PMID- 37870767
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20231108
IS  - 1520-6890 (Electronic)
IS  - 0009-2665 (Linking)
VI  - 123
IP  - 21
DP  - 2023 Nov 8
TI  - Orbital-Free Density Functional Theory: An Attractive Electronic Structure Method 
      for Large-Scale First-Principles Simulations.
PG  - 12039-12104
LID - 10.1021/acs.chemrev.2c00758 [doi]
AB  - Kohn-Sham Density Functional Theory (KSDFT) is the most widely used electronic 
      structure method in chemistry, physics, and materials science, with thousands of 
      calculations cited annually. This ubiquity is rooted in the favorable accuracy vs 
      cost balance of KSDFT. Nonetheless, the ambitions and expectations of researchers 
      for use of KSDFT in predictive simulations of large, complicated molecular 
      systems are confronted with an intrinsic computational cost-scaling challenge. 
      Particularly evident in the context of first-principles molecular dynamics, the 
      challenge is the high cost-scaling associated with the computation of the 
      Kohn-Sham orbitals. Orbital-free DFT (OFDFT), as the name suggests, circumvents 
      entirely the explicit use of those orbitals. Without them, the structural and 
      algorithmic complexity of KSDFT simplifies dramatically and near-linear scaling 
      with system size irrespective of system state is achievable. Thus, much larger 
      system sizes and longer simulation time scales (compared to conventional KSDFT) 
      become accessible; hence, new chemical phenomena and new materials can be 
      explored. In this review, we introduce the historical contexts of OFDFT, its 
      theoretical basis, and the challenge of realizing its promise via approximate 
      kinetic energy density functionals (KEDFs). We review recent progress on that 
      challenge for an array of KEDFs, such as one-point, two-point, and 
      machine-learnt, as well as some less explored forms. We emphasize use of exact 
      constraints and the inevitability of design choices. Then, we survey the 
      associated numerical techniques and implemented algorithms specific to OFDFT. We 
      conclude with an illustrative sample of applications to showcase the power of 
      OFDFT in materials science, chemistry, and physics.
FAU - Mi, Wenhui
AU  - Mi W
AUID- ORCID: 0000-0002-1612-5292
AD  - Key Laboratory of Material Simulation Methods & Software of Ministry of 
      Education, College of Physics, Jilin University, Changchun 130012, PR China.
AD  - State Key Laboratory of Superhard Materials, Jilin University, Changchun 130012, 
      PR China.
AD  - International Center of Future Science, Jilin University, Changchun 130012, PR 
      China.
FAU - Luo, Kai
AU  - Luo K
AD  - Department of Applied Physics, Nanjing University of Science and Technology, 
      Nanjing 210094, PR China.
FAU - Trickey, S B
AU  - Trickey SB
AUID- ORCID: 0000-0001-9224-6304
AD  - Quantum Theory Project, Department of Physics and Department of Chemistry, 
      University of Florida, Gainesville, Florida 32611, United States.
FAU - Pavanello, Michele
AU  - Pavanello M
AUID- ORCID: 0000-0001-8294-7481
AD  - Department of Physics and Department of Chemistry, Rutgers University, Newark, 
      New Jersey 07102, United States.
LA  - eng
PT  - Journal Article
PT  - Review
DEP - 20231023
PL  - United States
TA  - Chem Rev
JT  - Chemical reviews
JID - 2985134R
SB  - IM
EDAT- 2023/10/23 12:43
MHDA- 2023/10/23 12:44
CRDT- 2023/10/23 11:14
PHST- 2023/10/23 12:44 [medline]
PHST- 2023/10/23 12:43 [pubmed]
PHST- 2023/10/23 11:14 [entrez]
AID - 10.1021/acs.chemrev.2c00758 [doi]
PST - ppublish
SO  - Chem Rev. 2023 Nov 8;123(21):12039-12104. doi: 10.1021/acs.chemrev.2c00758. Epub 
      2023 Oct 23.