gamma-spectroscopic measurements. In the absence of background, the result of any gamma-spectroscopic measurement is represented by the spectrum of photons originating from the source that are collected by the multichannel analyzer MCA with the number of detected photons in a peak at a specific energy being proportional to the activity of the given radionuclide.

One of the main problems in quantitative gamma-ray spectroscopy is the determination of detection efficiency, for different energies, different source-detector geometries, and different compositions of voluminous samples or sources. This task represents the efficiency calibration of the detector. The quality of the results of gamma-spectrometric measurements is dependent on the knowledge of detector efficiency for different sample geometries, chemical compositions, and sample-detector geometries.

In reality, measurement depends on the geometry, structure, and the chemical composition of the sample, and the efficiency calibration for each specific case is not always available. That is why several methods for efficiency calibration were developed. These methods vary in difficulty, reliability of the obtained results, time and resources required, and so on. Experimental approach utilizes standardized sources calibration sources with composition, density, and geometry that are as close as possible to the measured samples.

However, this approach requires a large number of calibration sources, implying a high financial cost, a long counting time, and complicated and time-consuming preparation of the calibration sources. This problem is especially pronounced when environmental samples are of interest due to their diversity in composition and structure [ 1 ]. Numerical methods of the efficiency calibration consist of a computer simulation of the processes that contribute to the detection of the emitted photons.

Monte Carlo simulation codes are developed to simulate the response of complex particle detectors and for variety of different high energy and nuclear interactions [ 4 ].

In case of gamma spectrometry, these codes need defining appropriate processes for interaction of gamma photons with the detector and the corresponding database used in the development of the application for the particular detector, which may be time-consuming and may require proficiency in programming language [ 5 ].

Once an application is developed, the use is relatively easy and the results are straightforward. The third approach to the efficiency calibration is the semiempirical approach. It is based on the calculation of the efficiency for the measured sample on the basis of an experimental efficiency curve obtained for the same detector, but with a calibration source that can be of different sizes, geometries, densities, or compositions—the so-called efficiency transfer.

The procedure saves time and resources, since sample-specific experimental calibration is avoided. It has been proven especially useful in environmental measurements [ 8 ], where an ultimate precision in calibration is usually not required and a variety of different sources might be measured.

Many software packages were developed in order to perform efficiency transfer calculations with a known set of parameters. The result of the calculation is transfer coefficient, which is the ratio of the efficiency for unknown sample and reference efficiency. The aim of this paper is to analyze the semiempirical approach to the efficiency calibration of the HPGe detector. A specific example of the efficiency transfer software will be analyzed in more detail, with practical instruction, and advantages and drawbacks pointed out.

The results of the testing of this method will also be presented.Semiempirical quantum chemistry attempts to address two limitations, namely slow speed and low accuracy, of the Hartree-Fock calculation by omitting or parameterizing certain integrals based on experimental data, such as ionization energies of atoms, or dipole moments of molecules.

As a result, semiempirical methods are very fast, applicable to large molecules, and may give accurate results when applied to molecules that are similar to the molecules used for parameterization.

On the downside, accuracy of semiempirical methods is erratic on many systems. Existing semiempirical models differ by the further approximations that are made when evaluating one-and two-electron integrals and by the parameterization philosophy. Modified Neglect of Diatomic Overlap, MNDO by Michael Dewar and Walter Thiel, is the oldest NDDO-based model that parameterizes one-center two-electron integrals based on spectroscopic data for isolated atoms, and evaluates other two-electron integrals using the idea of multipole-multipole interactions from classical electrostatics.

MNDO has a number of known deficiencies, such as inability to describe the hydrogen bond due to a strong intermolecular repulsion. The MNDO method is characterized by a generally poor reliability in predicting heats of formation. For example, highly substituted stereoisomers are predicted to be too unstable compared to linear isomers due to overestimation of repulsion is sterically crowded systems. Austin Model 1, AM1 by Dewar and co-workers takes a similar approach to MNDO in approximating two-electron integrals but uses a modified expression for nuclear-nuclear core repulsion.

The modified expression results in non-physical attractive forces that mimic van der Waals interactions. The modification also necessitated reparameterization of the model, which was carried out with a particular emphasis on dipole moments, ionization potentials, and geometries of molecules. While this allows for some description of the hydrogen bond, other deficiencies, such as systematic over-estimates of basicities, remained.

Also, the lowest energy geometry for the water dimer is predicted incorrectly by the AM1 model.


While AM1 was parameterized largely based on a small number of atomic data, PM3 is parameterized to reproduce a large number of molecular properties. In some sense, chemistry gave way to statistics with the PM3 model. Different parameterization, and slightly different treatment of nuclear repulsion allow PM3 to treat hydrogen bonds rather well but it amplifies non-physical hydrogen-hydrogen attractions in other cases.

This results in serious problems when analyzing intermolecular interactions methane is predicted to be a strongly-bound dimer or conformations of flexible molecules OH is strongly attracted to CH3 in 1-pentanol.

The accuracy of thermochemical predictions with PM3 is slightly better than that of AM1. The PM3 model has been widely used for rapid estimation of molecular properties and has been recently extended to include many elements, including some transition metals. Despite their limitations, semiempirical methods are often used in computational chemistry because they allow study of systems that are out of reach of more accurate methods.

For example, modern semiempirical programs allow study of molecules consisting of thousands of atoms while ab initio calculations that produce similar thermochemical accuracy are feasible on molecules consisting of less than atoms. Semiempirical calculations can be useful in many situations, such as. The limitations of semiempirical methods should be kept in mind when deciding if these are suitable tools for the task.Switch to new thesaurus.

References in periodicals archive?


Three-dimensional molecule editing techniques and structural optimization using semiempirical PM7 Hamiltonian [4], and molecular docking were used to predict in silico the interaction energy between Ops pesticides and fullerene derivatives, designed based on AChE active site, as target to the organophosphates compounds, to describe in molecular level the interaction of Ops with proposed molecules.

So far, many empirical, semiempiricaland theoretical equations for description of viscosity as a function of stress or much more frequently of strain-rate have been proposed. SilviScan predicts MO[E. There are, in principle, three approaches to this issue: experimental, numerical, and semiempirical.

These methods vary in difficulty, reliability of the obtained results, time and resources required, and so on. For the purpose of this paper, we only describe the simplest model for unlimited growth exponential and three semiempirical models for limited growth.

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Using these compiled results of the analysis, a semiempirical correlation can be developed to account for the changes in the actual evaporation area of the molten salts in small cylindrical containers. InPacejka and Bakker established a semiempirical tire model that can accurately calculate the lateral force and aligning moment, which is one of the findings of the cooperation project between TU Delft and Volvo [11].

Wang [10] proposed a semiempirical algorithm which has the objective to estimate the wave height from Envisat ASAR wave mode imagery without any prior knowledge. Based on the experimental observations, a semiempirical equation of the Forchheimer's coefficients A and B dependent on hydraulic aperture and roughness was proposed. Optimization of parameters for semiempirical methods V: Modification of NDDO approximations and application to 70 elements. Caracterizacion del conjugado no covalente de grafeno y acido folico mediante espectroscopia Raman y metodos computacionales.

Dictionary browser? Full browser?Lets us use the above general ideas to arrive at a mass formula that describes the gross behaviour of the binding energy of nuclei. Imagine that we did have nuclear interactions that saturates a strong repulsive core to the nucleon-nucleon interaction that keeps the nucleons apart then we would expect that the binding energy of a nucleus would depend on the volume of the nucleus.

In the above argument we have neglected the fact that for nucleons near or at the surface of the nucleus, the number of nucleons they see on average is less than if they were in the nuclear medium itself. This means that we have to remove a contribution to the binding energy that depends on the area of the nuclear surface. Let us pause here and take note of the form that these two terms give for the binding energy of a chunk of nuclear material. A contribution that we have not considered is from the electromagnetic interaction.


We have considered only the effects of nuclear interactions thus far, as we have assumed that nuclear forces are much stronger than electromagnetic forces. This statement is absolutely true, but the electromagnetic contributions have a compensating feature that makes them an important. The electromagnetic interaction is long range, and acts over the entire volume of the nucleus, which we know is in contrast to the nuclear interaction which is limited to essentially those nucleons within at most an inverse pion mass.

You will recall that the potential energy of a charged sphere of radius is this form arises from bringing infinitesimally thin shells from infinity, computing the work done, and then bringing more shells up until the charged sphere is formed of radius. Before we get too bogged down at this point, lets move on, as we know there are other effects that have to be included in our semi-empirical mass formula, before we can rest and be happy.

Let us think about we we know about cramming non-interacting fermions we will justify this later into a small volume. In a closed box, the fermions fill up the levels up to the fermi-level by definition.

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There is one fermi level for the neutrons and one for the protons. Lets now consider the implications of this. Finally, there is one more ingredient to our binding energy recipe. From our somewhat superficial look at nucleon-nucleon interactions we saw that the interaction depended upon what spin-isospin channel was scattering. This tells us that the binding energy of 2 protons, is the same as two neutrons, but different for a neutron-proton pair. So we define a discrete operator that for odd A nuclei, for odd-odd nuclei and for even-even nuclei.

Figure: The value of Z for a given A that maximizes the binding energy per nucleon. Figure: Binding Energy per Nucleon verses A. Figure: The Binding energy per nucleon surface against Z and A. Figure: The Binding energy per nucleon as a contour plot against Z and A.To save this word, you'll need to log in. See more words from the same year Dictionary Entries near semiempirical semielastic semiellipse semielliptic semiempirical semi-erect semies semievergreen.

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