Computational Study of Low Interlayer Friction in Ti_{n+1}C_n (n = 1, 2, and 3) MXene
Summary¶
This corpus PDF is an ACS Applied Materials & Interfaces proof / accepted manuscript of the MXene friction study (same work as 2017difan-zhang-acs-computational-study). PBE(+vdw-DF2) DFT maps minimum-energy sliding paths; LAMMPS ReaxFF MD for Ti_{n+1}C_nO2 uses a Ti/C/O/F/OH-class parameter set with Langevin thermostat at 10 K and 298 K and 0.1 fs timestep. Static load–friction analysis gives coefficients of friction ~0.24–0.27 below 1.2 GPa normal load (DFT and ReaxFF aligned). Ti vacancies and terminal O vacancies increase friction but keep μ < 0.31. Ti3C2 with −OH or −OCH3 lowers μ to about 0.10–0.14 vs −O.
Application context in the article highlights MXenes as tunable solid lubricants where oxygen-terminated stacks can exhibit ultralow interlayer shear resistance, and emphasizes quantifying how Ti or O vacancies and mixed −OH/−OCH3 terminations perturb friction coefficients under GPa-class contact pressures.
Readers should verify numerical values, units, and section references against the peer-reviewed PDF and any Supporting Information, especially when extracts or galley PDFs truncate tables.
Methods¶
Static QM (DFT). VASP, PAW, PBE GGA; vdw-DF2 dispersion; spin-polarized; k-mesh density ~1000 points per atom; 520 eV cutoff; bilayer supercells with ~10 Å vacuum normal to layers (c lattice fixed to preserve vacuum in the optimization protocol described in ACS Appl. Mater. Interfaces); MEP analysis of interlayer sliding; force/stress thresholds per paper.
MD application (ReaxFF). LAMMPS drives ReaxFF with the Ti_{n+1}C_nT_x parameterization (T = O, F, OH class) on O-terminated Ti₂CO₂, Ti₃C₂O₂, and Ti₄C₃O₂ bilayers, including Ti sublayer and terminal O vacancies and Ti₃C₂ surfaces functionalized with −O, −OH, or −OCH₃. Protocol highlights in the accepted manuscript / proof mirror §2 of the VOR: conjugate-gradient relaxation of in-plane lattice vectors, Langevin thermostats at 10 K and 298 K, and an integration timestep of 0.1 fs, with PBC in-plane as in the DFT supercells. Friction is analyzed along static loading / sliding pathways to extract μ vs normal stress, cross-compared to DFT in the paper’s tables.
Force-field training is N/A. Electric fields and enhanced sampling are N/A in the indexed framing.
Any additional MD details (NPT segments, production times, shear-rate studies beyond the static friction workflow) should be read from the version-of-record PDF/SI at the DOI or from 2017difan-zhang-acs-computational-study (canonical pdf_path in this corpus).
MD blueprint honesty. LAMMPS molecular dynamics with PBC bilayers uses Langevin thermostats and 0.1 fs timesteps as quoted above. Equilibration/production segment lengths (ps/ns) for any finite-temperature sampling beyond the static friction workflow, plus explicit barostat/pressure control if NPT appears, are N/A on this proof-route summary—see VOR/SI.
Findings¶
Same substantive conclusions as 2017difan-zhang-acs-computational-study: low-barrier sliding paths for n = 1–3 stacks; μ ≈ 0.24–0.27 for p < 1.2 GPa on O-terminated surfaces (DFT and ReaxFF agreement); Ti and terminal O vacancies increase μ but keep μ < ~0.31; −OH / −OCH₃ on Ti₃C₂ drop μ to about 0.10–0.14 vs −O. Comparisons: DFT vs ReaxFF for μ; defect vs pristine; functionalization vs −O. Sensitivity: normal load (GPa range), defect density, and surface chemistry shift μ. Limitations: static friction estimates and limited temperature sampling may miss thermally activated slip; see manuscript discussion. Corpus honesty: this path is a proof PDF—prefer 2017difan-zhang-acs-computational-study for VOR tables.
Limitations¶
This file path points to a proof PDF; for pagination and final figures, prefer the version of record at the DOI or the duplicate corpus entry 2017difan-zhang-acs-computational-study (different pdf_path).
Relevance to group¶
van Duin co-authored ReaxFF validation against DFT for MXene tribology—a clear 2D materials + mechanics anchor in the corpus.
Reader notes (navigation)¶
- Canonical article PDF in corpus: 2017difan-zhang-acs-computational-study.