Subhajit Nandy

Bio: Subhajit Nandy is an academic researcher from Indian Association for the Cultivation of Science. The author has contributed to research in topics: Eigenvalues and eigenvectors & Catalysis. The author has an hindex of 5, co-authored 9 publications receiving 75 citations. Previous affiliations of Subhajit Nandy include University of Calcutta.

Stochastic diagonalization of Hamiltonian: A genetic algorithm‐based approach

Abstract: We propose and demonstrate the workability of a genetic-algorithm-based technique of finding the eigenvalues and eigenfunctions of a real symmetric Hamiltonian matrix. The algorithm can be tailored to extract all the eigenvalues at a time or to extract only the lowest or the highest eigenvalue first and then sequentially determine the next few higher (lower) eigenvalues. The algorithm is generalized to handle diagonalization problems in which the basis functions themselves are optimized simultaneously. Several model applications are reported. © 2002 Wiley Periodicals, Inc. Int J Quantum Chem, 2002

Coulomb explosion in dicationic noble gas clusters: A genetic algorithm-based approach to critical size estimation for the suppression of Coulomb explosion and prediction of dissociation channels

Abstract: We present a genetic algorithm based investigation of structural fragmentation in dicationic noble gas clusters, Ar(n)(+2), Kr(n)(+2), and Xe(n)(+2), where n denotes the size of the cluster. Dications are predicted to be stable above a threshold size of the cluster when positive charges are assumed to remain localized on two noble gas atoms and the Lennard-Jones potential along with bare Coulomb and ion-induced dipole interactions are taken into account for describing the potential energy surface. Our cutoff values are close to those obtained experimentally [P. Scheier and T. D. Mark, J. Chem. Phys. 11, 3056 (1987)] and theoretically [J. G. Gay and B. J. Berne, Phys. Rev. Lett. 49, 194 (1982)]. When the charges are allowed to be equally distributed over four noble gas atoms in the cluster and the nonpolarization interaction terms are allowed to remain unchanged, our method successfully identifies the size threshold for stability as well as the nature of the channels of dissociation as function of cluster size. In Ar(n)(2+), for example, fissionlike fragmentation is predicted for n=55 while for n=43, the predicted outcome is nonfission fragmentation in complete agreement with earlier work [Golberg et al., J. Chem. Phys. 100, 8277 (1994)].

Further Insight into the Conversion of a Ni-Fe Metal-Organic Framework during Water-Oxidation Reaction.

Abstract: Metal-organic frameworks (MOFs) are extensively investigated as catalysts in the oxygen-evolution reaction (OER). A Ni-Fe MOF with 2,5-dihydroxy terephthalate as a linker has been claimed to be among the most efficient catalysts for the oxygen-evolution reaction (OER) under alkaline conditions. Herein, the MOF stability under the OER was reinvestigated by electrochemical methods, X-ray diffraction, X-ray absorption spectroscopy, energy-dispersive spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy, nuclear magnetic resonance, operando visible spectroscopy, electrospray ionization mass spectroscopy, and Raman spectroscopy. The peaks corresponding to the carboxylate group are observed at 1420 and 1520 cm-1 using Raman spectroscopy. The peaks disappear after the reaction, suggesting the removal of the carboxylate group. A drop in carbon content but growth in oxygen content after the OER was detected by energy-dispersive spectra. This shows that after the OER, the surface of MOF is oxidized. SEM images also show deep restructures in the surface morphology of this Ni-Fe MOF after the OER. Nuclear magnetic resonance and electrospray ionization mass spectrometry show the decomposition of the linker in alkaline conditions and even in the absence of potential. These experimental data indicate that during the OER, the synthesized MOF transforms to a Fe-Ni-layered double hydroxide, and the formed metal oxide is a candidate for the OER catalysis. Generalization is not true; however, taken together, these findings suggest that the stability of Ni-Fe MOFs under harsh oxidation conditions should be reconsidered.

A density-matrix-based simulated annealing (sa) technique for locating minimum energy structures on the neutral polythiophene potential energy surface

Abstract: We use the elements of the single particle density matrix in the atomic orbital basis as the basic variables and the simulated annealing method as the optimization tool to locate the global minima on the potential surfaces of polythiophene and polyselenophene oligomers (PT)n, (PS)n with n up to 100. A modified version of the Su–Schrieffer–Heeger Hamiltonian is used to generate the PES and the unitary transformation of the density variables as the bond lengths change during random reconfiguring moves. The cost effectiveness of the method is analyzed.

Diagonalization of a real-symmetric Hamiltonian by genetic algorithm: A recipe based on minimization of Rayleigh quotient

Abstract: A genetic algorithm-based recipe involving minimization of the Rayleigh quotient is proposed for the sequential extraction of eigenvalues and eigenvectors of a real symmetric matrix with and without basis optimization. Important features of the method are analysed, and possible directions of development suggested

Genetic Algorithms, a Nature-Inspired Tool: Survey of Applications in Materials Science and Related Fields

Abstract: Genetic algorithms (GAs) are a tool used to solve high-complexity computational problems. Apart from modelling the phenomena occurring in Nature, they help in optimization, simulation, modelling, design and prediction purposes in science, medicine, technology, and everyday life. They can be adapted to the given task, be joined with other ones (this leads to combined or hybrid methods), and can work in parallel on many processors. The uses of GAs reported in literature represent a wide variety of approaches and led to solving of numerous computational problems of high complexity. In materials science and related fields of science and technology the GAs open possibilities for materials design, studies of their properties, or production at industrial scale. Here, the recent use of GAs in various domains connected to materials science, solid state physics and chemistry, crystallography, biology, and engineering is reviewed. The listed examples taken from recent literature show how broad the use of these metho...

Soft computing techniques in advancement of structural metals

Abstract: Current trends in the progress of technology demand availability of materials resources ahead of the advancing fronts of the application areas. During the last couple of decades, significant progress has been made in computational and experimental design of materials. Among the potential computational techniques, soft computing stands in distinction due to the inherent flexibility in capturing the complexity of the problem in global scale. Since 1990s remarkable success has been achieved in soft computing activities in different facets of materials science and engineering. Extensive efforts have been devoted in design of metals and alloys based on composition–process–microstructure–property correlation. The present review aims to address the contribution of soft computing in the field of structural metals and alloys including processing and joining. The critical issues concerning applicability of particular techniques in specific materials problem have been particularly emphasised encompassing the...

The Bloch wave operator: generalizations and applications: Part I. The time-independent case

Abstract: This is part 1 of a two-part review on wave operator theory and methods. The basic theory of the time-independent wave operator is presented in terms of partitioned matrix theory for the benefit of general readers, with a discussion of the links between the matrix and projection operator approaches. The matrix approach is shown to lead to simple derivations of the wave operators and effective Hamiltonians of Lowdin, Bloch, Des Cloizeaux and Kato as well as to some associated variational forms. The principal approach used throughout stresses the solution of the nonlinear equation for the reduced wave operator, leading to the construction of the effective Hamiltonians of Bloch and of Des Cloizeaux. Several mathematical techniques which are useful in implementing this approach are explained, some of them being relatively little known in the area of wave operator calculations. The theoretical discussion is accompanied by several specimen numerical calculations which apply the described techniques to a selection of test matrices taken from the previous literature on wave operator methods. The main emphasis throughout is on the use of numerical methods which use iterative or perturbation algorithms, with simple Pade approximant methods being found sufficient to deal with most of the cases of divergence which are encountered. The use of damping factors and relaxation parameters is found to be effective in stabilizing calculations which use the energy-dependent effective Hamiltonian of Lowdin. In general the computations suggest that the numerical applications of the nonlinear equation for the reduced wave operator are best carried out with the equation split into a pair of equations in which the Bloch effective Hamiltonian appears as a separate entity. The presentation of the theoretical and computational details throughout is accompanied by references to and discussion of many works which have used wave operator methods in physics, chemistry and engineering. Some of the techniques described in this part 1 will be further extended and applied in part 2 of the review, which deals with the changes which are required to extend wave operator theory to the case of a time-dependent Hamiltonian such as that which describes the interaction of a laser pulse with an atom or molecule.