Matches in SemOpenAlex for { <https://semopenalex.org/work/W3206522174> ?p ?o ?g. }
- W3206522174 abstract "Electronic structure calculations based on Kohn-Sham density functional theory (KSDFT) that incorporate exact-exchange or hybrid functionals are associated with a large computational expense, a consequence of the inherent cubic scaling bottleneck and large associated prefactor, which limits the length and time scales that can be accessed. Although orbital-free density functional theory (OFDFT) calculations scale linearly with system size and are associated with a significantly smaller prefactor, they are limited by the absence of accurate density-dependent kinetic energy functionals. Therefore, the development of accurate density-dependent kinetic energy functionals is important for OFDFT calculations of large realistic systems. To this end, we propose a method to train kinetic energy functional models at the exact-exchange level of theory by using a dictionary of physically relevant terms that have been proposed in the literature in conjunction with linear or nonlinear regression methods to obtain the fitting coefficients. For our dictionary, we use a gradient expansion of the kinetic energy nonlocal models proposed in the literature and their nonlinear combinations, such as a model that incorporates spatial correlations between higher order derivatives of electron density at two points. The predictive capabilities of these models are assessed by using a variety of model one-dimensional (1D) systems that exhibit diverse bonding characteristics, such as a chain of eight hydrogens, LiF, LiH, C4H2, C4N2, and C3O2. We show that by using the data from model 1D KSDFT calculations performed using the exact-exchange functional for only a few neutral structures, it is possible to generate models with high accuracy for charged systems and electron and kinetic energy densities during self-consistent field iterations. In addition, we show that it is possible to learn both the orbital dependent terms, i.e., the kinetic energy and the exact-exchange energy, and models that incorporate additional nonlinearities in spatial correlations, such as a quadratic model, are needed to capture subtle features of the kinetic energy density that are present in exact-exchange-based KSDFT calculations." @default.
- W3206522174 created "2021-10-25" @default.
- W3206522174 creator A5014272934 @default.
- W3206522174 creator A5033952903 @default.
- W3206522174 creator A5043352274 @default.
- W3206522174 creator A5052407431 @default.
- W3206522174 creator A5055448715 @default.
- W3206522174 creator A5064709946 @default.
- W3206522174 creator A5071612407 @default.
- W3206522174 creator A5082318215 @default.
- W3206522174 creator A5087157004 @default.
- W3206522174 date "2022-01-11" @default.
- W3206522174 modified "2023-09-27" @default.
- W3206522174 title "Accurate parameterization of the kinetic energy functional for calculations using exact-exchange" @default.
- W3206522174 cites W1537843484 @default.
- W3206522174 cites W1550061415 @default.
- W3206522174 cites W1752517290 @default.
- W3206522174 cites W1911433256 @default.
- W3206522174 cites W1965617046 @default.
- W3206522174 cites W1967087132 @default.
- W3206522174 cites W1968426044 @default.
- W3206522174 cites W1968648081 @default.
- W3206522174 cites W1969666707 @default.
- W3206522174 cites W1972038892 @default.
- W3206522174 cites W1975522299 @default.
- W3206522174 cites W1980807995 @default.
- W3206522174 cites W1982983163 @default.
- W3206522174 cites W1987166016 @default.
- W3206522174 cites W1987514218 @default.
- W3206522174 cites W1988372591 @default.
- W3206522174 cites W1988810072 @default.
- W3206522174 cites W1989335167 @default.
- W3206522174 cites W2004599916 @default.
- W3206522174 cites W2013183108 @default.
- W3206522174 cites W2014880496 @default.
- W3206522174 cites W2015797475 @default.
- W3206522174 cites W2018276631 @default.
- W3206522174 cites W2020786104 @default.
- W3206522174 cites W2030976617 @default.
- W3206522174 cites W2047444722 @default.
- W3206522174 cites W2070907261 @default.
- W3206522174 cites W2079105963 @default.
- W3206522174 cites W2088370223 @default.
- W3206522174 cites W2094045530 @default.
- W3206522174 cites W2120114129 @default.
- W3206522174 cites W2162574934 @default.
- W3206522174 cites W2230728100 @default.
- W3206522174 cites W2270536778 @default.
- W3206522174 cites W2277852287 @default.
- W3206522174 cites W2299526617 @default.
- W3206522174 cites W2317605420 @default.
- W3206522174 cites W2790736812 @default.
- W3206522174 cites W2804451518 @default.
- W3206522174 cites W2883151771 @default.
- W3206522174 cites W2898491714 @default.
- W3206522174 cites W2906112559 @default.
- W3206522174 cites W2939153492 @default.
- W3206522174 cites W2940346397 @default.
- W3206522174 cites W2946547583 @default.
- W3206522174 cites W2952711759 @default.
- W3206522174 cites W2971363634 @default.
- W3206522174 cites W2999933282 @default.
- W3206522174 cites W3009611342 @default.
- W3206522174 cites W3036850052 @default.
- W3206522174 cites W3044205763 @default.
- W3206522174 cites W3068185939 @default.
- W3206522174 cites W3094227282 @default.
- W3206522174 cites W3098463108 @default.
- W3206522174 cites W3099522629 @default.
- W3206522174 cites W3099950071 @default.
- W3206522174 cites W3133068160 @default.
- W3206522174 cites W3161206725 @default.
- W3206522174 cites W3198268924 @default.
- W3206522174 cites W4200318405 @default.
- W3206522174 cites W4242393813 @default.
- W3206522174 cites W43109728 @default.
- W3206522174 cites W794304800 @default.
- W3206522174 doi "https://doi.org/10.1063/5.0065217" @default.
- W3206522174 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35032977" @default.
- W3206522174 hasPublicationYear "2022" @default.
- W3206522174 type Work @default.
- W3206522174 sameAs 3206522174 @default.
- W3206522174 citedByCount "1" @default.
- W3206522174 countsByYear W32065221742023 @default.
- W3206522174 crossrefType "journal-article" @default.
- W3206522174 hasAuthorship W3206522174A5014272934 @default.
- W3206522174 hasAuthorship W3206522174A5033952903 @default.
- W3206522174 hasAuthorship W3206522174A5043352274 @default.
- W3206522174 hasAuthorship W3206522174A5052407431 @default.
- W3206522174 hasAuthorship W3206522174A5055448715 @default.
- W3206522174 hasAuthorship W3206522174A5064709946 @default.
- W3206522174 hasAuthorship W3206522174A5071612407 @default.
- W3206522174 hasAuthorship W3206522174A5082318215 @default.
- W3206522174 hasAuthorship W3206522174A5087157004 @default.
- W3206522174 hasBestOaLocation W32065221741 @default.
- W3206522174 hasConcept C104970782 @default.
- W3206522174 hasConcept C121332964 @default.
- W3206522174 hasConcept C121864883 @default.
- W3206522174 hasConcept C13280743 @default.
- W3206522174 hasConcept C135889238 @default.