ReviewJournal of molecular modeling2025
Density functional theory for nanomaterials: structural and spectroscopic applications-a review.
Review in Journal of molecular modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed.
- Design, Synthesis, Antimicrobial Evaluation, DFT Analysis, Molecular Docking and Molecular Dynamics Studies of Thiadiazol-Hydrazine Derivatives as Potential Dihydrofolate Reductase Inhibitors.The protein journal · 2026Article
- Theoretical investigation of the adsorption and sensing behavior of cephapirin on transition metal doped gallium nitride single-walled nanotubes.Scientific reports · 2026Article
- Electronic structure engineering of PVA/ZnO/graphene oxide nanocomposites: a DFT study toward CO₂ and humidity detection.Scientific reports · 2026Article
- Density functional theory investigation of adsorption and charge transfer of fungal polyketide mycotoxins on Si, N Co-doped carbon quantum dots.Journal of molecular modeling · 2026Article
- Article
- In silico identification of novel PTP1B inhibitors by the investigation of molecular mechanism, QSAR, and DFT studies.In silico pharmacology · 2026Article
- Density functional theory-accelerated design of perovskite quantum dots: unlocking atomic-level control for next-generation optoelectronics and sensors.RSC advances · 2025Review
- Combined DFT and experimental study of CuO and Ni-CuO nanoparticles: structural characterization, photocatalytic degradation, and antimicrobial activities.RSC advances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextNanoparticles (NPs) exhibit unique physical and chemical properties that defy classical mechanics, owing to their quantum nature. These properties are dictated by size, shape, and structure, rendering NPs indispensable across diverse applications, including catalysis, medical imaging, drug delivery, and energy research. Advanced computational tools have become indispensable in unraveling the intricacies of nanomaterial behavior, driving significant progress in theoretical and computational research. Among these tools, the density functional theory (DFT) has emerged as a powerful method for predicting material properties. In this review study, we delve into key aspects of DFT simulations applied to nanomaterials, including Optimal Geometries, Band Gap and Electronic Properties, Density of States (DOS), Natural Bond Orbitals (NBO), and spectroscopic features (Infrared, Raman Spectra, and UV-Visible Spectra). Despite its successes, DFT faces limitations, particularly concerning semiconductor materials. Researchers strive to enhance its accuracy while maintaining computational efficiency. Balancing generically accurate functionals for specific applications remains an ongoing challenge. As nanomaterial continues to play a significant part in a variety of industries, the progress of DFT is of great interest and exploration.
methodsThis review discusses DFT-based computational techniques employed for modeling nanomaterials. The calculations are generally done by utilizing generalized gradient approximation (GGA) functionals such as PBE (Perdew-Burke-Ernzerhof), and where necessary, hybrid functionals like B3LYP to enhance band gap accuracy. All calculations are performed using the standard quantum chemistry packages such as VASP, Gaussian, or Quantum ESPRESSO. This combination of methods offers a complete theoretical basis for the study of nanomaterial properties.
Indexed as
Identifiers
40682690What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.