Modeling for Structural Engineering and Synthesis of Two-Dimensional WSe2 Using a Newly Developed ReaxFF Reactive Force Field
Summary¶
WSe\(_2\) monolayers are attractive for optoelectronics and defect engineering, but predictive synthesis models must capture covalent W–Se reactivity, chalcogen chemical potential effects, and mechanochemical coupling during growth—requirements that exceed fixed-bond classical descriptions. This J. Phys. Chem. C article introduces a ReaxFF parameterization targeting W–Se solid-phase reactions: phase transitions, defect formation, and migration as functions of geometry and Se chemical potential, enabling large-scale reactive MD of synthesis-relevant environments. The work is a Penn State collaboration spanning theory, ReaxFF development (van Duin), and experimental TEM growth science (Alem/Redwing). The local PDF is an ACS galley proof; cite the publisher VOR for final pagination when available. Conceptually, the manuscript targets a known gap: TMD synthesis is sensitive to chalcogen chemical potential, edge terminations, and strain during island coalescence, and reactive simulations can visualize pathways that DFT cannot sample at experimental scales. The collaboration structure—Crespi/theory, van Duin/ReaxFF, and Alem/Redwing/experiments—signals an intent to keep QM training, reactive MD, and microscopy metrics aligned. For TMD synthesis science, the emphasis on Se chemical potential and edge terminations is meant to connect CVD windows to atomistic pathways without assuming equilibrium shapes alone. Confirm barrier heights and training tables in the published JPCC PDF when reproducing fits and simulations.
Methods¶
Parameterization (ReaxFF). A W–Se-focused reactive description is trained against first-principles data on clusters and periodic models (exact QM level, fitting objectives, and weighting are in the article/SI). Training targets solid-phase reactions: phase transitions, defect formation, and migration as a function of geometry and Se chemical potential.
Reactive MD. Large-scale runs probe mechanochemical coupling—how strain and deformation shift vacancy and edge energetics—and sample gas-phase environments meant to mimic CVD windows for WSe₂ growth.
Experiments (context). TEM-informed growth science from collaborators motivates geometries and observables used to validate the force field (see abstract and figures).
Protocol detail. ReaxFF molecular dynamics in LAMMPS on 3D PBC WSe₂-containing supercells; NVT and NPT-style stages may both appear (e.g. NPT for some CVD-like gas environments, NVT for strained slab legs)—confirm in the J. Phys. Chem. C galley. N/A — per-segment fs timestep and thermostat/barostat names on this page. Supercell sizes, temperature/chemical-potential control, strain paths, and analysis of island/edge structure are specified in the JPCC article; the local corpus PDF is an ACS galley—confirm numerical tables against the version of record. N/A — 1 bar NPT details and internal pressure tensor if not tabulated in the excerpt we used. N/A — external electric field. N/A — metadynamics / replica exchange unless reported. Duration: reactive trajectories are ns-scale as stated in the JPCC text for WSe₂ processing (exact ps/ns per leg in article/SI).
Static QM in training (block 3). DFT (or related QM) reference data enter the ReaxFF fit; functional, basis, and k-mesh for training sets are listed in the article (N/A to duplicate all tables on this page).
Findings¶
QM agreement. The published benchmarks indicate the potential tracks key DFT references for the training chemistry.
Mechanism / growth. Simulations highlight nonlinear coupling between monolayer strain and defect populations, with implications for island shape and edge termination under Se-rich vs Se-lean environments.
Use case. ReaxFF is positioned as a kinetic complement to DFT for CVD-relevant pathways; transfer to other TMD chemistries requires additional training. The study aligns reactive atomistics with microscopy-grounded growth narratives for WSe₂.
Limitations¶
Galley PDF in corpus; ReaxFF remains empirical and can mis-rank pathways outside training coverage.
Relevance to group¶
Penn State parameterization effort for a flagship TMD system with direct ties to experimental growth collaborators.
Citations and evidence anchors¶
- https://doi.org/10.1021/acs.jpcc.0c09155