Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Deb Sankar De"'
Publikováno v:
Condensed Matter, Vol 6, Iss 1, p 9 (2021)
Using fingerprints used mainly in machine learning schemes of the potential energy surface, we detect in a fully algorithmic way long range effects on local physical properties in a simple covalent system of carbon atoms. The fact that these long ran
Externí odkaz:
https://doaj.org/article/06c8fbf1e747404e91a1ffa20eb19a88
Autor:
Deb Sankar De, Sulay Saha, Raj Ganesh S. Pala, Sri Sivakumar, Dilip Kumar Behara, Arun Kumar, Anandh Subramaniam
Publikováno v:
Physical Chemistry Chemical Physics. 22:25366-25379
Stabilization of different morphologies of iso-material native/non-native heterostructures is important for electron-hole separation in the context of photo-electrochemical and opto-electronic devices. In this regard, we explore the stabilities of di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc7f87ce46c85c6cb4bf66e58325ba51
https://doi.org/10.1039/d0cp01300e
https://doi.org/10.1039/d0cp01300e
Publikováno v:
Physical Review B. 101
For C${}_{60}$, the potential energy surface exhibits a driving force toward the ground state that allows it to be found rapidly. However, the potential energy surface of a cluster can also exhibit features that prevent us from finding its global min
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9590b63c2ae34a1e471a40383c490ff
https://doi.org/10.1103/physrevb.101.214303
https://doi.org/10.1103/physrevb.101.214303
An assessment of the structural resolution of various fingerprints commonly used in machine learning
Autor:
Jörg Behler, Sandip De, Emir Kocer, Anatole von Lilienfeld, Stefan Goedecker, Anders S. Christensen, Deb Sankar De, Felix A. Faber, Behnam Parsaeifard
Atomic environment fingerprints are widely used in computational materials science, from machine learning potentials to the quantification of similarities between atomic configurations. Many approaches to the construction of such fingerprints, also c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2716e6d63de761d5db78de409181f0d9
Fingerprint distances, which measure the similarity of atomic environments, are commonly calculated from atomic environment fingerprint vectors. In this work we present the simplex method which can perform the inverse operation, i.e. calculating fing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ff43867eaba4a1b3174218456e80a60
Publikováno v:
Carbon. 129:847-853
A good hydrogen storage material should adsorb hydrogen in high concentrations and with optimal binding energies. Exohedrally metal decorated carbon fullerene structures were proposed as a promising material in this context. We present a fully ab-ini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::329a688bc8ce4d647df354425dfe3972
https://doi.org/10.1016/j.carbon.2017.11.086
https://doi.org/10.1016/j.carbon.2017.11.086
Finding complex reaction and transformation pathways, involving many intermediate states, is in general not possible on the DFT level with existing simulation methods due to the very large number of required energy and force evaluations. This is due
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c019ca3f1b275bae6b2c32154e30abf1
http://arxiv.org/abs/1906.06077
http://arxiv.org/abs/1906.06077
Autor:
Stefan Goedecker, Dipanwita Dutta, Joerg Lehmann, Shantanu Roy, H. Bartolf, Giovanni Alfieri, Daniel Fan, Massimo Camarda, Deb Sankar De, Maximilian Amsler, Thomas A. Jung
High power SiC MOSFET technologies are critical for energy saving in, e.g., distribution of electrical power. They suffer, however, from low near-interface mobility, the origin of which has not yet been conclusively determined. Here, we present uniqu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cdcb62a3fc3cfa3d1d0c43e9a9ee4d6
https://edoc.unibas.ch/73212/
https://edoc.unibas.ch/73212/
Publikováno v:
Condensed Matter
Volume 6
Issue 1
Condensed Matter, Vol 6, Iss 9, p 9 (2021)
Volume 6
Issue 1
Condensed Matter, Vol 6, Iss 9, p 9 (2021)
Using fingerprints used mainly in machine learning schemes of the potential energy surface, we detect in a fully algorithmic way long range effects on local physical properties in a simple covalent system of carbon atoms. The fact that these long ran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc9a9ea93d43f36d18eea4ed0ab2dcc3
https://doi.org/10.3390/condmat6010009
https://doi.org/10.3390/condmat6010009
Publikováno v:
Applied Surface Science. 371:343-348
Surface stress in solids can have profound effects in semi-infinite and nanoscale materials. The current work pertains to the simulation of surface stress, using the concept proposed by Shuttleworth [Proceedings of Physical Society 63 (1949) 444–45
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a38cf0146f584702de4e07926c4ecf87
https://doi.org/10.1016/j.apsusc.2016.02.201
https://doi.org/10.1016/j.apsusc.2016.02.201