Density functional theory (DFT) often is the method of choice for simulating the electronic properties of extended solids and surfaces from first principles due to a favorable compromise between accuracy and computational cost. In the field of heterogeneous catalysis, DFT is indispensable for deriving mechanistic insights and understanding trends in surface reactivity. The accuracy of DFT for surface reaction energetics depends strongly on the exchange-correlation (XC) approximation. We show here that optimization of such XC functionals for surface binding energies can lead to a worse description of surface reaction barriers, unless important physical exact conditions are fulfilled.
The application of density functional theory to heterogeneous catalysis is hindered by the shortcomings of conventional density functional approximations. We combine machine learning with explicitly non-local physically informed descriptors and introduce an exchange-correlation functional (CIDER26SS) framework regulari...
M. S. Abdallah, Zhuo-Tao Jin, Boris Kozinsky et al.· 1 citation· ⚡1
Self-interaction error (SIE) in density functional theory (DFT) leads to significant inaccuracies in the calculation of barrier heights of chemical reactions and band gaps of solid-state systems. In this work, we develop a neural-network-based exchange functional aimed at reducing SIE-related errors by training on exac...
A. Wijaya, D. Farhamsa· Physical Chemistry, Chemical...· 0 citations
This review presents a concise overview of the theoretical foundations of DFT and the major approximations used in modern calculations, as well as the practical workflow from structural preparation and convergence testing to geometry optimization, electronic-structure calculations and property analysis.
Hariharan Vaiyapuri Manemaran, Girija Kesavan· International Journal of Mul...· 0 citations
We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA through an optimized choice of reference orbitals and energy components, rather than a modification of the RPA correlation functional itself. The method employs an empirically constructed hybrid functi...
Neung-Kyung Yu, Johannes Voss, Andrew J Medford· Journal of Chemical Theory a...· 1 citation
Accurate adsorption energy predictions are central in computational catalysis. The need for higher accuracy without prohibitive computational costs has led to the development of correction schemes for density functional theory (DFT) predictions. For instance, dispersion corrections are nowadays routinely applied, eve...
Mahdiyeh Gholami, Ricardo Urrego-Ortiz, M. Pourfath et al.· cScience· 0 citations
The potential energy surface of an 8-atom periodic cell of carbon is explored using discrete path sampling with the energy, forces, and stress tensor represented by the MACE-MATPES-r2SCAN-0 potential evaluated via an interface to the Atomic Simulation Environment. The resulting enthalpy landscape is explored as a fun...
V. Neuman, Soon Woo Park, M. Wilson et al.· Journal of Physical Chemistr...· 0 citations
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