Density Functional Theory in the Age of Chemical Intelligence II
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: 30 April 2024 | Viewed by 1393
Special Issue Editors
2. Laboratory of Renewable Energies-Photovoltaics, R&D National Institute for Electrochemistry and Condensed Matter–INCEMC–Timisoara, Str. Dr. Aurel Podeanu 144, 300569 Timișoara, Romania
Interests: quantum physical chemistry; nanochemistry; reactivity indices and principles; electronegativity; density functional theory; path integrals; enzyme kinetics; QSAR; epistemology and philosophy of science
Special Issues, Collections and Topics in MDPI journals
2. Laboratory of Renewable Energies-Photovoltaics, R&D National Institute for Electrochemistry and Condensed Matter, Dr. A. Paunescu Podeanu Str. No. 144, RO-300569 Timisoara, Romania
Interests: nanostructures; topology; topological modeling
Special Issues, Collections and Topics in MDPI journals
Interests: computational and theoretical chemistry; CDFT and its applications; electronic structure principles; chemical reactivity; solid state chemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Density functional theory (DFT), as recognized by the Nobel Prize in Chemistry in 1998, is approaching new horizons of multi-, trans-, and nano-chemistry. Since its inception and follow-up innovative developments, it has succeeded in describing, in the otherwise truly complex/complicated realm of many electrons evolving in many charge potential fields, almost the entire chemistry of single and pair electronic interactions through appropriate rearrangements of potential/forces in many-electronic samples in order to properly represent the entire system’s structure and reactivity. However, beyond the (perhaps unique) way of representing N-interactions via 1- and 2- electronic interactions (+ the required corrections of representation, namely Exchange, correlation, gradient/perturbative terms, multiple-configurations, etc.), it recognized, relatively recently, that such an approach opens the door to chemical-based artificial intelligence by employing mono- and paired- bits/qubits of information in a complex information sample. Therefore, DFT is at the edge of reinventing itself, either in fundamental or applicative aspects: from the asymmetric Hubbard dimer to the self-assembly of carbon-based supramolecular complexes; from the description of dynamic chemical bonding/covalent bonding to deep learning (molecular) machines/algorithms; from mean-field density matrix decompositions to the time-dependent description of two-dimensional semiconductors; and from conceptual DFT explaining chemical reactivity to drug-likeness, bioactive scores and anticancer peptides, among others. All of these developments open new horizons for DFT as a theory, a versatile computational framework, and an adaptive paradigm for a plethora of phenomena in which the molecule unites with cells’ constituents and ultimately with intelligence (as an autonomous network entity of dynamical information); i.e., the molecular artificial in Cerebro and in silico models, simulations and intelligence to be next synthesized according to in vitro and in vivo protocols in 2021. I thus kindly invite you to contribute a visionary project from your particular viewpoint that is projected, sustained or aided by DFT.
Dr. Mihai V. Putz
Dr. Ottorino Ori
Dr. Savas Kaya
Guest Editors
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Keywords
- quantum chemistry and quantum computation
- chemical computation and network analysis
- inorganic/organic nano compounds and systems
- supramolecular chemistry
- chemical bond, structure, and reactivity
- QSPR, QSAR, and bio-specific interactions
- learning molecular machines
- artificial/quantum intelligence
