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Modeling and simulations for 2D materials: a ReaxFF perspective

Summary

2D materials research routinely couples experiment with simulation because edge and defect chemistry can dominate growth, etching, and stability; ReaxFF offers a reactive MD route when QM is too costly for large systems or long timelines. Nayir et al. present an IOP 2D Materials topical review of ReaxFF developments and applications targeting 2D materials families including graphene, transition metal dichalcogenides, MXenes, hexagonal boron nitride, and group III–V sheets, including heterostructure examples. The uncorrected proof abstract on file explicitly lists layered and nonlayered two-dimensional systems together with mixed-dimensional van der Waals heterostructures as scope, and it states that the review closes with an outlook on future ReaxFF development needs and large-scale simulation opportunities for guiding experimental discovery. The manuscript organizes parameterization strategies (classical parabolic optimization versus machine-learning-assisted workflows), simulation modalities (standard MD, accelerated sampling, force-biased Monte Carlo), and material-class sections before closing with outlook on large-scale ReaxFF for 2D discovery. The corpus pdf_path is papers/Nayir_2D_materials_ReaxFF_2023_galley.pdf, a galley/proof with production queries; a cleaner sibling ingest is [[2023nadire-nayir-2d-materials-modeling-simulations-2]].

Methods

4 — Review / perspective (2D Materials). The article is a narrative survey of how ReaxFF has been used for 2D TMDs, MXenes, hBN, group III–V sheets, nonlayered 2D phases, and vdW heterostructures, with outreach to ReaxFF+*continuum/phase-field coupling in CVD/ALD-themed* stories where the cited primary work did so. It does not own one simulation input deck; N/A to assign a single timestep/thermostat for the Manuscript—timesteps, ensembles, QEq treatments, and rare-*event* choices must be imported per DOI (10.1088/2053-1583/acd7fd) from the primary publications cited in each section**.

ReaxFF parameterization (review only). The text compares conventional parabolic ReaxFF optimization to ML-assisted parametrization in the literature; N/A as a new QM-driven fit by Nayir et al.—they catalog how others build and validate 2D-relevant parameter files.

MD / rare-event (review only). The article discusses typical ReaxFF+LAMMPS choices—0.2–0.25 fs in H-containing RMD, NVT/NPT on slab models, and metadynamics/parallel-*tempering/force-biased MC as used in cited work—N/A at this summary level as a repro package; N/A (new static DFT in this manuscript), N/A (E-field* RMD authored as a stand-*alone* case study in the review text), because this DOI is synthesis + outlook, not a primary simulation paper. Corpus role: this slug registers the galley file Nayir_2D_materials_ReaxFF_2023_galley.pdf; for final layout use 2023nadire-nayir-2d-materials-modeling-simulations-2 or a library VOR PDF**.

Cited-practice line (not one run). Reviewed ReaxFF work commonly reports molecular dynamics in LAMMPS with 3D periodic boundary conditions, slab supercells with 10³–10⁴ atoms, 0.2–0.25 fs timestep, NVT or NPT ensembles, Berendsen or Nose–Hoover thermostat damping, 1 bar NPT when cited, ps equilibration, ns production where cited, and temperature from 300 K to >1000 K; N/A for a universal electric field recipe in every example.

Findings

Across surveyed literature, 2D ReaxFF studies repeatedly pair QM training sets for edge and defect chemistries with validation against DFT or experiment on small cells before large-scale production runs. The review highlights trade-offs between classical parabolic optimization and machine-learning-assisted fitting when expanding element coverage for heterostructure interfaces.

Sampling and rare events

For etching, growth, and oxidation under operando-relevant conditions, the review discusses when authors adopt metadynamics, parallel tempering, force-biased Monte Carlo, or long MD segments, noting that barrier heights and nucleation times remain sensitive to collective-variable choices.

Outlook

The closing sections emphasize dataset gaps for in situ synthesis pathways and opportunities for larger ReaxFF campaigns when paired with experimental in situ probes—claims mirrored on the cleaner sibling page 2023nadire-nayir-2d-materials-modeling-simulations-2. This duplicate slug chiefly preserves PDF hash provenance for the papers/Nayir_2D_materials_ReaxFF_2023_galley.pdf ingest.

Limitations

IOP galley files sometimes retain author query tags; if your OCR or extract pipeline misfires on those pages, prefer [[2023nadire-nayir-2d-materials-modeling-simulations-2]]. Galley PDFs may differ in figure quality, line numbering, and copy edits from the final issue PDF. For citations, prefer [[2023nadire-nayir-2d-materials-modeling-simulations-2]] or the publisher PDF in your library. NON_PRIMARY_ARTICLE_PAPER_SLUGS.md covers proof duplicates.

Confidence rationale: med—galley duplicate; comprehensive prose delegated to VOR sibling.

Citations and evidence anchors

IOPscience records article type, submission dates, and CC-BY licensing metadata that help disambiguate galley ingests from final issue PDFs. DOI: 10.1088/2053-1583/acd7fd.

Reader notes (navigation)

2D Materials reviews are high-traffic entry points; when refreshing source_refs on theme hubs, ensure this DOI appears where ReaxFF 2D surveys are cited as evidence for method trends.