1. IDR@IIT Indore
  2. IITI Scholarly Publications
  3. Department of Chemistry
Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/9051
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJindal, Shwetaen_US
dc.contributor.authorBulusu, Satya Silendraen_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-21T11:30:49Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-21T11:30:49Z-
dc.date.issued2018-
dc.identifier.citationJindal, S., & Bulusu, S. S. (2018). An algorithm to use higher order invariants for modelling potential energy surface of nanoclusters. Chemical Physics Letters, 693, 152-158. doi:10.1016/j.cplett.2018.01.023en_US
dc.identifier.issn0009-2614-
dc.identifier.otherEID(2-s2.0-85040595006)-
dc.identifier.urihttps://doi.org/10.1016/j.cplett.2018.01.023-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/9051-
dc.description.abstractIn order to fit potential energy surface (PES) of gold nanoclusters, we have integrated bispectrum features with artificial neural network (ANN) learning technique in this work. We have also devised an algorithm for selecting the frequencies that need to be coupled for extracting the phase information between different frequency bands. We have found that higher order invariant like bispectrum is highly efficient in exploring the PES as compared to other invariants. The sensitivity of bispectrum can also be exploited in acting as an order parameter for calculating many thermodynamic properties of nanoclusters. © 2018en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.sourceChemical Physics Lettersen_US
dc.subjectGold Nanoclustersen_US
dc.subjectMolecular dynamicsen_US
dc.subjectMolecular physicsen_US
dc.subjectNanoclustersen_US
dc.subjectPotential energyen_US
dc.subjectPotential energy surfacesen_US
dc.subjectPower spectrumen_US
dc.subjectQuantum chemistryen_US
dc.subjectThermodynamic propertiesen_US
dc.subjectBispectrumen_US
dc.subjectDescriptorsen_US
dc.subjectDifferent frequencyen_US
dc.subjectHigher-orderen_US
dc.subjectLearning techniquesen_US
dc.subjectMolecular dynamics simulationsen_US
dc.subjectOrder parameteren_US
dc.subjectPhase informationen_US
dc.subjectNeural networksen_US
dc.titleAn algorithm to use higher order invariants for modelling potential energy surface of nanoclustersen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Chemistry

Files in This Item:
There are no files associated with this item.
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: