Scattering contributions to the internal partition function of a diatomic molecular system

Pramana ◽  
1979 ◽  
Vol 13 (1) ◽  
pp. 15-24 ◽  
Author(s):  
B Talukdar ◽  
M Chatterji ◽  
P Banerjee
1980 ◽  
Vol 35 (12) ◽  
pp. 1313-1316 ◽  
Author(s):  
A. Bernard ◽  
A. M. Sibaï

Abstract A consistent set of improved rotational constants is derived for the X2Σ+, A′2⊿r, A2Πr, B2Σ+,and C2Πr electronic states of lanthanum oxide from the reanalysis of all available data. These constants are obtained from a global fit of the respective bands by a "Direct Approach" technique using complete Hamiltonian matrices for the description of Π and ⊿ states. In order to fit the lines accurately it is shown necessary to include centrifugal distortion effects in the spin-orbit interactions (AJ, AJ and AJJ respectively in A′, and A and C states) as well as in Λ-doubling (PJ pJJ,qJ in C state) and spin-rotation interactions (γJ in B state). More reliable values for the internal partition function and dissociation equilibrium constant of La O are computed for temperatures between 1000 and 8000 K, by taking account of all the known electronic states and using present or recent values for the molecular parameters and dissociation energy.


2020 ◽  
Vol 7 (2) ◽  
pp. 1
Author(s):  
Khairul Azmi Mohamed ◽  
Asmat Ismail ◽  
Nur Azfahani Ahmad

The installation of an internal partition has resulted in lowering the illumination level inside a building. Therefore, this study is intended to evaluate the effects of several internal partition layout on indoor daylighting performance in student residential rooms. Several options of internal partition were simulated using Climate Based Daylight Modelling (CBDM) to suggest the effective partition layout to overcome low daylighting level inside the room at the annual level. The findings indicate that the internal partition perpendicular to the window layout has been proven to have the highest annual daylight sufficiency in a student residential room in the tropics.


2018 ◽  
Author(s):  
Roman Zubatyuk ◽  
Justin S. Smith ◽  
Jerzy Leszczynski ◽  
Olexandr Isayev

<p>Atomic and molecular properties could be evaluated from the fundamental Schrodinger’s equation and therefore represent different modalities of the same quantum phenomena. Here we present AIMNet, a modular and chemically inspired deep neural network potential. We used AIMNet with multitarget training to learn multiple modalities of the state of the atom in a molecular system. The resulting model shows on several benchmark datasets the state-of-the-art accuracy, comparable to the results of orders of magnitude more expensive DFT methods. It can simultaneously predict several atomic and molecular properties without an increase in computational cost. With AIMNet we show a new dimension of transferability: the ability to learn new targets utilizing multimodal information from previous training. The model can learn implicit solvation energy (like SMD) utilizing only a fraction of original training data, and archive MAD error of 1.1 kcal/mol compared to experimental solvation free energies in MNSol database.</p>


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